Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Corruption On Economic Growth: A Nonlinear Evidence

Several cross-country studies have found that corruption slows growth, but these findings are not universally robust. Therefore, the questions to be addressed are to what extent corruption can be tolerated and at what threshold it has a detrimental effect on an economy.This article investigates the impact of corruption on economic growth by testing the hypothesis that the relationship between these two variables is nonlinear. In this article, a panel data analysis has been used to examine 65 countries over the 1987 to 2011 period. Our findings are that corruption can have a positive effect on growth. The results indicate that beyond an optimal threshold, both high and low corruption levels can decrease economic growth. Under this optimal threshold, a moderate level of corruption, defined by the point of reversal of the curve of the marginal corruption effect on growth, could have advantages for economic growth.JEL: B23, C51, D73, O47.
Critical Path Detection for Civil Aircraft Collaborative Supply Network

Civil aircraft is a complex product to manufacture, and the collaborative supply network consist of grades suppliers plays an important part in the progress of development. Due to the interferences from every kind of uncertainties to the network, it’s necessary to find out the critical supply path which decides the completion date for the network going well. This paper first sets the supply network model based on the hierarchical structure of civil aircraft, and then uses Dijkstra and ant colony optimization (ACO) searching for the critical path respectively, in the last the two methods are compared in order to prove performance and superiority.
Early Institutional Experience of Dual Tracer and Single-Photon Emission Computed-Tomography/Computed-Tomography Mapping for Sentinel Node Biopsy: A Report of Two Early-Stage Breast Cancer

Intraoperative sentinel lymph node mapping (SLNM) with methylene blue dye (MBD) tracer has been the recommended method to detect SLN in early-stage breast cancer patients in low-resource settings. However, the use of MBD alone is hampered by the high false-negative rate; thus, it requires coupling with other mapping methods if the appropriate infrastructure and services are available. In this article, we present two prospective cases detailing our initial experience using the gold-standard dual tracer technique (DTT: MBD and 99mTc-nanocolloid radioisotope) in combination with hybrid single-photon emission computed-tomography/computed-tomography (SPECT/CT) preoperative mapping for image-guided SLN biopsy (SLNB). Overall, both studies were successful in identifying the SLNs, which aided in mapping the possible anatomical spread of the disease.
Multi-body Dynamics Analysis of Power Train Judder Oscillations Considering Aggregate Dynamics

Torsional oscillations in an open power train during start-up process are commonly called judder or clutch judder. Due to the rotational-translational coupling of tyres and body the longitudinal acceleration of the car passengers is, according to the appearing magnitudes, affected in a way that their driving comfort may be disturbed notably. Main subject of this paper is the simulation of judder oscillations. Additionally it provides a single-mass flywheel clutch model, which is integrated in a multi-body dynamics power train model to analyse the different mechanisms of judder. The results show, on the one hand, the massive influence of aggregate roll and stroke motions on judder vibrations, so it can be said that the clutch is not the only cause of those disturbances. On the other hand, a parameter study exposes sensitive values in the power train that have impact on those oscillations. Finally, different clutch concepts are compared with regard to judder.
Efficacy of flavonoids on biomarkers of type 2 diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials

Abstract A systematic review and meta-analysis of 28 randomized controlled trials (RCTs) to assess the efficacy of flavonoids intake on key biomarkers related to Type 2 diabetes mellitus was conducted. The mean difference (MD) with 95% confidence intervals (95% CI) was pooled using a random-effects model. Significant reduction in fasting glucose (MD: −0.22, 95% CI: −0.34 to −0.09, p = 0.0013), hemoglobin A1c (HbA1c) (MD: −0.26, 95% CI: −0.46 to −0.05, p = 0.021), homeostasis model assessment of insulin resistance (HOMA-IR) (MD: −0.40, 95% CI: −0.66 to −0.15, p = 0.0039), triglyceride (TG) (MD: −0.13, 95% CI: −0.21 to −0.05, p = 0.002), total cholesterol (TC) (MD: −0.14, 95% CI: −0.21 to −0.08, p = 0.0002), and low density lipoprotein-C (LDL-C) (MD: −0.15; 95% CI: −0.24 to −0.07, p = 0.0009) were observed in intervention group compare to placebo at the end of trial. Moreover, flavonoid intake had negative but non-significant effect on insulin (MD: −0.46), 2 h-postprandial glucose (2 h-PPG) (MD: −0.22), homeostasis model assessment of β-cell function (HOMA-β) (MD: −2.81), and insignificantly increased high-density lipoprotein-C (HDL-C) (MD: 0.03). In conclusion, flavonoid intake has modest but statistically significant benefits in glucose metabolism, insulin sensitivity, and lipid metabolism, especially for significantly lowing fasting blood glucose, HOMA-IR, HbA1c, TG, TC, and LDL-C.
Determination method of optimal operation schedule for fuel cells in collective housing

In this paper, the authors propose a power and heat interchange system using fuel cells (FCs) in a collective housing and develop a determination method of optimal operation schedule for FCs in this system. The developed method is based on tabu search which is one of non-linear optimization methods. In the developed method, the optimal operation schedule is determined by using Pareto optimal solutions from two evaluation viewpoints ((1) running cost, (2) CO 2 emission). In order to examine the validity of the developed method, numerical simulations are carried out for the collective housing model with 12 houses in winter, summer and middle season, and the optimal operation schedules are determined.
When Should a Test Be Automated

I want to automate as many tests as I can. I’m not comfortable running a test only once. What if a programmer then changes the code and introduces a bug? What if I don’t catch that bug because I didn’t rerun the test after the change? Wouldn’t I feel horrible? Well, yes, but I’m not paid to feel comfortable rather than horrible. I’m paid to be costeffective. It took me a long time, but I finally realized that I was over-automating, that only some of the tests I created should be automated. Some of the tests I was automating not only did not find bugs when they were rerun, they had no significant prospect of doing so. Automating them was not a rational decision. The question, then, is how to make a rational decision. When I take a job as a contract tester, I typically design a series of tests for some product feature. For each of them, I need to decide whether that particular test should be automated. This paper describes how I think about the tradeoffs.
Theoretical study of RF-breakdown in bulk GaN and GaN MESFETs

RF-breakdown was studied in bulk GaN and in GaN MESFETs using a full band Monte Carlo simulator. It was found that in bulk materials, increasing the frequency of an applied RF field would result in a lower overall impact ionization rate and consequently lead to higher breakdown fields. It was also found that the RF-breakdown voltage of devices increases with increasing frequency of the applied large signal RF excitation. The frequency dependence of RF-breakdown and the difference between RF and dc-breakdown is explained based on the time response of the particle energy to the change in the applied RF excitation.
Latent Classes of Bidirectional Face-to-Face and Cyber Intimate Partner Violence Among Lesbian, Gay, and Bisexual Emerging Adults: The Role of Minority Stressors

The rates of intimate partner violence have been found to be higher among lesbian, gay, and bisexual (LGB) individuals when compared with heterosexual populations. However, lesser is known about the impact of specific minority stressors experienced by LGB populations on their face-to-face intimate partner violence (IPV) and cyber IPV experiences. Using a three-step latent class approach, the present study investigated (i) the latent classes of self-reported types of face-to-face IPV and cyber IPV perpetration and victimization and (ii) their associations with LGB distal and proximal minority stressors (i.e., vicarious trauma, discrimination, family rejection, and LGB-identity disclosure). Participants were 288 LGB emerging adults in the age range of 18–29 years (bisexual: n = 168, gay: n = 72, and lesbian: n = 48). Findings showed the presence of four latent classes, namely, face-to-face IPV (n = 32; 37.5% gay, 18.8% lesbian, and 43.8% bisexual individuals), cyber IPV (n = 66; 33.3% gay, 12.1% lesbian, and 54.5% bisexual individuals), psychological and stalking cyber IPV (n = 89; 15.7% gay, 15.7% lesbian, and 68.5% bisexual individuals), and low IPV (n = 101; 23.8% gay, 19.8% lesbian, and 56.4% bisexual individuals). Furthermore, multinomial logistic regressions indicated that greater exposure to the minority stressors such as exposure to heterosexism, namely, discrimination and harassment, rejection from one’s family of origin, and exposure to vicarious trauma, as well as a lower degree of LGB-identity disclosure, largely predicted latent classes with greater probabilities of IPV exposure, namely, cyber IPV, face-to-face IPV classes, and psychological and stalking cyber IPV. Findings suggest the importance of addressing the role of minority stressors in IPV interventions and the creation of competent LGB-related services and training modules for clinicians.
Effects of Using the Surgical Mask and FFP2 during the 6-Min Walking Test. A Randomized Controlled Trial

During the COVID-19 pandemic, the use of masks has been recommended as a containment measure. The mask is a hindrance to normal breathing that causes discomfort. This could put more work on the respiratory accessory muscles, and, consequently, these muscles could see their tone increase. For this reason, during this clinical trial (registered in clincaltrials.gov, number: NCT04789603), it was observed whether the use of the mask produced changes in the distance traveled, in the heart rate, in the oxygenometry, in the self-perceived dyspnea and in the tone of accessory respiratory muscles during a 6-min walk test (6MWT). Fifty healthy volunteers were recruited and carried out the 6MWT on three occasions. They carried out the 6MWT in various situations: using an FFP2/N95 mask, using a surgical mask, and without using a mask. The distance walked, the heart rate, the oxygen therapy, the tone of the accessory respiratory muscles, and the self-perceived dyspnea were recorded in each situation. Significant differences were found between the three situations in terms of self-perceived dyspnea FFP2/N95 > surgical mask > no mask. However, there are no differences between the experimental situations during the 6MWT in terms of distance travelled, heart rate, oxygenometry or respiratory muscle tone.
Recent Advances in Trustworthy Explainable Artificial Intelligence: Status, Challenges and Perspectives

Artificial intelligence (AI) and Machine Learning (ML) have come a long way from the earlier days of conceptual theories, to being an integral part of todays technological society. Rapid growth of AI/ML and their penetration within a plethora of civilian and military applications, while successful, has also opened new challenges and obstacles. With almost no human involvement required for some of the new decision-making AI/ML systems, there is now a pressing need to gain better insights into how these decisions are made. This has given rise to a new field of AI research, Explainable AI (XAI). In this paper, we present a survey of XAI characteristics and properties. We provide an in-depth review of XAI themes, and describe the different methods for designing and developing XAI systems, both during and post model-development. We include a detailed taxonomy of XAI goals, methods, and evaluation, and sketch the major milestones in XAI research. An overview of XAI for security, and cybersecurity of XAI systems, is also provided. Open challenges are delineated, and measures for evaluating XAI system robustness are described.
Excessive Accumulation of Intracellular Ca2+ After Acute Exercise Potentiated Impairment of T-cell Function

Ca2+ is an important intracellular second messenger known to regulate several cellular functions. This research aimed to investigate the mechanisms of exercise-induced immunosuppression by measuring intracellular calcium levels, Ca2+-regulating gene expression, and agonist-evoked proliferation of murine splenic T lymphocytes. Mice were randomly assigned to the control, sedentary group (C), and three experimental groups, which performed a single bout of intensive and exhaustive treadmill exercise. Murine splenic lymphocytes were separated by density-gradient centrifugation immediately (E0), 3h (E3), and 24h after exercise (E24). Fura-2/AM was used to monitor cytoplasmic free Ca2+ concentration in living cells. The combined method of carboxyfluorescein diacetate succinimidyl ester (CFSE) labeling and flow cytometry was used for the detection of T cell proliferation. The transcriptional level of Ca2+-regulating genes was quantified by using qPCR. Both basal intracellular Ca2+ levels and agonist (ConA, OKT3, or thapsigargin)-induced Ca2+ transients were significantly elevated at E3 group (p<0.05 vs. control). However, mitogen-induced cell proliferation was significantly decreased at E3 group (p<0.05 vs. control). In parallel, the transcriptional level of plasma membrane Ca2+-ATPases (PMCA), sarco/endoplasmic reticulum Ca2+-ATPases (SERCA), TRPC1, and P2X7 was significantly downregulated, and the transcriptional level of IP3R2 and RyR2 was significantly upregulated in E3 (p<0.01 vs. control). In summary, this study demonstrated that acute exercise affected intracellular calcium homeostasis, most likely by enhancing transmembrane Ca2+ influx into cells and by reducing expression of Ca2+-ATPases such as PMCA and SERCA. However, altered Ca2+ signals were not transduced into an enhanced T cell proliferation suggesting other pathways to be responsible for the transient exercise-associated immunosuppression.
Detection and Segmentation of Pelvic Bones Metastases in MRI Images for Patients With Prostate Cancer Based on Deep Learning

Objective To establish and evaluate the 3D U-Net model for automated segmentation and detection of pelvic bone metastases in patients with prostate cancer (PCa) using diffusion-weighted imaging (DWI) and T1 weighted imaging (T1WI) images. Methods The model consisted of two 3D U-Net algorithms. A total of 859 patients with clinically suspected or confirmed PCa between January 2017 and December 2020 were enrolled for the first 3D U-Net development of pelvic bony structure segmentation. Then, 334 PCa patients were selected for the model development of bone metastases segmentation. Additionally, 63 patients from January to May 2021 were recruited for the external evaluation of the network. The network was developed using DWI and T1WI images as input. Dice similarity coefficient (DSC), volumetric similarity (VS), and Hausdorff distance (HD) were used to evaluate the segmentation performance. Sensitivity, specificity, and area under the curve (AUC) were used to evaluate the detection performance at the patient level; recall, precision, and F1-score were assessed at the lesion level. Results The pelvic bony structures segmentation on DWI and T1WI images had mean DSC and VS values above 0.85, and the HD values were <15 mm. In the testing set, the AUC of the metastases detection at the patient level were 0.85 and 0.80 on DWI and T1WI images. At the lesion level, the F1-score achieved 87.6% and 87.8% concerning metastases detection on DWI and T1WI images, respectively. In the external dataset, the AUC of the model for M-staging was 0.94 and 0.89 on DWI and T1WI images. Conclusion The deep learning-based 3D U-Net network yields accurate detection and segmentation of pelvic bone metastases for PCa patients on DWI and T1WI images, which lays a foundation for the whole-body skeletal metastases assessment.
Effectiveness of Medicinal Plants for Glycaemic Control in Type 2 Diabetes: An Overview of Meta-Analyses of Clinical Trials

Aims: To rank the effectiveness of medicinal plants for glycaemic control in Type 2 Diabetes (T2DM). Methods: MEDLINE, EMBASE, CINAHL and Cochrane Central were searched in October 2020. We included meta-analyses of randomised controlled clinical trials measuring the effectiveness of medicinal plants on HbA1c and/or Fasting Plasma Glucose (FPG) in patients with T2DM. Results: Twenty five meta-analyses reported the effects of 18 plant-based remedies. Aloe vera leaf gel, Psyllium fibre and Fenugreek seeds had the largest effects on HbA1c: mean difference –0.99% [95% CI−1.75, −0.23], −0.97% [95% CI −1.94, −0.01] and −0.85% [95% CI −1.49, −0.22] respectively. Four other remedies reduced HbA1c by at least 0.5%: Nigella sativa, Astragalus membranaceus, and the traditional Chinese formulae Jinqi Jiangtang and Gegen Qinlian. No serious adverse effects were reported. Several other herbal medicines significantly reduced FPG. Tea and tea extracts (Camellia sinensis) were ineffective. However, in some trials duration of follow-up was insufficient to measure the full effect on HbA1c (<8 weeks). Many herbal remedies had not been evaluated in a meta-analysis. Conclusion: Several medicinal plants appear to be as effective as conventional antidiabetic treatments for reducing HbA1c. Rigorous trials with at least 3 months’ follow-up are needed to ascertain the effects of promising plant-based preparations on diabetes.
The Proton in Biochemistry: Impacts on Bioenergetics, Biophysical Chemistry, and Bioorganic Chemistry

The proton is the smallest atomic particle, and in aqueous solution it is the smallest hydrated ion, having only two waters in its first hydration shell. In this article we survey key aspects of the proton in chemistry and biochemistry, starting with the definitions of pH and pK a and their application inside biological cells. This includes an exploration of pH in nanoscale spaces, distinguishing between bulk and interfacial phases. We survey the Eigen and Zundel models of the structure of the hydrated proton, and how these can be used to explain: a) the behavior of protons at the water-hydrophobic interface, and b) the extraordinarily high mobility of protons in bulk water via Grotthuss hopping, and inside proteins via proton wires. Lastly, we survey key aspects of the effect of proton concentration and proton transfer on biochemical reactions including ligand binding and enzyme catalysis, as well as pH effects on biochemical thermodynamics, including the Chemiosmotic Theory. We find, for example, that the spontaneity of ATP hydrolysis at pH ≥ 7 is not due to any inherent property of ATP (or ADP or phosphate), but rather to the low concentration of H+. Additionally, we show that acidification due to fermentation does not derive from the organic acid waste products, but rather from the proton produced by ATP hydrolysis.
Efficacy and Safety of TCMI in Patients With Combined Coronary Heart Disease and Heart Failure: A Systematic Review and Network Meta-Analysis

Objective: To compare the efficacy and safety of conventional treatments (CTs) to those that included traditional Chinese medicine injections (TCMIs) in patients with combined coronary heart disease and heart failure (CHD-HF). Methods: Eight electronic literature databases (PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, China National Knowledge Infrastructure Database, Chinese Scientific Journal Database, Wanfang Database, Chinese Biomedical Database) were searched from their inceptions to May 18, 2021, to identify relevant randomised controlled trials (RCTs). The primary outcomes analyzed included the total effectiveness rate and adverse events (ADRs). The secondary outcomes analyzed included the left ventricular ejection fraction (LVEF), N-terminal pro-brain natriuretic peptide (NT-proBNP), brain natriuretic peptide (BNP), and 6-min walk test (6MWT). Cochrane risk-of-bias tool was used to assess quality of the analyzed RCTs. Stata and OpenBUGS software were used to prior to the systematic review and network meta-analysis. Results: Sixty-one eligible trials involved 5,567 patients and one of the following 15 TCMIs: Shuxuetong, Shenmai, Shenfu, Shengmai, Danshenduofenyansuan, Danhong, Dazhuhongjingtian, Xinmailong, Dengzhanxixin, Gualoupi, Shuxuening, Xuesaitong, Yiqi Fumai, Shenqi Fuzheng, Huangqi. Network meta-analysis revealed that Shuxuetong injection + CT group was superior to CT only in improving the total effectiveness rate [odds ratio (OR): 7.8, 95% confidence interval (CI): 1.17–27.41]. Shenmai injection + CT was superior to CT only for LVEF (OR: 8.97, CI: 4.67–13.18), Xinmailong injection + CT was superior to CT only for NT-proBNP (OR: −317.70, CI: −331.10–303.10), Shenqi Fuzheng injection + CT was superior to CT only for BNP (OR: −257.30, CI: −308.40–242.80); and Danhong injection + CT was superior to CT only for 6MWT (OR: 84.40, CI: 62.62−106.20). Different TCMIs had different toxicity spectrums. Conclusion: TCMIs combined with CT are better than CT alone in treating CHD-HF. Different TCMIs improve different outcomes. Additional properly designed RCTs are needed to conduce a more refined comparison of various TCMIs. Systematic Review Registration: [https://www.crd. york.ac. uk/PROSPERO/], identifier [CRD42021258263].
Unveiling the Burden of Interactions Among Clinical Risk Factors for 1-Year Mortality in Hospitalized Older Patients

Background: Hospitalized older patients are particularly exposed to adverse health outcomes. Objective: In this study, we aimed at investigating the prognostic interactions between disability in basic activities of daily living (BADL), cognitive impairment, low handgrip strength, anticholinergic cognitive burden (ACB), and depression on 1-year mortality. Setting and Subjects: Our series consisted of 503 older patients discharged from acute care hospitals. Methods: Disability in at least one BADL, ACB, depression, cognitive impairment, and low handgrip strength was considered in the analysis. One-year mortality was investigated by Cox regression analysis and prognostic interactions among study variables were assessed by survival tree analysis. Results: Basic activities of daily living disability, ACB, cognitive impairment, and low handgrip strength were significantly associated with 1-year mortality. Survival tree analysis showed that patients with BADL disability and high ACB carried the highest risk of poor survival [hazard ratio (HR): 16.48 (2.63–74.72)], followed by patients with BADL disability and low ACB (HR: 8.43, 95% CI: 1.85–38.87). Patients with cognitive impairment and no BADL disability were characterized by a lower but still significant risk of mortality (HR: 6.61, 95% CI: 1.51–28.97) and those with high ACB scores and good cognitive and functional performance (HR: 5.28, 95% CI: 1.13–24.55). Conclusion: Basic activities of daily living dependency, cognitive impairment, and ACB score were the three main predictors of 1-year mortality among patients discharged from acute care hospitals; the interaction between BADL dependency and ACB score was found to significantly affect survival. Early identification of such high-risk patients may help tailor targeted interventions to counteract their detrimental effects on prognosis.