Miracle-dz/UniFAR-FTUs huggingface dataset:
The emerging role of lncRNAs in osteoarthritis development and potential therapy

Osteoarthritis impairs the functions of various joints, such as knees, hips, hands and spine, which causes pain, swelling, stiffness and reduced mobility in joints. Multiple factors, including age, joint injuries, obesity, and mechanical stress, could contribute to osteoarthritis development and progression. Evidence has demonstrated that genetics and epigenetics play a critical role in osteoarthritis initiation and progression. Noncoding RNAs (ncRNAs) have been revealed to participate in osteoarthritis development. In this review, we describe the pivotal functions and molecular mechanisms of numerous lncRNAs in osteoarthritis progression. We mention that long noncoding RNAs (lncRNAs) could be biomarkers for osteoarthritis diagnosis, prognosis and therapeutic targets. Moreover, we highlight the several compounds that alleviate osteoarthritis progression in part via targeting lncRNAs. Furthermore, we provide the future perspectives regarding the potential application of lncRNAs in diagnosis, treatment and prognosis of osteoarthritis.
Social support for overcoming fear of contagion at the start of the COVID-19 pandemic. Cross-sectional study in Latin America

Background The psychological impact of the COVID-19 pandemic on healthcare professionals has been widely studied, along with different strategies to minimize it. However, professionals’ assessment of the social support received and the factors that mitigated their fear of contagion have not been described. This study aimed to assess healthcare professionals’ satisfaction with the social support and information received and their efforts to self-isolate to avoid infecting loved ones in Chile, Colombia, and Ecuador. Methods A cross-sectional online survey, conducted from July to September 2020 in three Latin American countries, elicited healthcare professionals’ satisfaction with social support from colleagues, their community, the media, and scientific societies; as well as the information received about the evolution of the pandemic and measures to avoid contagion. The EASE scale was used to measure acute stress. Results Survey responses were received from 700 professionals. The response rate per country exceeded the estimated sample size except in the case of Colombia, which was 81.4%. In general, peer support was highly valued, though satisfaction was lower in high-risk units (p < 0.001). Those who directly assisted COVID-19 patients perceived the least community support (p = 0.023). Professionals from high-risk units (p = 0.013) and those who experienced greater acute stress (p = 0.05) assigned the lowest rating to the information offered by the centre on the pandemic. Men perceived more support from colleagues and better information from the centre than women (p < 0.05). Just 10.7% of professionals changed their residence during the pandemic, but those who worked in high-risk areas self-isolated more frequently (p = 0.026). Conclusion In the early stages of the COVID-19 pandemic, healthcare professionals in Chile, Colombia, and Ecuador greatly valued the support received from their peers. Being infected with COVID-19, working in high-risk areas, experiencing higher self-reported acute stress, and having an infected co-worker were predictors for self-isolation to protect their relatives. These results point to the appropriateness of putting in place institutional resources based on peer support and specific communication strategies and action protocols to build resilience and responsiveness to future health crises.
A Bayesian analysis for the Mann-Whitney statistic

Abstract A Bayesian analysis is developed for the Mann-Whitney (U) statistic. The analysis is focused on an Ω parameter, which is defined as the integrated proportion of the population in a generic experimental condition that has values that exceed values in a separate control condition. The likelihood function is approximated for both small and large sample size studies. The likelihood function is free of distributional assumptions about the actual experimental and control variates. A Monte Carlo method is used for small sample sizes, and a conjugate beta approximation model is developed for larger sample sizes. If there are 15 or more observations in each condition, the large sample approximation is highly accurate across a wide range of outcomes. The Bayes-factor efficiency and power efficiency are explored for the new Bayesian method. For properly specified Gaussian data, the power efficiency for the new method is nearly equal to that of the t test. But cases were identified for nonGaussian distributions where the power efficiency was superior for the Bayesian Mann-Whitney procedure. The new Bayesian analysis is thus a robust and powerful alternative to parametric models for examining the data from two independent conditions.
Unemployment and the Distribution of Liquidity

We study the long-run effects of money creation and inflation in a New Monetarist model of unemployment in which distributional considerations matter. Households face employment and expenditure risk and self-insure by accumulating assets with different liquidities and returns. Inflation affects unemployment primarily through two channels: an aggregate-demand channel, through which inflation reduces households’ liquid wealth and firms’ expected revenue, and an interest-rate channel, through which inflation affects firms’ financial discount rate. Quantitatively, the aggregate-demand channel dominates and the long-run Phillips curve has a positive slope—inflation increases unemployment—although inflation can have large redistributive effects and increase aggregate welfare.
Role of Internet of Things and Deep Learning Techniques in Plant Disease Detection and Classification: A Focused Review

The automatic detection, visualization, and classification of plant diseases through image datasets are key challenges for precision and smart farming. The technological solutions proposed so far highlight the supremacy of the Internet of Things in data collection, storage, and communication, and deep learning models in automatic feature extraction and feature selection. Therefore, the integration of these technologies is emerging as a key tool for the monitoring, data capturing, prediction, detection, visualization, and classification of plant diseases from crop images. This manuscript presents a rigorous review of the Internet of Things and deep learning models employed for plant disease monitoring and classification. The review encompasses the unique strengths and limitations of different architectures. It highlights the research gaps identified from the related works proposed in the literature. It also presents a comparison of the performance of different deep learning models on publicly available datasets. The comparison gives insights into the selection of the optimum deep learning models according to the size of the dataset, expected response time, and resources available for computation and storage. This review is important in terms of developing optimized and hybrid models for plant disease classification.
Characterization of corn, cassava, and commercial flours: Use of amylase‐rich flours of germinated corn and sweet potato in the reduction of the consistency of the gruels made from these flours—Influence on the nutritional and energy value

Abstract Malnutrition appears in weaning age and is usually due to weaning food which is of low nutritional value. This problem led us to investigate the study of the physicochemical and functional properties of cassava flours and corn flours, and the fluidification of the gruels made from these flours by germinated yellow corn and sweet white potato flours. To do this, the approximate chemical composition, physical and functional properties, and ability of amylase‐rich flours to digest the starch in order to reduce consistency were evaluated. From these analyses, it emerges that the chemical composition, and physical and functional properties are influenced by the nature and the treatment undergone by the flours. It appears that the amylase‐rich flours that we used at a concentration of 1%–3% during the preparation of the gruels significantly reduced their consistencies. Given their strong liquefying power, this reduction was more marked with germinated corn flour where 1% permits to obtain desired consistency with 21.50 g of DM of bitter cassava flour, thereby multiplying the energy density and nutritional value of this flour by 5.18. It also appears that the action of flours rich in amylases was depending on the concentration, the nature of the flour, its composition, and the treatment undergone. In view of all these results, we can therefore consider the formulation of a weaning food with the consistency, and energy and nutritional value necessary for the proper growth of children.
The impact of macroprudential policy and political institutions on bank credit risk in Ethiopia: A dynamic ordinary least squares analysis

Abstract Credit risk in financial institutions has been widely debated among experts and legislators as a substantial risk to the financial industry’s health. In addition to examining bank-specific and macroeconomic reasons, the study examines the impacts of political institutions and macroprudential regulations on credit risk in Ethiopia. Using panel data from 2011–2019 and employing dynamic ordinary least squares, the findings imply that political institutions have significant positive links to credit risk. It also found that macroprudential policy helps to control bank risk and reduce exposure in the banking industry. The results indicate that banks with larger sizes and profitability have less credit risk. The findings support the’skimping’ and “dark side of diversification” hypotheses; retaining a higher loan-to-asset ratio, cost-effectiveness, and diversity of the banking commercial model reduces credit quality by promoting credit risk. A higher inflation rate reduces credit risk by increasing borrowers’ potential to service their debts when lending rates are fixed. GDP and the exchange rate have little influence on credit risk. The outcomes of this study provide significant implications for authorities and bankers in developing countries such as Ethiopia in the understanding of credit risk-determining elements to implement prudential rules and remedial management policies.
Use of grain number components as selection criteria in pearl millet.

The use of panicle number/plant and panicle surface area as indirect selection criteria for grain yield was studied in an open pollinated, synthetic dwarf variety of Pennisetum glaucum (ICMS7901) at Patancheru. Spaced plants were grown in the rainy season of 1980 and selected selfed plants were evaluated during the rainy season of 1981; further field trials were conducted in 1982 and 1984 using subsynthetics. Information on grain yield and 4 yield components (number of panicles and grains per m², number of grains per panicle and grain weight) is tabulated for the selfed progeny and subsynthetics. Data indicated that selecting for both panicle number /plant and panicle size resulted in improvements in the yield components, while selecting only for increased panicle size resulted in a notably higher grain mass.
Type D personality in obese patients, including selected aspects of body image

Introduction and Objective . Obesity is a disease that develops due to the occurrence or co-occurrence of various factors. So far, it has not been possible to link a selected personality type to obesity, but many of the traits observed in obese people are reflected in the type D personality. Understanding a patient›s personality type or selected traits of this personality, allow improvement of the psychological functioning of the patient in the disease. This is particularly important in the case of chronic diseases, to which obesity belongs. The aim of the study was to determine the prevalence of type D personality among obese patients. There was also an attempt to assess the relationship between body perception and the occurrence of stress personality among obese people. Materials and method . The study group consisted of 443 patients with BMI ≥30 kg/m2, hospitalized in selected hospital facilities in the Silesia Province inj south-west Poland. The following research tools were used: the author's questionnaire, Type D Scale-14 (DS14), and the Body Image Questionnaire (KWCO-40). Results . The prevalence of type D personality among obese patients was almost 40%. The actual prevalence of type D personality among obese patients was within 95% CI: (33.6% – 42.6%), while non-type D personality was within 95% CI: (28.3% – 37.1%), and intermediate personality within 95% CI: (24.8% – 33.3%). The most dissatisfaction with body image was found among respondents with type D personality, women, and those with Class III obesity. Conclusions. Understanding and identifying the factors that influence the increasing problem of obesity is difficult, but based on the present study, the assumption is made that personality type may play a role in the development of this disorder.
Upland Hillslope Groundwater Subsidy Affects Low‐Flow Storage–Discharge Relationship

Large‐scale cross‐site scientific synthesis on low‐flow storage–discharge relation can promote developing transferable hypotheses on the interactions among critical zone attributes and on how such interactions affect catchments’ water vulnerabilities. This study leverages cross‐site empirical and theoretical analyses and develops a similarity index, based on the interactions among critical zone attributes, to help determine the less‐explored influence of upland hillslope groundwater subsidy on storage–discharge relation. We show that an increase in the relative extent of upland hillslope groundwater subsidy to low‐flow discharge, occurring through deep slow low‐moving (e.g., bedrock) storage unit, leads to (a) an increase in the nonlinearity of low‐flow discharge sensitivity to storage (β1) and (b) an increase in the convexity of low‐flow storage–discharge relation. Our findings also raise new hypotheses on the applicability of Boussinesq‐based hydraulic groundwater theory at low‐flow condition. Empirical results show that in a portion of our study catchments, particularly in those with a relatively small extent of upland hillslope groundwater subsidy, the theory’s proposed range of nonlinearity sufficiently explains the nonlinearity of low‐flow storage–discharge relation. However, in catchments with a strong influence of upland hillslope groundwater subsidy through deep slow‐moving storage unit, the current state of hydraulic groundwater theory, using one single (non)linear representative storage unit, may not be sufficient to explain the large nonlinearity and convexity of low‐flow storage–discharge relation (or the long tail of hydrograph late recession). Considering β1 informs the low‐flow vulnerability of catchments, the findings of this study deepen and generalize our understanding of where low‐flow discharge is vulnerable to storage’s change.
Prevalence of Urinary Tract Infection in Children With Severe Acute Malnutrition Aged Between Six Months and Five Years and Their Antibiotic Sensitivity Pattern

Objective This study was conducted to determine the prevalence of urinary tract infection in children with severe acute malnutrition (SAM) aged between six months and five years and to identify the causative organisms and their antibiotic sensitivity pattern. Study design This study was an observational cross-sectional study. Setting and participants The study was conducted in the Department of Paediatrics in a tertiary care hospital in India over a period of 18 months. A total of 140 children aged between six months and five years according to the World Health Organisation's criteria of severe acute malnutrition were included upon fulfillment of inclusion and exclusion criteria. Ultrasound of kidney, ureter, and bladder (USG-KUB) was also done to exclude children with any underlying anatomical anomaly. Intervention Detailed clinical examination was performed on each of the participants with emphasis on anthropometry. Relevant blood investigations were sent along with urine routine microscopy and culture sensitivity in all patients. Results The prevalence of urinary tract infection (UTI) in our study was 23.57%. The most common organism isolated was Escherichia coli found in 54.54% of cases, followed by Klebsiella in 24.24%. Other organisms isolated were Enterococcus in 12.12%, Pseudomonas aeruginosa 6.06% and Citrobacter in 3.03%. E. coli showed high sensitivity to imipenem (88.87%), meropenem (83.84%), nitrofurantoin (77.76%) and amikacin (72.23%). Overall these organisms showed good sensitivity to amikacin (60.06%), imipenem (66.6%), meropenem (63.63%) and nitrofurantoin (72.72%). Resistance to common antibiotics like ciprofloxacin, cefotaxime and cefuroxime was seen. Conclusion Children with malnutrition are at risk of UTI. Urine routine examination and urine culture should be performed in all these children before starting antibiotics. Selection of an antibiotic should be according to the local drug sensitivity data. These antibiotics should have good efficacy against gram-negative organisms.
Limited Asset Market Participation and the Euro Area Crisis. An Empirical DSGE Model

We estimate a medium scale DSGE model for the Euro area with Limited Asset Market Participation (LAMP). Our results suggest that in the recent EMU years LAMP is particularly sizeable (393 during 1993-2012) and important to understand business cycle features. The Bayes factor and the forecasting performance show that the LAMP model is preferred to its representative household counterpart. In the RA model the risk premium shock is the main driver of output volatility in order to match consumption correlation with output. In the LAMP model this role is played by the investment-specific shock, because Non-Ricardian households introduce a Keynesian multiplier effect and raise the correlation between consumption and investments. We also detect contractionary role of monetary policy shocks during the post-2007 years. In this period consumption of Non-Ricardian households fell dramatically, but this outcome might have been avoided by a more aggressive policy stance.
Could Natural Products Help in the Control of Obesity? Current Insights and Future Perspectives

Obesity is a global issue faced by many individuals worldwide. However, no drug has a pronounced effect with few side effects. Green tea, a well-known natural product, shows preventive effects against obesity by decreasing lipogenesis and increasing fat oxidation and antioxidant capacity. In contrast, other natural products are known to contribute to obesity. Relevant articles published on the therapeutic effect of natural products on obesity were retrieved from PubMed, Web of Science, and Scopus. The search was conducted by entering keywords such as “obesity”, “natural product”, and “clinical trial”. The natural products were classified as single compounds, foods, teas, fruits, herbal medicines—single extract, herbal medicines—decoction, and herbal medicines—external preparation. Then, the mechanisms of these medicines were organized into lipid metabolism, anti-inflammation, antioxidation, appetite loss, and thermogenesis. This review aimed to assess the efficacy and mechanisms of effective natural products in managing obesity. Several clinical studies reported that natural products showed antiobesity effects, including Coffea arabica (coffee), Camellia sinensis (green tea), Caulerpa racemosa (green algae), Allium sativum (garlic), combined Ephedra intermedia Schrenk, Thea sinensis L. , and Atractylodes lancea DC extract (known as Gambisan), Ephedra sinica Stapf, Angelica Gigantis Radix, Atractylodis Rhizoma Alba, Coicis semen, Cinnamomi cortex, Paeoniae radix alba, and Glycyrrhiza uralensis (known as Euiiyin-tang formula). Further studies are expected to refine the pharmacological effects of natural products for clinical use.
High and Dry: Trading Water Vapor, Fuel and Observing Time for SOFIA

The Stratospheric Observatory for Infrared Astronomy (SOFIA) is NASA's next generation airborne astronomical observatory. The facility consists of a 747-SP modified to accommodate a 2.5 meter telescope. SOFIA is expected to fly an average of 140 science flights per year over it's 20 year lifetime, and will commence operations in early 2005. The SOFIA telescope is mounted aft of the wings on the port side of the aircraft and is articulated through a range of 20 deg to 60 deg of elevation. A significant problem in future SOFIA operations is that of scheduling Facility Instrument (E) flights in support of the SOFIA General Investigator (GI) program. GIs are expected to propose small numbers of observations, and many observations must be grouped together to make up single flights. Approximately 70 GI flight per year are expected, with 5-15 observations per flight.
Empirical dietary inflammatory index and lifestyle inflammation score relationship with obesity: A population‐based cross‐sectional study

Abstract The present study aimed to investigate the association between the empirical dietary inflammatory index (EDII) and lifestyle inflammatory score (LIS) with general and abdominal obesity in Iranian adults using data from the Yazd Health study (YaHS). This cross‐sectional study was conducted using the information of participants of the YaHS study. The dietary assessment was conducted using a validated food frequency questionnaire (FFQ) and anthropometric measurements assessed by standard protocols. The inflammatory potential of diet and lifestyle were calculated using EDII and LIS scores. We also created a combinational index of EDII and LIS as an EDII‐LIS score. General and abdominal obesity were defined based on body mass index (BMI), waist circumference (WC), and waist‐to‐hip ratio (WHR) cut points, respectively. The odds ratio (OR) and 95% confidence interval (CI) of general and abdominal obesity across tertiles of EDII and LIS were estimated using logistic regression analyses, adjusted for potential confounders. A significant association was found between a higher EDII score and general obesity (OR: 1.21, 95% CI: 1.04–1.41, p trend: .016), however, there was no significant association between EDII and both definitions of abdominal obesity. Participants in the highest versus lowest tertile of LIS had higher odds of increased abdominal obesity (ORWC: 37.0, 95% CI: 28.8–47.5, p trend <.001, ORWHR: 3.30, 95% CI: 2.65–4.11, p trend <.001). In addition, there was also a direct relationship between the higher score of EDII‐LIS and the increased likelihood of abdominal obesity (ORWC: 15.0, 95% CI: 12.3–18.3, p trend <.001, ORWHR: 2.68, 95% CI: 2.18–3.29, p trend <.001). Greater adherence to the EDII score was associated with a higher odds of general obesity, but not abdominal obesity. Also, individuals with a higher score of LIS and EDII‐LIS are more prone to abdominal obesity.