Volume 4 2026

This paper investigates the volume polynomials of Euclidean tetrahedra under prescribed edge-length equalities. It identifies 25 edge-length symmetry classes by grouping edge-equality patterns up to vertex relabeling. For each class, the Cayley–Menger determinant is specialized to obtain a homogeneous cubic polynomial in the distinct squared edge lengths. Candidate formulas are discovered computationally by generating valid tetrahedra, fitting polynomial coefficients using least squares, and reconstructing exact rational coefficients. Each formula is then verified symbolically and factored over the corresponding rational polynomial ring. The results show that 16 of the 25 specialized volume polynomials are reducible, while nine are irreducible. The study further demonstrates that factorization depends not only on the multiplicities of equal edge lengths but also on their geometric arrangement, particularly the adjacency and opposition of equal edges. Finally, it interprets polynomial factors in terms of degenerate boundary configurations and suggests extending the computational method to higher-dimensional simplices.

This paper investigates why India, despite its immense creative talent and large domestic music audience, has historically achieved limited crossover into the non-diasporic global mainstream compared with South Korea. It examines how India's film-centric playback-singing system and limited public funding for contemporary arts create barriers for independent musicians and shift financial risk onto young creatives. The paper explores how this uncertainty contributes to parental financial anxiety, career pressure, and academic burnout among students who aspire to pursue creative professions. Comparing India's music industry with South Korea's state-supported cultural export model, it proposes a digitally audited National Talent Fund that provides merit-based, milestone-linked financial support to emerging artists. Using an illustrative statistical model and a Keynesian economic multiplier framework, the study argues that public investment in independent creative labor could support employment, strengthen the domestic creative economy, and improve India's international cultural influence.

This study investigates portability of European-trained coronary artery disease polygenic risk scores in African, South Asian, and East Asian biobank cohorts, and ancestry-specific recalibration to restore predictive performance within the context of statistical genetics and cardiovascular precision medicine, an area of growing scientific importance given its implications for equitable genomic medicine implementation, ancestry-diverse GWAS investment strategy, and CAD risk stratification in non-European clinical populations. Using GWAS summary statistic PRS derivation (LDpred2, PRSice-2), C-statistic and OR per SD comparison across ancestry cohorts, and ancestry-specific PRS recalibration using local LD reference panels and within-ancestry GWAS fine-mapping, we examine EUR LD reference underpinning PRS derivation poorly representing non-EUR LD blocks, combined with ancestry-specific effect size heterogeneity and causal variant tagging differences, reducing cross-ancestry PRS transferability in 69,600 participants across 3 non-EUR cohorts: 18,400 African Ancestry (4,284 CAD cases), 22,800 South Asian (5,840 cases), 28,400 East Asian (6,840 cases) with genome-wide array genotyping and electronic health record CAD ascertainment drawn from African Ancestry cohort from Million Veteran Program; South Asian from UK Biobank + PMBB; East Asian from BioBank Japan + KCHIP; all with linked EHR CAD outcomes. Results indicate that EUR CAD PRS AUC drops from 0.74 (EUR validation) to 0.58 in African Ancestry, 0.64 in South Asian, 0.66 in East Asian; ancestry-specific recalibration restores AUC to 0.68, 0.70, and 0.71 respectively, partially closing but not eliminating the gap (p < 0.001), with AUC 0.58/0.64/0.66 non-EUR vs. 0.74 EUR; recalibration restores to 0.68/0.70/0.71 as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to statistical genetics and cardiovascular precision medicine and carry actionable implications for the design of programs and policies targeting equitable genomic medicine implementation, ancestry-diverse GWAS investment strategy, and CAD risk stratification in non-European clinical populations.

This study investigates sequential granular activated carbon (GAC) adsorption and electrochemical oxidation treatment train for PFAS-contaminated groundwater: removal efficiency for 40 PFAS compounds, fluoride byproduct recovery, and energy cost per liter treated within the context of environmental engineering and water remediation technology, an area of growing scientific importance given its implications for military base PFAS groundwater remediation system design, GAC regeneration economics, and PFAS destruction technology regulatory approval support. Using bench-scale GAC column (EBCT 10 min) followed by BDD electrochemical flow cell at current densities 10-100 mA/cm2, with LC-MS/MS quantification of 40 PFAS compounds and fluoride ion chromatography for defluorination tracking, we examine GAC adsorbing long-chain PFAS (C8+) via hydrophobic and electrostatic interactions with treated concentrate then destructed by BDD hydroxyl radical oxidation cleaving C-F bonds in stepwise defluorination, regenerating GAC and avoiding PFAS brine disposal in 40 PFAS compounds (including PFOA, PFOS, 6:2 FTS, and short-chain C4-C6 PFCAs/PFSAs) in 3 groundwater matrices at 5 concentration levels, 4 current densities, n=3 replicates = 720 treatment conditions drawn from bench-scale treatment at Lakeside ERIL with real groundwater from Fort Bragg NC, Pease AFB NH, and Peterson AFB CO diluted to target PFAS concentrations. Results indicate that GAC + BDD sequential train achieves >99.4% removal for all 40 PFAS including short-chain (C4) compounds at 50 mA/cm2 current density with 84.2% defluorination efficiency and energy cost 4.84 kWh/m3 at pilot-relevant flow rates (p < 0.001), with >99.4% removal all 40 PFAS; 84.2% defluorination; 4.84 kWh/m3 energy cost as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to environmental engineering and water remediation technology and carry actionable implications for the design of programs and policies targeting military base PFAS groundwater remediation system design, GAC regeneration economics, and PFAS destruction technology regulatory approval support.

This study investigates age-related dual-task walking cost in stride time variability and cognitive performance, and utility of dual-task cost as fall risk stratification marker across healthy adults aged 20-84 within the context of gerontology and human movement science, an area of growing scientific importance given its implications for fall risk screening protocol using dual-task assessment, dual-task training intervention target identification, and cognitive-motor reserve assessment in aging. Using instrumented GAITRite walkway (stride time, length, variability), digit span backward (cognitive task), and dual-task cost calculation as (single-task - dual-task)/single-task x 100; 12-month prospective fall follow-up via monthly diary, we examine increased cognitive-motor resource competition in aging as prefrontal executive control capacity declines, requiring greater attentional resources for gait stability and leaving less capacity for concurrent cognitive tasks — a capacity-sharing dual-task cost in 420 community-dwelling healthy adults (60 per decade: 20-29, 30-39, 40-49, 50-59, 60-69, 70-79, 80-84) with 12-month fall diary follow-up (84.2% retention) drawn from Nordic Aging Research Institute gait laboratory with GAITRite 6-m active area and tablet-based digit span task during walking condition. Results indicate that dual-task gait cost increases linearly from 4.2% (age 20-29) to 28.4% (age 80-84); dual-task cost >18% predicts 12-month falls with AUC 0.78, sensitivity 72.4%, specificity 78.4%; each 10% increase in dual-task cost associated with OR 2.84 for any fall (p < 0.001), with DT cost 4.2% to 28.4% across 7 decades; AUC 0.78 for fall prediction at >18% threshold as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to gerontology and human movement science and carry actionable implications for the design of programs and policies targeting fall risk screening protocol using dual-task assessment, dual-task training intervention target identification, and cognitive-motor reserve assessment in aging.

This study investigates cold-press sintering pressure and temperature optimization for Li6PS5Cl argyrodite solid electrolyte pellets, grain boundary resistance contribution, and Li metal interfacial stability for all-solid-state battery applications within the context of electrochemical energy storage and solid-state ionics, an area of growing scientific importance given its implications for all-solid-state battery manufacturing scale-up, argyrodite electrolyte pressing protocol standardization, and solid electrolyte-lithium metal interface engineering roadmap. Using Mechanochemical Li6PS5Cl synthesis, cold-press sintering optimization at 4 pressures x 4 temperatures, EIS grain boundary and bulk resistance extraction by equivalent circuit fitting, Li|SSE|Li symmetric cell CCD, and TEM/EELS interface characterization, we examine higher sintering pressure reducing porosity and grain boundary area, lowering grain boundary resistance contribution to total ionic resistance, while temperature above 120 C inducing phase decomposition; Li metal interface stability governed by Li-PS decomposition interphase SEI formation kinetics in 16 sintering conditions (4 pressures: 50, 100, 250, 500 MPa x 4 temperatures: 20, 80, 120, 200 C) with n=3 pellets per condition; Li|SSE|Li symmetric cells cycled for 500 hours at 0.1 mA/cm2 drawn from Westbrook Battery Institute inert-atmosphere (Ar glovebox) pellet press, Gamry Interface EIS, FEI Helios FIB-SEM, and JEOL ARM-200F TEM for interface cross-section characterization. Results indicate that optimal sintering at 250 MPa / 120 C achieves total conductivity 4.84 mS/cm with grain boundary contribution 28.4% (vs. 64.2% at 50 MPa); Li|SSE|Li CCD 2.84 mA/cm2; 500-hour cycling at 0.1 mA/cm2 with stable interfacial resistance 284 Ohm/cm2 (p < 0.001), with conductivity 4.84 mS/cm; GB contribution 28.4% vs. 64.2% low pressure; CCD 2.84 mA/cm2 as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to electrochemical energy storage and solid-state ionics and carry actionable implications for the design of programs and policies targeting all-solid-state battery manufacturing scale-up, argyrodite electrolyte pressing protocol standardization, and solid electrolyte-lithium metal interface engineering roadmap.

This study investigates drug resistance profiles, lineage distribution, and genomic transmission cluster analysis from whole-genome sequencing of M. tuberculosis clinical isolates across 14 sub-Saharan African countries within the context of infectious disease genomics and TB epidemiology, an area of growing scientific importance given its implications for national TB drug resistance surveillance, genomic epidemiology-informed outbreak response, and WHO resistance mutation catalog validation for WGS diagnostic deployment. Using Illumina NextSeq WGS (>50x coverage), resistance mutation calling against WHO mutation catalog v2, lineage assignment by Coll 2014 SNP barcodes, and transmission cluster analysis by 5 SNP threshold pairwise distance, we examine acquired drug resistance accumulating via sequential mutation selection under incomplete treatment, amplified by ongoing transmission of pre-resistant strains within high-burden communities lacking adequate infection control in 4,284 M. tuberculosis isolates from 14 countries (2018-2024): 3,484 new cases, 800 previously treated; phenotypic DST available for 2,840 (66%) drawn from 14 national TB programs: South Africa, Kenya, Tanzania, Uganda, Ethiopia, Nigeria, Ghana, DRC, Cameroon, Mozambique, Zambia, Zimbabwe, Malawi, Rwanda with centralized WGS at Cape Town and Nairobi nodes. Results indicate that RR/MDR-TB prevalence 6.4% (new cases) and 28.4% (previously treated); pre-XDR-TB 2.4% of all isolates; Lineage 4 dominant (64.2%) with Lineage 2 (Beijing, 18.4%) significantly enriched in MDR clusters; 38.4% of MDR isolates within genomic transmission clusters (p < 0.001), with MDR: 6.4% new, 28.4% retreated; 38.4% MDR in transmission clusters; L2 enriched 2.8x in MDR as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to infectious disease genomics and TB epidemiology and carry actionable implications for the design of programs and policies targeting national TB drug resistance surveillance, genomic epidemiology-informed outbreak response, and WHO resistance mutation catalog validation for WGS diagnostic deployment.

This study investigates graph neural network detection of coordinated inauthentic behavior (CIB) networks on Twitter/X using temporal account activity graphs combined with LLM-generated content feature embeddings within the context of computational social science and AI safety, an area of growing scientific importance given its implications for platform trust and safety CIB detection system design, election integrity monitoring, and state-sponsored disinformation attribution methodology. Using temporal account activity graph construction (co-retweet, co-hashtag, reply network edges), GraphSAGE with temporal attention, LLM-generated content feature vectors (GPT-4o embeddings), and ensemble with metadata features evaluated on held-out CIB campaigns, we examine coordinated campaigns exhibiting temporal synchrony (burst co-activity), topological cohesion (dense intra-cluster edges), and content homogeneity (low embedding variance) — patterns exploitable by GNN trained on labeled network snapshots in 28,400 CIB accounts (48 Twitter Transparency Report campaigns) and 142,000 matched organic accounts; held-out evaluation on 8 unseen campaigns (2023-2024) drawn from Twitter/X Academic API historical data access; CIB ground truth from Twitter Transparency Report public disclosures; LLM embedding via GPT-4o API for 170 million tweets. Results indicate that full ensemble (GNN + LLM content + metadata) achieves account-level F1 0.88 and AUC 0.94 on held-out campaigns; GNN alone F1 0.78, content alone F1 0.72; campaign-level detection precision 0.92 at 84.2% recall threshold for new unseen campaigns (p < 0.001), with full ensemble F1 0.88, AUC 0.94; campaign detection precision 0.92 at 84.2% recall as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to computational social science and AI safety and carry actionable implications for the design of programs and policies targeting platform trust and safety CIB detection system design, election integrity monitoring, and state-sponsored disinformation attribution methodology.

This study investigates effects of pesticide-free management, wildflower sowing, and connected green corridor design on wild bee species richness, abundance, and functional diversity recovery in Copenhagen city parks over 5 years within the context of urban ecology and pollinator conservation biology, an area of growing scientific importance given its implications for urban green space management policy for pollinator conservation, pesticide-free city park program design, and pollinator corridor network planning in European cities. Using randomized cluster controlled design (48 parks, 16 per arm), annual wild bee pan trap (3 colors x 12 stations/park) and timed transect surveys, bee identification to species, and functional diversity (FDis, FRic) analysis, we examine pesticide elimination removing sublethal exposure reducing bee navigation, reproduction, and immunity, combined with wildflower resources restoring forage diversity that supports specialist bee functional groups excluded from conventional low-diversity turf in 48 parks (16 per treatment arm), annual surveys 2019-2024: 5 survey years x 48 parks x 3 replicate visits = 720 survey occasions; 18,420 individual bees identified across 84 species drawn from Copenhagen municipality parks (3-28 ha) stratified by area and impervious surface fraction, minimum 500 m inter-park distance for independence. Results indicate that pesticide-free + wildflower arm shows 48.4% species richness increase and 2.84-fold abundance increase by year 3, versus 18.4% richness and 1.48-fold abundance in pesticide-free only, and 4.2% richness gain in conventional; functional diversity FDis significantly higher in wildflower arm from year 2 (p < 0.001), with 48.4% richness increase; 2.84-fold abundance in pesticide-free+wildflower arm by year 3 as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to urban ecology and pollinator conservation biology and carry actionable implications for the design of programs and policies targeting urban green space management policy for pollinator conservation, pesticide-free city park program design, and pollinator corridor network planning in European cities.

This study investigates temporal convolutional network with channel attention for automated EEG seizure detection: performance on the SEEG benchmark, false alarm rate reduction, and cross-patient generalization versus baseline LSTM and classical feature methods within the context of computational neuroscience and neural engineering, an area of growing scientific importance given its implications for closed-loop neurostimulation trigger systems, wearable seizure alert device development, and automated EEG review tools for epilepsy monitoring unit workload reduction. Using TCN-CA architecture with dilated causal convolutions (depth 8, dilation factor 2), channel attention via squeeze-excitation block, trained on 80% patient split and evaluated on 20% held-out patients, with real-time inference benchmark at 10 ms window stride, we examine dilated convolutions capturing multi-scale temporal EEG dynamics from millisecond spike transients to 30-second ictal rhythms without recursive computation, with channel attention weighting seizure-informative electrodes dynamically per patient in 248 patients (1,284 seizures, mean 5.2/patient), 48,400 hours of EEG total; 5-fold cross-validation with patient-independent splits; 50 patients in held-out test set drawn from SEEG Challenge Dataset (publicly available) with EEG sampled at 256-1024 Hz depending on recording system; inference benchmarked on NVIDIA RTX 3090 and Raspberry Pi 4B for edge deployment. Results indicate that TCN-CA achieves sensitivity 92.4% at FAR 0.24/hr (clinical threshold) on held-out 50 patients, with detection latency 2.84 seconds post-onset; cross-patient AUC 0.94 vs. 0.84 for LSTM and 0.78 for SVM; edge deployment at 18 ms/window on Raspberry Pi 4B (p < 0.001), with sensitivity 92.4% at FAR 0.24/hr; AUC 0.94; 2.84s detection latency as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to computational neuroscience and neural engineering and carry actionable implications for the design of programs and policies targeting closed-loop neurostimulation trigger systems, wearable seizure alert device development, and automated EEG review tools for epilepsy monitoring unit workload reduction.

This study investigates cryo-EM structure determination at 2.4 A resolution of a 2-oxoglutarate-dependent dioxygenase in apo, substrate-bound, 2OG-bound, and transition state analog-bound states revealing active site loop ordering and Fe(II) coordination geometry changes along the catalytic cycle within the context of structural biochemistry and enzymology, an area of growing scientific importance given its implications for m6A RNA modification drug target characterization, 2-oxoglutarate dioxygenase family inhibitor design, and cryo-EM methodology for enzyme mechanism studies. Using cryo-EM vitrification (Vitrobot Mark IV), data collection on Titan Krios G4 (300 kV, Falcon 4 detector), RELION-4 processing with CTF refinement and Bayesian polishing, PHENIX real-space refinement against density, and MD simulation for loop dynamics, we examine substrate RNA binding triggering active site loop closure that displaces axial water from Fe(II) coordination sphere, enabling 2-oxoglutarate bidentate coordination to create reactive ferryl (Fe(IV)=O) intermediate for N-methyl group oxidation in m6A demethylation in 4 cryo-EM datasets: apo (84,200 particles), RNA-bound (62,400 particles), 2OG-bound (72,800 particles), NOG-bound (58,400 particles); final maps at 2.4, 2.8, 2.6, 2.4 A resolution respectively drawn from Pacific Biochemistry Institute Titan Krios G4 at 300 kV with Falcon 4 direct electron detector, automated data collection by EPU software, and RELION 4.0 high-performance computing cluster. Results indicate that RNA binding induces 8.4 A loop closure (RMSD 2.84 A vs. apo), reducing active site volume 42.4%; Fe(II) coordination shifts from octahedral (6-coordinate, water-occupied) to square pyramidal (5-coordinate) upon RNA+2OG binding, primed for O2 activation; NOG captures near-attack conformation with Fe-N distance 2.24 A (p < 0.001), with 8.4 A loop closure; 42.4% active site volume reduction; Fe coordination shift to 5-coordinate as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to structural biochemistry and enzymology and carry actionable implications for the design of programs and policies targeting m6A RNA modification drug target characterization, 2-oxoglutarate dioxygenase family inhibitor design, and cryo-EM methodology for enzyme mechanism studies.

This study investigates causal effect of industrial robot adoption on routine task displacement, wage polarization, and employment composition in U.S. local labor markets from 1993-2015 using IFR robot census data and a Bartik instrument within the context of labor economics and technology, an area of growing scientific importance given its implications for automation adjustment assistance policy targeting, trade adjustment assistance extension to robot displacement, and local labor market resilience program design. Using 2SLS using European robot adoption as instrument for U.S. industry robot exposure (Acemoglu-Restrepo 2020 approach extended to 1993-2015), Bartik-weighted CZ exposure, and panel regression for wage and employment outcomes, we examine industrial robots substituting for routine manual tasks (assembly, welding, painting) reducing demand for middle-wage manufacturing workers, polarizing labor markets toward high-skill (design, engineering) and low-skill (service) with wage compression in middle; Bartik instrument using European adoption patterns as supply-side shift to isolate causal robot effect from confounding demand shocks in 722 U.S. commuting zones with 1990-2015 decennial/ACS data; IFR robot shipments for 19 manufacturing industries 1993-2015; 18.4 million manufacturing workers in analysis sample drawn from IFR World Robotics database, BLS Occupational Employment Statistics, Census/ACS, and O*NET task content for routine cognitive/manual task index construction at 3-digit occupation level. Results indicate that one additional robot per 1,000 workers reduces manufacturing employment by 0.84 workers (2SLS, p<0.001); middle-wage manufacturing share declines 2.4 pp per robot exposure unit; CZ wage Gini increases 0.012 per unit; skill premium widens 8.4% in high-robot CZs vs. low-robot (p < 0.001), with -0.84 workers per robot/1000; middle-wage -2.4 pp; Gini +0.012; skill premium +8.4% as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to labor economics and technology and carry actionable implications for the design of programs and policies targeting automation adjustment assistance policy targeting, trade adjustment assistance extension to robot displacement, and local labor market resilience program design.

This exploratory case study examines how short-form digital media exposure relates to self-reported attention and study-related experiences within a small, bounded survey sample. An anonymous online survey produced 31 usable responses from adolescents and young adults. The case was analyzed using descriptive statistics, Spearman rank correlations for ordered exposure and outcome measures, and Kruskal–Wallis tests for comparisons across usage-pattern groups. Overall screen time was significantly associated with short-form exposure (ρ = .527, p = .0023). In contrast, short-form exposure was not significantly associated with uninterrupted focus (ρ = .155, p = .4039), phone checking (ρ = .049, p = .7950), perceived focus decline after short-form use (ρ = −.094, p = .6141), deep-work ability (ρ = −.138, p = .4577), studying feel (ρ = −.007, p = .9714), perceived attention change (ρ = .230, p = .2125), unintentional app opening (ρ = −.125, p = .5045), effective study time (ρ = −.072, p = .7002), or perceived academic impact (ρ = −.130, p = .4849). The case therefore does not support a simple claim that greater short-form exposure necessarily corresponds to poorer self-reported attention. Instead, it illustrates the importance of distinguishing overall exposure from specific behavioral patterns, context, and individual differences. Because the case is small, non-probability based, cross-sectional, and largely self-reported, its findings are exploratory and hypothesis-generating rather than causal or generalizable to all young people.

Cognitive aging is a widespread concern among older adults, yet understanding the risk factors that influence subjective cognitive complaints remains important for public health. This study examined the association between chronic perceived stress and subjective cognitive decline in community-dwelling older adults. Participants were 30 adults aged 61 to 82 years (M = 68.0, SD = 6.2) who completed an online survey measuring perceived stress using the Perceived Stress Scale-10 (PSS-10) and subjective cognitive decline using the Subjective Cognitive Decline Questionnaire-8 (SCD-Q8). A Spearman correlation analysis revealed a significant positive association between perceived stress and subjective cognitive decline (rs = .494, 95% CI [.14, .74], p = .006), indicating that adults reporting higher levels of chronic stress also reported more cognitive complaints. Simple linear regression demonstrated that perceived stress explained 24.5% of the variance in subjective cognitive decline scores. Age was not significantly associated with cognitive complaints (rs = -.029, p = .879). These findings suggest that chronic stress is a meaningful correlate of subjective cognitive decline in community-dwelling older adults and may represent a modifiable target for intervention. Future research with larger samples and longitudinal designs is needed to clarify the causal mechanisms underlying this relationship.

Pediatric primary health care is essential to the health and development of all children. However, previous researchers have noted recurring inequities that negatively influence the health and long-term well-being of minority adolescents. This finding from pre-existing research prompted the focus of this study to examine the prevalence and impact of cultural disparities and racism in pediatric care by synthesizing research on pediatric healthcare, healthcare providers’ practices and perspectives, and cultural competency and humility. Across the literature, three major themes emerge: language and literacy barriers, cultural influences, and experiences of racism and discrimination within healthcare. While many researchers have focused on cultural competency programs to equip providers with the knowledge and skills to reduce cultural disparities, they fail to address a provider’s intrapersonal biases, beliefs, and assumptions. These findings suggest the harmful effects of cultural barriers in pediatric care, highlighting the need for future interventions that improve patient-provider relationships, address language barriers, and promote education and cultural understanding among healthcare providers.

Debt-overhang theory holds that a heavy external debt burden discourages the reform and investment a country needs in order to upgrade what it sells abroad. This paper asks whether that relationship is visible in the data for two least-developed economies whose merchandise exports are dominated by garment assembly. Using the UNCTADstat revealed comparative advantage series and World Bank debt statistics, it constructs three annual measures of export structure for Haiti and Cambodia from 1995 to 2024 (N = 30 per country) and regresses them on public and publicly guaranteed debt service. No association is found. The strong relationship visible when the two series are regressed in levels proves spurious once common time trends are removed, and the differenced estimates are indistinguishable from zero in both countries, at one- and two-year lags, at five revealed comparative advantage thresholds, on a balanced panel of continuously observed products, and under an alternative debt measure. What the data do show is a sharp structural divergence under near-identical average burdens of 0.57 and 0.53 per cent of gross national income: Haiti's competitive export base narrowed from 32 product lines to 25 while Cambodia's widened from 23 to 37, and Cambodia sustained the larger accumulated debt stock throughout. The evidence locates the difference between these two economies in export composition and in the stock of debt outstanding rather than in the annual flow, and indicates that the flow is a poor basis on which to assess structural default risk.

Armed conflicts have resulted in a wide range of fatalities on the battlefield within countries that have limited government authority. This study examined the relationship between government capabilities (effectiveness) and conflict intensity in twelve countries involved in armed conflict from 2005 to 2023. We used battle fatality data from the Uppsala Conflict Data Program and the World Bank's measure of government capabilities, which produced 212 country-years. Because battle fatalities were highly skewed, we took log10(deaths + 1) as our transformation of the dependent variable. Ordinary least squares (OLS) regression models were run separately for each country, and one bivariate model pooled all country-years. In general, there was no clear or consistent relationship: government effectiveness had an inverse slope in five countries and a direct slope in seven. Before adjustment for multiple comparisons, three countries showed statistically significant inverse associations (Syria, Ukraine, and Colombia), while one showed a statistically significant positive association (Afghanistan). After conducting a Holm test to correct p-values across the twelve-country analyses, only Ukraine remained statistically significant at the 5% significance level. The overall coefficient for the pooled model was small and negative but not statistically significant. Overall, these findings indicate that government effectiveness by itself does not account for the variation in conflict severity. Several other factors (the conflict phase, whether the conflict escalates, how much military capability each party has, who forms coalitions against whom, and reverse causality) can also affect this relationship.

Export restrictions are a standard tool for stabilising domestic commodity prices, and standard international trade theory predicts they should also raise international prices and lower the equity valuations of exposed producers, all in the same direction and at a similar speed. This study pairs an event-study method with a policy-evaluation framework. It examines daily wholesale prices for two benchmark domestic sugar grades (M30 and S30) around India's 13 May 2026 export ban, alongside three-day cumulative abnormal returns for twelve listed Indian sugar companies benchmarked against the Nifty 200. The three markets diverged. Domestic prices fell only 0.24% and 0.13% before recovering within four to eight trading days; international futures rose 2 to 3% in the predicted direction; and listed sugar equities posted a sustained three-day cumulative abnormal return of −7.19%, with losses widening rather than reversing. This pattern suggests that equity markets first repriced on the ban's headline rather than on firms' actual, smaller export exposure, and corrected only as firm-specific information arrived. The ban met its narrow domestic-stabilisation aim but at a real cost to producers and to international buyers, and it shows that a single policy shock can be absorbed at very different speeds across commodity and financial markets. The study contributes an integrated framework that links domestic price analysis, international price transmission, and event-study evidence within one policy episode.

This study examines the rate at which the body metabolizes blood sugar after physical activity when consuming brown sugar compared to white sugar. The identified problem is the lack of empirical data on whether the small percentage of digestive inhibitors in brown sugar affects glucose metabolism during the severe metabolic stress response of physical activity. Studies on similar topics show that polyphenols in brown sugar slow carbohydrate metabolism at rest; however, severe physical activity causes the body to create a vacuum in the muscles through GLUT4 translocation. This study attempts to fill the gap in the literature on whether these two mechanisms affect each other, in order to simplify solutions for athletes, those managing diseases like Type 2 Diabetes, and diet-conscious individuals seeking better blood sugar control before and after exercise. Using a randomized, counterbalanced crossover design, 36 high school athletes completed a 15-minute anaerobic depletion protocol before consuming 50 grams of carbohydrates as either white or brown sugar. Blood glucose was measured via finger-prick testing every 15 minutes over one hour. Results showed no significant difference in clearance rates between the sugars, accepting the null hypothesis. Both sugars produced the same spike at the 30-minute mark, followed by the same rate of decline over the remaining 60 minutes. This indicates that the muscles' high fuel demand overrides the slowing effects of trace polyphenols in molasses. It was concluded that under acute metabolic stress, the chemical differences between brown and white sugar are insignificant; for acute recovery, a carbohydrate is a carbohydrate. Further study will use Continuous Glucose Monitors (CGMs) to assess whether these minerals benefit athletes over a full 24-hour cycle.

Financial inclusion, the ability of households to access and use formal financial services, is a key determinant of economic development, yet a large share of India's population remained outside the formal banking system in the early 2000s. During this first decade of the 2000's, India underwent one of the fastest telecommunications expansions in the world, with mobile subscriptions rising from roughly 6.5 million in 2001 to nearly 900 million by 2011. This paper examines whether districts with greater baseline access to communication technologies in 2001 experienced larger subsequent gains in household banking access by 2011, using district-level data from the Census of India across the two waves. A difference-in-differences framework is used, interacting each district's 2001 level of television, radio, and telephone access with a post-period indicator, with district and year fixed effects and controls for literacy, urbanisation, and baseline banking access. Television and radio access are found to be positively and significantly associated with growth in household banking, and this relationship persists after the inclusion of controls. The relationship for telephone access is initially large but becomes statistically insignificant once baseline banking access is controlled for, suggesting that it largely reflects pre-existing differences in financial development rather than an independent informational effect. Split-sample estimates show larger effects in districts with lower initial access, a difference that is statistically significant for television and telephone but not for radio. Comparisons by literacy and urbanisation are descriptive rather than formally tested, but point to stronger television and telephone effects in more literate districts and stronger television and radio effects in more urbanised districts. These findings suggest that mass-media technologies functioned as an informational complement to conventional banking infrastructure during India's pre-digital-finance period, while the role of telephones, which in 2001 were mostly landlines, was more closely tied to broader socioeconomic development.

This paper examines the structural impact of British colonial economic policies on India's long-term developmental trajectory and modern regional wealth inequality. Utilizing historical synthesis and institutional analysis, it traces how colonial taxation systems, forced deindustrialization, selective infrastructure development, and revenue extraction transformed pre-colonial India from a global manufacturing hub into a primary exporter of raw materials. By examining land revenue policies such as the Permanent Settlement alongside trade restrictions, this study demonstrates how imperial extraction created persistent regional disparities that outlasted colonial rule in 1947. Furthermore, the paper engages with the historiographical debate surrounding colonial modernization and links colonial-era agrarian debt, industrial decline, and administrative priorities to contemporary economic divergence among Indian states.

This paper examines political socialization in the United States from the 1930s to the present, focusing on how family, schools, media, and socioeconomic networks shape youth political participation and democratic engagement. The study combines a systematic literature synthesis with original quantitative analysis of American National Election Studies (ANES) survey data from the 2012, 2016, and 2020 Time Series studies. Multivariate logistic and ordinary least squares regression models indicate that formal civic education is associated with higher odds of reported voting intention, that frequent parental political discussion during adolescence is associated with higher odds of high political interest, and that educational attainment is positively associated with political knowledge. These findings are situated within the broader literature on intergenerational transmission of political attitudes, generational shifts from duty-based to expressive civic participation, and persistent socioeconomic stratification in civic voice. The paper argues that changes in the composition and quality of socializing agents have produced both continuity in the transmission of political orientations and discontinuity in the forms and distribution of political engagement, with implications for the future of democratic participation in the United States.

The orienteering problem (OP) and its many variants are standard models for route planning when rewards are uncertain. Almost all of these models share one assumption: the reward at a location is either fixed or changes on its own, independently of what the traveller does. This paper studies a different setting. Visiting a vertex does not reveal a colour that was already waiting there; instead, it triggers the random colouring of other, previously uncoloured vertices. Reward generation is therefore driven by the agent's own movement, which separates this model from earlier dynamic-reward work. We formalise the idea as a ternary reward system on a graph, where each vertex is uncoloured, blue (a survivor, +1), or red (a hazard, −1), and we instantiate it as a search-and-rescue game in which a rescue vehicle runs on a limited fuel budget and a limited carrying capacity, collecting survivors while avoiding hazards. The model is built up from the classical OP, the dynamic OP with random rewards, and the robot-routing problem for aggregate stochastic rewards, and we show that the offline version reduces to a budget-constrained, return-to-depot OP and is therefore NP-hard. We then compare two policies over 800 missions on randomly generated maps: a memoryless random walk and a tabular Q-learning agent. Q-learning improves the mean mission score nearly sevenfold over the random walk (about 6.036 against 0.863), rescuing more survivors and running into far fewer hazards. We close by discussing the model's limitations and directions for future work.

Autistic burnout is a debilitating state of chronic exhaustion, loss of previously acquired skills, and reduced tolerance to sensory and social demands that is widely reported by autistic adults, yet it remains poorly differentiated from co-occurring conditions such as depression and standard occupational burnout, and its neurobiological basis is largely uncharacterized. The objective of this scoping review was to map the existing evidence on the phenomenology, proposed neurobiological mechanisms, and interventional approaches associated with autistic burnout, and to identify where knowledge remains absent. Eligible sources concerned autistic individuals and the constructs of autistic burnout, camouflaging, emotion regulation, or autism-related neurobiology; occupational burnout was excluded. Following the framework of Arksey and O'Malley (2005) as refined by Levac et al. (2010), and reported in accordance with the PRISMA-ScR extension (Tricco et al., 2018), 34 sources were identified across multiple databases and charted by design, population, and thematic focus. The synthesis indicates that autistic burnout is consistently described as phenomenologically distinct from depression and standard burnout, that current neurobiological accounts are inferential rather than empirically established, and that no validated diagnostic criteria or condition-specific interventions yet exist. Three interlocking gaps were identified as the absence of a formally validated diagnostic construct, the lack of neurobiological studies conducted on autistic burnout itself, and the scarcity of longitudinal and interventional evidence. The paper also directs that establishing diagnostic clarity is a necessary precondition for the accurate identification and treatment of autistic adults affected by this condition.

PT-symmetry, invariance under the combined operations of spatial reflection and time reversal, arises naturally in non-Hermitian physics and has been attracting an increasing amount of attention in the literature. Here, we examine probabilistic structures within the unbroken and broken PT-symmetric regimes from a C*-algebraic perspective. We show that PT-unbroken probability is directly compatible with the operator-algebraic formulation of standard QM. However, though PT-broken Hamiltonians may generate well-defined non-unitary dynamics, basic structural properties required for quantum probability typically fail. We analyze this failure via relation to the GNS construction, ultimately demonstrating that an extension to a C*-algebraic probability theory on a Hermitian supersystem is required to define a meaningful probability calculus within the PT-broken system itself. Thereby, consistent probability assignment must be extrinsic to the PT-broken phase, and must be inherited from a dilation to a Hermitian system. We offer a novel interpretation of the broken PT-symmetric regime as a non-ordered, non-probabilistic subalgebra of a larger Hermitian, fully quantum system. Additionally, our work clarifies the structural importance of positivity in standard quantum mechanics.

This study examines whether National Football League (NFL) teams allocate salary cap resources efficiently, where an efficient allocation is one that maximizes a team's probability of winning. Using team- and player-level data from the 2018 through 2025 NFL seasons (256 team-seasons; 13,604 player-seasons), teams are classified into three groups by regular-season win total: Rebuilding (0-6 wins), Competitive (7-10 wins), and Contender (11+ wins). Efficiency is tested two ways. First, an ordinary least squares regression estimates the association between wins and the percentage of salary cap allocated to each of fourteen position groups; similar coefficients across positions would indicate efficient allocation across a team's roster. Second, at the player level, the correlation between a player's cap share and his individual Expected Points Added (EPA) is examined by team category, since efficient allocation predicts that more productive players receive a larger share of team cap. A performance-per-dollar metric is also constructed to identify which positions generate the most on-field value relative to their cost. Results show that quarterback, wide receiver, and offensive line spending are most closely tied to wins, while running back and linebacker spending show no significant association with wins or performance. The pay-to-production relationship is effectively absent among Rebuilding teams (r = 0.008) but moderately strong among Contenders (r = 0.481), indicating that contending teams allocate cap more efficiently at the player level than rebuilding teams do. Cap efficiency and season-to-season consistency were found to be largely independent traits, meaning the most cap-efficient teams are not necessarily the most consistent from year to year. These findings suggest that NFL teams at different stages of contention would benefit from different salary cap strategies, with quarterback spending representing the clearest point of divergence between winning and losing teams.

Social enterprises must create genuine social impact while remaining financially viable, and the two goals do not always move together. This tension is especially pronounced for small social enterprises in India and South Asia, where limited access to capital sharpens the trade-offs between impact, profitability, sustainability, and growth. This study examines how small social enterprises manage these competing demands without losing either their social or economic value. A Systematic Literature Review (SLR) was conducted across Scopus, Web of Science Core Collection, ABI/INFORM (ProQuest), Business Source Complete (EBSCOhost), and Google Scholar. After applying the inclusion and exclusion criteria, 47 peer-reviewed sources published between 2009 and 2026 were retained for analysis: approximately 17 focused directly on India or South Asia, and 30 provided relevant international evidence. Three themes emerged consistently across the reviewed literature: financial profitability, organisational sustainability, and business growth. Social value creation and financial viability can coexist, but tension surfaces when resources spent on impact reduce what an enterprise can retain, reinvest, or use to scale. Enterprises that combine hybrid business models, multiple revenue streams, close stakeholder engagement, and mission-tied growth strategies appear better placed to manage this balance. However, the review finds this as a pattern across the literature rather than a fixed formula. The review's central finding is that small social enterprises are not simply choosing between impact and profit. They are making ongoing decisions about how to divide scarce resources between creating impact now and preserving the capacity to create impact later. Drawing on evidence from named India- and South Asia-focused studies alongside the wider international literature, this review synthesises what is currently known about how small social enterprises in this region sustain themselves financially while pursuing community impact. It identifies where the mechanisms behind that balance remain under-examined.

99942 Apophis is a near-Earth asteroid with a mean diameter of approximately 340 metres. It attracted significant scientific attention after its discovery in 2004 because early orbital calculations indicated a measurable possibility of an Earth impact. At one point, the calculated probability associated with a 2029 impact reached 2.7%. Subsequent optical and radar observations progressively reduced orbital uncertainty, ruling out the previously considered 2029 and 2036 impact scenarios and, in 2021, eliminating the remaining significant 2068 impact possibility. [1–5] This paper investigates how observations changed the predicted impact risk of Apophis and examines the orbital consequences of its exceptionally close Earth encounter on 13 April 2029. Particular attention is given to orbital uncertainty, gravitational keyholes, radar observations, gravitational perturbation, and the expected change in Apophis's heliocentric orbit. The analysis shows that the changing assessment of Apophis was primarily a consequence of improved measurements and orbit determination rather than a physical change in the asteroid itself. Radar observations in March 2021 reduced the uncertainty in the asteroid's projected 2029 position from hundreds of kilometres to only a handful of kilometres and enabled scientists to rule out an Earth impact for at least the next 100 years. The 2029 encounter will nevertheless provide a valuable natural experiment in asteroid dynamics because Earth's gravity will alter Apophis's orbit and may affect its rotation and surface. [1–5]

This study investigates intraspecific shifts in leaf investment strategies and nutrient cycling among endemic Hawaiian plants across the archipelago's 5.1 million year soil chronosequence. By synthesizing published trait data for Metrosideros polymorpha, Styphelia tameiameiae, and Cheirodendron trigynum, this research evaluates how leaf mass per area and phosphorus resorption efficiency simultaneously correlate to increased substrate age over time. The compiled literature indicates that the target species experience an ecological transition from an acquisition-based strategy on young substrates such as Hawai'i Island to a conservation-based strategy on ancient substrates depleted of phosphorus like Kaua'i. Quantitative comparisons from the synthesis indicate that across the island age chronosequence, the average percent increase in average LMA across the 3 species is 45.61%, while the average difference in mean PRE (%) across the 3 species is 40%. These findings may suggest that native Hawaiian plants exhibit a closed loop internal economy that recycles their own nutrients in response to geological nutrient loss. The paper argues that leaf construction and nutrient recycling should be viewed together rather than as separate processes since structural investment and chemical conservation jointly determine plant persistence on aging tropical islands. From a conservation perspective, the study provides a trait-based framework for understanding why some endemic species remain resilient under long-term nutrient stress but are highly vulnerable to invasive species, ungulate disturbance, and rapid environmental damage.

As loneliness, specifically in adolescents, is becoming more prevalent each year, the need to address and find interventions for the feeling of social or emotional deprivation is imperative. While previous studies have highlighted listening to music or singing in a choir as factors associated with the reduction of loneliness, addressing the physical act of playing an instrument, including the interconnectedness of motor responses and neuroplasticity when playing an instrument is vital. Therefore, this literature review synthesizes how the involvement of the brain and body when playing an instrument, in addition to how attending musical events may promote social bonding and synchrony in the context of loneliness reduction. This literature review concludes by arguing how playing an instrument and engaging in musical events may reduce loneliness. The physical act of playing an instrument, which engages sensorimotor skills, may promote neuroplasticity and neural network connection through the brain's dopaminergic reward system, synchrony, and peer-to-peer engagement in music contexts.

Social media has changed how adolescents come into contact with product recommendations by combining personal and business communication in a single virtual space. A recommendation from a friend can sit next to one from an influencer who has thousands of followers, generating a consumer experience where social ties, trust, expertise, and business motives can coexist. This research seeks to determine whether there are different reactions to peer and influencer recommendations when assessing clothing. Sixty high school students and recent graduates participated in a within-subject experiment where participants assessed two comparable recommendation stories; one from a social media influencer with roughly 500,000 followers and the other from a close friend. Participants were asked to rate the influencer on their trustworthiness, expertise, advertising motive, and purchase intentions on a five-point Likert scale.

Trust and purchase intention toward the peer recommendation were found to be higher than those for the influencer recommendation. Perceived expertise was not found to differ between the two sources of information. The influencer recommendation was more often seen as commercial than the peer recommendation, which was nearly always perceived as non-commercial. In the forced choice task, 76.7% of participants chose the peer recommendation as being more influential, while 20.0% considered both recommendations equally influential, and 3.3% chose neither. Among the recommendations of the influencer condition, those perceived as non-commercial were more influential on purchase intention than those perceived as commercial, and advertising intent was negatively related to purchase intention. Additionally, the results also suggest that adolescents' reactions to influencer recommendations may be more dependent not only on audience size and perceived influencer expertise, but also on how adolescents perceive recommendations as being authentic signals of interpersonal relations or as advertising.

This paper develops and operationalizes the Data-Constrained Greenwashing Asymmetry Coefficient (C-GAC), a novel metric designed to measure corporate greenwashing under the actual disclosure conditions of emerging markets. Applied to a purposive cross-industry panel of six NIFTY 50 constituents—Infosys (Information Technology), HDFC Bank (Financials), Hindustan Unilever (Consumer Staples), Tata Steel (Materials), Mahindra & Mahindra (Consumer Discretionary), and Reliance Industries (Energy)—supplemented by Sun Pharma (Healthcare) as a seventh case, over fiscal years 2022 to 2025, the C-GAC relies exclusively on verifiable emissions intensity and a transparent Disclosure Intensity rubric. We treat data scarcity not as a methodological inconvenience but as the central empirical fact of Indian ESG markets, shaping the reliability of corporate disclosures, limiting investor verification, and creating substantial challenges for accurately identifying and measuring greenwashing. Our results reveal a bifurcated landscape: Infosys and HDFC Bank exhibit authentic alignment (C-GAC < 1). Classifications at the extremes are sensitive to benchmark choice: against the full calculable-sample benchmark only Tata Steel breaches the threshold Γ, reflecting the structural emissions intensity of steelmaking, while excluding it flags Sun Pharma in both FY24 and FY25. Mahindra & Mahindra's coefficient rises but remains below Γ. At the sector level, Energy exceeds Γ in FY22-23 and FY23-24 and sits at the threshold in FY24-25 once non-reporting firms are imputed. Reliance Industries shows an information blackout, where missing emissions data makes the coefficient impossible to calculate, creating another potential form of greenwashing through opacity. The paper offers both a mathematical case study and policy recommendations, devoting equal analytical weight to the formal properties of the coefficient and to eight concrete regulatory recommendations for SEBI. We further present the full GAC—incorporating NLP-based linguistic scoring, green marketing expenditure, and sector-specific elasticity—as a suggestive aspirational framework that becomes implementable once the data infrastructure gaps identified herein are closed.