Miracle-dz/UniFAR-FTUs huggingface dataset:
Circularly polarized square slot microstrip antenna for RFID applications

In this paper, a novel circularly polarized square slot microstrip antenna is proposed for radio frequency identification (RFID) applications. The circular polarization is achieved by incorporating an arc-shaped strip in the square slot antenna. This antenna is fed by deformed bent feeding line to achieve a broad bandwidth (BW). The key parameters of the antenna are used for parametric study to understand the influence on the antenna performance. To validate simulation results of the design, a prototype is fabricated on the commercially available FR4 material. Measured results show a good agreement with the simulated results. It is found that the antenna shows an impedance BW of 170 MHz (844–1014 MHz) and axial-ratio BW of 170 MHz (834–1004 MHz), which shows that the proposed antenna is a good candidate to be used as a RFID antenna.
Distance to Schools and Equal Access in School Choice Systems

This paper studies the limits of school choice policies in the presence of residential segregation. Using data from the Boston Public Schools choice system, I show that white prekindergarteners are assigned to higher-achieving schools than minority students, and that cross-race school achievement gaps under choice are no lower than would be generated by a neighborhood assignment rule. To understand why choicebased assignments do not reduce gaps in school achievement, I use data on applicants’ rank-order choices to estimate preferences over schools, and consider a series of counterfactual assignments. I find that half of the gap in school achievement between white and Black or Hispanic students is explained by minorities’ longer travel distance to high-performing schools. Differences in demand parameters explain a smaller fraction of the gap, while algorithm rules have no effect. ∗I am grateful to Scott Ashworth, Kerwin Charles, Steven Durlauf, Seth Zimmerman for continuous advice and support. I also thank Santiago Caicedo, Michael Dinerstein, Margaux Luflade, Derek Neal, Luis Martinez, Peng Shi, Charlie Murry, Peter Ganong and the participants of the Harris Ph.D. Workshop and the Harris Student Applied Working Group, for helpful comments and discussions. I thank Lisa Harvey and Apryl Clarkson from Boston Public Schools for providing data and guidance. I gratefully acknowledge support by the Successful Pathway from School to Work initiative of the University of Chicago, funded by the Hymen Milgrom Supporting Organization. The conclusions of this research do not necessarily reflect the opinions or official position of Boston Public Schools, or the Massachusetts Department of Education. All errors are my own. This paper previously circulated under the name “Unequal Assignments to Public Schools and the Limits of School Choice”. †Department of Economics, Boston College. Email: mariana.laverde@bc.edu. Maloney Hall, Chestnut Hill, MA 02467, USA
REVIEW ON EDGE-CLOUD COMPUTING COLLABORATION

: The traditional cloud-based paradigm is under tremendous pressure on network bandwidth and communication latency, which is why a newly emerging paradigm of computing paradigm is involved. As a result, AIoT applications can be implemented in a cloud-based environment, where model building and model abuse are embedded in the cloud and edges, respectively. However, engineers still face the challenge of building AIoT systems in practice due to the natural diversity of IoT devices, diminishing accuracy of trained models, security and privacy issues, etc. In this paper, I want to introduce the development of an industrial edge-cloud based collaboration platform aimed at facilitating the implementation of AIoT applications. In addition, a land use case was filed in this paper, which proved the effectiveness of the AIoT application building on the platform.
RNA isolation and global gene expression analysis: Total RNA was isolated with TRIzol and quantified and verified for integrity using the Bioanalyzer 2100 (Agilent)

quantified and verified for integrity using the Bioanalyzer 2100 (Agilent). The Human Genome U133A GeneChip (Affymetrix, Santa Clara, CA) was used for gene expression profiling. cRNA synthesis, hybridization, and posthybridization staining were performed as previously described Irby and Malek using standard protocols as recommended by the manufacturer (Affymetrix). Stained chips were scanned on a GeneChip Scanner 3000 7G (Affymetrix), and data files were processed using the Affymetrix GeneChip Operating Software (GCOS) to provide probe set presence/absence detection calls (settings τ = 0.015, α1 = 0.05, α2 = 0.065), calculate signal intensities, determine quality of hybridizations, scale hybridization experiments, and calculate gene expression change. All hybridizations were scaled (normalized) to an average intensity of 500. The mean scaling factor was 5.7 with no two values differing by more than 2-fold. Additional Affymetrix quality metrics for each hybridization included % presence calls > 42%, and Sig(3′/5′) ratios less than 2 for house keeping genes such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and actin. A total of 44 hybridizations were performed for this study: naïve PBMC (3 hybridizations from individual donors, 1 hybridization from a pool of 10 donors), naïve CD8+ (3 hybridizations from individual donors, 1 hybridization from a pool of 10 donors), activated PBMC (3 hybridizations from individual donors), activated CD8+ (3 hybridizations from individual donors), leukemic LGL (30 hybridizations from individual patients).
Characterizing Spoken Dialog Corpora using Interaction Style Dimensions

The construction of dialog systems today relies heavily on appropriate corpora, but corpus selection is more an art than a science. This paper describes initial explorations with a new technique that may help: characterizing spoken dialog corpora in terms of a dimensional model of interaction styles. After discussing the need for more informative characterization of spoken dialog corpora and surveying related work, this paper presents the model, illustrates its potential utility by applying it to subsets of the Switchboard corpus, and outlines some next steps.
DMSO_A_351492 673..683

Purpose: Chronic hepatitis B (CHB) and metabolic associated fatty liver disease (MAFLD) are both important public health problems. The effect of concomitant MAFLD on patients with CHB is still unclear. This study aimed to explore the influence of MAFLD on liver fibrosis and inflammation in CHB patients with different hepatitis B e antigen (HBeAg) status. Patients and Methods: We retrospectively collected the clinical data of 399 treatment-naïve CHB patients who underwent liver biopsy. All patients were divided into two groups (HBeAg± group). Logistic regression analysis was used to identify factors associated with liver inflammatory activity and significant fibrosis in patients with CHB. Multivariable logistic regressions were repeated in subgroups stratified by HBeAg status. Results: In patients with CHB, MAFLD was independently associated with a risk of moderate-to-severe liver activity and significant fibrosis (P <0.05). In the HBeAg-negative group, patients with MAFLD had significantly higher levels of alanine aminotransferase (ALT) (P <0.05) and more severe liver inflammatory activity and fibrosis (P <0.05) compared to those without MAFLD. MAFLD was independently associated with a risk of moderate-to-severe liver activity (A ≥3: OR 3.97, 95% CI 1.71–9.22, P =0.001) and significant fibrosis (F ≥2: OR 2.02, 95% CI 1.09–3.73, P =0.026). In the HBeAg-positive group, MAFLD was found to be independently associated with moderate-to-severe liver activity (OR 2.44, 95% CI 1.03–5.79, P =0.044) but not fibrosis (P =0.618). Conclusion: MAFLD is associated with the risk of liver fibrosis and inflammatory activity in HBeAg-negative CHB patients. Sufficient attention should be paid to the prevention and treatment of MAFLD in patients with CHB, especially in HBeAg-negative patients.
Adverse HeAltH effects Among Workers in An egyptiAn leAd crystAl glAss

Introduction: Glass production workers are exposed to several workplace factors that may affect their health. Lead encountered in the manufacture of crystal glass is known to cause harmful effects. It is necessary to highlight the health effects of lead among Egyptian crystal glass workers. Aim of work: The aim of the study was to identify some health disorders in relation to blood lead level (BLL) among Egyptian workers exposed to lead in a lead crystal glass factory and find the association between (BLL) and psychological morbidities and biochemical parameters. Materials and methods: A comparative cross-sectional study was carried out in the occupational health clinic at Faculty of Medicine, Ain Shams University. It included 50 workers from a lead crystal glass manufacturing plant (exposed group) and 50 non-exposed workers. Data collected included personal data, occupational and medical histories, clinical examination and body mass index (BMI). Blood lead level (BLL), serum calcium, serum uric acid, red blood cell (RBC) count, haemoglobin, serum creatinine, and blood urea nitrogen (BUN) were measured for both groups. A general health questionnaire was used to assess psychological morbidities. Results: Exposed workers and controls were matched for gender and age. Exposed workers had significantly more gastro-intestinal, neurological, heat-related, ear and nose symptoms. Regarding biochemical parameters, BLL, blood urea nitrogen (BUN) were significantly higher among exposed workers, while serum creatinine was higher among non-exposed workers. Psychological distress was statistically significantly more prevalent among exposed workers and the difference was statistically significant. Among the exposed workers, only 60%, 56%, 56% and 26% used gloves, masks, uniform and boots, respectively. Conclusion: Elevated BLL is associated with higher BUN and psychological morbidity among exposed workers.
Optimization and Efficient Transmission Schedule for 802.11 Networks with Jamming Characteristics

- In Wireless 802.11 networks, Multiple-path source routing allows data source node to distribute the total traffic among the possible available paths. However, in this case jamming effects were not considered. Recent work has presented jamming mitigation scheme, anti-jamming Reinforcement System on 802.11 networks by assessing physical-layer functions such as rate adaptation and power control. Rate adaptation algorithms significantly degrade network performance. Appropriate tuning of carrier sensing threshold allows transmitter to send packets even on jam that enable receiver to capture desired signal. Efficient schedules need to be investigated for redundant transmission to perform well in presence of jammer. In this paper, the proposal in our work presents an Efficient Time and Transmission Schedule Scheme for wireless 802.11 networks in presence of jamming that guarantee low waiting time and low staleness of data. Schedules are optimal even jamming signal has energy limitations. Each packet is encoded by an error-correcting code (Reed-Solomon). Reed solomon code allow schedule to minimize waiting time of the clients and staleness of the received data. Jammers have restrictions on length of jamming pulses and length of intervals between subsequent jamming pulses.
Hgs Deficiency Caused Restrictive Cardiomyopathy via Disrupting Proteostasis

The molecular mechanisms underlying restrictive cardiomyopathy (RCM) are not fully understood. Hepatocyte growth factor-regulated tyrosine kinase substrate (HGS) is a vital element of Endosomal sorting required for transport (ESCRT), which mediates protein sorting for degradation and is crucial for protein homeostasis (proteostasis) maintenance. However, the physiological function and underlying mechanisms of HGS in RCM are unexplored. We hypothesized that HGS may play vital roles in cardiac homeostasis. Cardiomyocyte-specific Hgs gene knockout mice were generated and developed a phenotype similar to human RCM. Proteomic analysis revealed that Hgs deficiency impaired lysosomal homeostasis in cardiomyocytes. Loss of Hgs disrupted cholesterol transport and lysosomal integrity, resulting in lysosomal storage disorder (LSD) with aberrant autophagosome accumulation and protein aggregation. Suppression of protein aggregation by doxycycline treatment attenuated cardiac fibrosis, and diastolic dysfunction in Hgs-knockout mice. These findings uncovered a novel physiological role of HGS in regulating cardiac lysosomal homeostasis and proteostasis, suggesting that the deficient HGS contributes to LSD-associated RCM-like cardiomyopathy.
Reverse Inflammaging: Long-term effects of HCV cure on biological age

Background and Aims: Chronic hepatitis C virus (HCV) infection can be cured with direct-acting antiviral agents (DAA). However, not all sequelae of chronic hepatitis C appear to be completely reversible after sustained virologic response (SVR). Recently, chronic viral infections have been shown to be associated with biological age acceleration defined by the epigenetic clock. The aim of this study was to investigate whether chronic HCV infection is associated with epigenetic changes and biological age acceleration and whether this is reversible after SVR. Methods: We included 54 well-characterized patients with chronic hepatitis C at three time points: DAA treatment initiation, end of treatment, and long-term follow-up (median 96 weeks after end of treatment). Genome-wide DNA methylation status from peripheral blood mononuclear cells (PBMC) was generated and used to calculate epigenetic age acceleration (EAA) using Horvath's clock. Results: HCV patients had an overall significant EAA of 3.12 years at baseline compared with -2.61 years in the age-matched reference group (p<0.00003). HCV elimination resulted in a significant long-term increase in DNA methylation dominated by hypermethylated CpGs in all patient groups. Accordingly, EAA decreased to 1.37 years at long-term follow-up. The decrease in EAA was significant only between the end of treatment and follow-up (p=0.01). Interestingly, eight patients who developed hepatocellular carcinoma after SVR had the highest EAA and showed no evidence of reversal after SVR. Conclusions: Our data contribute to the understanding of the biological impact of HCV elimination after DAA and demonstrate that HCV elimination can lead to "reverse inflammaging". In addition, we provide new conceptual ideas for the use of biological age as a potential biomarker for HCV sequelae after SVR.
An efficient method to remove mixed Gaussian and random-valued impulse noise

Mixed Gaussian and Random-valued impulse noise (RVIN) removal is still a big challenge in the field of image denoising. Existing denoising algorithms have defects in denoising performance and computational complexity. Based on the improved “detecting then filtering” strategy and the idea of inpainting, this paper proposes an efficient method to remove mixed Gaussian and RVIN. The proposed algorithm contains two phases: noise classification and noise removal. The noise classifier is based on Adaptive center-weighted median filter (ACWMF), three-sigma rule and extreme value processing. Different from the traditional “detecting then filtering” strategy, a preliminary RVIN removal step is added to the noise removal phase, which leads to three steps in this phase: preliminary RVIN removal, Gaussian noise removal and final RVIN removal. Firstly, RVIN is processed to obtain a noisy image approximately corrupted by Gaussian noise only. Subsequently, Gaussian noise is re-estimated and then denoised by Block Matching and 3D filtering method (BM3D). At last, the idea of inpainting is introduced to further remove RVIN. Extensive experimental results demonstrate that the proposed method outperforms quantitatively and visually to the state-of-the-art mixed Gaussian and RVIN removal methods. In addition, it greatly shortens the computation time.
A hybrid Neural Network-SEIR model for forecasting intensive care occupancy in Switzerland during COVID-19 epidemics

Anticipating intensive care unit (ICU) occupancy is critical in supporting decision makers to impose (or relax) measures that mitigate COVID-19 transmission. Mechanistic approaches such as Susceptible-Infected-Recovered (SIR) models have traditionally been used to achieve this objective. However, formulating such models is challenged by the necessity to formulate equations for plausible causal mechanisms between the intensity of COVID-19 transmission and external epidemic drivers such as temperature, and the stringency of non-pharmaceutical interventions. Here, we combined a neural network model (NN) with a Susceptible-Exposed-Infected-Recovered model (SEIR) in a hybrid model and attempted to increase the prediction accuracy of existing models used to forecast ICU occupancy. Between 1st of October, 2020 - 1st of July, 2021, the hybrid model improved performances of the SEIR model at different geographical levels. At a national level, the hybrid model improved, prediction accuracy (i.e., mean absolute error) by 74%. At the cantonal and hospital levels, the reduction on the forecast’s mean absolute error were 46% and 50%, respectively. Our findings illustrate those predictions from hybrid model can be used to anticipate occupancy in ICU, and support the decision-making for lifesaving actions such as the transfer of patients and dispatching of medical personnel and ventilators.
Impacts of the COVID-19 pandemic on food prices: Evidence from storable and perishable commodities in India

The supply chain disruptions caused by the COVID-19 outbreak have led to changes in food prices globally. The impact of COVID-19 on the price of essential and perishable food items in developing and emerging economies has been lacking. Using a recent phone survey by the World Bank, this study examines the impact of the COVID-19 pandemic on the prices of the three essential food items in India. The results indicate that price of basic food items such as atta (wheat flour) and rice increased significantly during the pandemic compared to the pre-pandemic period. In contrast, during the same period, the price of onions declined significantly. The findings may suggest panic-buying, hoarding, and storability of food items. The results further reveal that remittance income and cash transfers from the government negatively affected commodity prices. Thus, this study’s findings suggest that families may have shifted the demand away from essential foods during the pandemic.
The effect of cognitive function and central nervous system depressant use on mortality—A prospective observational study of previously hospitalised older patients

Background Older patients are often users of prolonged Central Nervous System Depressants (CNSD) (Z-hypnotics, benzodiazepines and opioids), which may be associated with reduced cognition. The long-term effects of CNSD use and reduced cognitive function in older patients are unclear. The aim of this study was to examine whether cognitive function and CNSD use at baseline hospitalisation were associated with all-cause mortality two years after discharge. Methods We conducted a prospective observational study, including baseline data (2017–2018) from previously hospitalised older patients (65–90 years), assessing all-cause mortality two years after discharge. We used logistic regression to assess the primary outcome, all-cause mortality two years after baseline hospitalisation. The primary predictors were cognitive function measured by The Mini Mental State Examination (MMSE) and prolonged CNSD use (continuous use ≥ 4 weeks). Adjustment variables: age, gender, education, the Hospital Anxiety and Depression Scale (HADS) and the Cumulative Illness Rating Scale for Geriatrics (CIRS-G), using receiver operating characteristics (ROC) to compare the predictive power of the models. In a sub-analysis we used, the Neurobehavioural Cognitive State Examination (Cognistat) and the Clock Drawing Test. Results Two years after discharge, out of 246 baseline patients, 43 were deceased at follow-up, among these 27 (63%) were CNSD users, and 16 (36%) were non-users at baseline, (p = 0.002). In the multivariable models cognitive function (MMSE score) was a predictor of mortality (OR 0.81 (95% CI 0.69; 0.96), p = 0.014). CNSD use was associated with mortality (OR 2.71 (95% CI 1.06; 6.95), p = 0.038), with ROC AUC: 0.74–0.77 for these models. Results using Cognistat supported the findings. The Clock Drawing Test was not significant predictor of mortality. Conclusion Two years after discharge from the hospital, older patients with reduced cognitive function and CNSD use during hospital stay had higher mortality. This underlines that inappropriate (prolonged and concurrent) use of CNSDs should be avoided by older patients, particularly in patients with reduced cognitive function. Trial registration NCT03162081, 22 May 2017.
Evaluation of pharmacovigilance systems for reporting medication errors in Africa and the role of patients using a mixed-methods approach

Background Reviewing the epidemiological profile of medication errors (MEs) reported by African countries and the systems put in place to report such errors is crucial because reporting plays an important role in improving patient safety. The objectives of this study were to characterize the profile of spontaneously reported MEs submitted by African countries to VigiBase; the World Health Organization (WHO) global database of individual case safety reports, describe systems in place for reporting these errors, and explore the challenges and facilitators for spontaneous reporting and understand the potential role of patients. Methods In the present study, we used, a mixed-methods sequential explanatory design involving a quantitative review of ME reports over a 21-year period (1997–2018) and qualitative interviews with employees from African countries that are members of the WHO Program for International Drug Monitoring (WHO PIDM). Descriptive statistics were used to summarize key variables of interest. Results A total of 4,205 ME reports were submitted by African countries to VigiBase representing 0.4% of all reports in the database. Only 15 countries out of the 37 WHO PIDM members from Africa contributed ME to reports, with 99% (3,874) of them reports originating from Egypt, Morocco, and South Africa. The reasons given for low reporting of MEs were weak healthcare and pharmacovigilance systems, lack of staff capacity at the national centers, illiteracy, language difficulties, and socio-cultural and religious beliefs. Some facilitators suggested by the participants to promote reporting included proactive engagement of patients regarding issues relating to MEs, leveraging on increased technology, benchmarking and mentoring by more experienced national centers. Sixteen of the twenty countries interviewed had systems for reporting MEs integrated into adverse drug reaction reporting with minimal patient involvement in seven of these countries. Patients were not involved in directly reporting MEs in the remaining 13 countries. Conclusions MEs are rarely reported through pharmacovigilance systems in African countries with limited patient involvement. The systems are influenced by multifactorial issues some of which are not directly related to healthcare.