Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of Overlays Placed Over Sealed Decks under Static and Fatigue Loading

In order to enhance the effectiveness of portland cement overlays placed over existing bridge decks, the deck may be sealed with an acceptable sealer before placing the overlay. The main purpose for such a treatment of the deck is to seal the existing cracks, and prevent penetration of chlorides into the deck if the overlay cracks. The presence of a sealer at the deck-overlay interface is expected to reduce the available bond strength. The reported research was carried out to investigate the performance of overlays placed over sealed bridge decks, examine the level of bond strength, and develop simple yet effective means to restore the bond strength as much as possible. Test results indicate that the sealer reduces the available bond strength by as much as 50%. Up to 85% of the bond strength can be restored if sand is broadcast over the sealer while it is curing or if the dried sealed surface is lightly sanded. These observations were validated through fatigue loading and loading to failure of a one-third-scale subassemblage of a steel stringer bridge.
Pathogenic CD8 T cells defined by longitudinal liver sampling in chronic hepatitis B patients starting antiviral therapy

Accumulation of activated immune cells results in non-specific hepatocyte killing in chronic hepatitis B (CHB), leading to fibrosis and cirrhosis. We enrolled 15 CHB patients with active liver damage to receive antiviral therapy, and performed longitudinal liver sampling using fine-needle aspiration to investigate mechanisms of CHB pathogenesis in the human liver. Single-cell sequencing of total liver cells revealed a distinct liver-resident, polyclonal CD8 T cell population that was enriched at baseline and displayed a highly activated immune signature during liver damage. Cytokine combinations, identified by in silico prediction of ligand-receptor interaction, induced the activated phenotype in healthy liver CD8 T cells, resulting in non-specific Fas ligand-mediated killing of target cells. These results define a CD8 T cell population in the human liver that can drive pathogenesis, and a key pathway involved in their function in CHB patients.
Sex biased effect of acute heat shock on the antioxidant system of non-native round goby Neogobius melanostomus

Monitoring oxidative stress biomarkers has become a powerful and common tool to estimate organismal condition and response to endogenous and environmental factors. In the present study, we used round goby (Neogobius melanostomus) from non-native European populations, as a model species to test sex differences in oxidative stress biomarkers. Considering sex differences in reproductive investment, we hypothesized that males would display lower resistance to abiotic stress. Fish were exposed to a heat shock (temperature elevated by 10°C) for 1h, 6h, and 12h and catalase activity (CAT), reduced glutathione (GSH), total antioxidant capacity (TAC) and lipid peroxidation (LPO) were measured in liver and muscle tissues. Liver of males was significantly more responsive compared to liver of females in all tested parameters. GSH was found to be the most responsive to heat stress exposure in both sexes. The results supported our hypothesis that male reproductive investment (territoriality, courtship, and brood care) and likelihood of only a single spawning period in their lifetime influenced on higher sensitivity of their antioxidant defence. On the other hand, for females antioxidant defence is considered more important to survive the environmental changes and successfully reproduce in the next season. Our experiments exposed fish to acute thermal stress. Further research should determine the effects of exposure to chronic thermal stress to corroborate our understanding on sex differences in antioxidant defence in the round goby.
Detection of child depression using machine learning methods

Background Mental health problems, such as depression in children have far-reaching negative effects on child, family and society as whole. It is necessary to identify the reasons that contribute to this mental illness. Detecting the appropriate signs to anticipate mental illness as depression in children and adolescents is vital in making an early and accurate diagnosis to avoid severe consequences in the future. There has been no research employing machine learning (ML) approaches for depression detection among children and adolescents aged 4–17 years in a precisely constructed high prediction dataset, such as Young Minds Matter (YMM). As a result, our objective is to 1) create a model that can predict depression in children and adolescents aged 4–17 years old, 2) evaluate the results of ML algorithms to determine which one outperforms the others and 3) associate with the related issues of family activities and socioeconomic difficulties that contribute to depression. Methods The YMM, the second Australian Child and Adolescent Survey of Mental Health and Wellbeing 2013–14 has been used as data source in this research. The variables of yes/no value of low correlation with the target variable (depression status) have been eliminated. The Boruta algorithm has been utilized in association with a Random Forest (RF) classifier to extract the most important features for depression detection among the high correlated variables with target variable. The Tree-based Pipeline Optimization Tool (TPOTclassifier) has been used to choose suitable supervised learning models. In the depression detection step, RF, XGBoost (XGB), Decision Tree (DT), and Gaussian Naive Bayes (GaussianNB) have been used. Results Unhappy, nothing fun, irritable mood, diminished interest, weight loss/gain, insomnia or hypersomnia, psychomotor agitation or retardation, fatigue, thinking or concentration problems or indecisiveness, suicide attempt or plan, presence of any of these five symptoms have been identified as 11 important features to detect depression among children and adolescents. Although model performance varied somewhat, RF outperformed all other algorithms in predicting depressed classes by 99% with 95% accuracy rate and 99% precision rate in 315 milliseconds (ms). Conclusion This RF-based prediction model is more accurate and informative in predicting child and adolescent depression that outperforms in all four confusion matrix performance measures as well as execution duration.
Degradation mechanism in carbon-doped GaAs minority-carrier injection devices [HBTs]

Degradation behavior and mechanism of GaAs-based devices under minority-carrier injection has been studied by measuring the increase in the leakage current and the luminescence lifetime of minority carriers. It is found that hydrogen unintentionally incorporated in GaAs-based devices induces degradation under minority-carrier injection, i.e., increase in injection leakage current at low bias voltage. "Isolated" hydrogen donors (H/sup +/) induce rapid degradation, and even carbon-hydrogen (C-H) complexes which are believed to be electrically neutral induce slow degradation. Degradation is induced by the decomposition of the C-H complexes, enhanced by minority-carrier injection producing electrically active isolated hydrogen donors (H/sup +/). The kinetics of the leakage current increase are well explained by the decomposition kinetics of the C-H complexes. Under minority-carrier injection, H/sup +/ changes to hydrogen acceptors (H/sup - /) by capturing two electrons. Hydrogen donors (H/sup +/) and hydrogen acceptors (H/sup -/) combine and become a molecular hydrogen which Is thought to form {111} platelets. This decomposition mechanism are not due to recombination-enhanced defect reaction (REDR) but is related to charge state effects by two-electron capturing. We infer that the degradation mechanism is closely related to the leakage through the {111} platelets.
Development and evaluation of an online integrative histology module: simple design, low-cost, and improves pathology self-efficacy

ABSTRACT Integration of core concepts is an important aspect of medical curriculum enhancement. Challenges to improving integration include the risk of curtailing the basic sciences in the process and the push to decrease contact hours in medical curricula. Self-paced learning tools can be developed that deliberately relate basic and clinical sciences to aid students in making interdisciplinary connections. The purpose of this project was to develop, implement, and evaluate a self-paced learning module that would be applicable to integration of different disciplines in medical education. The module was intended to improve integration between histology and anatomic pathology before a respiratory pathology laboratory session. Qualtrics XM, a survey software commonly available at educational institutions, was used in a novel manner to create the module. Module activities included pre- and post-module quizzes; four short videos emphasizing normal histological features and recalling associated pathologies; three categorization activities designed for students to recognize normal versus abnormal characteristics of lung specimens; and post-activity feedback. Preliminary data from first-year medical students showed that post-module quiz scores were significantly higher than pre-module quiz scores (p < 0.001) and that module users’ pre-laboratory pathology self-efficacy was significantly higher than non-users (p < 0.05). These data suggest that module use facilitated short-term knowledge gain and improved pathology self-efficacy before the laboratory session. Online modules can be developed affordably using Qualtrics XM to integrate anatomical sciences with other disciplines, while providing students interactive learning resources without increasing contact hours. The module presented in this report focused on normal versus abnormal morphology, guiding students through recognizing the continuum from healthy to disease states before learning about the pathologies more in depth. A similar module design would likely be effective in integrating other disciplines in medicine, especially in disciplines that require recognition of changes in morphology.
Performance of GenoType MTBDRsl assay for detection of second-line drugs and ethambutol resistance directly from sputum specimens of MDR-TB patients in Bangladesh

Background Rapid and early detection of drug susceptibility among multidrug-resistant tuberculosis (MDR-TB) patients could guide the timely initiation of effective treatment and reduce transmission of drug-resistant TB. In the current study, we evaluated the diagnostic performance of GenoType MTBDRsl (MTBDRsl) ver1.0 assay for detection of resistance to ofloxacin (OFL), kanamycin (KAN) and ethambutol (EMB), and additionally the XDR-TB among MDR-TB patients in Bangladesh. Methods The MTBDRsl assay was performed directly on 218 smear-positive sputum specimens collected from MDR-TB patients and the results were compared with the phenotypic drug susceptibility testing (DST) performed on solid Lowenstein-Jensen (L-J) media. We also analyzed the mutation patterns of gyrA, rrs, and embB genes for detection of resistance to OFL, KAN and EMB, respectively. Results The sensitivity and specificity of the MTBDRsl compared to phenotypic L-J DST were 81.8% (95% CI, 69.1–90.9) and 98.8% (95% CI, 95.6–99.8), respectively for OFL (PPV: 95.7% & NPV: 94.1%); 65.1% (95% CI, 57.5–72.2) and 86.7% (95% CI, 73.2–94.9), respectively for EMB (PPV: 94.9% & NPV: 39.4%); and 100% for KAN. The diagnostic accuracy of KAN, OFL and EMB were 100, 94.5 and 69.6%, respectively. Moreover, the sensitivity, specificity and diagnostic accuracy of MtBDRsl for detection of XDR-TB was 100%. The most frequently observed mutations were at codon D94G (46.8%) of gyrA gene, A1401G (83.3%) of rrs gene, and M306V (41.5%) of the embB gene. Conclusion Considering the excellent performance in this study we suggest that MTBDRsl assay can be used as an initial rapid test for detection of KAN and OFL susceptibility, as well as XDR-TB directly from smear-positive sputum specimens of MDR-TB patients in Bangladesh.
Supplementation of chicory root powder as an alternative to antibiotic growth promoter on gut pH, gut microflora and gut histomorphometery of male broilers

The experiment was conducted to study the effect of chicory root powder on the gut performance of broilers. For this purpose, two hundred commercial male broiler chicks were randomly divided into 5 treatment groups with 8 replications of 5 birds each and reared in battery brooders up to 42 days of age. The experimental design consisted of; T1 basal diet (BD) without antibiotic, T2: BD + antibiotic (BMD at 500 gm/ton), T3: BD + chicory root powder (0.5%), T4: BD + chicory root powder (1.0%), T5: BD + chicory root powder (1.5%). The results revealed that supplementation of 1.0% chicory root powder recorded significantly (P<0.05) higher body weight gain, feed intake and better feed conversion ratio (FCR) compared to antibiotic, control and 0.5 & 1.5% chicory powder at 42 days of age. Supplementation of various levels of chicory root powder significantly (P<0.05) lowered (P<0.05) the pH in duodenum, jejunum, ileum and caecum compared to control. Supplementation of chicory root powder (0.5, 1.0 & 1.5%) significantly (P<0.05) decreased the E. coli and Salmonella counts and (P<0.05) increased the Lactobacilli counts in ileum when compared to control and antibiotic groups. Supplementation of chicory (1.0% and 1.5%) groups significantly (P<0.05) increased the villus height (VH), crypt depth (CD), VH:CD ratio and villus width (VW) in the duodenum, ileum and jejunum at 42 d of age. Supplementation of chicory 1.0% and 1.5% groups significantly (P<0.05) increased the goblet cell number in duodenum, jejunum and ileum of broilers. Therefore, chicory root powder (1.0 and 1.5%) can be used as an alternative to antibiotic for improving gut performance of broiler chicken.
Surge in SARS-CoV-2 transmission in school-aged children and household contacts, England, August to October 2021

Easing of COVID-19 restrictions in England in the summer of 2021 was followed by a sharp rise in cases among school-aged children. Weekly rates of SARS-CoV-2 infection in primary and secondary school children reached 733.3 and 1,664.7/100,000 population, respectively, by week 39 2021. A surge in household clusters with school-aged index cases was noted at the start of the school term, with secondary cases predominantly in children aged 5–15 years and adults aged 30–49 years.
Modeling the onset of symptoms of COVID-19: Effects of SARS-CoV-2 variant

Identifying order of symptom onset of infectious diseases might aid in differentiating symptomatic infections earlier in a population thereby enabling non-pharmaceutical interventions and reducing disease spread. Previously, we developed a mathematical model predicting the order of symptoms based on data from the initial outbreak of SARS-CoV-2 in China using symptom occurrence at diagnosis and found that the order of COVID-19 symptoms differed from that of other infectious diseases including influenza. Whether this order of COVID-19 symptoms holds in the USA under changing conditions is unclear. Here, we use modeling to predict the order of symptoms using data from both the initial outbreaks in China and in the USA. Whereas patients in China were more likely to have fever before cough and then nausea/vomiting before diarrhea, patients in the USA were more likely to have cough before fever and then diarrhea before nausea/vomiting. Given that the D614G SARS-CoV-2 variant that rapidly spread from Europe to predominate in the USA during the first wave of the outbreak was not present in the initial China outbreak, we hypothesized that this mutation might affect symptom order. Supporting this notion, we found that as SARS-CoV-2 in Japan shifted from the original Wuhan reference strain to the D614G variant, symptom order shifted to the USA pattern. Google Trends analyses supported these findings, while weather, age, and comorbidities did not affect our model’s predictions of symptom order. These findings indicate that symptom order can change with mutation in viral disease and raise the possibility that D614G variant is more transmissible because infected people are more likely to cough in public before being incapacitated with fever.
Neural evidence for image quality perception based on algebraic topology

In this paper, the algebraic topological characteristics of brain networks composed of electroencephalogram(EEG) signals induced by different quality images were studied, and on that basis, a neurophysiological image quality assessment approach was proposed. Our approach acquired quality perception-related neural information via integrating the EEG collection with conventional image assessment procedures, and the physiologically meaningful brain responses to different distortion-level images were obtained by topological data analysis. According to the validation experiment results, statistically significant discrepancies of the algebraic topological characteristics of EEG data evoked by a clear image compared to that of an unclear image are observed in several frequency bands, especially in the beta band. Furthermore, the phase transition difference of brain network caused by JPEG compression is more significant, indicating that humans are more sensitive to JPEG compression other than Gaussian blur. In general, the algebraic topological characteristics of EEG signals evoked by distorted images were investigated in this paper, which contributes to the study of neurophysiological assessment of image quality.
Speed sensor-less maximum power point tracking and constant output power operation of wind-driven wound rotor induction generators

A simple control strategy has been proposed for maximum power point tracking (MPPT) mode and constant output power mode operation of variable speed wind turbine system employing wound rotor induction generators (WRIGs). The control strategy proposed in this paper has been implemented using TMS320LF2407A real time digital signal processor (DSP) and detailed procedure for such implementation is given. The salient feature of the proposed controller is that it employs only a single switch, which is an IGBT chopper and does not require any mechanical sensors or machine parameters. This makes the overall controller simple, flexible and robust. Further, space heating and battery loads are connected at rotor side of the machine through a diode bridge rectifier and the IGBT chopper. A method has been developed for the analysis of such grid connected WRIGs with variable external resistance at the chopper circuit. The successful working of the proposed controller has been amply demonstrated through extensive simulation and experimental results on the WRIG system for MPPT and constant output power operation.
Ultrasound-Guided Minimally Invasive Tissue Sampling: A Minimally Invasive Autopsy Strategy During the COVID-19 Pandemic in Brazil, 2020

Abstract Background Minimally invasive autopsies, also known as minimally invasive tissue sampling (MITS), have proven to be an alternative to complete diagnostic autopsies (CDAs) in places or situations where this procedure cannot be performed. During the coronavirus disease 2019 (COVID-19) pandemic, CDAs were suspended by March 2020 in Brazil to reduce biohazard. To contribute to the understanding of COVID-19 pathology, we have conducted ultrasound (US)–guided MITS as a strategy. Methods This case series study includes 80 autopsies performed in patients with COVID-19 confirmed by laboratorial tests. Different organs were sampled using a standardized MITS protocol. Tissues were submitted to histopathological analysis as well as immunohistochemical and molecular analysis and electron microscopy in selected cases. Results US-guided MITS proved to be a safe and highly accurate procedure; none of the personnel were infected, and accuracy ranged from 69.1% for kidney, up to 90.1% for lungs, and reaching 98.7% and 97.5% for liver and heart, respectively. US-guided MITS provided a systemic view of the disease, describing the most common pathological findings and identifying viral and other infectious agents using ancillary techniques, and also allowed COVID-19 diagnosis confirmation in 5% of the cases that were negative in premortem and postmortem nasopharyngeal/oropharyngeal swab real-time reverse-transcription polymerase chain reaction. Conclusions Our data showed that US-guided MITS has the capacity similar to CDA not only to identify but also to characterize emergent diseases.
Why enterprise resource planning initiatives do succeed in the long run: A case-based causal network

Despite remarkable academic efforts, why Enterprise Resource Planning (ERP) post-implementation success occurs still remains elusive. A reason for this shortage may be the insufficient addressing of an ERP-specific interior boundary condition, i.e., the multi-stakeholder perspective, in explaining this phenomenon. This issue may entail a gap between how ERP success is supposed to occur and how ERP success may actually occur, leading to theoretical inconsistency when investigating its causal roots. Through a case-based, inductive approach, this manuscript presents an ERP success causal network that embeds the overlooked boundary condition and offers a theoretical explanation of why the most relevant observed causal relationships may occur. The results provide a deeper understanding of the ERP success causal mechanisms and informative managerial suggestions to steer ERP initiatives towards long-haul success.
Lockdown impact on age-specific contact patterns and behaviours, France, April 2020

Background Many countries implemented national lockdowns to contain the rapid spread of SARS-CoV-2 and avoid overburdening healthcare capacity. Aim We aimed to quantify how the French lockdown impacted population mixing, contact patterns and behaviours. Methods We conducted an online survey using convenience sampling and collected information from participants aged 18 years and older between 10 April and 28 April 2020. Result Among the 42,036 survey participants, 72% normally worked outside their home, and of these, 68% changed to telework during lockdown and 17% reported being unemployed during lockdown. A decrease in public transport use was reported from 37% to 2%. Participants reported increased frequency of hand washing and changes in greeting behaviour. Wearing masks in public was generally limited. A total of 138,934 contacts were reported, with an average of 3.3 contacts per individual per day; 1.7 in the participants aged 65 years and older compared with 3.6 for younger age groups. This represented a 70% reduction compared with previous surveys, consistent with SARS-CoV2 transmission reduction measured during the lockdown. For those who maintained a professional activity outside home, the frequency of contacts at work dropped by 79%. Conclusion The lockdown affected the population's behaviour, work, risk perception and contact patterns. The frequency and heterogeneity of contacts, both of which are critical factors in determining how viruses spread, were affected. Such surveys are essential to evaluate the impact of lockdowns more accurately and anticipate epidemic dynamics in these conditions.