Miracle-dz/UniFAR-FTUs huggingface dataset:
Patients’ Characteristics and General Practitioners’ Management of Patients with Symptom Diagnoses

Introduction: Symptom diagnoses are diagnoses used in primary care when the relevant diagnostic criteria of a disease are not fulfilled. Although symptom diagnoses often get resolved spontaneously without a clearly defined illness nor treatment, up to 38% of these symptoms persist more than 1 year. It is largely unknown how often symptom diagnoses occur, which symptoms persist, and how general practitioners (GPs) manage them. Aim: Explore morbidity rates, characteristics and management of patients with nonpersistent (≤1 year) and persistent (>1 year) symptom diagnoses. Methods: A retrospective cohort study was performed in a Dutch practice-based research network including 28,590 registered patients. We selected symptom diagnosis episodes with at least 1 contact in 2018. We performed descriptive statistics, Student’s T and χ2 tests to summarize and compare patients’ characteristics and GP management strategies in the nonpersistent and persistent groups. Results: The incidence rate of symptom diagnoses was 767 episodes per 1000 patient-years. The prevalence rate was 485 patients per 1000 patient-years. Out of the patients who had a contact with their GPs, 58% had at least 1 symptom diagnosis, from which 16% were persistent (>1 year). In the persistent group, we found significantly more females (64% vs 57%), older patients (mean: 49 vs 36 years of age), patients with more comorbidities (71% vs 49%), psychological (17% vs 12%) and social (8% vs 5%) problems. Prescriptions (62% vs 23%) and referral (62.7% vs 30.6%) rates were significantly higher in persistent symptom episodes. Conclusion: Symptom diagnoses are highly prevalent (58%) of which a considerable part (16%) persists more than a year.
Bulk Scattering Approximations for Collimated Light Transmitted through Paper

Paper is a complex fibrous material whose production involves substantial amounts of natural and industrial resources. To reduce its manufacturing costs, the pulp and paper industry often employs optical technology such as high sensitivity laser sensors used to measure physical parameters like thickness and opacity. More recently, computer simulations of paper optical properties are also being used to accelerate the research cycle required to the development of new types of paper. In these simulations, the bulk scattering of paper is usually approximated by analytical formulas, notably the Henyey-Greenstein function. In this work, we qualitatively investigate the degree of accuracy of such approximations with respect to collimated light. More specifically, an experimental set-up was devised to record the transmission of red and green HeNe lasers through different paper samples. The measured data was compared with data obtained using the Henyey-Greenstein function and data obtained using an alternative exponentiated cosine function. The comparisons are used to qualitatively assess the degree of accuracy of the bulk scattering approximations provided by both functions. This work closes with a discussion on the practical implications of our findings for the modeling of paper optical properties.
Development of plywood bonded with a novel adhesive film made from polystyrene foam waste dissolved in D-limonene

ABSTRACT The polystyrene film as a formaldehyde-free adhesive for plywood production was developed from polystyrene foam waste (PSF) and D-limonene, extracted from orange peel waste. The influence of the weight ratio of solvent (D-limonene) to foam in the range of 1, 1.5 and 2 (w/w) on the properties of adhesive film and plywood panels was studied. In addition, the effects of pressing temperatures of 150°C, 165°C and 180°C on the properties of the plywood were investigated. The adhesive film was characterized by measuring the melt flow index, the average molecular weight of the polymers and by FTIR. The bonding quality of the adhesive films was investigated by shear strength tests. Integrated gel permeation chromatography has also shown that the average molecular weight of PSF is drastically reduced by doubling the solvent content. Shear strength and bending properties were also significantly reduced by doubling the weight ratio of solvent to foam. The mechanical properties of plywood are positively affected with increasing press temperature to 165°C. In general, plywood bonded with an adhesive film prepared with a solvent to foam weight ratio of 1 and press temperature of 165°C was fulfilled the requirement according to EN314-2 for interior use.
Isolation and Identification of Salmonella from Chickens Prepared for Slaughter in the State of Kuwait

Salmonella enterica serovar Enteritidis throughout the world, is frequently linked to food-borne illness. Products made from poultry are important sources of transmission. Therefore, this study aimed to identify the incidence of Salmonella species in Kuwait's broiler flocks and determine which antibiotics are the most effective against the various Salmonella serotypes. A total of 2064 chicken samples (liver, intestine, and caecum) were collected from dead carcasses raised ten broiler flocks, between January and December 2017. The results revealed that S. enterica were found in the chicken older than 7 days old even though they did not have any signs of a clinical illness. It means that S. enterica can enter the human food supply through slaughterhouses and the contaminate carcasses. There was significant difference between the rate of Salmonella isolation and seasons, where the winter season had higher rate of Salmonella isolation compared to the other seasons. Salmonella Enteritidis and S. typhimurium were the most frequently isolated serotypes. Antimicrobials susceptibility testing showed that 88% to 60% of the isolates were sensitive to Amoxicillin Clavulanic acid. However, most of Salmonella isolates revealed high resistance to Cefotaxime, Ampicillin, Amoxicillin, Sulfamethoxazole trimethoprim followed by Gentamycin, Spiramycin, Doxycycline and Chloramphenicol. The study highlights the implementation of unique biosecurity and biocontrol strategies for Salmonella management that can prevent the negative effects of antibiotics and can make the environment and foods derived from animals safe. ـــــــــــــــــــــــــــــــــــــــــ
Temperature distribution analysis inside the strawberry flower head

Different studies by numerous researchers were carried out recently to describe different heat flux components of heat balance equations for radiation frost condition in plants. The aim of most of the papers was to present more simple and clear mathematical algebra to show the plant heat balance formulas. To achieve this aim several simplifications were made. Nevertheless there are studies reporting different flower damage rates during spring frost sessions that mentioned studies cannot explain. This leads us to the need to find the temperature distribution inside the flower to understand why during the similar energy flux conditions the flowers act against frost stress differently. It's easy to measure the fl ower surface temperature but rather difficult to measure temperature distribution inside the flower head due to very small flower head scale compared to sensor sizes. To help to overcome these difficulties the authors make simplification by substituting the strawberry flower head with spherical homogeneous body though it is clear that the flower head is not homogeneous because of varying flower structure. The aim of this study is to present mathematical formulas for temperature distribution calculation inside the spherical body in terms of heat transfer conditions characteristic to radiation frost. Transient numerical methods are implemented for different conditions in case of spherical body. This approach enables us to decide if suggested mathematical solution is usable for non- homogeneous body. Computer program was prepared to analyse the results.
Resonance-spacing tuning over whole free spectral range in a single microring resonator

In this paper, we present a single microring resonator structure formed by incorporating a reflectivity-tunable loop mirror for the tuning of resonance spacing. Based on the optical mode-splitting in the resonator structure, spacing between two adjacent resonances can be tuned from zero to one whole free spectral range (FSR) by controlling the coupling strength between the two counter-propagating degenerate modes in the microring resonator. In experiment, by integrating metallic microheater, the resonance-spacing tuning over the whole FSR (1.17 nm) is achieved within 9.82 mW heating power dissipation. The device is expected to have potential applications in reconfigurable optical filtering and microwave photonics.
An Adaptive Channel Selection and Graph ResNet Based Algorithm for Motor Imagery Classification

—In Brain-Computer interface (BCI) applications, achieving accurate control relies heavily on the classification accuracy and efficiency of motor imagery electroencephalogram (EEG) signals. However, factors such as mutual interference between multi-channel signals, inter-individual variability, and noise interference in the channels pose challenges to motor imagery EEG signal classification. To address these problems, this paper proposes an Adaptive Channel Selection algorithm aimed at optimizing classification accuracy and Information Translate Rate (ITR). First, C3, C4, and Cz are selected as key channels based on neurophysiological evidence and extensive experimental studies. Next, the channel selection is fine-tuned using spatial location and absolute Pearson correlation coefficients. By analyzing the relationship between EEG channels and key channels, the most relevant channel combination is determined for each subject, reducing confounding information and improving classification accuracy. To validate the method, the SHU Dataset and the PhysioNet Dataset are used in experiments. The Graph ResNet classification model is employed to extract features from the selected channel combinations using deep learning techniques. Experimental results show that the average classification accuracy is improved by 5.36% and 9.19%, and the Information Translate Rate is improved by 29.24% and 26.75%, respectively, compared to a single channel combination.
Down-Syndrome-Related Maternal Dysbiosis Might Be Triggered by Certain Classes of Antibiotics: A New Insight into the Possible Pathomechanisms

Down syndrome (DS) is a leading human genomic abnormality resulting from the trisomy of chromosome 21. The genomic base of the aneuploidy behind this disease is complex, and this complexity poses formidable challenges to understanding the underlying molecular basis. In the spectrum of the classic DS risk factor associations, the role of nutrients, vitamins, and, in general, the foodborne-associated background, as part of the events ultimately leading to chromosome nondisjunction, has long been recognized as a well-established clinical association. The integrity of the microbiome is a basic condition in these events, and the dysbiosis may be associated with secondary health outcomes. The possible association of DS development with maternal gut microbiota should therefore require more attention. We have hypothesized that different classes of antibiotics might promote or inhibit the proliferation of different microbial taxa; and hence, we might find associations between the use of the different classes of antibiotics and the prevalence of DS through the modification of the microbiome. As antibiotics are considered major disruptors of the microbiome, it could be hypothesized that the consumption/exposure of certain classes of antibiotics might be associated with the prevalence of DS in European countries (N = 30). By utilizing three different statistical methods, comparisons have been made between the average yearly antibiotic consumption (1997–2020) and the estimated prevalence of people living with DS for the year 2019 as a percentage of the population in European countries. We have found strong statistical correlations between the consumption of tetracycline (J01A) and the narrow-spectrum, beta-lactamase-resistant penicillin (J01CF) and the prevalence of DS.
Parameterization of the Dry Convective Boundary Layer Based on a Mass Flux Representation of Thermals

Presented is a mass flux parameterization of vertical transport in the convective boundary layer. The formulation of the new parameterization is based on an idealization of thermal cells or rolls. The parameterization is validated by comparison to large eddy simulations (LES). It is also compared to classical boundary layer schemes on a
Hsa_circ_0079557 promotes CRC proliferation through miR-502-5p/CCND1 axis

Chao Yu Zhujiang hospital, Southern Medical University Xue Huang Zhujiang hospital, Southern Medical University Renli Huang Zhujiang hospital, Southern Medical University Peiqi Wang Zhujiang hospital, Southern Medical University Zongda Cai Fujian Medical University Zeyi Guo Zhujiang hospital, Southern Medical University Qingnan Lan Zhujiang hospital, Southern Medical University Haodi Cao Southern Medical University Jinlong Yu (  yujinlong640506@163.com ) Zhujiang hospital, Southern Medical University
Survey on Detecting Hate Tweets — Twitter Sentiment Analysis

Poisonous web-based content has turned into a significant issue in this day and age because of a dramatic expansion in the utilization of the web by individuals of various societies and educational backgrounds. Separating hate speech and offensive language is a vital challenge in the automatic detection of toxic text content. In this report, we propose a way to deal with consequently group tweets on Twitter into two classes: hate speech and non-hate speech. Utilizing the Twitter lives tweets, in our project we are connecting the twitter to our application and it take the tweet of linked twitter account as the live dataset and it will be processed by sentimental analysis using NLP to predict the toxic content in the dataset and the accuracy of the prediction will be analyzed using the RSNET deep learning algorithm.
Handbook of Ion Channels

of the channel pore such that helices B and J lie antiparallel on opposite sides of the triangular prism-shaped monomer. Helices Q and P fold back behind O, while H and I fold back behind G to make up the QPHI surface (most of the dimer interface) when viewed from the base of the prism. Crystal positions of the helix–helix linkers are uncertain for ClC-1 and are not drawn to scale but are generally indicative of their respective loop lengths. Importantly, CBS2 lies close to the cytoplasmic helix–helix loops and the linker between CBS2 and the poly-proline (PP) helix lies close to helix r and its linker to CBS1. the structures of the segments linking CBS1 to CBS2 and linking helix PP to the C terminus are quite unknown, as is the position of helix PP, although structural and functional studies (Macías et al., 2007; Feng et al., 2010; Ma et al., 2011) suggest that helix PP and the C terminus lie close to the cytoplasmic face of the membrane resident region of the monomer.
Audit Quality: A Literature Overview and Research Synthesis

: The paper aim is to evaluate the current literature on audit quality. To satisfy the aim, the author carries out a secondary research in which past research on the topic has been evaluated and the following findings have been found. for this, the author has considered 1981 to present as a relevant period for conducting this research. Additionally, “audit quality”, “definition”, “processes”, “inputs”, “audit evidence”, and factor related search terms have been used for obtaining the required data. Firstly, there is no universal definition of audit quality as different authors have separately defined it. Secondly, the author has summarized various indicators of audit quality after establishing the audit quality framework. Here, it is necessary to mention that there are various local and international jurisdictions that are applicable and followed by various local and international firms. At the same time, various audit quality indicators are important to assess how they are linked to audit quality. For example, professional skepticism is one the important input indicators that is highly essential to determine audit quality.
A bivariate INAR(1) process with application

The study of time series models for count data has become a topic of special interest during the last years. However, while research on univariate time series for counts now flourishes, the literature on multivariate time series models for count data is notably more limited. In the present paper, a bivariate integer-valued autoregressive process of order 1 (BINAR(1)) is introduced. Emphasis is placed on models with bivariate Poisson and bivariate negative binomial innovations. We discuss properties of the BINAR(1) model and propose the method of conditional maximum likelihood for the estimation of its unknown parameters. Issues of diagnostics and forecasting are considered and predictions are produced by means of the conditional forecast distribution. Estimation uncertainty is accommodated by taking advantage of the asymptotic normality of maximum likelihood estimators and constructing appropriate confidence intervals for the fe-step-ahead conditional probability mass function. The proposed model is applied to a bivariate data series concerning daytime and nighttime road accidents in the Netherlands.
Recent Progress in Micro- and Nanotechnology-Enabled Sensors for Biomedical and Environmental Challenges

Micro- and nanotechnology-enabled sensors have made remarkable advancements in the fields of biomedicine and the environment, enabling the sensitive and selective detection and quantification of diverse analytes. In biomedicine, these sensors have facilitated disease diagnosis, drug discovery, and point-of-care devices. In environmental monitoring, they have played a crucial role in assessing air, water, and soil quality, as well as ensured food safety. Despite notable progress, numerous challenges persist. This review article addresses recent developments in micro- and nanotechnology-enabled sensors for biomedical and environmental challenges, focusing on enhancing basic sensing techniques through micro/nanotechnology. Additionally, it explores the applications of these sensors in addressing current challenges in both biomedical and environmental domains. The article concludes by emphasizing the need for further research to expand the detection capabilities of sensors/devices, enhance sensitivity and selectivity, integrate wireless communication and energy-harvesting technologies, and optimize sample preparation, material selection, and automated components for sensor design, fabrication, and characterization.
Deep Reinforcement Learning for MiniGrid

In this project we plan to study the application of deep reinforcement learning (DRL) in solving problems in the MiniGrid gym environment and a classic control problem CartPole. Speciﬁcally, we plan to employ the proximal policy optimization (PPO) algorithm which is a modiﬁed version of actor-critic policy gradient method. We choose two testing environments from the MiniGrid environment and the CartPole environment from OpenAI Gym to verify our implementations.
Analysis and Generation of Verbal Humor in Portuguese Paper type: Doctoral Consortium

Computational Creativity is the field of research focused on formalizing, discussing, and developing computational systems capable of producing artifacts which would be considered as creative by humans. For Natural Language Processing, working with creativity is specially challenging and intriguing, since it raises questions about figurative language, pragmatics, ambiguity, and other topics which are still open for fruitful research. From the many tasks involving language within the Computational Creativity area, this project focuses on the automatic recognition and generation of humor-ous texts (jokes, riddles, puns, and the like). The core of this project will be to integrate knowledge from different levels of linguistic investigation – such as Phonol-ogy, Semantics, Pragmatics, and others – in order to produce, analyze and evaluate texts which can be considered more funny by human readers. It will also be important to measure how important each of the information types are for computational tasks involving humor. As a side effect, it is expected to develop resources, tools, and methods which could be valuable for research not only in Computational Creativity but also in Natural Language Processing as a whole, specially for the Portuguese language, the main target of this project, which is considerably less researched than other languages such as English or Mandarin Chinese.
EV Smart Regeneration using Super Capacitor with Battery Bank

A EV is defined as a vehicle that can be powered by an electric motor that draws electricity from a battery and is capable of being charged from an external source. The biggest factor that determines the range of an EV is the capacity of the lithium-ion battery in the car. This paper proposes a real time optimal driving torque distribution strategy for an electric vehicle (EV) with independently driven front and rear wheels. The proposed optimal torque distribution strategy among the front and rear wheels, improves the overall energy efficiency of the vehicle, there by increasing the driving range achievable per charge cycle of the EV. The torque is optimized with the objective of minimizing the energy consumption during driving as well as maximizing the regenerative energy recuperation during the braking. Here, a real time torque distribution control system is proposed which can realize optimal distribution of driving-braking torque corresponding to the driving commands, for constant speed driving, acceleration, braking and grade climbing driving modes. The optimal torque distribution ensures minimal energy consumption, thus improving the energy efficiency of the EV. By reducing the energy consumption the driving range achievable per charge cycle is improved, realizing range extension of EV.
Emotional Intelligence and Performance of Police Officers at Gulu Central Police Station, Uganda

The study examined the effect of EI on performance of police officers at Gulu Central Police station. Specifically, the study addressed: the effect of self-awareness and self-regulation in recruitment and selection on performance of Police officers, the effect of motivation and social skills in task assignment on performance of police officers, and the effect of empathy in training on performance of police officers. The study adopted a cross sectional descriptive study design with only quantitative approaches. The study used a sample size of 155 respondents. The items/constructs used in this research were measured on a five point Likert Scale. Factor analysis and principle component analysis were used to test whether the constructs were appropriate for the study. Pairwise correlation matrix was used to test for multicollinearity of the independent variables. Multiple linear regression model was used to examine the effect EI on the performance of police officers. The findings revealed that self-awareness and self-regulation in recruitment and selection had a positive and significant effect on performance of police officers in Gulu City Police Station at 5% significance level (B=0.461, P-value=0.001). Empathy in training was found to have a positive and significant effect on the performance of police officers in Gulu City Police Station (B=0.921, P-value=0.000). The study also found that motivation and social skills in task assignment had a positive and significant effect on the performance of police officers (B=0.586, P-value=0.000). It can be concluded that the effect of emotional intelligence on the performance of police officers at Gulu City Police Station was positive and significant. The study recommends that UPF improves knowledge dissemination on what EI is and its importance to the police officers.