Miracle-dz/UniFAR-FTUs huggingface dataset:
Trans-ancestry genome-wide association study identifies novel genetic mechanisms in rheumatoid arthritis

Trans-ancestry genetic research promises to improve power to detect genetic signals, fine-mapping resolution, and performances of polygenic risk score (PRS). We here present a large-scale genome-wide association study (GWAS) of rheumatoid arthritis (RA) which includes 276,020 samples of five ancestral groups. We conducted a trans-ancestry meta-analysis and identified 124 loci (P < 5 x 10-8), of which 34 were novel. Candidate genes at the novel loci suggested essential roles of the immune system (e.g., TNIP2 and TNFRSF11A) and joint tissues (e.g., WISP1) in RA etiology. Trans-ancestry fine mapping identified putatively causal variants with biological insights (e.g., LEF1). Moreover, PRS based on trans-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between European and East Asian populations. Our study provides multiple insights into the etiology of RA and improves genetic predictability of RA.
Semi-Cooperative Control for Autonomous Emergency Vehicles

Autonomous control of an emergency vehicle will save lives through faster transport and shorter response. Towards this goal, it must overcome the challenge of inter- acting with existing human drivers on the road. We present a game-theoretic approach for semi-cooperative control of an autonomous emergency vehicle that can interact efficiently with humans on the road. We model the interactions between autonomous and human driven cars with Social Value Orientation, a metric from social psychology, that allows the controller to leverage their influence on the trajectories of neighboring human drivers. In addition, by using a modified version of iterative best response, we direct the algorithm to converge to Nash equilibria that are cooperative. We demonstrate the efficacy of our algorithm in simulations of drivers in traffic, with a variety of traffic densities and driver personalities. In simulations of prosocial human drivers, our algorithm provides an 8% improvement in distance-traveled compared to egoistic human drivers.
Factors Influencing the Adoption of Cyber Security Standards Among Public Listed Companies in Malaysia

Employee’s failure to adhere to their organization’s cyber security policies contributes most of the cyber incidents. To secure information security systems, companies need to communicate behavioral and technical solutions to their employees, due to the fragility of the human factor since it plays a critically significant role in securing cyber systems. The necessity to safeguard information systems have speed up the evolution of the present method of cyber security, which should be based on adequately adopting cyber security standards to secure business enterprise’s assets and users in cyberspace. This paper studies factors influencing the adoption of cyber security standards among public listed companies in Malaysia. Through online survey that was distributed among 275 Public listed companies. The findings indicated that expected related benefits and perceived ease of use had significant impact on the adoption of cyber security standards. On the other hand, perceived security had played important moderating influence on the relationship between organizational factors and the adoption of cyber security standards. Keywords—Cyber security; human factor; cyberspace; cyber security standards
A new simplified space-vector PWM method for three-level inverters

In this paper, a newly developed simplified space vector PWM (SVPWM) method for three-level inverter is presented. The space vector diagram of the three-level inverter is simplified into that of a two-level inverter. So the selection of switching sequence and the calculation of the dwelling time is done as conventional two-level SVPWM method. The control of DC link neutral-point potential is easy to implement. The proposed SVPWM method can be applied to the multi-level inverter. The validity of the new SVPWM method is verified by simulation and experiment with a three-level IGBT inverter.
Helicobacter pylori infection reduces likelihood of death from advanced cancer: A longitudinal analysis from the Japanese DAIKO prospective cohort study

Background Paradoxically, patients with advanced stomach cancer who are Helicobacter pylori-positive (HP+) have a higher survival rate than those who are HP-. This finding suggests that HP infection has beneficial effects for cancer treatment. Present study examines whether HP+ individuals have a lower likelihood of death from cancer than those who are HP-. Methods and findings Prospective cohort data (n = 4,982 subjects enrolled in the DAIKO study between 2008-2010) was used to assess whether anti-HP antibody status as a surrogate for past-present HP infection was associated with cancer incidence. The median age in the primary registry was 53 years-old (range 34-69 years-old). Over the 8-year observation period there were 234 (4.7%) cancer cases in the cohort and 88 (1.8%) all-cause deaths. Urine anti-HP antibody data was available for all but one participant (n = 4,981; 99.97%). The number of HP+ and HP- individuals was 1,826 (37%) and 3,156 (63%), respectively. Anti-HP antibody distribution per birth year revealed that earlier birth year was associated with higher HP+ rates. To remove confounding factors associated with birth year, a birth year-matched cohort (n = 3,376) was generated for subsequent analyses. All-cancer incidence was significantly higher in HP+ individuals than those who were HP- (p=0.00328), whereas there was no significant difference in the cancer death rate between HP+ and HP- individuals (p=0.888). Strikingly, we found that HP+ individuals who developed cancer had a better survival rate than would be expected based on cancer incidence. These results suggest that cancer patients who are HP+ may have a higher likelihood of survival than those who are HP-. Cox regression analysis for prognostic factors revealed that the hazards ratio of HP+ was 1.59-fold (95%CI 1.17-2.26) higher than HP- in all-cancer incidence. Conclusions Potential systemic effects of HP+ status may contribute to reduced likelihood of death for patients with cancer.
Detailed patient-individual reporting of lymph node involvement in oropharyngeal squamous cell carcinoma with an online interface

Purpose/Objective: Whereas the prevalence of lymph node level (LNL) involvement in head & neck squamous cell carcinomas (HNSCC) has been reported, the details of lymphatic progression patterns are insufficiently quantified. In this study, we investigate how the risk of metastases in each LNL depends on the involvement of upstream LNLs, T-category, HPV status and other risk factors. Materials/Methods: We retrospectively analyzed patients with newly diagnosed oropharyngeal HNSCC treated at a single institution, resulting in a dataset of 287 patients. For all patients, involvement of LNLs I-VII was recorded individually based on available diagnostic modalities (PET, MR, CT, FNA) together with clinicpathological factors. To analyze the dataset, a web-based graphical user interface (GUI) was developed, which allows querying the number of patients with a certain combination of co-involved LNLs and tumor characteristics. Results: The full dataset and GUI is part of the publication. Selected findings are: Ipsilateral level IV was involved in 27% of patients with level II and III involvement, but only in 2% of patients with level II but not III involvement. Prevalence of involvement of ipsilateral levels II, III, IV, V was 79%, 34%, 7%, 3% for early T-category patients (T1/T2) and 85%, 50%, 17%, 9% for late T-category (T3/T4), quantifying increasing involvement with T-category. Contralateral levels II, III, IV were involved in 41%, 19%, 4% and 12%, 3%, 2% for tumors for tumors with and without midline extension, respectively. T-stage dependence of LNL involvement was more pronounced in HPV negative than positive tumors, but overall involvement was similar. Ipsilateral level VII was involved in 14% and 6% of patients with primary tumors in the tonsil and the base of tongue, respectively. Conclusions: Detailed quantification of LNL involvement in HNSCC depending on involvement of upstream LNLs and clinicopathological factors may allow for further personalization of CTV-N definition in the future.
The Effect of Race and Shear Stress on CRP-Induced Responses in Endothelial Cells

Background C-reactive protein (CRP) is an independent biomarker of systemic inflammation and a predictor of future cardiovascular disease (CVD). More than just a pure bystander, CRP directly interacts with endothelial cells to decrease endothelial nitric oxide synthase (eNOS) expression and bioactivity, decrease nitric oxide (NO) production, and increase the release of vasoconstrictors and adhesion molecules. Race is significantly associated with CRP levels and CVD risks. With aerobic exercise, the vessel wall is exposed to chronic high laminar shear stress (HiLSS) that shifts the endothelium phenotype towards an anti-inflammatory, antioxidant, antiapoptotic, and antiproliferative environment. Thus, the purpose of this study was to assess the racial differences concerning the CRP-induced effects in endothelial cells and the potential role of HiLSS in mitigating these differences. Methods Human umbilical vein endothelial cells (HUVECs) from four African American (AA) and four Caucasian (CA) donors were cultured and incubated under the following conditions: (1) static control, (2) CRP (10 μg/mL, 24 hours), (3) CRP receptor (FcγRIIB) inhibitor followed by CRP stimulation, (4) HiLSS (20 dyne/cm2, 24 hours), and (5) HiLSS followed by CRP stimulation. Results AA HUVECs had significantly higher FcγRIIB receptor expression under both basal and CRP incubation conditions. Blocking FcγRIIB receptor significantly attenuated the CRP-induced decrements in eNOS expression only in AA HUVECs. Finally, HiLSS significantly counteracted CRP-induced effects. Conclusion Understanding potential racial differences in endothelial function is important to improve CVD prevention. Our results shed light on FcγRIIB receptor as a potential contributor to racial differences in endothelial function in AA.
Declines and pronounced regional disparities in prescription opioid use in the United States

Background. The United States (US) opioid epidemic is a persistent and pervasive public health emergency as it continues to claim the lives of Americans through addiction and overdose. There have been sustained efforts to reverse this iatrogenic crisis over the past decade. This study analyzed the changes in prescription opioid distribution for pain and identified regional differences between 2010 and 2019. Methods and Findings. Opioid production data was obtained from the DEAs annual production quotas. Total opioid production has decreased 41.5% from 2013 (87.6 morphine mg equivalent metric tons) to 2019 (51.3). Opioid distribution from 2010 to 2019 was collected for ten prescription opioids (codeine, fentanyl, hydrocodone, hydromorphone, meperidine, methadone, morphine, oxycodone, oxymorphone, and tapentadol) from the US Drug Enforcement Administrations Automation of Reports and Consolidated Orders System. Regional variance was expressed as the ratio of the 95th to 5th percentiles of opioid distribution per state, corrected for population. The peak year for all ten prescription opioids was identified, individually, as between 2010 and 2013, except for codeine (2015). There was a 51.96% overall decrease in opioid distribution per capita with the largest decrease in Florida (-61.61%) and smallest in Texas (-18.64%). The largest quantities of opioid distribution were observed in Tennessee (520.70 morphine mg equivalent or MME per person) and Delaware (251.45) in 2011 and 2019. The smallest was Nebraska (153.39) in 2011 and Minnesota (90.49) in 2019. The highest to lowest state ratio of total opioid use, corrected for population, was sizable in 2011 (5.25) and 2019 (2.78). Similarly, the mean 95th/5th ratio was relatively stable in from 2011 (4.78 +0.70) and 2019 (5.64+0.98). The 95th/5th ratio in 2019 was greatest for methadone (10.23) and oxymorphone (10.09) and smallest for morphine (2.20) and fentanyl (2.12). Southern states (e.g MS, TN, AL, AK, DE, and NC) had the highest per capita distribution for eight of the ten opioids in 2019. The strength of the correlation between per capita hydrocodone and codeine, and hydromorphone and codeine increased significantly from 2011 to 2019. Conclusions. This study found a decline in total production and distribution for ten prescription opioids during the last half-decade. However, distribution was non-homogeneous at a state level. Analysis of regional differences revealed a three-fold difference in the 95th:5th percentile ratio between states which was unchanged over the past decade. Future research focused on identifying factors contributing to the observed regional variability could prove valuable to understanding, and potentially remediating, the pronounced disparities in prescription opioid use in the US.
The Effect of Using Zeolite (Clinoptilolite) as a Litter on Some Milk Yield and Welfare Parameters in Tent-Type Sheep Shelters

This research was conducted to determine the effect of using zeolite used as a litter in tent-type sheep shelters on milk yield, milk quality, and animal welfare parameters. A total of 34 İvesi sheep in the control (n=17) and zeolite (n=17) groups were used as animal material in the study. Milk yield, milk quality, and blood parameters were monitored for 30 days period from the beginning of the study. In-shelter climatic conditions were recorded daily. The average milk yield in the control and zeolite groups were 1137.18 and 1168.94 g on the 2nd control (P>0.05); 536.83 and 790.88 g (P<0.05) on the 3rd control (P<0.05) respectively. In terms of somatic cell count, the zeolite group got a lower value on the 2nd and 3rd control of the study (P<0.05). According to the findings obtained from the research, other milk quality parameters were not affected by zeolite. Ammonia and humidity rates in the shelter are lower in the zeolite group (P<0.05). On the 3rd control of the study, significant differences were found between the groups in terms of BUN, urea, LDL, and TAC values (P<0.05). According to the our results, it may be stated that using zeolite as a litter contributes positively to the improvement of milk yield and animal welfare in the tent-type shelter environment.
UNDERWATER GLIDERS FOR OCEAN RESEARCH

Underwater gliders are autonomous vehicles that profile vertically by buoyancy control and move horizontally on wings. Gliders are reviewed, from their conception by Stommel as an extension of autonomous profiling floats, through their development in 3 models, and including their first deployments singly and in numbers. This paper discusses the basics of glider function as implemented by University of Washington, Seaglider, Scripps Institution of Oceanography, and Webb Research in Slocum. Preliminary results are presented from a recent demonstration project that used a network of gliders off Monterey. A wide range of sensors has already been deployed on gliders, with many under development, and a wider range of future possibilities. Glider networks appear to be among the best approaches to achieving subsurface spatial resolution necessary for ocean research.
A comprehensive study of thermal noise in the MOS transistor

This paper revisits the fundamental theory of thermal noise in the MOS transistor. It has been recognized quite early that carrier velocity saturation and eventually also carrier heating degrades the thermal noise performance of short-channel MOS devices. This degradation is evaluated in terms of the delta thermal noise parameter defined initially by van der Ziel as the ratio between the thermal noise conductance at the drain and the channel conductance at VDS=0. For long-channel devices this factor is equal to 2/3. Today, there is still a controversy about what the value of this factor actually is for short-channel devices. Some authors measured a significant degradation of up to 7, attributing it mainly to carrier heating. Some other measured values that where always smaller than 2 on several devices over several technologies and pretend that there is no need of carrier heating to explain this moderate degradation, assuming that velocity saturation only can explain it. More recently, some other authors attribute this degradation to the effect of channel-length modulation. Based on a truly physical charge-based model, this paper tries to clarify the contribution of these different effects on δ. It also highlights the fact that for circuit designers, the real important parameter is not so much the δ factor but rather the ratio of the thermal noise to the transconductance at the same bias point defined as the γ thermal noise excess factor.
NBER WORKING PAPER SERIES OPTIMAL TRANSPORT NETWORKS IN SPATIAL EQUILIBRIUM

We thank Thomas Chaney, Arnaud Costinot, Don Davis, Jonathan Eaton, Cecile Gaubert, Gueorgui Kambourov, Ezra Oberfield, Stephen Redding, Esteban Rossi-Hansberg and Jonathan Vogel for helpful comments. We thank seminar participants at Chicago Booth, CEMFI, Chinese University of Hong Kong, Columbia, Dartmouth, Humboldt, MIT, National University of Singapore, Penn State, Princeton, Ridge, Science Po, SED, SMU, Toronto, Universidad de Barcelona, USC, and West Coast Trade Workshop. Edouard Schaal acknowledges financial support from the Spanish Ministry of Economy and Competitiveness, through the Severo Ochoa Programme for Centres of Excellence in R&D (SEV-2015-0563) and the Barcelona GSE (grant SG-2017-07). The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
An empirical analysis of the Co-movement of Crude, Gold, Rupee-Dollar Exchange rate and Nifty 50 Stock Index during Sub-prime and Coronavirus crisis periods SHAHANI, RAKESH and PALIWAL, RIYA

The present study empirically investigates the inter-linkages and co-movement between different asset class namely Crude, Gold, Nifty 50 Stock Index and Rupee-Dollar Exchange Rate during the two crisis periods viz. the Sub-Prime and the Coronavirus Crisis. The methodology employed for ascertaining inter-relationship includes Johansen Co-integration technique and Toda & Yamamoto Causality model. Besides this, the entire model has been set up under the VAR Framework with Variance Decomposition and Impulse Responses giving useful insight into the relationship amongst the stated variables. The results of the study however failed to identify any co-integration amongst the assets during any of the two crisis periods , however there was evidence of short run cause-effect relation amongst some of the variables. The causality flow was uni-directional from Nifty 50 to both crude and exchange rate in Period I(Sub Prime Crisis Period) while in Period II(Coronavirus Crisis Period) it was bi-directional between Gold and Nifty 50. Causality was also seen from Foreign Exchange to Gold in Period II. Further ADF Breakpoint showed all the variables were I(1) stationary and the VAR Model was also proved stable as shown by AR Characteristics Root Plots. The impulses showed that Period II or Coronavirus Crisis Period retained the innovations of other variables for longer periods than Period I ( Sub Prime Period).
Improving Customer Churn Classification with Ensemble Stacking Method

Due to the high cost of acquiring new customers, accurate customer churn classification is critical in any company. The telecommunications industry has employed single classifiers to classify customer churn; however, the classification accuracy remains low. Nevertheless, combining several classifiers' decisions improves classification accuracy. This article attempts to enhance ensemble integration via stack generalisation. This paper proposed a stacking ensemble based on six different learning algorithms as the base-classifiers and tested on five different meta-model classifiers. We compared the performance of the proposed stacking ensemble model with single classifiers, bagging and boosting ensemble. The performances of the models were evaluated with accuracy, precision, recall and ROC criteria. The findings of the experiments demonstrated that the proposed stacking ensemble model resulted in the improvement of the customer churn classification. Based on the results of the experiments, it indicates that the prediction accuracy, precision, recall and ROC of the proposed stacking ensemble with MLP meta-model outperformed other single classifiers and ensemble methods for the customer churn dataset. Keywords—Stacking ensemble; customer churn prediction; bagging; boosting
Towards Measuring User Experience based on Software Requirements

—User Experience (UX) provides insights into the users’ product perceptions while using or intending to use an application. Software products are known for complexity and changeability, starting from requirements engineering until the product operation. Users often evaluate software UX based on a prototype; however, UX is semantically embedded in the software requirements, a crucial indicator for project success. The problem of current UX evaluation methods is their dependence on the actual involvement of users or experts, a time-consuming process. First, this paper builds a benchmark dataset of UX based on textual software requirements crowdsourcing several UX experts. Second, the paper develops a machine learning model to measure UX based on the dataset. This research describes the dataset characteristics and reports its statistical internal consistency and reliability. Results indicate a high Cronbach Alpha and a low root mean square error of the dataset. We conclude that the new benchmark dataset could be used to estimate UX instantly without the need for subjective UX evaluation. The dataset will serve as a foundation of UX features for machine learning models.
Raceway under Wheel-Rail Excitation

With the increasing speed of high-speed trains, the service conditions of axle-box bearing system worsen, and meanwhile, the dynamic performance of the axle-box bearing directly affects the operational safety. However, the dynamic interactions of the axle-box bearing in the traditional vehicle-track system are often ignored. In this paper, a vehicle-track coupling dynamic model considering axle-box bearing has been built, and the effectiveness of the model is proved by field tests. Dynamic performance of the axle-box bearing has been analyzed and discussed through numerical simulations under different working conditions. Comparing the roller-raceway contact load characteristics under different working conditions, results show that the peak values of roller-outer raceway contact load with wheel-polygonal excitation are basically the same with those without wheel-rail excitation. However, most of the peak values of roller-outer raceway contact force under track irregularity and comprehensive excitation conditions are far greater than those under wheel-polygonal excitation and no wheel-rail excitation conditions, which indicates that the impact of track irregularity on the contact load is dominant.