bluuebunny/crossref_metadata_2025 huggingface dataset:
A cottonseed oil-enriched diet improves liver and plasma lipid levels in a male mouse model of fatty liver
Authors: Son Yura , Shockey Jay , Dowd Michael K. , Shieh Josephine G. , Cooper Jamie A. , Paton Chad M.
Published: December 2022

A high-fat (HF) diet causes fatty liver, hyperlipidemia, and hypercholesterolemia, and cottonseed oil (CSO) has been shown to improve liver and plasma lipids in human and mouse models. The purpose of this study was to determine the effect of CSO vs. olive oil (OO)-enriched diets on lipid levels in a HF-diet model of fatty liver disease. We placed mice on a HF diet to induce obesity and fatty liver, after which mice were placed on CSO or OO diets, with chow and HF (5.1 kcal/g) groups as control. When CSO- and OO-fed mice were given isocaloric diets with the HF group, there were no differences in body weight, plasma, or hepatic lipids. However, when the CSO and OO diets were reduced in calories (4.0 kcal/g), CSO and OO groups reduced body weight. The CSO group had lower plasma total cholesterol (−56 ± 6%, P < 0.01), free cholesterol (−53 ± 7%, P < 0.01), triglycerides (−61 ± 14%, P < 0.01), and LDL (−42 ± 16%, P = 0.01) vs. HF group whereas the OO diet lowered LDL (−18 ± 12%, P = 0.05) vs. HF. Furthermore, the CSO diet decreased hepatic total cholesterol (−40 ± 12%, P < 0.01), free cholesterol (−23 ± 11%, P = 0.04), and triglycerides (−47 ± 12%, P = 0.02). There were no significant changes in lipogenesis and fatty acid oxidation among the groups. However, the CSO group increased lipid oxidative gene expression in liver and dihydrosterculic acid increased PPARα target genes with in vitro models. Taken together, consuming a reduced calorie diet enriched in CSO reduces liver and plasma lipid profiles in an obese model of fatty liver.
Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE
Authors: Meng Dejun , Miao Changyun. , Li Xianguo , Shi Jia , Liu Yi , Li Jie
Published: December 2022

Fault diagnosis of rolling bearing is important for ensuring the safe operation of industrial machinery. In order to improve diagnosis accuracy of bearing fault, a rolling bearing fault diagnosis method based on multiscale combined morphological filter (MCMF) and self-adaption improved multiscale fuzzy entropy (SAIMFE) is proposed in this paper. First, the MCMF is designed to eliminate noise and preserve fault information more effectively. Second, SAIMFE is proposed to extract bearing fault features, and the optimized scale factor of SAIMFE is determined based on the absolute skewness. Third, some experiments are completed to demonstrate the effectiveness and superiority of the proposed method. The experimental results show that the proposed method not only has high diagnosis accuracy but also less dependent on the diagnosis model.
Assessment of Feasibility for Biodigestion of Cattle Waste in Gwalior City, India
Authors: Shukla Ram Kishore , Kumar Shrivastava Rakesh , Singh Bhadauria Sudhir , Jain Shrey
Published: December 2022

Different biodegradable waste may indeed be processed by biodigesters to generate biogas, a clean and sustainable source of energy. Different digesters are classified according to their digestive process, which is either aerobic or anaerobic. The rate at which organic waste is loaded, the temperature, the amount of dilution, etc., all affect the size of the digesters. A biodigester typically needs a relatively steady atmosphere as well as ongoing agitation. Additionally, it necessitates a large land area. Although it has numerous advantages, the nature of the feedstock is the main factor on which the potential of biogas production depends, as well as the design of the reactor and operational parameters. Though many authors attempted to establish the effect of various factors on the process of biodigestion of food waste, very few studies on reactor design to achieve maximum biogas production were reported. The current study focuses on the use of a reactor with multiple stages that requires a smaller footprint to increase the rate of gas production from solid substrates. In the study, an experiment was attempted to determine the effect of substrate composition, food waste size, and multiple stages inside the reactor on biogas production. It has been found from the results that agricultural and environmental sustainability associated with livestock waste can reduce pollution risk considerably through biodigestion. It has also been found that stages inside the reactor do have an effect on gas production, which has been increased by up to 30%.
Transcription Factor–Forced Astrocytic Differentiation Impairs Human Glioblastoma Growth In Vitro and In Vivo
Authors: Trovato Francesco , Stefani Francesca Romana , Li Jiaxin , Zetterdahl Oskar G. , Canals Isaac , Ahlenius Henrik , Bengzon Johan
Published: December 2022

Direct cellular reprogramming has recently gained attention of cancer researchers for the possibility to convert undifferentiated cancer cells into more differentiated, postmitotic cell types. While a few studies have attempted reprogramming of glioblastoma (GBM) cells toward a neuronal fate, this approach has not yet been used to induce differentiation into other lineages and in vivo data on reduction in tumorigenicity are limited. Here, we employ cellular reprogramming to induce astrocytic differentiation as a therapeutic approach in GBM. To this end, we overexpressed key transcriptional regulators of astroglial development in human GBM and GBM stem cell lines. Treated cells undergo a remarkable shift in structure, acquiring an astrocyte-like morphology with star-shaped bodies and radial branched processes. Differentiated cells express typical glial markers and show a marked decrease in their proliferative state. In addition, forced differentiation induces astrocytic functions such as induced calcium transients and ability to respond to inflammatory stimuli. Most importantly, forced differentiation substantially reduces tumorigenicity of GBM cells in an in vivo xenotransplantation model.

The current study capitalizes on cellular plasticity with a novel application in cancer. We take advantage of the similarity between neural developmental processes and cancer hierarchy to mitigate, if not completely abolish, the malignant nature of tumor cells and pave the way for new intervention strategies.
Recalcitrant Subcutaneous Panniculitis-Like T-Cell Lymphoma Responsive to Histone Deacetylase Inhibitor
Authors: Gleason Laura , Joffe Daniel , Bhatti Safiyyah , Cohen Alexa , Banner Lauren , Correia Emily , Alpdogan Onder , Porcu Pierluigi , Nikbakht Neda
Published: December 2022

Subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare subtype of cutaneous T-cell lymphoma that usually presents with tender subcutaneous nodules on the trunk and extremities. Immunosuppressive therapy is considered first-line treatment for SPTCL, while multiagent chemotherapy is used for SPTCL complicated by hemophagocytic lymphohistiocytosis (HLH). Here, we report a 42-year-old Hispanic man that presented with a 5-year history of recurrent painful subcutaneous lesions in the absence of constitutional symptoms, lymphadenopathy, and hepatosplenomegaly. A punch biopsy revealed an atypical lymphoid infiltrate in between subcutaneous adipose lobules. Lymphocytes expressed CD3, CD8, and Beta F-1 and did not express CD4 and CD56. Based on clinical and histologic findings, the patient was diagnosed with SPTCL. In addition, laboratory findings did not demonstrate any evidence of HLH. He was initially started on both prednisone and hydroxychloroquine with no improvement. A trial of cyclosporine and methotrexate yielded no clinical improvement. As the lesions failed to resolve after treatment with multiple immunosuppressive agents, romidepsin, an intravenous histone deacetylase (HDAC) inhibitor, was initiated. After two cycles of romidepsin, the patient achieved complete clinical response. He continues to be in remission 12 months later with monthly maintenance therapy. This case illustrates that romidepsin can be useful as monotherapy for refractory SPTCL without HLH.
Prehospital Ultra-Early Neurological Deterioration in Intracerebral Hemorrhage: Definition, Prevalence, and Association with Outcomes
Authors: Deng Lan , Li Zuo-Qiao , Yang Wen-Song , Li Rui , Lv Xin-Ni , Li Yu-Lun , Wang Zi-Jie , Hu Xiao , Zhao Li-Bo , Lv Fa-Jin , Yao Sheng-Tao , Cao Fang , Xie Peng , Li Qi
Published: December 2022

Introduction: The objective of this study was to define prehospital ultra-early neurological deterioration (UND) and to investigate the association with functional outcomes in patients with intracerebral hemorrhage (ICH). Methods: We conducted a prospective cohort study of consecutive acute ICH patients. The stroke severity at onset and hospital admission was assessed using the Chongqing Stroke Scale (CQSS), and prehospital UND was defined as a CQSS increase of ≥2 points between symptoms onset and admission. Early neurological deterioration (END) was defined as the increase of ≥4 points in NIHSS score within the first 24 h after admission. Poor outcome was defined as a modified Rankin Scale (mRS) of 4–6 at 3 months. Results: Prehospital UND occurred in 29 of 169 patients (17.2%). Patients with prehospital UND had a median admission NIHSS score of 17.0 as opposed to those without prehospital UND with a median NIHSS score of 8.5. There were three patterns of neurological deterioration: prehospital UND only in 21 of 169 patients (12.4%), END but without prehospital UND in 20 of 169 patients (11.8%), and continuous neurological deterioration in both phases in 8 patients (4.7%). Prehospital UND was associated with worse 3-month outcomes (median mRS score, 4.0 vs. 2.0, p = 0.002). After adjusting for age, time from onset to admission, END, and systolic blood pressure, prehospital UND was an independent predictor of poor outcome (odds ratio [OR] 3.27, 95% confidence interval [CI] 1.26–8.48, p = 0.015). Conclusion: Prehospital UND occurs in approximately 1 in 7 patients between symptom onset and admission and is associated with poor functional outcome in patients with ICH. Further research is needed to investigate the prehospital UND in the prehospital phase in the triage of patients with ICH.
Pros and Cons of Current Diagnostic Tools for Risk-Based Screening of Prediabetes and Type 2 Diabetes in Children and Adolescents with Overweight or Obesity
Authors: Garonzi Chiara , Maguolo Alice , Maffeis Claudio
Published: December 2022

It is still a matter of debate which is the most suitable diagnostic test for risk-based screening of prediabetes and type 2 diabetes (T2D) in children and adolescents with overweight or obesity. This review highlighted benefits and pitfalls of currently recommended screening tools (fasting plasma glucose [FPG], oral glucose tolerance test [OGTT], glycated hemoglobin A1c [HbA1c]). The greatest advantage of OGTT is the ability to detect people with impaired glucose tolerance, a subcategory at high risk of developing both T2D and cardiovascular disease. Important disadvantages are low reproducibility and inconvenience. FPG measurement is more practical, as it needs only one blood draw, although both OGTT and FPG require fasting. The reliability of HbA1c as a screening tool has been questioned, especially in children and adolescents, but its undeniable convenience can lead to increased adherence to screening. In contrast, it can be altered by several nonglycemic factors. Importantly, none of these tests have been validated in the pediatric population. Alternative tests have been recently proposed, including new OGTT-derived biomarkers and additional nonfasting glycemic markers. In conclusion, when choosing the most suitable test in clinical practice, advantages and disadvantages should be considered, as well as the possibility of performing different tests at once.
Type II Left Pulmonary Artery Sling Associated with Double-Outlet Right Ventricle Diagnosed by Fetal Echocardiography and Postnatal Computer Tomography
Authors: Zhou Dan , Yao Longmei , Liu Yushan , Zeng Shi
Published: December 2022

Introduction: Left pulmonary artery sling (LPAS) is a rare congenital vascular anomaly which can be isolated or associated with other malformations. Patients with LPAS usually have symptoms of airway obstruction. Case Presentation: We present a case of LPAS with double-outlet right ventricle diagnosed by fetal echocardiography at 33 weeks’ gestation. Postnatal computed tomography echocardiography confirmed the diagnosis. Additional bronchial bridge and left main bronchial stenosis found by computed tomography led to a diagnosis of type II LPAS. Conclusion: It is crucial to trace pulmonary artery branches in the prenatal diagnosis. Prenatal diagnosis of LPAS will facilitate postnatal care and timely treatment.
Variant in ACTG2 Causing Megacystis Microcolon Hypoperistalsis Syndrome and Severe Familial Postpartum Bleeding
Authors: Krabek Rikke , Smed Vibe Madsen , Oestergaard Elsebet , Sundberg Karin
Published: December 2022

Introduction: Megacystis microcolon hypoperistalsis syndrome (MMIHS) is a rare condition with high morbidity and mortality. It is characterized by megacystis, microcolon, and intestinal hypoperistalsis leading to various grades of bladder and bowel obstruction. Case Presentation: This report describes a pregnant woman with a history of bowel obstruction, urine retention, and heavy postpartum bleeding where ultrasound findings of fetal megacystis during pregnancy led to genetic testing in the family. The fetus, the pregnant woman, and four female family members were heterozygous for a pathogenic variant detected in the ACTG2 gene. The fetus was treated successfully for hydronephrosis using vesicoamniotic shunting. Discussion: Early diagnosis of a fetus with MMIHS is important to secure multidisciplinary prenatal and neonatal treatment. Furthermore, gene testing must be considered when a woman presents a history of pseudo-obstruction and urine retention to prevent complications during pregnancy and labor. Finally, recurrent familial postpartum bleeding should lead to referral to genetic evaluation.
Multi-channel of electroencephalogram signal in multivariable brain-computer interface
Authors: Djamal Esmeralda Contessa , Sury Dimas Andhika
Published: December 2022

Brain-computer interface (BCI) usually uses Electroencephalogram (EEG) signals as an intermediate device to drive external devices directly from the brain. The development of BCI capabilities is carried out by involving multivariable EEG signals as movement commands. EEG signals are recorded using multi-channel, enriching information if it uses the suitable method and architecture. This research proposed a two-dimensional convolutional neural networks (CNN) method to recognize multi-channel EEG signals. The vertical dimension is the channel, while the horizontal is the signal sequence. Hence, the signal is connected with the information time series of the same channel and between channels simultaneously. BCI was arranged with multivariable signals, specifically motor imagery and emotion. Both variables have different characteristics, and the information is from different channels. Therefore, it needs multiple CNNs to recognize the two variables in the EEG signal. The experiment showed that the accuracy of multiple 2D-CNN increased to 94.62% compared to 85.44% of single 2D CNN. Multiple 2D-CNN gave accuracy from 82.04% to 94.62% more than multiple 1D-CNN. 2D-CNN makes the channel extraction perfect into vectors to maintain the signal sequence. Signal extraction is essential, so the used Wavelet filter upgraded accuracy from 73.75% to 94.62%.
An improved artificial bee colony with perturbation operators in scout bees’ phase for solving vehicle routing problem with time windows
Authors: Mortada Salah , Yusof Yuhanis
Published: December 2022

An example of a combinatorial problem is the vehicle routing problem with time windows (VRPTW), which focuses on choosing routes for a limited number of vehicles to serve a group of customers in a restricted period. Meta-heuristics algorithms are successful techniques for VRPTW, and in this study, existing modified artificial bee colony (MABC) algorithm is revised to provide an improved solution. One of the drawbacks of the MABC algorithm is its inability to execute wide exploration. A new solution that is produced randomly and being swapped with best solution when the previous solution can no longer be improved is prone to be trapped in local optima. Hence, this study proposes a perturbed MABC known as pertubated (P-MABC) that addresses the problem of local optima. P-MABC deploys five types of perturbation operators where it improvises abandoned solutions by changing customers in the solution. Experimental results show that the proposed P-MABC algorithm requires fewer number of vehicles and least amount of travelled distance compared with MABC. The P-MABC algorithm can be used to improve the search process of other population algorithms and can be applied in solving VRPTW in domain applications such as food distribution.
An efficient security analysis of bring your own device
Authors: Soubhagyalakshmi Pullagura , Reddy Kalli Satyanarayan
Published: December 2022

The significant enhancement in demand for bring your own device (BYOD) mechanism in several organizations has sought the attention of several researchers in recent years. However, the utilization of BYOD comes with a high risk of losing crucial information due to lesser organizational control on employee-owned devices. The purpose of this article is to review and analyze the various security threats in BYOD; further we review the existing work that was developed in order to reduce the risks present in BYOD. A detailed review is presented to detect BYOD security threats and their respective security policies. A phase-by-phase mitigation strategy is developed based on the components and crucial elements identified using review policy. Managerial-level, social-level and technical level issues are identified such as illegal access, leaking delicate company data, lower flexibility, corporate data breaching, and employee privacy. It is analyzed that collaboration of people, security policy factors and technology in an effective manner can mitigate security threats present in the BYOD mechanism. This article initiates a move towards filling the security gap present the BYOD mechanism. This article can be utilized for providing guidelines in various organizations. Ultimately, successful implementation of BYOD depends upon the balance created between usability and security.
Cross-checked screening application for reliable categorisation of familial hypercholesterolaemia: design and development of the prototype
Authors: Rosli Marshima Mohd , Annamalai Muthukkaruppan , Mohd Kasim Noor Alicezah , Yung-An Chua , Nawawi Hapizah Mohd
Published: December 2022

The paper describes the development of a computer-based familial hypercholesterolemia (FH) screening application (FH CatScreen©). The application facilitates automatic scoring and categorisation of patients by medical practitioners based on four well-known FH diagnostic criteria. In the absence of a FH diagnostic criterion for Malaysian population, these four diagnostic criteria are commonly used criteria to classify patients FH severity levels to manage early interventions. We applied an adaptive software development approach comprising planning, development and validation phases to develop FH CatScreen©. A user study involving thirty medical practitioners was conducted to evaluate the effectiveness and usability of FH CatScreen©. The study showed that FH CatScreen© was able to provide a more correct, faster and better-informed assessment compared to the traditional paper-based method. The study further showed that FH CatScreen© has a good degree of performance and acceptance by the participants. The participants indicated that the simultaneous use of the four diagnostic criteria in FH CatScreen© has assisted them to compare the outcomes of each of the criterion side-by-side. It allowed them to decide on the severity of patient condition with high confidence. FH CatScreen© has demonstrated its expediency and efficacy in collecting the data on FH incidence and prevalence in Malaysia.
A high frame-rate of cell-based histogram-oriented gradients human detector architecture implemented in field programmable gate arrays
Authors: Fuada Syifaul , Adiono Trio , Kasan Hans
Published: December 2022

In respect of the accuracy, one of the well-known techniques for human detection is the histogram-oriented gradients (HOG) method. Unfortunately, the HOG feature calculation is highly complex and computationally intensive. Thus, in this research, we aim to achieve a resource-efficient and low-power HOG hardware architecture while maintaining its high frame-rate performance for real-time processing. A hardware architecture for human detection in 2D images using simplified HOG algorithm was introduced in this paper. To increase the frame-rate, we simplify the HOG computation while maintaining the detection quality. In the hardware architecture, we design a cell-based processing method instead of a window-based method. Moreover, 64 parallel and pipeline architectures were used to increase the processing speed. Our pipeline architecture can significantly reduce memory bandwidth and avoid any external memory utilization. an altera field programmable gate arrays (FPGA) E2-115 was employed to evaluate the design. The evaluation results show that our design achieves performance up to 86.51 frame rate per second (Fps) with a relatively low operating frequency (27 MHz). It consumes 48,360 logic elements (LEs) and 4,363 registers. The performance test results reveal that the proposed solution exhibits a trade-off between Fps, clock frequency, the use of registers, and Fps-to-clock ratio.
K-means clustering analysis and multiple linear regression model on household income in Malaysia
Authors: Yee Gan Pei , Rusiman Mohd Saifullah , Ismail Shuhaida , Suparman Suparman , Hamzah Firdaus Mohamad , Shafi Muhammad Ammar
Published: December 2022

Household income plays a significant role in determining a country's socioeconomic standing. This measure is often used by the government to formulate the federal budget and policies that are most appropriate for national development. In spite of this, Malaysia's current economic circumstances continue to be characterized by income disparity. Therefore, this shortcoming can be addressed by analyzing the household income survey (HIS) conducted by Department of Statistics Malaysia (DoSM). In this study, the hybrid model is proposed where K-means and multiple linear regression (MLR) for clustering and predicting household income in Malaysia. Based on the experimental results, the K-means clustering analysis in conjunction with the MLR model outperformed the MLR model without clustering with a smaller mean square error. As a result, clustering analysis results in a more accurate estimate of household income because it reduces the variation between households. It is important that household income information reflect the concern of policymakers about the impact of universal and targeted interventions on different socioeconomic groups.
Machine learning classifiers for detection of glaucoma
Authors: Verma Reshma , Shrinivasan Lakshmi , Hiremath Basvaraj
Published: December 2022

Glaucoma is a disease that affects the optic nerve. This disease, over a period of time, can lead to loss of vision. Which is known as ‘silent thief of sight’. There are several methods in which the disease can be treated, if detected at an early stage It is not possible for any technology, including artificial intelligence, to replace a doctor. However, it is possible to develop a model based on several classical image processing algorithms, combined with artificial intelligence that can detect onset of glaucoma based on certain parameters of the retinal fundus. This model would play an important role in early detection of the disease and assist the doctor. The traditional methods to detect glaucoma, as efficient as they may be, are usually expensive, a machine learning approach to diagnose from fundus images and accurately classify its severity can be considered to be efficient. Here we propose support vector machine (SVM) method to segregate, train the models using a high-end graphics processor unit (GPU) and augment the hull convex approach to boost the accuracy of the image processing mechanisms along with distinguishing the different stages of glaucoma. A web application for the screening process has also been adopted.
Thai Hom Mali rice grading using machine learning and deep learning approaches
Authors: Thammastitkul Akara , Petsuwan Jitsanga
Published: December 2022

Thai Jasmine rice or Thai Hom Mali rice is a well-known rice type that originated in Thailand. Rice grain qualities are important in determining market pricing and are used in grading systems. The purpose of this research is to use machine learning and deep learning to improve the grading of Thai Hom Mali rice following standardized grading criteria. The appearance of grains and foreign items will determine the grade of rice. The experiment has two parts: grain categorization and rice grading. Multi-class support vector machine (SVM) and convolutional neural network (CNN) are proposed. There are 15 features used as input for multi-class SVM, including morphology and color features. With ImageNet pre-trained weights, CNN with DenseNet201 architecture is implemented. The experiment also tested into how CNN worked with both original and preprocessed images. The results are then compared to a neural network (NN) baseline approach. The CNN approach, which identified each rice variety using preprocessed images, archieved the greatest accuracy rate of 98.25%, with an average accuracy of 94.52% across six categories of rice grading.
Predicting students’ academic performance using e-learning logs
Authors: Abdullah Malak , Al-Ayyoub Mahmoud , Shatnawi Farah , Rawashdeh Saif , Abbott Rob
Published: December 2022

The outbreak of coronavirus disease 2019 (COVID-19) drives most higher education systems in many countries to stop face-to-face learning. Accordingly, many universities, including Jordan University of Science and Technology (JUST), changed the teaching method from face-to-face education to electronic learning from a distance. This research paper investigated the impact of the e-learning experience on the students during the spring semester of 2020 at JUST. It also explored how to predict students’ academic performances using e-learning data. Consequently, we collected students’ datasets from two resources: the center for e-learning and open educational resources and the admission and registration unit at the university. Five courses in the spring semester of 2020 were targeted. In addition, four regression machine learning algorithms had been used in this study to generate the predictions: random forest (RF), Bayesian ridge (BR), adaptive boosting (AdaBoost), and extreme gradient boosting (XGBoost). The results showed that the ensemble model for RF and XGBoost yielded the best performance. Finally, it is worth mentioning that among all the e-learning components and events, quiz events had a significant impact on predicting the student’s academic performance. Moreover, the paper shows that the activities between weeks 9 and 12 influenced students’ performances during the semester.
Modeling of an artificial intelligence based enterprise callbot with natural language processing and machine learning algorithms
Authors: Aattouri Imad , Mouncif Hicham , Rida Mohamed
Published: December 2022

The management of customer services by telephone encounters several problems: an uncontrollable flow of calls, complicated resource management, a very high cost of service, and more. Opportunities to improve the quality of service, save time and money triggered the widespread implementation of artificial intelligence (AI) based callbot. This article outlines the straightforward workflow developed to model the architecture of the callbot. Therefore, several algorithms were evaluated and compared based on real knowledge of a call center of an insurance society. The algorithms considered are: k-nearest neighbours (KNN), support vector machine (SVM), random forests (RF), logistic regression (LR), and Na¨ıve Bayes (NB). The comparison criteria are: correct responses, response time, accuracy, Cohen’s kappa and F1 score using n-gram (1.1) and (2.2). The results obtained show that the SVM (accuracy=70.29%) presents the best results on all the comparison criteria. The comparison between the results of the human agents and the callbot shows an improvement in several levels: the cost savings are greater than 80% on all the tests carried out, the holding time decrease to 0 seconds, and the processing time (almost a third or more). The results obtained sufficiently meet the objectives of this project.
Combating propaganda texts using transfer learning
Authors: Abdullah Malak , Abujaber Dia , Al-Qarqaz Ahmed , Abbott Rob , Hadzikadic Mirsad
Published: December 2022

Recently, it has been observed that people are shifting away from traditional news media sources towards trusting social networks to gather news information. Social networks have become the primary news source, although the validity and reliability of the information provided are uncertain. Memes are crucial content types that are very popular among young people and play a vital role in social media. It spreads quickly and continues to spread rapidly among people in a peer-to-peer manner rather than a prescriptive. Unfortunately, promoters and propagandists have adopted memes to indirectly manipulate public opinion and influence their attitudes using psychological and rhetorical techniques. This type of content could lead to unpleasant consequences in communities. This paper introduces an ensemble model system that resolves one of the most recent natural language processing research topics; propaganda techniques detection in texts extracted from memes. The paper also explores state-of-the-art pretrained language models. The proposed model also uses different optimization techniques, such as data augmentation and model ensemble. It has been evaluated using a reference dataset from SemEval-2021 task 6. Our system outperforms the baseline and state-of-the-art results by achieving an F1-micro score of 0.604% on the test set.
Spectrum sensing using 16-QAM and 32-QAM modulation techniques at different signal-to-noise ratio: a performance analysis
Authors: Chaudhary Neha , Mahajan Rashima
Published: December 2022

Spectrum sensing techniques are implemented for effective use of spectrum resources in the cognitive-radio. In this research work attempt has been made for the performance of energy detector with cooperative spectrum sensing using double dynamic threshold on the MATLAB software. Additive white gaussian noise is used and the frequency range between 54 MHz to 862 MHz is considered with wideband. Findings in receiver operative curve have been observed to analyze probability-of-detection (𝑃𝑑) under different values of probability-of-false alarm (𝑃𝑓) condition and diverse ranges of signal to noise ratio with different number of samples of input signal. Presence and absence of primary user has been marked by using a hypothetical model based on Neyman pearson approach. From the results, it has been observed that more the number of sample values, better is the probability-of-detection (𝑃𝑑) value as achieved for 32-QAM signal as compared to 16-QAM signal. Also, better results have been witnessed at -9db signal to noise ratio value as compared to -15db and -20db. This work provides almost 10% of enhancement in the probability of detection at -9db signal to noise ratio for 16-QAM modulated signal as compared to the existing model where the implementation of energy detector spectrum sensing technique through simulink model.
Association Between Income and Risk of Out-of-Hospital Cardiac Arrest: A Retrospective Cohort Study
Authors: van Nieuwenhuizen Benjamin P. , Tan Hanno L. , Blom Marieke T. , Kunst Anton E. , van Valkengoed Irene G.M.
Published: December 2022

Background:

Previous studies have observed a higher out-of-hospital cardiac arrest (OHCA) risk among lower socioeconomic groups. However, due to the cross-sectional and ecological designs used in these studies, the magnitude of these inequalities is uncertain. This study is the first to assess the individual-level association between income and OHCA using a large-scale longitudinal study.

Methods:

This retrospective cohort study followed 1 688 285 adults aged 25 and above, living in the catchment area of an OHCA registry in a Dutch province. OHCA cases (n=5493) were linked to demographic and income registries. Cox proportional hazard models were conducted to determine hazard ratios of OHCA for household and personal income quintiles, stratified by sex and age.

Results:

The total incidence of OHCA per 100 000 person years was 30.9 in women and 87.1 in men. A higher OHCA risk was observed with lower household and personal income. Compared with the highest household income quintile, the adjusted hazard ratios from the second highest to the lowest household income quintiles ranged from 1.24 (CI=1.01–1.51) to 1.75 (CI=1.46–2.10) in women and from 0.95 (CI=0.68–1.34) to 2.30 (CI=1.74–3.05) in men. For personal income, this ranged from 0.95 (CI=0.68–1.34) to 2.30 (CI=1.74–3.05) in women and between 1.28 (CI=1.16–1.42) and 1.68 (CI=1.48–1.89) in men. Comparable household and personal income gradients were found across age groups except in the highest (>84 years) age group. For example, household income in women aged 65 to 74 ranged from 1.25 (CI=1.02–1.52) to 1.65 (CI=1.36–2.00). Sensitivity analyses assessing the prevalence of comorbidities at baseline and different lengths of follow-up yielded similar estimates.

Conclusions:

This study provides new evidence for a substantial increase in OHCA risk with lower income in different age and sex groups. Low-income groups are likely to be a suitable target for intervention strategies to reduce OHCA risk.
The first annotated checklist of Pentatomoidea (Hemiptera: Heteroptera) fauna of Alta Murgia National Park (Apulia region, Southern Italy)
Authors: LATERZA ILARIA , TAMBURINI GIOVANNI , PANZARINO ONOFRIO , LOVERRE PAMELA , MASTRONARDI MARIA GRAZIA , DIOLI PARIDE , DE LILLO ENRICO
Published: December 2022

Information regarding Pentatomoidea is scarce in Southern Italy, and in particular concering the Apulia region (Sourthern Italy), an area of high biodiversity potential. We conducted an extensive survey of Pentatomoidea fauna in the Alta Murgia National Park, a Site of Community Importance, and neighbouring areas located in central part of Apulia region. The survey was carried out in 2016, 2017 and 2020, sampling different habitat types. We found 55 species, with five new records for Apulia: Solenosthedium bilunatum, Acrosternum millierei, Sciocoris homalonotus, Cyphostethus tristriatus and Holcogaster fibulata. The polyphagous pest Halyomorpha halys was found only in urban areas, whereas Ventocoris falcatus, Ellipsocoris kalashiani and Tholagmus flavolineatus, considered rare species, were collected in dry grasslands, confirming the crucial role of natural habitat for biodiversity conservation.
Changes in Pediatricians’ Child Passenger Safety Counseling With Initiation of a Booster Seat Program
Authors: Kelly Jessica M. , Piotrowski Joy , Zonfrillo Mark R. , Riese Alison
Published: December 2022

Booster seats reduce injury in motor vehicle crashes, yet they are used less frequently than car seats and seat belts. Primary care providers are well positioned to educate and encourage families to use booster seats. We aimed to assess how a booster seat distribution program affected the documentation of restraint usage and anticipatory guidance at well-child visits at a pediatric primary care practice. We performed a retrospective chart review of patients aged 4 to 12 years from June to December in 2019 and 2020, representing before and after a booster seat program. The most frequently documented restraints in 2019 and 2020 were seat belts (51% vs 30%), booster seats (25% vs 27%), and not documented/unclear (17% vs 25%) ( P < .001). The program significantly increased referrals for booster seats ( P < .001). Despite significant differences in the proportion of children in each restraint category, overall booster seat use was similar between years.
The Role of Neighborhoods in the Age of Crime Hot Spots: A Multi-Level Theory of the Spatial Distribution of Robbery in Chicago
Authors: Schnell Cory , DeWitt Samuel E. , Spencer M. Dylan
Published: December 2022

This study observes the spatial distribution of robbery using a multi-level framework to further understand the unique contribution of both micro-places and neighborhoods to the spatial variability of crime patterns. Mixed-effects regression models were estimated to determine if the influence of spatial interdependence measured with a spatial lag variable at street segments had a random effect between Chicago’s community areas. The variance parameters guided an exploratory spatial data analysis which revealed clusters of robbery patterns which were larger than crime hot spots and often nested within neighborhoods. We found there is an important distinction between places in Chicago where the spatial transmissibility of robberies is most acutely experienced across entire neighborhoods or within the immediate proximity of certain micro-places.
Failure mechanism of weft-knitted insertion fabric/Surlyn resin flexible composite for stab resistance
Authors: Liu Qing , Sun Yaxin , Zhao Junzhu , Ma Pibo
Published: December 2022

In this paper, two kinds of aramid fibers were used to prepare weft-knitted insertion fabrics, flexible Surlyn resin as matrix to prepare reinforced weft-knitted insertion fabrics, the effects of hot-pressing temperature, resin content, pressure and holding time on reinforced weft-knitted insertion fabric were explored. Through lamination and co-curing, the effects of the lamination numbers, preparation methods and lamination sequence on the stab resistance of the multilayer system were studied. The results showed that appropriate hot-pressing temperature, resin content, pressure and holding time can improve the stab resistance by improving the permeability of resin in the fabric. However, over high temperatures, pressure and holding time have a negative impact on the stab resistance or flexibility of the composite; high resin content means higher weight, which is not conducive to human wearing. When the area density is similar, the stab resistance of the co-cured composite is the best, followed by the superposition of single-layer composite, finally is the superposition of film and fabric. Weft-knitted insertion fabrics and reinforced weft-knitted insertion fabrics can dissipate puncture energy through shear force, tensile fracture, friction and deformation of yarn or fabric. In addition, composites also have other energy dissipation pathways such as filament compression splitting, fabric/matrix debonding and matrix delamination.
Challenges to Identifying Economic Development Impacts
Authors: Rohlin Shawn
Published: December 2022

Researchers investigating causal estimates of economic development programs face many challenges. This commentary highlights three challenges for future researchers to consider. Specifically, the author discusses how important it is to examine distributional changes and not just mean effects. Additionally, the merits of determining migration effects when studying economic development programs to better understand if original residents benefit from the program are discussed. Finally, the author questions how the pandemic will affect economic development research, particularly relating to how labor markets are defined.
Arts and Cultural Innovation as Small City Economic Development
Authors: Markusen Ann
Published: December 2022

Arts and journalism enterprises may serve as effective economic development tools for small cities and neighborhoods. The author demonstrates how a new, for-profit, weekly newspaper serving a Minnesota city of 12,000 residents in a county of 36,000 has diversified and energized a depopulated downtown and surrounding region. Through powerful investigative reporting and by investing in and hosting exhibits by area artists, the newspaper has attracted new businesses into adjacent unoccupied retail spaces.
The Epistemological Chain: A Tool to Guide TNE Development
Authors: Grecic David
Published: December 2022

Transnational Education (TNE) has been a growing area of university business with a range of models developed to provide high quality educational products to partners across the world. However, given the changing geo-political environment, the continued rationale, efficacy, and legitimacy of current TNE partnership templates must be questioned. This paper therefore presents an alternative conceptualization to drive future work in this area, one which prioritizes the place of knowledge and transformational learning. I propose a new learning-based framework, the Epistemological Chain (EC), and describe how this can guide future TNE interactions and establish an alternative paradigm based upon cooperation and the co-creation of learning. Exemplars are provided that illustrate the extremes of the framework. The EC's future utility and application are then discussed with regard to TNE partnership design, operation, and evaluation. In summary the paper provides an original framework that places education firmly back at the heart of TNE.
Patterns of Unnatural Deaths Among Children and Adolescents: Autopsy Study (2011-2018)
Authors: Ben Abderrahim Sarra , Belhaj Azza , Bellali Mohamed , Hmandi Ons , Gharbaoui Meriem , Harzallah Hana , Naceur Yomn , Ben Khelil Mehdi , Allouche Mohamed
Published: December 2022

Background and Aims:

The problem of unnatural death in children is still relevant because of their vulnerability. This work aimed to describe the epidemiological profile and patterns of these medicolegal deaths in children and adolescents in northern Tunisia.

Methods:

We conducted a retrospective study from January 2011 to December 2018, within the Forensic Department of Charles Nicolle Hospital in Tunis. All children who died of unnatural causes were included (767 cases).

Results:

An overall male predominance was observed (sex ratio = 2.4). Accidental deaths represent the most common manner of death (81.4%) involving most frequently domestic accidents occurring in children aged between 1 and 4 years. In cases of suicide, the highest risk profile was a female child aged between 15 and 18 years. The suicide occurred most often in the victim’s home with hanging representing the common means of suicide. For the criminal form, the most common means in those cases were stabbing and blunt injuries.

Conclusion:

Our study delivered a broad picture of unnatural deaths among children in Tunisia. These deaths, largely absent from child survival initiatives presently on the global agenda, can be prevented if they are addressed strategically, as their injury prevention strategies differ from adults.
Stroke in Africa: A systematic review and meta-analysis of the incidence and case-fatality rates
Authors: Okekunle Akinkunmi Paul , Jones Stephanie , Adeniji Olaleye , Watkins Caroline , Hackett Maree , Di Tanna Gian Luca , Owolabi Mayowa , Akinyemi Rufus
Published: December 2022

Background:

The burden of stroke (a leading cause of disability and mortality) in Africa appears to be increasing, but a systematic review of the best available data to support or refute this observation is lacking.

Aim:

To determine the incidence and 1-month case-fatality rates from high-quality studies of stroke epidemiology among Africans.

Summary of review:

We searched and retrieved eligible articles on stroke epidemiology among indigenous Africans in bibliographic databases (MEDLINE, ScienceDirect, Google Scholar, and Cochrane library) using predefined search terms from the earliest records through January 2022. Methodological assessment of eligible studies was conducted using the Newcastle–Ottawa scale. Pooling of incidence and case-fatality rates was performed via generalized linear models (Poisson-Normal random-effects model). Of the 922 articles retrieved, 14 studies were eligible for inclusion. The total number of stroke cases was 2568, with a population denominator (total sample size included in population-based registries or those who agreed to participate in door-to-door community studies) of 3,384,102. The pooled crude incidence rate of stroke per 100,000 persons in Africa was 106.49 (95% confidence interval (CI) = 58.59–193.55), I2 = 99.6%. The point estimate of the crude incidence rate was higher among males, 111.33 (95% CI = 56.31–220.12), I2 = 99.2%, than females, 91.14 (95% CI = 47.09–176.37), I2 = 98.9%. One-month case-fatality rate was 24.45 (95% CI = 16.84–35.50), I2 = 96.8%, with lower estimates among males, 22.68 (95% CI = 18.62–27.63), I2 = 12.9%, than females, 27.57 (95% CI = 21.47–35.40), I2 = 51.6%.

Conclusion:

The burden of stroke in Africa remains very high. However, little is known about the dynamics of stroke epidemiology among Africans due to the dearth of high-quality evidence. Further continent-wide rigorous epidemiological studies and surveillance programs using the World Health Organization STEPwise approach to Surveillance (WHO STEPS) framework are needed.
Accident analysis and risk prediction of tank farm based on Bayesian network method
Authors: Wu Xingguang , Huang Huirong , Yu Weichao , Lin Yuming , Xue Yanhui , Cai Qingwen , Xu Jili
Published: December 2022

In recent decades, many attempts have been made to establish the cause-effect relationship model of accidents, while little work has been carried out to comprehensively consider the interdependence between the causal factors and their complex interactions with the accident outcomes. In this study, a novel accident analysis approach based on Bayesian networks (BNs) was proposed to achieve quantitative accident analysis and dynamic risk prediction of accident types and consequences. To develop the BN-based accident analysis model, a total of 1144 accident cases occurred in tank farm of China from 1960 to 2018 were collected. The BN model that can comprehensively characterize the dependencies among accident elements was established through structural learning based on accident case analysis and parameter learning based on EM algorithm. The reliability and validity of the BN model were verified by k-fold cross-validation method and comparison of predicted data with real data, and the results showed that the BN model had good classification and prediction performance. Furthermore, the established BN model was applied to the accident occurred in Huangdao, China. The analysis results show that not only the accident outcome can be accurately predicted, but also the hidden correlation can be deeply explored through the established BN model. The proposed method and findings can provide technical reference for accident investigation and analysis, and provide decision support for accident prevention and risk management.