Miracle-dz/UniFAR-FTUs huggingface dataset:
Christianity and Subjective Wellbeing: A Study of Hong Kong

This paper examined the relationship between Christianity and subjective wellbeing by embedding in a revised homeostatic model of subjective wellbeing (SWB) which integrates the affective (homeostatically protected mood: content, happy and excited), cognitive (self-esteem, optimism and perceived control: primary control and secondary control) and experiential factors relating to SWB. In Christianity, God is the creator and lord of life and its doctrine advocates self-abnegation and committing to God; hence, three hypotheses were tested as: First, compared with those without religious belief, the Christians would be higher in SWB, secondary control and optimism, but lower in primary control and self-esteem. Second, for the Christians, each of the cognitive factors of secondary control and optimism would predict more significant SWB variance beyond the other homeostatic model factors than that of primary control and self-esteem. Third, compared with those without religious belief, each of the cognitive factors of secondary control and optimism for Christians would predict more significant SWB variance beyond the other homeostatic model factors, while that of primary control and self-esteem would predict less significant SWB variance. Four hundred and eighteen Chinese respondents were recruited in Hong Kong (178 Christians and 240 without religious belief) to complete a questionnaire. The results revealed that no significant intergroup difference was found on SWB and all cognitive factors. Besides, while Christians’ optimism predicted more significant SWB variance than primary control (3%) and self-esteem (1%), their secondary control failed to make any independent contribution. Additionally, compared with those without religious belief, Christians’ primary control (2%) and self-esteem (3%) explained lesser significant SWB variance. However, while Christians’ optimism predicted more significant variance (3%) than those without religious belief, secondary control for each of the groups failed to make any independent contribution. The results were discussed in terms of inappropriateness and non-specificity of the scale used in measuring secondary control, and a newly proposed construct of religious self-esteem.
Profiling undergraduate soil science education in Canada: Status and projected trends

Abstract: Global declines in postsecondary enrollment in soil science programs over the last several decades have been mainly attributed to an overemphasis on the connection with agronomy and production agriculture but recent enrollment increases in the USA suggest change is afoot. To determine if similar trends are occurring in Canada, we inventoried undergraduate soil science course offerings at postsecondary institutions and conducted a survey to assess the status and projected trends in soil science education. We found that 64% of universities and 37% of colleges offer undergraduate soil science courses as part of degrees or diplomas in which knowledge of soil science is important (e.g., agriculture and resource management). In Canada, there are 149 undergraduate soil science courses taught in universities and 58 at colleges. On average, there are 3.2 courses taught at each university and 1.9 at each college that offer soil science courses. Soil science programs at the University of British Columbia, University of Saskatchewan, and University of Manitoba offer between eight and nine soil science courses and represent 17.4% of the national total. Enrollments in all courses across the country are projected to be steady with some anticipated growth, trends that are consistent with those reported in the USA and the Netherlands.
Clinical Association Between Behçet Syndrome, Cytopenia, and Acquired Trisomy 8: a New Clinical Syndrome?

Objectives: Behçet syndrome (BS) is heterogeneous with clinical variability across ethnicities and geographic locations. This study analyzed the clinical characteristics of BS associated with cytopenia and trisomy 8.Methods: This was a retrospective study of Chinese BS patients in the Shanghai Behçet’s disease database who were diagnosed with cytopenia and trisomy 8 between October 2012 and April 2019. All subjects fulfilled the International Study Group (ISG) criteria or the International Criteria for Behçet’s Disease (ICBD). Results: Twenty-one patients with BS had cytopenia with trisomy 8; 16 (16/21, 76.2%) were diagnosed with myelodysplastic syndrome (MDS). Compared with 1,147 patients with BS without cytopenia, patients with BS and trisomy 8/cytopenia were more likely to be female (23.8% vs 51.8%,p= 0.011), older (37.9 ± 12.8 vs 45.1 ± 12.0, p = 0.007), have fewer skin lesions (33.3% vs 56.7%,p= 0.033), fever (52.4% vs 1.1%, p < 0.001), have higher C-reactive protein, have higher erythrocyte sedimentation rate (ESR), and display a higher rate of gastrointestinal (GI) ulceration (61.9% vs 9.2%, p < 0.001). By contrast, they had a lower leukocyte count, lower hemoglobin levels, and a lower platelet count (p < 0.05 for all comparisons). Ulcers in the ileocecal region were more frequently seen in intestinal patients with BS with trisomy 8 than in patients with BS without cytopenia (100.0% vs 41.8%; p = 0.002). Compared with 54 patients with MDS without BS symptoms, those with BS and trisomy 8-cytopenia were more likely to be female (23.8% vs 70.4%, p< 0.001) and younger (37.9 ± 12.8 vs 67.2 ± 12.4, p= 0.001). In the follow-up, three patients with BS with trisomy 8 (3/21, 14.3%) died, which is a higher rate than in patients with BS (5/1147, 0.44%) and much lower than in patients with MDS (13/54, 24.1%). Conclusions: The data on patients with BS with cytopenia and trisomy 8 were different from BS or MDS in epidemiology, clinical performance, and prognosis. BS with cytopenia and acquired trisomy 8 may be a new clinical syndrome.
Leadership, Public Health Messaging, and Containment of Mobility in Mexico During the COVID-19 Pandemic

The effectiveness of wide-spread policy measures in the midst of the COVID-19 pandemic hinges upon compliance with the ordinances. This study explores how leaders’ discourse relates to compliance with stay-at-home orders to mitigate the spread of the COVID-19 pandemic in Mexico. We use municipality-level mobility data from geolocation events of smartphone users and daily briefings from the President and Health Minister Dr. Hugo Lopez-Gatell. Using quantile regressions, sentiment analysis and topic modelling, we shed light on the dynamics between political discourse and contention of mobility. We find discrepancies between the content and tone of the President and those of the COVID-19 czar. These contrasts translate into differences on the association between the content of the speeches and mobility patterns. Our findings, using a LASSO penalized quantile regression, indicate that when President AMLO's discourse is positive, mobility tends to decrease, but when the Health Minister's discourse is positive, mobility tends to increase. Across the distribution of mobility changes, those in the inter-quantile range are more responsive to the discourse. We also find that the discourse's association to mobility is mediated by awareness of COVID-related topics and by individuals’ political affiliation. Lastly, we show that mobility patterns prior to the conferences are not causing a change in discourse which clears concerns over reverse causality. Overall, messaging across top officials shows mixed results on mobility, but even minor changes in mobility represent relevant channels of transmission in a pandemic. It remains untested whether a concerted message would effectively increase compliance with social distancing.
Further enhancement on H ∞ sliding mode control design for singular Markovian jump systems with partly known transition probabilities

This study considers the designing of the H ∞ sliding mode controller for a singular Markovian jump system described by discrete-time state-space realization. The system under investigation is subject to both matched and mismatched external disturbances, and the transition probability matrix of the underlying Markov chain is considered to be partly available. A new sufficient condition is developed in terms of linear matrix inequalities to determine the mode-dependent parameter of the proposed quasi-sliding surface such that the stochastic admissibility with a prescribed H ∞ performance of the sliding mode dynamics is guaranteed. Furthermore, the sliding mode controller is designed to assure that the state trajectories of the system will be driven onto the quasi-sliding surface and remain in there afterward. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design algorithms.
National Spatial Data Infrastructure vs Cadastre System for Economic Development: Evidence from Pakistan

The growth of Pakistan’s agriculture-based economy depends on elevating agriculture production and raising the per-capita income of rural communities. This paper evaluates the value of two simultaneous initiatives for the economic development of Pakistan, i.e., (i) reforming and modernization of the cadastre system, and (ii) the implementation of national spatial data infrastructure (NSDI). Both can provide crucial frameworks to assemble geographic information necessary for effective agriculture policies in the country. Their execution at the national level requires substantial technical, human, and finical resources. These mega initiatives may become highly challenging, due to the already shrinking economy of the country from COVID-19. The study makes use of an evaluation framework, official documents, such as project proposals, minutes of meetings, in addition to data collected through questionnaire and from ministries, such as the ministry of planning, development, and reforms (commonly known as planning commission), as well as Pakistan bureau of statistics. Our findings indicate that both the projects share some commonalities in terms of benefits, problems, and resources. However, the economic benefits of the NSDI project are high compared to the cadastre for the country, especially for effective agricultural policy-making. The results output will help practitioners from both systems to reduce the overlapping value, cost, and scope of the work involved.
Assessment of Andean lupin (Lupinus mutabilis) Genotypes for Improved Frost Tolerance

Spring frost poses a challenge for all major crops and, in the case of Lupinus mutabilis (Andean lupin) can cause severe damage or even total loss of the crop. Within the LIBBIO project consortium, we conducted a series of experiments in order to develop a suitable protocol for screening lupin germplasm under frost-simulation conditions. Four lupin accessions, one Lupinus albus and three Andean lupins were used in the experiments (L. albus Mihai, L. mutabilis LIB 220, LIB 221, LIB 222). Seedlings at four developmental stages were challenged with five different levels of ‘frost’ stress from low (−2 °C) to high (−10 °C). Notably, young seedling (cotyledons just breaking through the soil surface) showed little evidence of frost damage for temperatures down to −6 °C. At −8 °C, however, damage was evident, suggesting a cold tolerance threshold occurs at this temperature. Interestingly, for later developmental stages, when the first and second leaves were visible, notable differences were observed starting at −6 °C. The results indicate that the plant growth stage is an important parameter when screening for frost tolerance in germplasm. Overall, by identifying Andean lupin genotypes adapted to high abiotic stress factors, farmers will be able to use it as a reference crop with potentially a commercial interest from the food sector, or cosmetics, and biofuel industries.
CONTENT BASED MEDICAL IMAGE RETRIEVAL SYSTEM FOR ACCURATE DISEASE DIAGNOSES USING MODIFIED MULTI FEATURE FUSED XCEPTION MODEL

The Content Based Medical Image Retrieval (CBMIR) system helps to fulfill the need to diagnose the disease and provide proper treatment. The numerous complex deep neural networks are being applied to solve the same problem. This paper aims to design a simpler and accurate deep neural network-based CBMIR system. To achieve the same, the original Xception model is compressed by 58.33% by reducing the number of layers. The features of intermediate layers are fused to increase the accuracy of the proposed modified Xception model. This modified Multi-Feature Fused Xception (MFF-Xception) model is tested for two different X-ray image datasets: Image Retrieval in Medical Application (IRMA) dataset and the human’s chest dataset. It gives an Average Precision Rate (APR) of 90.14% for the IRMA dataset while providing 100% APR for the human chest dataset. It is also tested for another dataset containing skin images of seven different diseases and gives an APR of 100% for the skin dataset. The proposed modified MFF-Xception model also shows significant performance improvement over the original Xception model for all three datasets.
Effect of Acromioplasty on Postoperative Pain Following Rotator Cuff Repair

Background: The surgical treatment of rotator cuff tears traditionally involves rotator cuff repair (RCR) with concomitant acromioplasty. However, there is some doubt as to whether acromioplasty is of value to this procedure. Questions/Purpose: We sought to evaluate whether RCR with acromioplasty provided better outcomes than RCR without acromioplasty in a cohort of more than 1000 patients. Methods: This retrospective cohort study involved 1320 patients with rotator cuff tears who subsequently received a primary arthroscopic RCR, with acromioplasty (n = 160) or without acromioplasty (n = 1160), performed by a single surgeon. Acromioplasty was performed if there was significant mechanical impingement on the rotator cuff. To assess outcomes, all patients completed a standardized, modified L’Insalata questionnaire in which they reported the level and severity of pain at rest and during activities. An examiner assessed shoulder strength and range of motion before and 1 week, 6 weeks, 12 weeks, and 6 months after surgery. Results: Patients who had RCR with concurrent acromioplasty had a greater level of pain and more frequent pain 1 week after surgery. However, at 6 months there were no differences between patients who underwent RCR with or without acromioplasty in any patient-reported outcome (level of pain with overhead activity, at rest and during sleep; frequency of pain with activity, sleep and extreme pain, difficulty of activity overhead and behind back, level of shoulder stiffness; and overall shoulder satisfaction). The postoperative re-tear rate in both groups was 13%. Conclusion: This study showed no additional benefit to acromioplasty in patients undergoing RCR.
Subsequent criminal participation among young people first admitted to psychiatric inpatient care during early and middle adolescence

ABSTRACT Adolescents brought before court suffer excessively of mental disorders. Less is known about subsequent criminal participation of adolescent psychiatric inpatients. Our register study comprised all subjects that had between 1980 and 2010 been admitted to psychiatric inpatient care in Finland for the first time in their lives at ages 13–17 (n = 16 842), identified in the Care Register for Health Care and followed up for up to 10 years in the Register of Prosecutions, Sentences and Punishments. Incidence of register entry for any crime was 2.4/100 person-years, 4.0 in males and 1.9 in females. Incidence of violent crime was 0.9/100 person-years, 1.5 in males and 0.3 in females. Greatest risk for subsequent crime was associated with diagnoses of conduct, personality and substance use disorders (F90–92, F60–69, F10–19). Schizophrenia group diagnoses (F20–29) were associated with lowest risk. Later criminality was manifold among those who already had a crime register entry before the index treatment. Need for psychiatric inpatient care during adolescence associates with a great risk of antisocial development. Treatment needs to address this risk by systematically implementing evidence-based interventions. Health and social policies need to ensure resources and skills to these treatments.
Using Machine Learning and Feature Selection for Alfalfa Yield Prediction

Predicting alfalfa biomass and crop yield for livestock feed is important to the daily lives of virtually everyone, and many features of data from this domain combined with corresponding weather data can be used to train machine learning models for yield prediction. In this work, we used yield data of different alfalfa varieties from multiple years in Kentucky and Georgia, and we compared the impact of different feature selection methods on machine learning (ML) models trained to predict alfalfa yield. Linear regression, regression trees, support vector machines, neural networks, Bayesian regression, and nearest neighbors were all developed with cross validation. The features used included weather data, historical yield data, and the sown date. The feature selection methods that were compared included a correlation-based method, the ReliefF method, and a wrapper method. We found that the best method was the correlation-based method, and the feature set it found consisted of the Julian day of the harvest, the number of days between the sown and harvest dates, cumulative solar radiation since the previous harvest, and cumulative rainfall since the previous harvest. Using these features, the k-nearest neighbor and random forest methods achieved an average R value over 0.95, and average mean absolute error less than 200 lbs. /acre. Our top R2 of 0.90 beats a previous work’s best R2 of 0.87. Our primary contribution is the demonstration that ML, with feature selection, shows promise in predicting crop yields even on simple datasets with a handful of features, and that reporting accuracies in R and R2 offers an intuitive way to compare results among various crops.
SARS-COV-2 Spike Glycoprotein as Inhibitory Target for In silico Screening of Natural Compounds

Coronavirus disease (Covid-19) caused by SARS-Cov-2 has raised global health concerns without approved drugs to manage this life-threatening disease. This study aimed to predict the inhibitory potential of quercetin-3-o-rutinoside against SARS-Cov-2 spike glycoprotein. Targeting the SARS-Cov-2 Nucleocapsid spike glycoprotein (pdb id: 6m3m) is gaining importance. In this present study, the relationship between plant-derived natural drug and spike glycoprotein was predicted using in silico computational approach. The results were evaluated according to the glide (Schrodinger) dock score. Among the five (5) screened natural compounds, quercetin-3-o-rutinoside has the best docking score (-9.296) with the target. Molecular dynamic (MD) simulation analysis was performed for 1000ps to confirm the spike protein's stability behavior and quercetin-3-o-rutinoside complex. The MD simulation analysis validated the stability of quercetin-3-o-rutinoside in the spike protein binding pocket as a potent inhibitor. The pharmacokinetics screening of the natural compounds showed that quercetin-3-o-rutinoside possesses good oral bioavailability with no side effects.
Fixed-Time Average Consensus of Nonlinear Delayed MASs Under Switching Topologies: An Event-Based Triggering Approach

This article addresses the fixed-time average consensus problem of nonlinear multiagent systems (MASs) subject to input delay, external disturbances, and switching topologies. Different from the finite-time convergence, the convergence time of the fixed-time convergence is independent of initial conditions. Then, an event-based control strategy is presented to reach the fixed-time average consensus under switching topologies and intermittent communication. Because the nonlinear dynamics, external disturbances, switching topologies, and triggering condition for intermittent communication are considered, the fixed-time consensus problem is more challenging under the event-based control than under the continuous-time control. Besides, a new measurement error is designed based on the hyperbolic tangent function to avoid Zeno behavior. Furthermore, an improved triggering function is designed to avoid continuous monitoring. Hence, resource consumption is reduced significantly. Finally, the effectiveness of the algorithms is validated by three simulation examples.
Political Power Local Policy Uncertainty and IPO Pricing

Greater partisan alignment among lawmakers enhances their ability to respond rapidly to adverse shocks, but it also undermines the quality of checks and balances and encourages excessive governmental intervention in local areas aligned with the ruling party. We investigate how this form of local policy risk affects IPO underpricing. One standard-deviation increase in political alignment between local politicians and the federal government translates into an extra $1.58 million being left on the table, which corresponds to 5.39% of the average valuation discount. This effect is concentrated in firms that are vulnerable to legislative interventions and has important long-term implications. Our robustness analysis also shows that our baseline results are not sensitive to the inclusion/exclusion of influential states and years with high IPO activity.
Alternative Risk Premia Timing: A Point-in-Time Macro, Sentiment, Valuation Analysis

We investigate the question of dynamic allocation across a diversified range of alternative risk premia. By using a set of point-in-time indicators across macro, sentiment and valuation dimensions, we find that a majority of indicators deliver a positive information ratio for a majority of alternative risk premia over the period 2005–2020. In our empirical simulations, the macro dimension seems to have worked well, notably during recession periods. Sentiment (based on market stress and momentum) struggled during recovery periods, but added value elsewhere. Valuation has worked well from 2005 to 2013 and lost part of its appeal since then. The combination of indicators allows to deliver a higher information ratio thanks to the low correlation among them. Our research also finds that point-in-time macroeconomic variables (“nowcasters”) can add value over traditional indicators, while this improvement is not significant in the case of the market stress indicator.
Holistic Approach to Design, Test, and Optimize Stand-Alone SOFC-Reformer Systems

Reliable electrical and thermal energy supplies are basic requirements for modern societies and their food supply. Stand-alone stationary power generators based on solid oxide fuel cells (SOFC) represent an attractive solution to the problems of providing the energy required in both rural communities and in rurally-based industries such as those of the agricultural industry. The great advantages of SOFC-based systems are high efficiency and high fuel flexibility. A wide range of commercially available fuels can be used with no or low-effort pre-treatment. In this study, a design process for stand-alone system consisting of a reformer unit and an SOFC-based power generator is presented and tested. An adequate agreement between the measured and simulated values for the gas compositions after a reformer unit is observed with a maximum error of 3 vol% (volume percent). Theoretical degradation free operation conditions determined by employing equilibrium calculations are identified to be steam to carbon ratio (H2O/C) higher 0.6 for auto-thermal reformation and H2O/C higher 1 for internal reforming. The produced gas mixtures are used to fuel large planar electrolyte supported cells (ESC). Current densities up to 500 mA/cm2 at 0.75 V are reached under internal reforming conditions without degradation of the cells anode during the more than 500 h long-term test run. More detailed electrochemical analysis of SOFCs fed with different fuel mixtures showed that major losses are caused by gas diffusion processes.