Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of En-bloc Transurethral Resection of Bladder Tumour on Clinical, Pathological and Oncological Outcomes: A Cohort Study

Background En-bloc transurethral resection of bladder tissue (ETURBT) has recently been proposed as a good alternative technique to trans-urethral resection of bladder tissue (TURBT) in terms of outcomes for bladder carcinoma. This study aims to assess the effectiveness of the technique in terms of clinical, pathological and oncological outcomes. Methodology In this prospective study, data was collected from patients who underwent ETURBT for bladder space-occupying lesions between June 2021 and June 2022. Demographic characteristics, tumour characteristics, and postoperative outcomes were recorded. Results A total of 52 patients were studied with the majority being male and a mean age of 50.87 years. Smoking was recorded in 22 (38.5%) patients and 8 (15.4%) were on antiplatelet therapy. The majority fell in the American Society of Anesthesiology (ASA) class I (59.6%). Most of the tumours were solitary (90.4%), primary (82.8%), papillary architecture (73.1%), and between 1-3 cm in size. The lateral wall was the most common position, and detrusor muscle was seen in 98.1% of the specimens. T1 stage (57.7%) and low grade (67.3%) were the common characteristics noted. 76.9% of the ETURBT was conducted using monopolar cautery. Recurrence was noted in 3 (5.8%) and bladder perforation in 1 patient (1.9%). Cautery artifact was seen in six patients (11.5%) and obturator jerk in nine patients (17.3%). Conclusion Our study suggests that ETURBT is a technique with a good success rate for bladder tumours less than 3 cm in size. The benefits include high chances of detrusor sampling while minimising crush artefacts and cautery damage. Specimen retrieval was challenging when the bladder tumour was solid and over 2 cm.
A Two-Parameter Logistic Extension Model: An Efficient Variant of the Three-Parameter Logistic Model

A three-parameter logistic (3PL) model variant, named the two-parameter logistic extension (2PLE) model, was developed. This new model employs a function that integrates item features according to an examinee’s ability level instead of a fixed guessing parameter used in the 3PL model to quantify guessing behavior. Correct response probabilities from a solution behavior and guessing behavior increase as the level of ability increases. At extreme cases in which the level of ability is close to negative infinity, the 2PLE model degenerates into a 3PL model with a guessing probability at chance level (i.e., 1/m, where m is the number of options). The properties of the 2PLE model were described and compared with those of other guessing models. Then, a simulation study comparing the performance of the 2PLE model with that of the 3PL model under three scenarios was conducted. Results showed that the 2PLE model generally outperforms the 3PL model. Finally, the application of the new model in comparison with several existing models was demonstrated by using two real data sets.
Are Energy and Protein Intakes Lower Than Requirements in Older Adults? An Urgent Issue in Hospitals and Nursing Homes

Energy and protein intakes lower than requirements are associated with worsening health outcomes. Here we set out to evaluate gaps between energy and protein intakes and requirements in older adults in hospitals and in nursing homes (NH). A cross-sectional study included 360 inpatients and residents aged 75 years and older in two acute care wards; i.e., a multidisciplinary care unit (MCU) and a geriatric care unit (GCU), a geriatric rehabilitation unit (GRU), and two NH. Intakes were measured for three days. Requirements were based on French National Health Authority recommendations. Energy and protein intakes were under the minimum requirement of 30 kcal/kg/day and 1.2 g/kg/day in 89.5% and 100% of MCU patients, respectively, 75.5% and 64.2% of GCU patients, 92.7% and 90.9% of GRU patients, and 83.8% and 83.8 of NH residents. Intake-to-requirement gaps were not significantly associated with malnutrition, except in the GCU group where non-malnourished patients had higher energy gaps than malnourished patients. Intakes fell dramatically short of requirements in older adults in both hospital and NH settings irrespective of malnutrition status. A new paradigm based on a patient-centered approach should be developed to adapt meals served in hospital and in NH.
Prevalence and Determinants of Long COVID among the COVID-19 Survivors: A Cross-sectional Study from A Rural Area of Maharashtra

Background: Most patients infected with the COVID-19 virus may experience long-term effects from COVID-19 infection, known as post-COVID or long COVID conditions. Long COVID may last for weeks, months or years and may limit ones day to day activities and needs health care. Aim & Objective: To study the prevalence and risk factors of long COVID among the COVID-19 survivors of a rural area of Maharashtra. Methods and Material: A Community-based cross-sectional study was conducted in adult subjects residing in Chanai village from Maharashtra who have had a history of COVID-19 and have passed more than 3 months since the diagnosis from May 2022 to June 2022. The interview of the study participants was conducted with the help of a pre-designed, semi-structured questionnaire for data collection. Statistical Analysis: Data was analyzed using Microsoft Excel 2010, Open EPI-Info version 3.01 updated on 2013/04/06. Data was presented in tables, graphical format, frequencies and percentages and the statistical association was shown using the chi- square test. Results: The majority of participants were males (59%), from 19 to 39 years of age group (57%), having fever as presenting symptom (83%), with mild COVID (13%), and required hospitalization (53%). Long COVID was associated with the elderly age group, male sex (27.1%), severe COVID presentation (88.2%) after 12 weeks, and those required intubation (80%). Conclusion: The prevalence of long COVID was 17.5%. Determinants associated with long COVID were the elderly age group, male sex, severe COVID presentation and who required intubation.
N-Doped Graphenic Carbon Derived from Coconut Shell as n-Type Semiconducting Layer

The presence of N-dopant in Reduced Graphene Oxide has contributed to the change of their optical band gap. In this research, this mechanism has been implemented to synthesize nitrogen-doped graphenic carbon (NGC) proposed as an n-type semiconducting layer. The graphenic-based carbon (GC) was derived from coconut shells by a green synthesis method. The two sources of nitrogen dopants were prepared from ammonia water (NH4OH) and urea (CH4N2O). Synthesis of NGC was conducted from GC and a particular dopant with a ratio of 1:20 and 1:40 by wet mixing. Then the NGC solution was deposited onto a 1x1 cm2 glass substrate using a nanospray method to form a layer. X-ray diffraction (XRD) of NGC film has indicated an amorphous characteristic of the film. According to Energy Dispersive X-ray (EDX) spectroscopy, the presence of nitrogen as a doping material in the GC was successfully demonstrated. The SEM cross-section image has performed the NGC layer on the substrate. Absorbance analysis from UV-Vis spectroscopy also explains the occurrence of electronic transitions, both in the form of a solution and a layer of NGC material. The further analysis explained that the optical band gap of the NGC material ranged from 1.66 – 1.86 eV, which exhibits the semiconductor characteristic of the NGC material.
Supervisory sanctions, ESG practices, and banks’ reputation: A market performance analysis of sanctioned banks

The purpose of this paper is to study the impact of environmental, social, and governance (ESG) practices on banks’ reputation and market performance. In particular, we aim to analyse whether banks adopting ESG-compliant practices can reduce their reputational damage due to financial sanctions and increase their market performance. In order to demonstrate the effect of banks’ ESG practices in reducing reputational damage due to financial penalties imposed by supervisors for breaches of regulatory requirements, we analyze a sample of 21 banks — selected because of the availability of information on sanctions imposed by the supervisory authorities — by applying a pre-selection model based on the trend of historical returns. With reference to the selected sample, we verify the percentage of securities characterized by different levels of sanctions and different ESG scores. Overall, we find that ESG aspects have a positive impact on stock performance, although higher ESG scores do not, per se, mean a lower probability of sanctions. Differing from previous research, our study, by focusing on financial sanctions, provides useful insights concerning the ESG impact on both market performance and reputational aspects.
L-serine: Neurological Implications and Therapeutic Potential

L-serine is a non-essential amino acid that plays a vital role in protein synthesis, cell proliferation, development, and sphingolipid formation in the central nervous system. It exerts its effects through the activation of glycine receptors and upregulation of PPAR-γ, resulting in neurotransmitter synthesis, neuroprotection, and anti-inflammatory effects. L-serine shows potential as a protective agent in various neurological diseases and neurodegenerative disorders. Deficiency of L-serine and its downstream products has been linked to severe neurological deficits. Despite its crucial role, there is limited understanding of its mechanistic production and impact on glial and neuronal cells. Most of the focus has been on D-serine, the downstream product of L-serine, which has been implicated in a wide range of neurological diseases. However, L-serine is approved by FDA for supplemental use, while D-serine is not. Hence, it is imperative that we investigate the wider effects of L-serine, particularly in relation to the pathogenesis of several neurological deficits that, in turn, lead to diseases. This review aims to explore current knowledge surrounding L-serine and its potential as a treatment for various neurological diseases and neurodegenerative disorders.
SRDF: Single-Stage Rotate Object Detector via Dense Prediction and False Positive Suppression

Oriented object detection has made astonishing progress. However, existing methods neglect to address the issue of false positives caused by the background or nearby clutter objects. Meanwhile, class imbalance and boundary overflow issues caused by the predicting rotation angles may affect the accuracy of rotated bounding box predictions. To address the above issues, we propose a single-stage rotate object detector via dense prediction and false positive suppression (SRDF). Specifically, we design an instance-level false positive suppression module (IFPSM), IFPSM acquires the weight information of target and nontarget regions by supervised learning of spatial feature encoding, and applies these weight values to the deep feature map, thereby attenuating the response signals of nontarget regions within the deep feature map. Compared to commonly used attention mechanisms, this approach more accurately suppresses false-positive regions. Then, we introduce a hybrid classification and regression method to represent the object orientation, the proposed method divide the angle into two segments for prediction, reducing the number of categories and narrowing the range of regression. This alleviates the issue of class imbalance caused by treating one degree as a single category in classification prediction, as well as the problem of boundary overflow caused by directly regressing the angle. In addition, we transform the traditional post-processing steps based on matching and searching to a 2-D probability distribution mathematical model, which accurately and quickly extracts the bounding boxes from dense prediction results. Extensive experiments on Remote Sensing, synthetic aperture radar (SAR), and Scene Text benchmarks demonstrate the superiority of the proposed SRDF method over state-of-the-art (SOTA) rotated object detection methods. Our codes are available at https://github.com/TomZandJerryZ/SRDF.
Evaluation of Antibiotic Prescribing Pattern Using WHO Access, Watch and Reserve Classification in Kinshasa, Democratic Republic of Congo

Background: The AWaRe tool was set up by the World Health Organization (WHO) to promote the rational use of antimicrobials. Indeed, this tool classifies antibiotics into four groups: access, watch, reserve and not-recommended antibiotics. In The Democratic Republic of Congo, data on antibiotic dispensing (prescribing) by health professionals according to the AWaRe classification are scarce. In this research work, we aimed to explore antibiotic dispensing pattern from health professionals according to the WHO AWaRe classification to strengthen the national antimicrobial resistance plan. Methods: For this purpose, a survey was conducted from July to December 2022 in the district of Tshangu in Kinshasa. From randomly selected drugstores, drug-sellers were interviewed and randomly selected customers attending those drugstores were included in the study for medical prescriptions collection. The prescribed antibiotics were classified into the access, watch, reserve and not-recommended antibiotics group and by antibiotics number by prescription among pharmacies surveyed. Results: 400 medical prescriptions were collected from 80 drugstores and among which, 301 (75.25%) contained antibiotics. Out of 301 prescriptions, we noticed 164 (54.5%) containing one antibiotic, 117 (38.9%) containing two antibiotics, 15 (5%) containing three antibiotics and 5 (1.6%) containing four antibiotics. A total of 463 antibiotics were prescribed and distributed as 169 (36.5%) were from the access group, 200 (43.2%) from the watch group and 94 (20.3%) from not-recommended antibiotics group, respectively. This can explain the fact of emerging bacterial strains, as, according to the WHO recommendations, the access group should be prioritized because of its activity against a wide range of commonly encountered pathogens and its showing low resistance susceptibility compared to antibiotics from other groups. Based on the anatomical, therapeutic and chemical (ATC) classifications, we observed that third generation cephalosporins represented 34.33% of the prescribed antibiotics, followed by penicillins (17.17%), macrolides (7.63%), aminoglycosides (7.36%) and Imidazole (7.36%), thus accounting approximately for 74% of the classes of antibiotics prescribed. Additionally, among them, the most frequently prescribed antibiotics were Ceftriaxone (21.38%), Amoxicillin (11.01%), Gentamycin (5.61%), Amoxicillin-clavulanic acid (5.61%), Azithromycin (4.97%) and Metronidazole (4.75%), thus accounting for approximately 54% of all the prescribed antibiotics. Conclusion: These results highlight the importance of strict implementation of the national plan to combat antimicrobial resistance and the need to train health workers in the correct application of the WHO AWaRe classification.
On the Correlation between Total Condensate and Moist Heating in Tropical Cyclones and Applications for Diagnosing Intensity

While the transfer of moist enthalpy from the ocean to the atmosphere is the fundamental energy source for tropical cyclones, the release of latent heat in moist convection is the mechanism by which this energy is converted into the kinetic and potential energy of these storms. Most observational estimates of this heat release rely on satellite estimates of rain rate. Here, examination of five high-resolution numerical simulations of tropical cyclones reveals that there is a close correlation between the total condensate and the total heating, even though the former quantity is an amount and the latter is a rate. This relationship is due to the fact that for condensate to be sustained at large values, it must be rapidly replaced by new condensate and associated latent heating. Total condensate and total rain rate within fixed radial distances such as 111 km also show good correlations with the current intensity of the storm, but surprisingly, high values of condensate at high altitudes and close to the storm center are not good predictors of imminent intensification. These relationships are confirmed with an additional ensemble of 270 idealized simulations of tropical cyclones with varying sizes and intensities. Finally, simulated measurements of total condensate are computed from narrow swaths modeled after the cloud profiling radar on the CloudSat satellite. Despite their narrow footprint and the fact that they rarely cut through the exact center of the cyclone, these estimates of total condensate also show a useful correlation with current intensity.
Lower hybrid waves at comet 67P/Churyumov–Gerasimenko

We investigate the generation of waves in the lower hybrid frequency range by density gradients in the near plasma environment of comet 67P/Churyumov–Gerasimenko. When the plasma is dominated by water ions from the comet, a situation with magnetized electrons and unmagnetized ions is favourable for the generation of lower hybrid waves. These waves can transfer energy between ions and electrons and reshape the plasma environment of the comet. We consider cometocentric distances out to a few hundred km. We find that when the electron motion is not significantly interrupted by collisions with neutrals, large average gradients within tens of km of the comet, as well as often observed local large density gradients at larger distances, are often likely to be favourable for the generation of lower hybrid waves. Overall, we find that waves in the lower hybrid frequency range are likely to be common in the near plasma environment.
Polynomials, random walks and risk processes: a multivariate framework

This paper is concerned with two families of multivariate polynomials: the Appell polynomials and the Abel-Gontcharoff polynomials. Both families are well-known in the univariate case, but their multivariate version is much less standard. We first provide a simple interpretation of these polynomials through particular constrained random walks on a lattice. We then derive nice analytical results for two special cases where the parameters of the polynomials are randomized. Thanks to the interpretation and randomization of the polynomials, we can derive new results and give other insights for the study of two different risk problems: the ruin probability in a multiline insurance model and the size distribution in a multigroup epidemic.
One Material-Opposite Triboelectrification: Molecular Engineering Regulated Triboelectrification on Silica Surface to Enhance TENG Efficiency

Molecular engineering is a unique methodology to take advantage of the electrochemical characteristics of materials that are used in energy-harvesting devices. Particularly in triboelectric nanogenerator (TENG) studies, molecular grafting on dielectric metal oxide surfaces can be regarded as a feasible way to alter the surface charge density that directly affects the charge potential of triboelectric layers. Herein, we develop a feasible methodology to synthesize organic–inorganic hybrid structures with tunable triboelectric features. Different types of self-assembled monolayers (SAMs) with electron-donating and withdrawing groups have been used to modify metal oxide (MO) surfaces and to modify their charge density on the surface. All the synthetic routes for hybrid material production have been clearly shown and the formation of covalent bonds on the MO’s surface has been confirmed by XPS. The obtained hybrid structures were applied as dopants to distinct polymer matrices with various ratios and fiberization processes were carried out to the prepare opposite triboelectric layers. The formation of the fibers was analyzed by SEM, while their surface morphology and physicochemical features have been measured by AFM and a drop shape analyzer. The triboelectric charge potential of each layer after doping and their contribution to the TENG device’s parameters have been investigated. For each triboelectric layer, the best-performing tribopositive and tribonegative material combination was separately determined and then these opposite layers were used to fabricate TENG with the highest efficiency. A comparison of the device parameters with the reference indicated that the best tribopositive material gave rise to a 40% increase in the output voltage and produced 231 V, whereas the best tribonegative one led to a 33.3% rise in voltage and generated 220 V. In addition, the best device collected ~83% more charge than the reference device and came up with 250 V that corresponds to 51.5% performance enhancement. This approach paved the way by addressing the issue of how molecular engineering can be used to manipulate the triboelectric features of the same materials.
Data to accompany the article "Observations of whitecap coverage and the relation to wind stress, wave slope, and turbulent dissipation"

Shipboard measurements of whitecap coverage are presented from two cruises in the North Pacific, and compared with in situ measurements of wind speed and friction velocity, average wave steepness, and near-surface turbulent dissipation. A threshold power law fit is proposed for all variables, which incorporates the flexibility of a power law with the threshold behavior commonly seen in whitecapping. The fit of whitecap coverage to wind speed, U10, closely matches similar relations from three recent studies, particularly in the range of 6–14 m/s. At higher wind speeds, the whitecap coverage data level off relative to the fits, and an analysis of the residuals shows some evidence of reduced whitecapping in rapidly developing waves. Wave slope variables are examined for potential improvement over wind speed parameterizations. Of these variables, the mean square slope of the equilibrium range waves has the best statistics, which are further improved after normalizing by the directional spread and frequency bandwidth. Finally, the whitecap coverage is compared to measurements of turbulent dissipation. Though still statistically significant, the correlation is worse than the wind or wave relations, and residuals show a strong negative trend with wave age. This may be due to an increased influence of microbreaking in older wind seas.
PARAMETERIZATION OF SURFACE MOMENTUM FLUX DURING CONVECTIVE CONDITIONS

Parameterization of surface momentum flux estimates near-surface turbulent momentum fluxes from differences of mean wind speeds between the surface skin and the mid-mixed layer (ML). The rate of this turbulent transport is proportional to the product of a convective velocity times an empirical transport coefficient. To further investigate parameterization of surface momentum flux, some topics are discussed. New data from three different sites within Boundary Layer Experiment - 1996 (BLX96) are presented, and used to evaluate surface momentum flux parameterization. Old data from three other field programs (BLX83, Koorin, and TOGA-COARE) are re-analyzed to test this parameterization. Evidence from virtually all of these experiments indicates that the empirical transport coefficients for momentum fluxes depend on surface roughness. Fluks momentum turbulen dekat permukaan dapat diestimasi dari selisih antara kecepatan angin di batas permukaan (surface skin) dan di bagian tengah lapisan tercampur (mid-mixed layer). Kecepatan dari transpor turbulen ini sebanding dengan perkalian antara koefisien empiris transpor dengan kecepatan konvektif. Untuk pengamatan lebih lanjut akan didiskusikan beberapa hal. Data baru dari hasil pengukuran BLX96 pada 3 lokasi yang berbeda akan digunakan untuk mengevaluasi parameterisasi ini. Sementara data yang diperoleh dari yang pernah dilakukan sebelumnya (BLX83, Koorin, and TOGA-COARE) digunakan untuk menguji hasil parameterisasi ini. Hasil yang diperoleh mengindikasikan bahwa koefisien empiris transpor untuk fluks momentum tergantung pada kekasaran permukaan (surface roughness).