Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Retracted Publications in Medical Literature Due to Ethical Violations

Background Retraction is an essential procedure for correcting scientific literature and informing readers about articles containing significant errors or omissions. Ethical violations are one of the significant triggers of the retraction process. The objective of this study was to evaluate the characteristics of retracted articles in the medical literature due to ethical violations. Methods The Retraction Watch Database was utilized for this descriptive study. The ‘ethical violations’ and ‘medicine’ options were chosen. The date range was 2010 to 2023. The collected data included the number of authors, the date of publication and retraction, the journal of publication, the indexing status of the journal, the country of the corresponding author, the subject area of the article, and the particular retraction reasons. Results A total of 177 articles were analyzed. The most retractions were detected in 2019 (n = 29) and 2012 (n = 28). The median time period between the articles’ first publication date and the date of retraction was 647 (0–4,295) days. The leading countries were China (n = 47), USA (n = 25), South Korea (n = 23), Iran (n = 14), and India (n = 12). The main causes of retraction were ethical approval issues (n = 65), data-related concerns (n = 51), informed consent issues (n = 45), and fake-biased peer review (n = 30). Conclusion Unethical behavior is one of the most significant obstacles to scientific advancement. Obtaining appropriate ethics committee approvals and informed consent forms is crucial in ensuring the ethical conduct of medical research. It is the responsibility of journal editors to ensure that raw data is controlled and peer review processes are conducted effectively. It is essential to educate young researchers on unethical practices and the negative outcomes that may result from them.
Very Accurate Flexible pH Microsensor Based on Nanoporous Titanium Nitride Material for In Vivo Application

Recently, the need for a real-time and less invasive solution to replace in-laboratory blood analysis by analyzing in situ biological fluids (sweat, saliva, tear, urine, and interstitial fluid) has grown alongside the development of microfabrication techniques. pH determination is crucial for health monitoring (e.g., fetal acidosis supervision, sport activity, tumor detection, and wound monitoring). Our work focuses on developing a potentiometric microsensor, targeting pH measurement on the fetal scalp during labor, employing nanoporous titanium nitride (TiN) as an alternative sensing material. The pH probe contains a working electrode (WE) of $400\times 800\,\,\mu \text{m}$ in size, integrated on a flexible polyimide (PI) substrate, creating an ultrathin sensor with thickness below $20 \mu \text{m}$ . Microfabrication process and a complete characterization on performance of our flexible pH microsensor are presented, demonstrating a sensitivity of 53.2 mV/pH. Hysteresis was found at 3-mV maximum after six cycles, demonstrated a good reproducibility, and led to a precision of 0.05 in pH. A comparison of the performance between porous and flat TiN (sensitivity of 53.7 mV/pH, hysteresis maximum of 5 mV, and precision of 0.09 in pH) is presented, along with an evaluation of the dependence in the electrode size versus their performances. A preliminary in vivo test was conducted on mice with the probe implanted under the skin. We recorded a stable open-circuit voltage (OCV) signal under anesthesia conditions. A compact measurement system was designed with a customized liquid crystal display (LCD) screen for signal visualization, an EZO ORP circuit for data acquisition, and an integrated secure digital (SD card) for data storage.
The Role Of Market Performance Studies With A Strategic Orientation

In Southeast Sulawesi, during the Corona Virus Disease Pandemic, this study sought to examine the impact of the strategic orientation dimension on the market performance of the culinary industry. The descriptive and quantitative methods used non-probability sampling and a purposive sample technique. During the COVID-19 pandemic, the population was made up of actors in the food industry who had managed to survive and run their companies for more than two years. Only 38 people responded to the survey's sample, which was small. This study used Smart-PLS 3.0's route analysis for data analysis. To help culinary business actors perform better in the market during the COVID-19 pandemic, the analysis of the strategic aspects that have an aggressive attitude and significantly affect market performance were presented.
Examining the impact of overlying aerosols on the retrieval of cloud optical properties from passive remote sensing

[1] Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space‐based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX‐A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below‐aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol‐induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS‐retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1–2 mm) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS‐retrieved cloud optical thickness and effective radius can reach values of 10 and 10 mm, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.
Occurrence and abundance of soil‐specific bacterial membrane lipid markers in the Têt watershed (southern France): Soil‐specific BHPs and branched GDGTs

Recently, four bacteriohopanepolyols (BHPs), adenosylhopane, and structurally similar adenosylhopane‐type 1, 2‐methyl adenosylhopane, and 2‐methyl adenosylhopane‐type 1, have been suggested to be characteristic of soil microbial communities and therefore can serve as molecular markers for soil organic matter (OM) supply in river, lake, and marine sediments. In this study, we analyzed BHPs in peats and soils collected in the Têt watershed (southern France) and compared them with branched glycerol dialkyl glycerol tetraethers (GDGTs), a more established molecular tracer of soil OM. Adenosylhopane‐type I is identified in all of the samples from the study area except one collected near the Têt River mouth with up to three of the related compounds also frequently present, particularly in the surface samples. The concentrations of soil‐specific BHPs in peat environments have been shown to increase with lower δ15N values, providing evidence that N2‐fixing bacteria are probably a major source of soil‐specific BHPs in acidic environments. It seems likely that soil pH is a major factor controlling BHP occurrence based on statistical analysis of environmental parameters and BHP concentration data. The comparison of the soil‐specific BHP concentrations with those of branched GDGTs shows no clear relationship in the Têt River system, supporting the concept that these two groups of soil‐specific compounds are synthesized by different microbial organisms living in different niches in the soil profile (e.g., oxic top versus anoxic deep).
Purge the Evil From Your Midst: Material Cancel Culture Among Religiously Observant Jews

This article explores cancel culture as a material endeavor on the ground. We draw on ethnographic tools to call attention to formative material dimensions of canceling and employ the conceptual lens of material culture to analyze rationales and practices around the canceling of objects. The case study concerns how ultra-Orthodox Jews in Israel manage allegations of sexual abuse against a beloved author by engaging in a myriad of material-canceling actions around his books. We cluster and investigate these actions under three categories: Time-Out, Taking Out, and Casting Out. We offer the term Material Cancel Culture as a productive intervention in a literature that generally focuses on the discursive and digital components of cancel culture. The multiplicity of possible material (dis)engagements allows us to move beyond a somewhat dichotomous outline of cancel versus not-cancel, and to consider how the material immediacy and properties of objects open up new scripts of action in response to public sentiments of rage and critique.
Soil acidity in New South Wales ― current pH values and estimates of acidification rates

An estimate has been made of the mean pH of the surface soils (0-10 or 0-15 cm) of New South Wales by mapping the soil pH (1:2, soil: 0.01 M CaCl2) values of soil samples analysed by the NSW Agriculture & Fisheries soil testing service. Within mapped classes the soil pH values vary around the mean by about 20.4 units for low pH soils (3.8-5.0) to about 20.9 units for high pH soils (>6.0). It is estimated that the areas of surface soils within agricultural holdings in NSW in the pH classes 1000 mm) and on low pH buffer capacity soils (sand to sandy loam texture). In the south of the state the area of low pH soils is broader, and extends into lower rainfall zones. Within the mapped pH classes the higher pH buffer capacity clay soils had pH values 0.83 (s.e. 0.6) units higher than the mean, whilst sands and sandy loams had pH values 0.34 (s.e. 0.1) units lower than the mean. Data on the acid addition rates for a number of agricultural systems in NSW and adjacent areas were collated and show net rates of acid addition to the soil profile from near zero to rates of 3-5 kmoles H+ ha-l year-1 over extensive areas. High acid addition rates, of 10-20 kmoles H+ ha-1 year-1, have been measured in some exploitative systems. These acid addition rate values can be used in association with soil pH buffer capacity data to estimate the rate of pH change in the future. At an acid addition rate of 4 kmol H+ ha-1 year-1, the soil pH can decline by one unit, in the surface 30 cm within 30 years for sandy loam soils, and within 120 years for clay soils.
MITS: Mobility-Aware Intelligent Task Scheduling in Vehicular Fog Networks

Vehicular Fog Computing (VFC) has emerged as a captivating research paradigm to increase computing resources for Internet of Vehicles (IoV) applications. However, the allocation of the best possible computing resources is challenging due to the enormous growth of services in vehicular networks, such as augmented reality, 3-D gaming, autonomous driving, etc., and their severe delay limitations, processing demands, and mobility of vehicles. Mainly, achieving strict task latency is a challenging problem while vehicles traverse through the roadside unit (RSU) regions. In this work, the vehicle's task processing latency and energy consumption are considered by deciding which tasks should be scheduled to either the local RSU or the neighbour RSUs along the vehicle's path. We study the mobility-aware task scheduling problem to jointly optimize the service latency of the tasks and energy consumption of the vehicles. Initially, we employ the Markov renewal process (MRP) to model the vehicle's mobility. Subsequently, we establish that our proposed objective function is a monotone submodular function and provide a greedy heuristic for the maximization of the submodular function with an approximation of ($1-\frac{1}{\mathrm{e}}$). Further, we propose a hybrid optimization algorithm that combines particle swarm optimization (PSO) and simulated annealing (SA) algorithms to solve mobility-aware task scheduling problems for large-scale networks. We compare our proposed algorithm with existing mobility-aware scheduling approaches and simulation results show that the proposed algorithm performs efficiently for task scheduling problems.
An Adaptive Agent Decision Model Based on Deep Reinforcement Learning and Autonomous Learning

This research focuses on the research of adaptive agent decision model based on deep reinforcement learning and autonomous learning. With the rapid development of artificial intelligence, the role of agents in decision-making tasks is becoming more and more important. However, traditional decision models tend to perform poorly in the face of complex and uncertain environments. Therefore, this study aims to propose a new decision-making model that enables agents to make adaptive decisions in complex environments by combining the techniques of deep reinforcement learning and autonomous learning. The significance and purpose of this study is to promote the development of the agent decision model and provide a new way to solve complex decision problems. Traditional decision models often face challenges in complex environments, but the adaptive agent decision model based on deep reinforcement learning and autonomous learning has better adaptability and generalization ability.
Exploring the Antibacterial Potential of Konjac Glucomannan in Periodontitis: Animal and In Vitro Studies

Background and Objectives: Periodontitis is an inflammatory disease in the supporting tissues of the teeth caused by specific microorganisms or groups of microorganisms. P. gingivalis bacterium is the keystone pathogen in periodontitis, so even at low concentrations, it has a considerable influence on the oral community. Antimicrobials and antiplaque agents can be used as adjunctive therapy for periodontitis treatment. Konjac glucomannan (KGM), as a natural polysaccharide, has flavonoid (3,5-diacetyltambulin) and triterpenoids (ambylon) compounds that show antibacterial activity. This research aims to analyze the antibacterial activity of KGM on animal and in vitro periodontitis models. Materials and Methods: The animal study divided 48 mice into four groups (control, KGM, periodontitis, KGM + periodontitis). Mice were given an intervention substance by oral gavage from day 1 to day 14, periodontitis was induced on day 7, and decapitation was performed on day 14. Samples from the right maxillary jaw of mice were used for histological preparations and morphometrics analysis. In vitro studies were carried out by adding several concentrations of KGM (25, 50, and 100 μg/mL) into a planktonic P. gingivalis and P. gingivalis biofilm. Results: In the animal model, KGM could prevent alveolar bone loss in the periodontitis mice model, both in histologic and morphometrics assessments. In vitro, KGM had antibacterial activity against P. gingivalis with better bacteriostatic (15–23%) than bactericidal (11–20%) ability, proven by its ability to inhibit P. gingivalis proliferation. Conclusions: KGM can be considered to have the potential as an antibacterial agent to prevent periodontitis. The prevention of periodontitis may improve patient well-being and human quality of life.
Tunable diode laser measurements of methane fluxes from an irrigated rice paddy field in the Philippines

This paper presents the first micrometeorological-based measurements of methane (CH4) emissions from Asian rice paddies of which we are aware. The research features the tunable diode laser trace gas analyzer system (TGAS) recently developed at the University of Guelph. CH4 fluxes were measured between March 9 and 24, 1992, from an irrigated rice paddy field at the International Rice Research Institute (IRRI), the Philippines. The daytime CH4 flux averaged 6.0 μg m−2 s−1. The CH4 fluxes displayed a diurnal trend similar to daily soil temperature curves, with peak emissions of about 8 μg m−2 s−1 in the early afternoon. A tenfold increase in CH4 emissions (to about 70μg m−2 s−1) during a brief weeding experiment resulted from soil disturbance. Up to 25 μg m−2 s−1 of CH4 were released during a drying of the field, after which unsuitable soil redox potentials apparently suppressed methanogenesis. The CH4 flux was also arrested when the field was flooded with oxygen-rich water during a heavy rainstorm.
Dynamic low power management technique for decision directed inter-layer communication in three dimensional wireless network on chip

3D ICs, a novel technology, might significantly impact multicore NoCs with hundreds or thousands of processing components on a single chip. Multiple 2D chips can be stacked vertically to create multiple active processing elements at various levels. Adding active device layers to 3D ICs can enhance system performance, increase functionality, and increase packing density. New architectural and IC technology advancements hinder energy-efficient design research. Achieving a balance between chip power and performance is crucial. This paper describes the “Dynamic Low Power Management Method in 3DWiNoC” (DLPM 3DWiNoC) architecture, which enables self-organized, centrally managed service management using Smart Master Agents. The approach utilizes SMA's ODA DD module for self-organized, centrally managed service management. To improve power regulation, data flow across vertical interconnects (TSVs) is reconfigured based on a dynamic evaluation of channel link use. SMA aims to reduce congestion by increasing connection utilization through high-frequency, bi-directional vertical channels via TSVs. The suggested system is modeled in MATLAB Simulink. Compared to 3D stacking, TSV stacking of vertical interconnects with the SMA method ensures low parasitic (latency and power) and higher bandwidth with higher vertical wire densities. Experimental results show that the proposed architecture decreases area overhead by 5%-7%, network latency by 12%-15%, and NoC power consumption by 15%-20% compared to the present multi-NoC design.
An Intelligent Deep Learning Architecture Using Multi-scale Residual Network Model for Image Interpolation

—Image interpolation techniques based on learning have been shown to be efficient in recent days, due to their promising results. Deep neural networks can considerably enhance the quality of image super-resolution, according to recent studies. Convolutional neural networks with deeper layers are commonly used in current research to improve the performance of image interpolation. As the network’s depth grows, more issues with training arise. This research intends to implement an advanced deep learning mechanism called Deep Multi-Scaled Residual Network (DMResNet) for effective image interpolation. A network cannot be substantially improved by merely increasing the depth of the network. New training strategies are required for improving the accuracy of interpolated images. By using the proposed framework, the Low Resolution (LR) images are reconstructed to the High Resolution (HR) images with low computational burden and time complexity. In order to dynamically discover the image features at multiple scales, convolution kernels of various sizes based on the residual blocks have been utilized in this work. In the meantime, the multi-scaled residual architecture is formulated to allow these characteristics to interact with one another for obtaining the most accurate image data. The interpolation performance and image reconstruction efficiency of the proposed model have been validated by using a variety of measures such as PSNR, SSIM, RMSE, Run time analysis, and FSIM. Popular datasets IAPR TC-12, DIV 2K, and CVDS are used for validating the proposed model. This model outperforms the state-of-art interpolation techniques in its performance, by yielding an increase of 8% in PSNR, 6% in SSIM, 1.2% in FSIM, and a decrease of 38.79% in RMSE, 5.875 times in run time analysis.
The Impacts of Burnout on Athletic Identity and Attitude towards Sport

Sports can be a positive experience for some. However, it can also lead to increased stress and ultimately result in burnout. Previous research has examined burnout in sports. Although, little research has been conducted on how experiencing burnout can affect other factors such as an athlete’s view of their sport and their athletic identity. Collegiate athletes face many responsibilities: school, work, long hours of practice, physical, emotional, and social demands. An accumulation of these factors, combined with the inability to effectively cope with such demands, can lead an athlete to experience high levels of burnout. The purpose of this study was to examine the potential impacts that burnout could have on a collegiate athlete’s attitude towards their sport and their athletic identity. A phenomenological approach was used to examine five participants who scored high on the Athlete Burnout Questionnaire. Participants underwent a 1 h interview that evaluated their attitude towards sport and athletic identity. It was found that there was a meaningful negative change in attitude towards sport; however, no meaningful or permanent change was prevalent when evaluating athletic identity.
Assessment of Heavy Metal Enrichment, Bioavailability, and Controlling Factors in Sediments of Taihu Lake, China

Heavy metal distribution, bioavailability, and ecological risk in the surface sediment of Taihu Lake were evaluated. Samples were collected from eight representative sites in September 2011 and February 2012. In the surface sediment, average metal contents were in the order of Cr > Zn > Ni > Pb > Cu. Spatially, Zhushan Bay maintained higher Cu, Ni, and Zn contents and Xiaomeikou maintained higher Cr and Pb contents than other sites. Spatial and temporal variation were observed in the bioavailable metals determined by acid-soluble fraction of BCR extraction. The labile metals in Zhushan Bay and Xiaomeikou were quantified by diffusive gradients in thin films (DGT) and DGT-labile concentrations of Zn, Ni, Cu, Pb, and Cd were in descending order, indicating the inconsistence of labile concentrations of different heavy metals with the total metal contents and that the toxic effect of Cd in sediment should be given attention. The ecological risk assessed by Hakanson potential ecological risk index showed that Zhushan Bay suffered the most serious pollution and should be given special attention. Bioavailability of metals should be taken into account during risk assessment for more accurate estimation.