Miracle-dz/UniFAR-FTUs huggingface dataset:
Studi eksplorasi pengetahuan dan sikap terhadap kesiapsiagaan bencana banjir di SD Pilanggede Kecamatan Balen Kabupaten Bojonegoro

This study aims to determine the knowledge and attitude of flood disaster preparedness of Elementary School Pilanggede, District Balen, Bojonegoro. Knowledge is a key factor to preparedness. Knowledge can affect the attitude and awareness to standby in anticipating the disaster. Children from an early age should be given a proper understanding of the types of disasters that may be affecting their area and ways of dealing with disasters when it comes suddenly. The vulnerability of children to disasters is triggered by a limited understanding of the risks surrounding them, resulting in a lack of preparedness in the face of disasters. Elementary School Pilanggede District Balen, Bojonegoro is one that has flood every year. Not only the school buildings are flooded, but most of the students live as well. This research uses quantitative approach with survey method. The survey was conducted to find out the description of the condition of knowledge and attitude of student preparedness to the flood disaster that occurred in the environment. Furthermore, a descriptive analysis was conducted. The data needed in this research is primary data obtained from observation and spreading of questionnaire conducted at grade 3 to 6 Elementary School Pilanggede. The research findings indicate that students' knowledge of the flood disaster is still poorly proved by an understanding of the causes and occurrence of low floods. The student's attitude in reducing flood risk is also quite low as evidenced by playing during floods and the use of electronic during floods and the provision of equipment is minimal. Additional findings in this study is that there has been a study of flood disasters and how to overcome them, but not continued. Keywords: Knowledge, Attitude, Flood Preparedness http://dx.doi. org/10.17977/um022v2i12017p001
Contemporary Surgical Management of Colorectal Liver Metastases

Simple Summary Colorectal cancer is a common cancer diagnosis, with many patients suffering from metastatic disease. Unfortunately, the prognosis for these patients remains grim, but there is a cohort in whom surgery remains a viable option, with the potential for a cure. The management of this cohort of patients is complex and requires the guidance of a dedicated hepatobiliary surgeon. There also remains a deep interplay between perioperative and operative decisions, which ultimately need tailoring to each individual patient. In this review, we aim to define these key perioperative and operative considerations in the contemporary management of colorectal liver metastasis. Abstract Colorectal cancer is the third most common cancer in the United States and the second most common cause of cancer-related death. Approximately 20–30% of patients will develop hepatic metastasis in the form of synchronous or metachronous disease. The treatment of colorectal liver metastasis (CRLM) has evolved into a multidisciplinary approach, with chemotherapy and a variety of locoregional treatments, such as ablation and portal vein embolization, playing a crucial role. However, resection remains a core tenet of management, serving as the gold standard for a curative-intent therapy. As such, the input of a dedicated hepatobiliary surgeon is paramount for appropriate patient selection and choice of surgical approach, as significant advances in the field have made management decisions extremely nuanced and complex. We herein aim to review the contemporary surgical management of colorectal liver metastasis with respect to both perioperative and operative considerations.
COVID-19 in Patients with Different Hematological Malignancies: Treatment Strategy and Outcome: An Iraqi Experience

Background: Patients with hematological malignancies may have higher rates of morbidity and mortality due to SARS-COVID-19 than those in the general population. Objectives: To evaluate the outcome of SARS-COVID-19 in patients with different hematological malignancies undergoing active or modified therapy. Settings: This was a retrospective cohort, multicenter study conducted on 167 patients diagnosed with SARS-COVID-19. The selected patients had been diagnosed with different hematological malignancies and had received treatment (chemotherapy or immunosuppressive). The study was carried out in different centers across Iraq between 1 December 2020 and 1 December 2021. Patients and Methods: This study was conducted in seven hematology centers across Iraq with 167 patients; of these, this study showed that 88 (52.7%) were males and 79 (47.3%) were females (mean age 51.9 ± 18.3 years). All patients had had a COVID-19 infection confirmed through RNA-specific fragments by real-time reverse transcriptase polymerase chain reaction (RT-PCR) of the nasopharyngeal swab specimens, and by computed tomography (CT) of the chest. Demographic data were obtained from patient files, which included the type of hematological malignancy, treatment (chemotherapy, immunotherapy, supportive), severity of COVID-19, modification of treatment and disease outcome for patients, whether alive or not. Patients identified as having benign or non-hematological malignancies were excluded. Results: The treatment protocol was modified in 124 patients (74.3%), while 43 patients (25.7%) continued on the same protocol. Regarding treatment outcomes, 77.2% of patients were alive at the end of the study and 22.8% had died. The survival of COVID-19 patients did not change significantly when the treatment protocol was modified compared to those who continued on treatment as per protocol. The death rate was significantly higher among patients with severe disease compared to those with mild and moderate disease (61.4% v. 0% and 5.0%, respectively) (p<0.001). Conclusions: The management of patients with hematological malignancies during the COVID-19 pandemic may be challenging, with higher mortality in patients with concurrent hematological malignancies and COVID-19. The survival of COVID-19 patients did not change significantly when treatment was modified. Age groups, sex, type of hematological malignancy, and disease status did not affect the survival of these patients. The death rate was significantly higher among patients with hematological malignancies and severe COVID-19 compared with mild or moderate disease.
Electric Motor Systems: Relative Study on Diverse Motors in the Electric Vehicles

In the contemporary world, Electric Vehicles (EV) is the essential technology to reduce the carbon emission in the transport industry. It uses electricity to charge the batteries as an alternate of the fossils fuels such as diesel or petrol. In the EV, electric motor plays the significant role to convert the electrical energy to mechanical energyto run the EV. There are diverse varieties of electric motors that are used in the EV vehicles. The presented paper signifies the types of EV and examines the different types of motors. Moreover, it analyse the features and limitations of the electric motors. Correspondingly, several researches focused on the diverse techniques for the enhancement of the electric motors to improve the performance of the electric vehicles. The presented paper compiles diverse electric motor researches and analyse the efficiency of the four types of electric motors. Similarly, it depicts the features and limitations of the electric motors. Moreover, a recent trend in the enhancement of the electric motors is signified in the projected study. The projected study is intended to contribute in the researchers related to the enhancement of efficiency of the EV.
Assessment of Kara Abattoir Effluent on the Water Quality of Ogun River, Nigeria

Direct discharge of abattoir effluents into water bodies contributes to problem of water pollution. This study assessed the impact of Kara Abattoir effluents on Ogun River in Nigeria using standard methods to measure the physiological characteristics and heavy metal levels. The results made it evident that most of the chemical parameters in this study exceeded the accepted standards; phosphate was seen to range between 0.34-109mg/l with a mean value of 27.62mg/l. All the twelve heavy metals observed in the water samples were within acceptable limits. The most alarming result observed is the presence of a “too many to count” range of microbial load and faecal coliform which can be attributable to a major cause of diarrhoea, urinary tract infections, respiratory illness and other threat to human health. Ogun River serves as habitat to some organisms; and is also used for domestic activities by nearby communities; hence, urgent policy implementation is required. Keywords : Abattoir, Effluents, Ogun River, Pollution
Perceptions of Higher Education Students towards ChatGPT Usage

In the context of contemporary technological advancements, Artificial Intelligence (AI) has gained considerable significance in the field of education. In light of ChatGPT’s growing popularity, this research aims to explore how higher education students perceive the use of ChatGPT in academics, examining factors influencing its acceptance, as well as its benefits, limitations, and ethical concerns. The study applied a survey design, collecting data through Google Forms from undergraduate, postgraduate, and doctoral students. A total of 162 participants, who were using ChatGPT selected through convenience sampling. The findings indicate a positive perception among respondents regarding ChatGPT's academic applications, its benefits, limitations, acceptance factors, and ethical concerns. The study also reveals that the perception of higher education students towards ChatGPT usage is not significantly influenced by gender, academic programs, and streams. The insights gained from this study holds significant implications for the responsible and effective integration of ChatGPT in higher education environments, taking into account its perceived benefits and ethical concerns.
Analysis of Factors Affecting Proper Functioning of Smallholder Agricultural Cooperatives in the Limpopo Province of South Africa

Abstract The present study determined factors that affected the proper functioning of smallholder-cooperatives in the Lepelle Nkumpi municipality, Limpopo Province of South Africa. By employing discriminant analysis, data collected from 140 cooperative members from 13 different agricultural cooperative were analysed to identify factors that can be used to discriminate between functional and dysfunctional agricultural cooperatives. The results indicated that the independent variables that accounted for most the differences between functional and dysfunctional cooperatives were size of cooperative, availability of stakeholders to assist in improving the level of skill of members, satisfaction of members with assistance provided, number of females in the cooperative, number of years the cooperative had been in existence, members participation in decision making and age group. It was recommended that government should intensify efforts to improve skills of members and also provide assistance to the satisfaction of cooperative members in order to assist cooperatives to become functional.
1066 and All that: Some Deep Determinants of Voting Shares in the 2016 Referendum on EU Membership

Recent evidence from UK opinion surveys suggests that inhabitants of areas where there is a high density of universities have opinions that are significantly more liberal with regard to immigration and minority rights; this effect is robust to controlling for the individual's own age and education level, suggesting that university towns have a distinctive culture. Moreover, variation in the density of universities is explained partly by variation in the density of earlier educational institutions, and the variation in the density of these earlier institutions is associated with medieval exposure to religious and ethnic diversity. Support for EU membership is known to be correlated with liberalism, and this paper shows that patterns of voting in the 2016 referendum are also associated with the density of universities and earlier educational institutions, and with medieval exposure to religious and ethnic diversity.
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The influence of smoking and impaired glucose homoeostasis on the outcome in patients presenting with an acute coronary syndrome: a cross-sectional study. influence of smoking and impaired glucose homoeostasis on the outcome in patients presenting with an acute coronary syndrome: a cross-sectional study. BMJ Open, 4(7), e005077. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? The influence of smoking and impaired glucose homoeostasis on the outcome in patients presenting with an acute coronary syndrome: a cross-sectional study The influence of smoking and impaired glucose homoeostasis on the outcome in patients presenting with an acute coronary syndrome: a cross-sectional study. ▸ Prepublication history for this paper is available online. To view these files please visit the journal online ABSTRACT Objectives: Smoking, diabetes, male sex, hypercholesterolaemia and hypertension are well-established risk factors for the development of coronary artery disease (CAD). However, less is known about their role in influencing the outcome in the event of an acute coronary syndrome (ACS). The aim of this study was to determine if these risk factors are associated specifically with acute myocardial infarction (MI) or unstable angina (UA) in patients with suspected ACS. Design: Cross-sectional study. Setting: Patients admitted to the coronary care unit, via the emergency room, at a central county hospital over a 4-year period (1992–1996). Participants: From 5292 patients admitted to the coronary care unit, 908 patients aged 30–74 years were selected, who at discharge had received the diagnosis of either MI (527) or UA (381). A control group consisted of 948 patients aged 30–74 years in whom a diagnosis of ACS was excluded.
SOLVING SENTIMENT ANALYSIS USING TRANSFORMER BASED BERT

The most prevalent sequence transduction models use neural networks containing encoders and decoders. The better versions also have an attention mechanism that connects the encoder and decoder. An innovative language representation paradigm, BERT stands for bidirectional Encoder Representations from Transformers. Because it takes into account both the left and right sides of the text at every level, BERT can pre-train deep bidirectional representations from unlabeled text. For a wide variety of tasks, such as answering questions and making inferences about languages, the pre-trained BERT model may be fine-tuned to create cutting-edge models with just one extra output layer. It's easy to use, and it's backed by a tonne of data from the scientific community.
RISK FACTORS FOR DEVELOPMENT OF STOMA Evaluation of Risk Factors for Development of Stoma Related Complications in Patient with Anorectal Malformation

necrosis, mislocation, parastomal hernia. Prolapse is a common complication with some potential consequences that are mostly preventable. ABSTRACT: BACKGROUND : Colostomy in patient with ARM has complications. There are some risk factors have impact on complications development. OBJECTIVE : Predict risk factors for development of stoma complications in ARM patients. METHODS : A prospective study conducted on neonates and infants with ARM who underwent colostomy at the department of pediatric surgery - central Child Teaching Hospital/Baghdad-Iraq from January/2019 till January/2021, searching for stoma complications and evaluating the effect of several variables on stoma morbidity. RESULTS :
Learning Dark Matter Representation From Strong Lensing Images Through Self-Supervision

Gravitational lensing is one of the most important probes of dark matter and has recently seen a surge in applications of machine learning techniques. This is typically studied in the context of supervised learning, but given the upcoming influx of gravitational lensing data from Euclid and LSST, manual labeling for deep learning tasks has become an unsustainable approach. To address this challenge, self-supervised learning (SSL) emerges as a scalable solution. By leveraging unlabeled strong lensing data to learn feature representations, self-supervised models have the potential to enhance our understanding of dark matter via the effect of its substructure in strong lensing images. This work implements contrastive learning, Bootstrap Your Own Latent (BYOL), Simple Siamese (SimSiam), and self-distillation with no labels (DINO) using ResNet50 and Vision Transformer (ViT) networks, to acquire unsupervised embeddings for strong lensing images simulated for different dark matter models: ultra-light axions, cold dark matter, and halos without substructure. The learned representations of the encoder are fine-tuned using supervision and applied to classification and regression tasks which are also benchmarked against a fully supervised, ResNet50 baseline. Our results show that the self-supervised methods can consistently outperform their supervised counterparts.
Unifying Local and Global Knowledge: Empowering Large Language Models as Political Experts with Knowledge Graphs

Large Language Models (LLMs) have revolutionized solutions for general natural language processing (NLP) tasks. However, deploying these models in specific domains still faces challenges like hallucination. While existing knowledge graph retrieval-based approaches offer partial solutions, they cannot be well adapted to the political domain. On one hand, existing generic knowledge graphs lack vital political context, hindering deductions for practical tasks. On the other hand, the nature of political questions often renders the direct facts elusive, necessitating deeper aggregation and comprehension of retrieved evidence. To address these challenges, we propose a P olitical E xperts through Knowledge G raph Integration ( PEG ) framework. PEG entails the creation and utilization of a multi-view political knowledge graph (MVPKG), which integrates U.S. legislative, election, and diplomatic data, as well as conceptual knowledge from Wikidata. With MVPKG as its foundation, PEG enhances existing methods through knowledge acquisition, aggregation, and injection. This process begins with refining evidence through semantic filtering, followed by its aggregation into global knowledge via implicit or explicit methods. The integrated knowledge is then utilized by LLMs through prompts. Experiments on three real-world datasets across diverse LLMs confirm PEG’s superiority in tackling political modeling tasks.
Influence of Perceived Clinical Supervision of Student Nurses on Influence of Perceived Clinical Supervision of Student Nurses on their Burnout Experience their Burnout Experience

Purpose : The study aimed to investigate the in ﬂ uence of perceived clinical supervision of student nurses on their burnout experience. Method : This study is a descriptive cross-sectional design. A total of 389 nursing students participated in the convenience sampling study. The study was conducted online from March 2021 to July 2021. The study used the clinical supervision Evaluation Questionnaire and Maslach Burnout Inventory e Student Survey adopted in China. A regression analysis was used to determine the predictors and in ﬂ uence of clinical supervision on the burnout experience among student nurses. Results : Nursing students achieved a high mean on the clinical supervision purpose subscale. Student nurses had high cynicism, emotional exhaustion, and lower academic ef ﬁ cacy mean scores. Personal factors and process dimensions of clinical supervision in ﬂ uenced the burnout experience of nursing students. Discussion : The study shows that clinical supervision decreases burnout based on cross-country comparisons.
WIP: Towards Practical LiDAR Spoofing Attack against Vehicles Driving at Cruising Speeds

—LiDAR (Light Detection and Ranging) is an essential sensor for autonomous driving (AD), increasingly being integrated not only in prototype vehicles but also in commodity vehicles. Due to its critical safety implications, recent studies have explored its security risks and exposed the potential vulnerability against LiDAR spoofing attacks, which manipulate measurement data by emitting malicious lasers into the LiDAR. Nevertheless, deploying LiDAR spoofing attacks against driving AD vehicles still has significant technical challenges particularly in accurately aiming at the LiDAR of a moving AV from the roadside. The current state-of-the-art attack can be successful only at ≤ 5 km/h. Motivated by this, we design novel tracking and aiming methodology and conduct a feasibility study to explore the actual practicality of LiDAR spoofing attacks against AD vehicles at cruising speeds. In this work, we report our initial results demonstrating that our object removal attack successfully makes the targeted pedestrian undetectable with ≥ 90% success rates in a real-world scenario where the adversary at the roadside attacks the victim AD approaching at 35 km/h. Finally, we discuss the current challenges and our future plans.
Effect of Harvesting and Non-Harvested Forest Management on Carbon Stocks

Forest management is an important strategy which can significantly contribute to climate change mitigation through appropriate care of forest resources. This study was carried out to evaluate two systems of carbon stock accumulation; a harvested forest verses a non-harvested forest. Both the above-ground and below-ground cabon stocks were assessed. Biomass of standing trees, poles and ground vegetation was measured for carbon determination in defined areas using an allometric relationship. Soil (core and composite) samples were collected from 0 –20, 20 – 40 cm and below 40 cm depths, assessed for density, carbon concentration, and profiles C-stocks were estimated. ANOVA and t-tests were performed to compare the effects of forest management on total carbon stocks. The results showed that the total above ground timber carbon (AGTC) was higher in non-harvested forest (220±154 t/ha–1) than in harvested forest (128.6±86.1 t/ha-1). The overall mean carbon stock was higher in the non-harvested forest (357±179) than in the harvested forest (257.4±93.1), which was statistically significant (p=0.031, >0.05). However, the soil organic carbon (SOC) pool was observed to be higher in the harvested forest (101.5±36.1) than in non-harvested forest (89.6±26.5).