One-Dimensional Three-Body Scattering Problem Used As A Testing Ground For The K-Matrix Method For Scattering Reactions Of Complex Systems

The scattering reactions of three equal-mass particles constrained to move in a straight line and interacting with each other via zero-range potentials have been analyzed on the basis of the extended R-matrix theory. The simplicity of the model facilitates an exposition of the complexities that result from the existence of rearrangement channels and from the possibility for breakup into three-body channels. The conventional expressions for the K matrix and the T matrix are derived on a rigorous basis. A practical method for approximating the continuum of three-body breakup channels by a discrete set is used to carry out a distorted-wave Born approximation (DWBA) K-matrix calculation of the probabilities for transmission, knockout, and breakup when one particle is incident on a bound state of the other two. This method is found to give much better results than a DWBA T-matrix calculation

Leveraging population admixture to characterize the heritability of complex traits.

Despite recent progress on estimating the heritability explained by genotyped SNPs (h(2)g), a large gap between h(2)g and estimates of total narrow-sense heritability (h(2)) remains. Explanations for this gap include rare variants or upward bias in family-based estimates of h(2) due to shared environment or epistasis. We estimate h(2) from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (h(2)γ). We show that h(2)γ = 2FSTCθ(1 - θ)h(2), where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We applied this approach to the analysis of 13 phenotypes in 21,497 African-American individuals from 3 cohorts. For height and body mass index (BMI), we obtained h(2) estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of h(2)g in these and other data but smaller than family-based estimates of h(2)

Flexible and twistable ZnMn2O4-electrodeposited yarn supercapacitors for wearable electronics

The growing demand for wearable electronics has driven interest in flexible fiber-based supercapacitors (F-SCs) as power sources, offering tunable sizes, adaptable shapes, and versatile design possibilities. This study presents the fabrication of a highly flexible and twistable fiber-shaped yarn supercapacitor (F-SC) via direct electrodeposition of ternary metal-oxide nanostructures (ZnMn2O4) onto flexible and conductive carbon yarn substrates. The uniform growth of ZnMn2O4 nanostructures on the carbon yarn not only enhances the capacitive performance of the fabricated devices but also significantly enhances the mechanical integrity of the electrodes, ensuring excellent bending and electrochemical stability for the F-SC device. The device exhibits a high areal capacitance of 87.6 mF/cm2 at a scan rate of 10 mV/s and 35.4 mF/cm2 at a current density of 0.1 mA/cm2. Furthermore, it retains 92% of its capacitance after 10,000 charge–discharge cycles, achieving energy and power densities of 11 μWh/cm2 and 385 μW/cm2, and maintaining consistent performance under varying bending and twisting conditions. This work offers a simple, cost-effective, and efficient strategy for developing flexible and twistable fiber electrodes using a straightforward electrodeposition process. The fabricated electrodes hold great potential in developing flexible energy storage technologies and enabling seamless integration into next-generation portable and wearable electronics

Genome-wide Comparison of African-Ancestry Populations from CARe and Other Cohorts Reveals Signals of Natural Selection

The study of recent natural selection in human populations has important applications to human history and medicine. Positive natural selection drives the increase in beneficial alleles and plays a role in explaining diversity across human populations. By discovering traits subject to positive selection, we can better understand the population level response to environmental pressures including infectious disease. Our study examines unusual population differentiation between three large data sets to detect natural selection. The populations examined, African Americans, Nigerians, and Gambians, are genetically close to one another (FST < 0.01 for all pairs), allowing us to detect selection even with moderate changes in allele frequency. We also develop a tree-based method to pinpoint the population in which selection occurred, incorporating information across populations. Our genome-wide significant results corroborate loci previously reported to be under selection in Africans including HBB and CD36. At the HLA locus on chromosome 6, results suggest the existence of multiple, independent targets of population-specific selective pressure. In addition, we report a genome-wide significant (p = 1.36 × 10−11) signal of selection in the prostate stem cell antigen (PSCA) gene. The most significantly differentiated marker in our analysis, rs2920283, is highly differentiated in both Africa and East Asia and has prior genome-wide significant associations to bladder and gastric cancers

Genome-wide Scan of 29,141 African Americans Finds No Evidence of Directional Selection since Admixture

The extent of recent selection in admixed populations is currently an unresolved question. We scanned the genomes of 29,141 African Americans and failed to find any genome-wide-significant deviations in local ancestry, indicating no evidence of selection influencing ancestry after admixture. A recent analysis of data from 1,890 African Americans reported that there was evidence of selection in African Americans after their ancestors left Africa, both before and after admixture. Selection after admixture was reported on the basis of deviations in local ancestry, and selection before admixture was reported on the basis of allele-frequency differences between African Americans and African populations. The local-ancestry deviations reported by the previous study did not replicate in our very large sample, and we show that such deviations were expected purely by chance, given the number of hypotheses tested. We further show that the previous study’s conclusion of selection in African Americans before admixture is also subject to doubt. This is because the FST statistics they used were inflated and because true signals of unusual allele-frequency differences between African Americans and African populations would be best explained by selection that occurred in Africa prior to migration to the Americas

Leveraging population admixture to explain missing heritability of complex traits

Despite recent progress on estimating the heritability explained by genotyped SNPs (hg2), a large gap between hg2 and estimates of total narrow-sense heritability (h2) remains. Explanations for this gap include rare variants, or upward bias in family-based estimates of h2 due to shared environment or epistasis. We estimate h2 from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (hγ2). We show that hγ2 = 2FSTCθ(1−θ)h2, where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We examined 21,497 African Americans from three cohorts, analyzing 13 phenotypes. For height and BMI, we obtained h2 estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of hg2 in these and other data, but smaller than family-based estimates of h2

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Weighting versus pruning in rule validation for detecting network and host anomalies

For intrusion detection, the LERAD algorithm learns a succinct set of comprehensible rules for detecting anomalies, which could be novel attacks. LERAD validates the learned rules on a separate held-out validation set and removes rules that cause false alarms. However, removing rules with possible high coverage can lead to missed detections. We propose to retain these rules and associate weights to them. We present three weighting schemes and our empirical results indicate that, for LERAD, rule weighting can detect more attacks than pruning with minimal computational overhead