Miracle-dz/UniFAR-FTUs huggingface dataset:
(Almost Full) EFX Exists for Four Agents (and Beyond)

The existence of EFX allocations is a major open problem in fair division, even for additive valuations. The current state of the art is that no setting where EFX allocations are impossible is known, and EFX is known to exist for ($i$) agents with identical valuations, ($ii$) 2 agents, ($iii$) 3 agents with additive valuations, ($iv$) agents with one of two additive valuations and ($v$) agents with two-valued instances. It is also known that EFX exists if one can leave $n-1$ items unallocated, where $n$ is the number of agents. We develop new techniques that allow us to push the boundaries of the enigmatic EFX problem beyond these known results, and, arguably, to simplify proofs of earlier results. Our main results are ($i$) every setting with 4 additive agents admits an EFX allocation that leaves at most a single item unallocated, ($ii$) every setting with $n$ additive valuations has an EFX allocation with at most $n-2$ unallocated items. Moreover, all of our results extend beyond additive valuations to all nice cancelable valuations (a new class, including additive, unit-demand, budget-additive and multiplicative valuations, among others). Furthermore, using our new techniques, we show that previous results for additive valuations extend to nice cancelable valuations.
Artificial Intelligence Enhanced Rapid and Efficient Diagnosis of Mycoplasma Pneumoniae Pneumonia in Children Patients

Artificial intelligence methods have been increasingly turning into a potentially powerful tool in the diagnosis and management of diseases. In this study, we utilized logistic regression (LR), decision tree (DT), gradient boosted decision tree (GBDT), support vector machine (SVM), and multilayer perceptron (MLP) as machine learning models to rapidly diagnose the mycoplasma pneumoniae pneumonia (MPP) in children patients. The classification task was carried out after applying the preprocessing procedure to the MPP dataset. The most efficient results are obtained by GBDT. It provides the best performance with an accuracy of 93.7%. In contrast to standard raw feature weighting, the feature importance takes the underlying correlation structure of the features into account. The most crucial feature of GBDT is the"pulmonary infiltrates range"with a score of 0.5925, followed by"cough"(0.0953) and"pleural effusion"(0.0492). We publicly share our full implementation with the dataset and trained models at https://github.com/zhenguonie/2021_AI4MPP.
Selection and Validation of Reference Genes for RT-qPCR Analysis in Spinacia oleracea under Abiotic Stress

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is an accurate and convenient method for mRNA quantification. Selection of optimal reference gene(s) is an important step in RT-qPCR experiments. However, the stability of housekeeping genes in spinach (Spinacia oleracea) under various abiotic stresses is unclear. Evaluating the stability of candidate genes and determining the optimal gene(s) for normalization of gene expression in spinach are necessary to investigate the gene expression patterns during development and stress response. In this study, ten housekeeping genes, 18S ribosomal RNA (18S rRNA), actin, ADP ribosylation factor (ARF), cytochrome c oxidase subunit 5C (COX), cyclophilin (CYP), elongation factor 1-alpha (EF1α), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), histone H3 (H3), 50S ribosomal protein L2 (RPL2), and tubulin alpha chain (TUBα) from spinach, were selected as candidates in roots, stems, leaves, flowers, and seedlings in response to high temperature, CdCl2, NaCl, NaHCO3, and Na2CO3 stresses. The expression of these genes was quantified by RT-qPCR and evaluated by NormFinder, BestKeeper, and geNorm. 18S rRNA, actin, ARF, COX, CYP, EF1α, GAPDH, H3, and RPL2 were detected as optimal reference genes for gene expression analysis of different organs and stress responses. The results were further confirmed by the expression pattern normalized with different reference genes of two heat-responsive genes. Here, we optimized the detection method of the gene expression pattern in spinach. Our results provide the optimal candidate reference genes which were crucial for RT-qPCR analysis.
Drug Resistance Conferring Mutation and Genetic Diversity of Mycobacterium tuberculosis Isolates in Tuberculosis Lymphadenitis Patients; Ethiopia

Background Tuberculosis lymphadenitis (TBLN) is a growing public health concern in Ethiopia. However, there is limited information available on gene mutations conferring drug resistance and genetic diversity of M. tuberculosis isolates from TBLN patients. Methods Drug resistance and genetic diversity analysis were done on 91 M. tuberculosis isolates from culture positive TBLN patients collected between 2016 and 2017. Detection of mutations conferring resistance was carried out using GenoType MTBDRplus VER 2.0. Thereafter, isolates were typed using spoligotyping. Results Out of the 91 strains, mutations conferring resistance to rifampicin (RIF) and isoniazid (INH) were observed in two (2.2%) and six (6.6%) isolates, respectively. The two RIF resistant isolates displayed a mutation at codon 531 in the rpoB gene with amino acid change of S531L. Among the six INH resistant strains, four isolates had shown mutation at the KatG gene at codon 315 with amino acid change of S315T, one isolate had a mutation at the inhA gene at codon 15 with amino acid change of C15T and one isolate had a mutation at the inhA gene with unknown amino acid change. All drug resistant isolates were from treatment naive TBLN patients. The dominantly identified Spoligo International Types (SITs) were SIT25, SIT149, and SIT53, respectively; these accounted for 43% of the total number of strains. The isolates were grouped into four main lineages; Lineage 1 (2, 2.2%), Lineage 3 (38, 41.7%), Lineage 4 (49, 53.8%) and Lineage 7 (2, 2.2%). Four out of six (66.7%) isolates with drug resistance conferring mutations belonged to clustered strains (strains with shared SIT). Conclusion The detection of drug resistant conferring mutation in treatment naïve TBLN patients together with detection of drug resistant isolates among clustered strains might suggest resistant strains' transmission in the community. This needs to be carefully considered to prevent the spread of drug resistant clones in the country.
Impact of a Yogic Breathing Technique on the Well-Being of Healthcare Professionals During the COVID-19 Pandemic

Background The COVID-19 pandemic has created unprecedented challenges for healthcare globally, the brunt of which has been borne by the health care providers (HCPs). These challenges are felt more keenly in India, as they stretch an insufficiently resourced healthcare system. The long hours, cross over of responsibilities, lack of resources to adequately care for patients, and concerns around safety of self and loves ones, have led to a spike in anxiety, depression, insomnia and other stress – related disorders in healthcare providers. Sudarshan Kriya Yoga (SKY) is a mind-body intervention that has been studied in multiple clinical populations. Prior to this study, there has been no exploration of the impact of SKY on healthcare providers, specifically the impact of a mind-body intervention like SKY on HCPs during a pandemic. Objective This study aims to investigate the impact of SKY on the well-being of HCPs during the COVID-19 pandemic. Methods We conducted a pilot feasibility study with a single arm pre-post design. SKY was taught to participants in a 4-day online breath and meditation workshop. We measured outcomes related to depression, anxiety, resilience, life satisfaction, and quality of sleep. Results Ninety-two subjects completed the study survey before and after the intervention. A significant reduction was observed in the levels of stress, anxiety and depression immediately after the program. In addition, the participants reported sig1nificant improvement in life satisfaction, resilience, and the quality of their sleep. Conclusion The results indicate that SKY breathing technique had a positive impact on the well-being of healthcare professionals during the pandemic. Participants experienced improved quality of sleep, enhanced satisfaction with life, and increased resilience after SKY. This pilot study provides important data for future multi-site randomized controlled trials to study the impact of yogic techniques on well-being of the HCPs.
Correlation Between Academic and Clinical Practice Performance of Nursing Students at a Pediatrics and Child Health Nursing Course; Mizan-Tepi University, Ethiopia

Background Members of the nursing profession face problems in relating knowledge with practice. However, there was no study on the correlation between academic and practice performance of pediatrics nursing in Ethiopia. Methods A cross-sectional study was conducted at Mizan-Tepi University using 396 nursing students’ academic and practice achievements on a pediatric nursing course. SPSS version 21.0 was used for analysis. Spearman’s rho correlation (rs), one way ANOVA, independent t-test and determination coefficient (R2) were computed at p<0.05. Results The academic performance was strongly correlated with practice performance of the 2015 (rs (394) = 0.7, p<0.001) and 2017 (rs (394) = 0.7, p<0.001) batches of regular students. However, there was a moderate correlation between academic and practice performance for the batch of 2016 regular students (rs(394) = 0.43, p<0.001). There was a moderate correlation between academic and practice performance of the 2015 (rs (394) = 0.6) and 2016 (rs (394) = 0.51, p<0.001) batches of summer students. Linear regression analysis showed that academic performance explained 17.9% to 44.1% of variability in practice performance of the regular students. The linear regression analysis also showed that academic performance explained 26.5% to 41.2% of the variability in the practice performance of summer students. Independent T-test revealed significant mean performance difference by admission type (academic (t (144.7) = 6.43, p<0.001) and practice (t (115.5) = 5.71, p<0.001)). The mean performance difference significantly varied with sex both at academic (t (394) = 3.38, p=0.001) and practice (t (394) = 4.57, p<0.001) levels. Conclusion There was a moderate to strong correlation between academic and practice performance. In addition to academic performance, variation in practice was also explained by other factors which deserve more study. Enhancing academic performance can further increase practice performance. In general, the achievements of regular and male students at pediatrics was statistically significantly higher than their counterparts. Hence, female and summer nursing students deserve extra support from nurse educators to enhance their performance.
DEVELOPMENT OF HIGH-PERFORMANCE HEAVY OIL HYDROCRACK1NG CATALYSTS: CHARACTERIZATION OF ATMOSPHERIC RESIDUE FEED

ABSTRACT The characterization results of the atmospheric residue obtained from Saudi Arabian Light crude oil show the complex nature and composition of this material. The distillation results showed that about 50 percent of Arab Light crude is the atmospheric residue. The elemental analysis of the residue showed that high amount of carbon, sulfur and nitrogen is present along with heavy metals such as nickel and vanadium. The determination of hydrocarbon types by HPLC exhibited that 12% polars and 27% aromatics are present along with 6% asphaltenes. Nuclear magnetic resonance study conducted on the residue and its fraction provides a detailed composition in terms of aliphatic and aromatic nature of the residue and its fractions. The results showed that the residue contains 21% aromatic and 79% aliphatic carbon. The aliphatic carbon is present in saturates and as side chains of aromatic and polar molecules whereas the aromatic carbons are those in the ring structure. Asphaltenes separated from the residue were characterized for their different properties to understand its complexity. The use of electron spin resonance spectroscopy provides determination of the free radicals present in the residue. Asphaltenes were analyzed using the state-of-the-art high temperature high pressure electron spin resonance (ESR) technique in the temperature range 20 to 625 °C and at 30 and 50 bar hydrogen pressure. The ESR determination at 30 bar shows that me pressure was not enough to prevent the boiling of the asphaltene and thus a decrease in the spin concentration was observed beyond 350 °C temperature. The data at 50 bar pressure showed the adequacy of this pressure for ESR measurement. The PMRTA analysis of asphaltene showed a decrease in residual hydrogen with increasing temperature.
The Role of Subjective Experiences in Conflict Tasks: A Review

Cognitive control research is concerned with the question how we install adaptive behaviour in the case of (cognitive) conflict. In this review we focus on the role that awareness of this conflict plays in our ability to exert cognitive control. We will argue that visual conflict is not the only building block of metacognitive experiences of conflict and discuss how they are related to cognitive control. So, a first aim of the current review is to understand how these different metacognitive judgements are created. To do so, we draw some remarkable parallels with research on metacognition in decision making and memory research. Next, we elaborate on the relationship between metacognition and adaptive behaviour, with a specific focus on the role of subjective experiences in the Gratton effect. The grey areas that persist in the current literature are highlighted. In addition to deciphering the mechanisms of metacognitive judgements in cognitive control, this overview also aims to further enlarge our understanding of metacognitive abilities at a more general level.
The Coronavirus Pandemic: A Possible Model of the Direct and Indirect Impact of the Pandemic on Sleep Quality in Italians

Purpose This study aimed to assess the direct and indirect impact of COVID-19-related aspects on self-reported sleep quality, considering the moderator role of some psychological variables. Methods During the first weeks of the lockdown in Italy, 2286 respondents (1706 females and 580 males; age range: 18–74 years) completed an online survey that collected sociodemographic information and data related to the experience with the COVID-19 pandemic. Some questionnaires assessed sleep quality, psychological well-being, general psychopathology, Post-Traumatic Stress Disorders symptoms, and anxiety. The path analysis was adopted. Results The study confirms a direct effect of some aspects ascribable to the pandemic, with a mediator role of the psychological variables. Lower sleep quality was directly related to the days spent at home in confinement and the knowledge of people affected by the COVID-19. All the other aspects related to the COVID-19 pandemic influenced sleep quality through the mediator effect of psychological variables. Conclusion This study highlighted that the psychological condition of the population has been influenced by the COVID-19 pandemic and the government actions taken to contain it, but it has also played an important role in mediating the quality of sleep, creating a vicious circle on people’s health. The results suggest that a health emergency must be accompanied by adequate social support programs to mitigate the fear of infection and promote adequate resilience to accept confinement and social distancing. Such measures would moderate psychological distress and improve sleep quality.
The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models

This paper emphasizes the importance of rigorous validation as a crucial, integral component of Quantitative Structure Property Relationship (QSPR) model development. We consider some examples of published QSPR models, which in spite of their high fitted accuracy for the training sets and apparent mechanistic appeal, fail rigorous validation tests, and, thus, may lack practical utility as reliable screening tools. We present a set of simple guidelines for developing validated and predictive QSPR models. To this end, we discuss several validation strategies including (1) randomization of the modelled property, also called Y-scrambling, (2) multiple leave-many-out cross-validations, and (3) external validation using rational division of a dataset into training and test sets. We also highlight the need to establish the domain of model applicability in the chemical space to flag molecules for which predictions may be unreliable, and discuss some algorithms that can be used for this purpose. We advocate the broad use of these guidelines in the development of predictive QSPR models.
Clustering based Rewarding Algorithm to Detect Adversaries in Federated Machine Learning based IoT Environment

In recent times, federated machine learning has been very useful in building the intelligent intrusion detection system for IoT devices. As IoT devices are equipped with a security architecture vulnerable to various attacks, these security loopholes may bring a risk during federated training of decentralized IoT devices. Adversaries can take control over these IoT devices and inject false gradients to degrade the global model performance. In this paper, we have proposed an approach that detects the adversaries with the help of a clustering algorithm. After clustering, it further rewards the clients for detecting honest and malicious clients. Our proposed gradient filtration approach does not require any processing power from the client-side and does not use excessive bandwidth, making it very much feasible for IoT devices. Further, our approach has been very successful in boosting the global model accuracy, up to 99% even in the presence of 40% adversaries.
Clinical evidence of dietary supplementation with sesame on cardiovascular risk factors: An updated meta-analysis of randomized controlled trials

Abstract The present analysis was to summarize the evidence of the effects of sesame and its derivatives supplementation on cardiovascular disease (CVD) risk factors by performing a meta-analysis of randomized controlled trials (RCTs). Electronic databases were searched from their inception to July 2020. Two investigators independently assessed articles for inclusion, extracted data, and statistical analysis. The quality of included articles was assessed according to the Cochrane risk of bias tool. Major outcomes were synthesized using a random effect model and presented as weighted mean difference and 95% confidence interval. Heterogeneity, subgroup analyses, sensitivity analysis, meta-regression, and publication bias were also conducted. The GRADE approach was used to evaluate the quality of evidence. Overall, 16 trials involving 908 participants were included for statistical pooling. Compared with the control group, sesame intake significantly decreased the levels of total cholesterol, triglycerides, systolic blood pressure, diastolic blood pressure, body weight, body mass index, hip circumference, and waist circumference (P < 0.05). These results were stable in sensitivity analysis, and no significant publication bias was detected. Our findings provided evidence that sesame consumption may reduce the risk of CVD by improving blood lipids, blood pressure, and body weight management. Further large-scale, well-designed RCTs are required to confirm these results.
Influence of the Water and Cluster Structure on the PFSA Membrane Conductivity

固体高分子形燃料電池に広く用いられているpolyperfluorosulfonic acid (PFSA) 膜について, 湿度を変化させながら赤外 (IR) および小角X線散乱 (SAXS) 測定を行い, 含水状態およびクラスターサイズの変化がイオン伝導度に与える影響を調べた. その結果, 膜中の自由水は束縛水よりもイオン伝導度に対する寄与が大きく, 束縛水と自由水の存在比は膜が置かれた環境の相対湿度に依存して変化した. 30%RH以下では膜中の水はすべて束縛水であり, 60%RH以上で自由水が飛躍的に増加した. 湿度の増加とともにクラスターサイズは徐々に大きくなるが, 60%RHを境に高次構造変化がおき, それまで独立していたクラスターがネットワーク状の太いイオンチャンネルを形成すると考えられた. このような高次構造の変化や自由水の飛躍的な増加により, イオン伝導度が大きくなると考えられた.
Personalized screening intervals for measurement of N-terminal pro-B-type natriuretic peptide improve efficiency of prognostication in patients with chronic heart failure.

Although natriuretic peptide levels have been associated with incident heart failure and prognosis of heart failure patients, trials on natriuretic peptide-guided treatment have provided inconsistent results. Existing trials mostly used predefined screening intervals and target levels, which do not account for variations in temporal patterns of circulating biomarkers between individuals. This may hamper their potential use for therapy guidance. In contrast, a personalized screening approach with screening intervals and target levels based on the evolution of biomarkers in individual patients may further improve risk assessment and therapy guidance. Such personalized screening intervals maximize information gain on the individual patients’ disease progression, while minimizing the necessary number of measurements. In the Bio-SHiFT study, we demonstrated that individual temporal patterns of serially measured chronic heart failure (CHF)-related biomarkers are associated with the prognosis of CHF patients. We also demonstrated a method to obtain a patient-specific dynamic estimate of prognosis. This estimate is updated after every additional measurement, as each measurement provides additional information. This personalized risk assessment can also be used to derive personalized screening intervals for future CHF patients. However, the benefits of this approach, over predefined screening intervals and targets, have not yet been investigated in CHF patients. Here, we compare personalized scheduling of N-terminal pro-B-type natriuretic peptide (NT-proBNP) measurements to a predefined, fixed scheduling approach. In 263 stable CHF patients from the Bio-SHiFT study, NT-proBNP was measured trimonthly according to a prespecified, fixed schedule. The composite primary endpoint (PE) consisted of cardiac death, cardiac transplantation, left ventricular assist device implantation or heart failure hospitalization. Using joint models for time-to-event and longitudinal data, we modelled the association between repeated NTproBNP measurements and the PE. Subsequently, we performed a simulation study where we generated 750 patients with baseline characteristics and NTproBNP profiles similar to the 263 patients included in the Bio-SHiFT study. We divided these patients into a training (700 patients) and testing (50 patients) set. In the training set, we fitted a new joint model for NT-proBNP. We compared scheduling of NT-proBNP
Case report of adrenocortical carcinoma associated with double germline mutations in MSH2 and RET

Adrenocortical carcinoma (ACC) is a rare aggressive malignancy that originates in the outer layer of the adrenal gland. Most ACCs are sporadic, but a small percentage of cases are due to hereditary cancer syndromes such as Li‐Fraumeni syndrome (LFS), Lynch syndrome (LS), and familial adenomatous polyposis (FAP). Multiple endocrine neoplasia type 2A (MEN2A) is an inherited disorder that predisposes to medullary thyroid cancer, pheochromocytoma, and parathyroid hyperplasia. We present here a case of ACC with both LS and MEN2A; the family and medical history were consistent with Lynch. This is, to our knowledge, the first report of a patient with ACC associated with germline mutations in RET and MSH2, and no phenotypical characteristics of MEN2A.