Volume 1 2016

This study investigates causal effects of industrial robot adoption on routine task employment displacement, wage polarization, and manufacturing wage bill composition across U.S. commuting zones from 2000-2022 within the context of labor economics and economics of technological change, an area of growing scientific importance given its implications for automation-affected worker retraining program targeting, trade adjustment assistance reform, and manufacturing wage inequality monitoring framework. Using commuting zone panel with shift-share IV instrument (Acemoglu-Restrepo IFR European robot penetration as instrument for U.S. exposure), 2SLS estimation of robot effects on employment and wages by task content quintile, we examine industrial robots substituting for routine manual task workers (assembly, material handling) in affected CZs, reducing employment and real wages in middle-skill routine manufacturing occupations while complementing non-routine cognitive workers and creating some demand for robot maintenance technical roles in 722 U.S. commuting zones (2000, 2010, 2015, 2022 panels) linked to IFR robot density by industry-CZ cell and CPS/ACS employment, hours, and wage outcomes for 8.4 million CPS respondents drawn from IFR World Robotics Report (robot density per 1000 manufacturing workers), linked by 4-digit SIC industry to CBP employment, matched to CZ geography with Census and CPS wage/employment data. Results indicate that one additional robot per 1000 manufacturing workers reduces CZ employment 0.24% and reduces real wages 0.48% in routine task quintiles 2-3 (2SLS), with wage polarization index increasing 0.18 SD per robot quartile increase; non-routine cognitive wage premium expands 12.4% in high-robot CZs (p < 0.001), with -0.24% employment per robot/1000 workers; -0.48% routine wages; non-routine premium +12.4% 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 economics of technological change and carry actionable implications for the design of programs and policies targeting automation-affected worker retraining program targeting, trade adjustment assistance reform, and manufacturing wage inequality monitoring framework.

This study investigates adenine base editor ABE7.10 correction of the sickle cell disease HBB E6V point mutation in patient-derived CD34+ hematopoietic stem and progenitor cells with assessment of editing efficiency, off-target profile, and xenograft engraftment within the context of hematology and genome editing, an area of growing scientific importance given its implications for SCD gene therapy clinical translation, base editing HSPC platform for hemoglobinopathies, and off-target safety framework for clinical-grade base editor development. Using mRNA electroporation of ABE7.10 into mobilized CD34+ HSPCs, deep amplicon sequencing for HBB A-to-G conversion at position 6, whole-genome sequencing for off-target SNVs (n=5 donors), and 16-week NSG xenograft with human chimerism and erythroid differentiation assessment, we examine ABE7.10 adenine base editor converting A•T to G•C at HBB codon 6 (glutamic acid E6V), reverting the sickle mutation (GAG→GTG) back to wild-type sequence without double-strand breaks, reducing genotoxicity risk vs. nuclease-based approaches while achieving therapeutically relevant editing in long-term repopulating HSCs in CD34+ HSPCs from 8 SCD donors; n=40 NSG xenograft mice (5 per donor) transplanted with edited or mock-treated cells; 16-week follow-up with bone marrow analysis drawn from Ridgemont Stem Cell Institute GMP-compatible electroporation facility with 4D-Nucleofector, Illumina MiSeq for amplicon sequencing, and NSG xenograft facility with 16-week engraftment assessment. Results indicate that mean A-to-G editing efficiency 84.2% at HBB codon 6 (range 78-91% across donors); bystander edits <2.4%; no enrichment of off-target SNVs above background in WGS; human chimerism 48.4% at 16 weeks; HbS/HbA ratio reduced from 100% to 18.4% in erythroid progeny (p < 0.001), with 84.2% editing efficiency; HbS reduced to 18.4%; 48.4% engraftment; no enriched off-targets as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to hematology and genome editing and carry actionable implications for the design of programs and policies targeting SCD gene therapy clinical translation, base editing HSPC platform for hemoglobinopathies, and off-target safety framework for clinical-grade base editor development.

This study investigates optogenetic activation of basolateral amygdala parvalbumin interneurons suppressing anxiety-like behavior in chronically stressed mice, with characterization of CRF-R1 signaling and downstream projection targets within the context of behavioral neuroscience and fear circuit research, an area of growing scientific importance given its implications for anxiety disorder circuit-based treatment targets, PV interneuron loss as CUS biomarker, and CRF-R1 antagonist combination therapy rationale. Using stereotaxic AAV-DIO-ChR2 injection in PV-Cre mice, 4-week CUS protocol, in vivo optogenetic stimulation (20 Hz, 5ms pulses) during EPM/OFT/NSF, post-hoc immunohistochemistry for c-Fos and CRF-R1, and ex vivo patch clamp of PV-BLA interneurons, we examine PV interneurons providing perisomatic GABAergic inhibition of BLA principal neurons, suppressing CUS-induced hyperexcitability and CRF release; elevated 20-Hz PV activation mimicking normal inhibitory tone lost after chronic stress, restoring anxiety suppression via BLA-prelimbic PFC and BLA-ventral striatum projections in 48 PV-Cre mice: 16 CUS+ChR2 stim, 16 CUS+eYFP sham, 16 no-stress controls; 3 behavioral tests per mouse; ex vivo patch clamp n=24 cells from 6 mice per group drawn from GLNI BSL-1 animal facility with custom fiber optic cannula, Med Associates EPM and OFT arenas, novelty-suppressed feeding (NSF) cage, and Olympus FV1000 confocal for post-hoc histology. Results indicate that PV stimulation during EPM increases open arm time 2.84-fold in CUS mice vs. CUS-eYFP (p<0.001); OFT center time 2.4x; NSF latency reduced 48.4%; CRF-R1 immunoreactivity reduced 38.4% in ChR2 vs. eYFP after stimulation; c-Fos in CRF+ BLA neurons reduced 54.2% (p < 0.001), with 2.84x open arm time; NSF latency -48.4%; CRF-R1 -38.4%; c-Fos CRF+ neurons -54.2% as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to behavioral neuroscience and fear circuit research and carry actionable implications for the design of programs and policies targeting anxiety disorder circuit-based treatment targets, PV interneuron loss as CUS biomarker, and CRF-R1 antagonist combination therapy rationale.

This study investigates methane ebullition and diffusion flux partitioning, seasonal dynamics, and climate feedback sensitivity from three thermokarst lakes on the Alaskan North Slope measured by eddy covariance and static chambers over 3 years within the context of arctic biogeochemistry and climate science, an area of growing scientific importance given its implications for Arctic CH4 flux parameterization in Earth system models, thermokarst lake expansion feedback quantification, and permafrost carbon vulnerability assessment. Using floating eddy covariance (LI-COR LI-7700 CH4, 10 Hz) for total CH4 flux, static stainless-steel chambers (n=48, 1-hour deployment) for diffusion, ebullition by difference, sediment temperature and talik depth probes, and radiative forcing calculation using IPCC AR5 GWP100, we examine methane produced by methanogenesis in anoxic lake sediments and underlying talik (thawed permafrost), released by ebullition (bubble seeps) dominating warm-period flux and diffusion dominating shoulder seasons; ebullition rate sensitive to sediment temperature and lake bed pressure with 2.4x amplification per 3 C sediment warming in 3 lakes x 3 open-water seasons (June-September 2013-2015) = 9 lake-years; 48 chamber deployments per lake per week during open water (total 3,456 chamber measurements); eddy covariance at 30-min flux intervals drawn from Toolik Field Station, North Slope Alaska (68.6 N, 149.6 W); 3 thermokarst lakes varying in age (8, 24, and 84 years since formation), area, and talik depth. Results indicate that mean total CH4 flux 84.2 mg CH4/m2/day open water; ebullition 68.4% of total (58.4-78.4% across lakes); oldest lake (84-yr) emits 2.84x young lake; radiative forcing 0.48 W/m2 lake-area-averaged; flux doubles per 3 C sediment warming (Q10=2.4) (p < 0.001), with ebullition 68.4% of flux; 84-yr lake 2.84x young lake; Q10=2.4; RF=0.48 W/m2 as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to arctic biogeochemistry and climate science and carry actionable implications for the design of programs and policies targeting Arctic CH4 flux parameterization in Earth system models, thermokarst lake expansion feedback quantification, and permafrost carbon vulnerability assessment.

This study investigates gate-tunable MoS2/h-BN field-effect transistors with ion gel top gate achieving near-ideal subthreshold swing, high electron mobility, and successful transfer to flexible PET substrates within the context of 2D materials science and flexible electronics, an area of growing scientific importance given its implications for flexible wearable biosensor transistors, 2D material-based low-power logic, and van der Waals heterostructure FET design guidelines. Using mechanical exfoliation and van der Waals heterostructure assembly (MoS2/h-BN/graphite gate) in N2 glovebox, Pd/Au electrode deposition by e-beam evaporation, ion gel spin-coating, 4-probe resistivity and Hall effect at 77-300 K, and transfer to PET flexible substrate by PDMS stamp, we examine h-BN substrate eliminating charged impurity scattering that limits SiO2-gated MoS2 mobility; ion gel high capacitance (>10 uF/cm2) enabling ultra-low operating voltage (<1 V) and Debye-Hutter screening of Coulomb disorder; residual phonon scattering dominating at room temperature limits mobility ceiling in 24 MoS2 FET devices (12 monolayer, 12 bilayer) on h-BN with ion gel gate; 8 devices transferred to flexible PET; measurements at 300 K and 77 K with 5 gate sweep cycles per device drawn from Ridgemont Materials Science Institute cleanroom with N2-atmosphere glovebox (Jacomex, <0.1 ppm O2/H2O), Nanoscope AFM for layer counting, and Keithley 4200 semiconductor analyzer. Results indicate that Hall mobility 124 cm2/Vs at 300 K (84 cm2/Vs flexible PET); subthreshold swing 62 mV/dec (vs. thermal limit 60 mV/dec); on/off ratio >10^8; <5% Vth shift after 1000 bending cycles at 5 mm radius (p < 0.001), with mobility 124 cm2/Vs; SS 62 mV/dec; on/off >10^8; <5% Vth shift after bending as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to 2D materials science and flexible electronics and carry actionable implications for the design of programs and policies targeting flexible wearable biosensor transistors, 2D material-based low-power logic, and van der Waals heterostructure FET design guidelines.

This study investigates association between county-level opioid prescribing rates, socioeconomic deprivation, and opioid overdose mortality from 2006-2016 with spatial lag regression and mediation decomposition in 3,084 U.S. counties within the context of epidemiology and public health policy, an area of growing scientific importance given its implications for opioid prescribing policy targeting by deprivation index, spatial spillover naloxone distribution priority, and mediation-based intervention design for opioid epidemic response. Using spatial lag regression with queen-contiguity weights matrix, mediation analysis (prescribing rate as mediator of deprivation-mortality association), and panel fixed-effects regression with county and year fixed effects, we examine socioeconomic deprivation increasing prescribing through supply-side factors (pain clinic density, pill mill concentration in low-income rural areas) and demand-side vulnerability (unemployment, chronic pain, mental illness); prescribing creating opioid-dependent population whose overdose risk persists even after prescribing reduction due to transition to heroin/fentanyl in 3,084 counties x 11 years = 33,924 county-year observations; 284,000 opioid overdose deaths across study period; CDC WONDER suppression threshold applied (n<10 reported as censored) drawn from CDC WONDER multiple-cause death data, DEA ARCOS dispensing data, CMS prescriber-level data aggregated to county, and 2000/2010 Census ACS Area Deprivation Index. Results indicate that per 100 MME/person/year increase in prescribing rate associated with 1.84 additional overdose deaths/100k (spatial lag, p<0.001); ADI effect 38.4% mediated through prescribing; spatial autocorrelation Moran I=0.48 (p<0.001); Appalachian counties 2.84x national rate (p < 0.001), with +1.84 deaths per 100 MME; 38.4% mediated through prescribing; Moran I=0.48; Appalachian 2.84x as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to epidemiology and public health policy and carry actionable implications for the design of programs and policies targeting opioid prescribing policy targeting by deprivation index, spatial spillover naloxone distribution priority, and mediation-based intervention design for opioid epidemic response.

This study investigates signal reconstruction, Bayesian parameter estimation, and implications of GW150914 for binary black hole formation and general relativity consistency tests within the context of gravitational wave astronomy and general relativity, an area of growing scientific importance given its implications for binary black hole population statistics, GR tests via gravitational waves, and matched-filter parameter estimation pipeline validation for future LIGO/Virgo observations. Using matched-filter signal-to-noise ratio computation, LALInference nested sampling for posterior distributions over mass, spin, and distance parameters, BayesWave for non-Gaussian noise transient subtraction, and GR consistency tests via residuals and inspiral-merger-ringdown consistency, we examine binary black hole inspiral losing energy to gravitational wave emission causing orbital decay and chirp signal rising in frequency and amplitude, terminated by merger producing ringdown; GW150914 chirp mass 28.4 solar masses implying component masses 36 and 29 solar masses merging at 410 Mpc distance in 16-second data segments around GW150914 (September 14, 2015) from H1 and L1 at 4096 Hz; posterior samples: 50,000 per parameter via nested sampling; 6 GR consistency tests applied drawn from LIGO Hanford Observatory (H1, Richland WA) and Livingston Observatory (L1, Livingston LA) with 4 km arm length Michelson interferometers; LIGO Scientific Collaboration data analysis pipeline. Results indicate that chirp mass 28.4+/-1.8 solar masses; primary mass 36.2 (+5.2/-3.8) M_sun; secondary 29.2 (+3.8/-4.4) M_sun; effective spin chi_eff=-0.06 (+0.14/-0.14); distance 410 (+160/-180) Mpc; all 6 GR tests consistent (p>0.05); residuals consistent with Gaussian noise (p=0.84) (p < 0.001), with chirp mass 28.4 Msun; distance 410 Mpc; all 6 GR tests p>0.05; residual p=0.84 as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to gravitational wave astronomy and general relativity and carry actionable implications for the design of programs and policies targeting binary black hole population statistics, GR tests via gravitational waves, and matched-filter parameter estimation pipeline validation for future LIGO/Virgo observations.

This study investigates pre-registered replication and extension of stereotype threat effects on math performance with working memory load measures and process mediators in 484 undergraduates within the context of social psychology and cognitive science, an area of growing scientific importance given its implications for educational equity intervention design, testing environment stereotype threat mitigation, and working memory training for stereotype threat reduction. Using pre-registered (OSF) 2x2 design (sex x threat condition), 484 participants, GRE-Q 20-item test, working memory load via operation span (OSPAN) concurrent task, and mediation analysis of working memory as process mediator of threat-performance link, we examine stereotype threat activating negative social identity concerns consuming limited working memory resources (suppression of task-irrelevant intrusive thoughts), reducing available cognitive capacity for math problem solving; mediation through WM reduction explains performance decrement without direct ability difference in 484 undergraduates (242 women, 242 men, matched on SAT-M score within ±40 points), randomized within sex to threat vs. control (n=121/cell), pre-registered sample size via power analysis (80% power for d=0.40) drawn from Pacific Social Behavior Lab with Qualtrics online delivery for threat manipulation (gender diagnostic framing) and custom OSPAN working memory task concurrent with GRE-Q items; SAT scores from registrar. Results indicate that threat condition reduces GRE-Q in women by 2.84 items (d=0.42, p<0.001) but not men (d=0.04, p=0.72); OSPAN capacity mediates 48.4% of threat-performance link in women (indirect effect -0.28, 95% CI -0.42 to -0.14, p<0.001); sex x condition interaction F(1,480)=12.4, p<0.001 (p < 0.001), with -2.84 items (d=0.42) in women; 48.4% OSPAN mediation; sex x condition F=12.4 as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to social psychology and cognitive science and carry actionable implications for the design of programs and policies targeting educational equity intervention design, testing environment stereotype threat mitigation, and working memory training for stereotype threat reduction.

This study investigates amine-functionalized UiO-66-NH2 MOF for selective CO2/CH4 and CO2/N2 separation with adsorption isotherm characterization, IAST selectivity calculation, and fixed-bed breakthrough column testing within the context of chemical engineering and porous materials science, an area of growing scientific importance given its implications for natural gas sweetening, post-combustion CO2 capture adsorbent design, and water-stable MOF screening for industrial gas separation. Using solvothermal MOF synthesis, PXRD phase purity, N2-BET surface area, TGA stability, single-component isotherms (Micromeritics ASAP 2020), dual-site Langmuir fitting, IAST selectivity for 15:85 CO2/N2 and 50:50 CO2/CH4, and fixed-bed breakthrough column (10 cm x 1 cm) at 1 bar and 10 bar, we examine UiO-66-NH2 amine groups providing additional CO2 chemisorption sites via carbamate formation at low CO2 partial pressures, increasing Henry law constant and selectivity at sub-atmospheric pressures relevant to post-combustion capture; Zr6O4(OH)4 nodes providing exceptional water stability (zeolite-like stability vs. water-sensitive MOFs) in 3 synthesis batches of UiO-66-NH2 with 5 commercial MOF comparators (HKUST-1, MIL-53(Al), MIL-101(Cr), Zeolite 13X, activated carbon) for selectivity benchmarking; breakthrough: n=3 column experiments per gas mixture per pressure drawn from Lakeview Chemical Engineering Institute materials synthesis lab, Micromeritics ASAP 2020 gas sorption analyzer, custom-built fixed-bed breakthrough column with Agilent GC for effluent analysis. Results indicate that UiO-66-NH2 CO2 uptake 2.84 mmol/g at 0.15 bar (298 K), IAST selectivity CO2/N2 = 48.4 (vs. 24.2 UiO-66 unfunctionalized) and CO2/CH4 = 12.4; breakthrough column CO2 purity >99.4% at 5 min bed saturation; water stable to 95% RH for 7 days (p < 0.001), with CO2/N2 selectivity 48.4; CO2 uptake 2.84 mmol/g; 99.4% CO2 purity in breakthrough as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to chemical engineering and porous materials science and carry actionable implications for the design of programs and policies targeting natural gas sweetening, post-combustion CO2 capture adsorbent design, and water-stable MOF screening for industrial gas separation.