bluuebunny/crossref_metadata_2025 huggingface dataset:
KDM1A represses the apoptosis in osteosarcoma cells via demethylating Bcl-2/c-Myc
Authors: Zhao Xuezheng , Li Lijun , Zheng Sihua , Tang Baoyong , Zhang Yebing , Gao Wei
Published: August 2023

Introduction

Background: Considering the poorly understood mechanism of lysine demethylase 1A (KDM1A) in osteosarcoma (OS), we here commence our investigation to fill the blank.

Material and methods

Methods: Following the transfection as appropriate, 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) and flow cytometry assays were used to determine the viability and apoptosis of OS cells MG-63, in which the generation of reactive oxygen species (ROS) and the binding between KDM1A and Bcl-2/ cellular Myc (c-Myc) were separately confirmed via DCF-DA method and chromatin immunoprecipitation-PCR. Reverse-transcription quantitative PCR and western blot were finally introduced to quantify the levels of KDM1A/Bcl-2/c-Myc and endoplasmic reticulum (ER) stress-related factors.

Results

Results: Overexpressed KDM1A enhanced the viability (48 hours) yet repressed the apoptosis and ROS generation, with the downregulation on ER stress-related factors (C/EBP homologous protein [CHOP]; proline-rich extensin-like receptor kinase (PERK) and activating transcription factor 4 [ATF4]) yet the elevation of Bcl-2/c-Myc, while its depletion exerted contrary effects. More importantly, KDM1A could act as the demethylase of Bcl-2/c-Myc, as reflected by the results that the depletion of KDM1A decreased the enrichment of Bcl-2/c-Myc promoter using the antibody against KDM1A yet increased the enrichment by the antibody targeting H3K9me2. Bcl-2/c-Myc silencing, conversely, promoted the ROS generation and apoptosis, elevated the levels of ER stress-related factors and abolished the effects of KDM1A on OS cells.

Conclusions

Conclusion: KDM1A exerts a repressive effect on the apoptosis of OS cells MG-63 by inhibiting the ROS generation and ER stress via demethylation of Bcl-2 and c-Myc.
Melatonin Enhances the Viability of Random-Pattern Skin Flaps by Activating the NRF2 pathway
Authors: Shen Zhihao , Miao Keze , Zhang Xue , Wu Feng , Zheng Wenhao , Cai Leyi
Published: August 2023

Introduction

Random skin flap transplantation has been widely used in reconstructive and plastic surgery. As a well-known antioxidant, melatonin has the functions of eliminating reactive oxygen species (ROS), promoting angiogenesis, and protecting ischemia-reperfusion injury (IRI). We explored the effects of melatonin on random skin flap survival and the potential molecular mechanisms.

Material and methods

A total of 72 rats were randomly assigned to the control group, the melatonin (MEL) group, and MEL + ML385 groups. After the construction of random skin flap model, these groups were treated with physiological saline, melatonin, and melatonin + ML385. The general conditions of random skin flaps were observed daily after the procedure. Laser doppler blood flow imaging was used to evaluate the subcutaneous vascular network. On postoperative day 7, the animals were euthanized to obtain flap specimens. Hematoxylin-Eosin staining was used to evaluate the vessel density. Immunohistochemistry, immunofluorescence staining, and western blotting were used to evaluate the expression of proteins involved in angiogenesis, oxidative stress, and inflammation.

Results

Compared to the control group, the MEL group exhibited lower tissue water, more abundant vascular, and higher vascular density, thereby enhancing the survival of random flaps. Additionally, the MEL group showed increased expression of angiogenesis-related proteins, enhanced expression of antioxidant proteins, and decreased expression of inflammatory factors. Furthermore, ML385, reversed the beneficial effect of melatonin on random skin flaps.

Conclusions

These findings of our present study demonstrated that melatonin promotes angiogenesis, inhibits oxidative stress, and inflammation by activating NRF2 signaling pathway, thus the improving the survival of random skin flaps.
Penerapan Model Direct Intruction terhadap Hasil Belajar Peserta Didik Pada Materi Bulu Tangkis Kelas X di SMA Negeri 2 Peusangan
Authors: Mirza Mirza
Published: August 2023

Penelitian ini bertujuan untuk mengetahui pengaruh penerapan model Direct Intruction terhadap hasil belajar peserta didik pada materi bulu tangkis kelas X di SMA Negeri 2 Peusangan. Pengumpulan data dilakukan pada 12 s/d 14 2022. Metode yang digunakan dalam penelitian ini adalah metode eksperimen dengan rancangan pretest posttest control design. Penelitian ini dilaksanakan di SMA Negeri 2 peusangan dengan sampel penelitian berjumlah 146 peserta didik. Analisis data menggunakan uji normalitas, homogenitas, dan uji t dengan bantuan Exel 2007 pada taraf signifikan 0,05. Hasil penelitian menunjukkan Dari hasil penelitian tersebut diperoleh hasil t hitung > t table (4,08 > 2,00) dengan menggunakan taraf signifikansi 0,05, sehingga disimpulkan model Direct Intruction berpengaruh terhadap hasil belajar peserta didik kelas X pada materi bulu tangkis di SMA Negeri 2 Peusangan.
Code Generation based on Controlled Natural Language Input
Authors: Dittmer Howard , Jia Xiaoping
Published: August 2023

Over time the level of abstraction embodied in programming languages has continued to grow. However, most programming languages still require programmers to conform to rigid constructs. These constructs have been implemented in the name of efficiency for the computer. The continual increase in computing power allows us to consider techniques not so limited. To this end, we have created CABERNET, a Controlled Natural Language (CNL) based approach to program creation. CABERNET allows programmers to use an outline-based syntax. Using heuristics and inference to analyze and determine the programmer’s intent, this tool chain can create mobile applications. Using templates, a CABERNET application can be processed to run on multiple run-time environments. Since processing a CABERNET program file results in a native application, performance is maintained. In this paper, we compared sample applications created in Swift, SwiftUI, and CABERNET. The CABERNET implementations were consistently shorter than those produced in the other two languages. In addition, users surveyed consistently found CABERNET easier to understand
FROM RESEARCH TO PRACTICE: DOES AI PROMOTE OR PREVENT THE USE OF AN MBSE TOOL?
Authors: Charfi Asma , Kochbati Takwa , Mraidha Chokri
Published: August 2023

In this paper, we will investigate the role that can play the AI in adopting a Model Based System-Engineering (MBSE) tool. The MBSE approach is widely adopted in the development of complex systems (real time systems, cyber physical systems, system of systems, etc.) however, in the practice, the tools implementing this approach are facing several problems and are far from being adopted by system provider. We contend that the integration of AI into the appropriate MBSE phase can yield advantageous outcomes. Furthermore, we propose that further exploration into the implementation of AI techniques (such as Machine Learning and NLP) in MBSE tools is necessary to align with the requirements of stakeholders
PROPAGATION OF SOFTWARE REQUIREMENTS TO EXECUTABLE TESTS
Authors: Kesserwan Nader , Al-Jaroodi Jameela , Mohamed Nader , Jawha Imad
Published: August 2023

Executable test cases start at the beginning of testing as abstract requirements representing the system behavior. The manual development of these test cases is labor-intensive, error-prone, and costly. Describing the system requirements into behavioral models and transforming them into a scripting language has the potential to automate their propagation to executable tests. Ideally, an efficient testing process should begin as early as possible, refine the use cases with sufficient details and facilitate test case creation. We propose an approach that enables automation in propagating functional requirements to executable test cases through model transformation. The proposed testing process begins with capturing system behavior as visual use cases, adopting a domain-specific language, defining transformation rules, and finally transforming the use cases into executable tests.
Requirements Engineering Framework using Contextualization, Profiling, and Modelling
Authors: Khannur Arunkumar , Hiremath Manjunatha
Published: August 2023

The proposed Requirements Engineering Framework (REF) is novel and efficacious in producing quality Requirements Specifications. The framework is based on the principles of design thinking that include empathy; system visualization to understand the system, its components, and the pattern of their interactions; and observing the possible behavior under different contexts and situations. The proposed framework includes requirement elicitation, requirement understanding, defining requirement goals, requirement profiling, requirement contextualization, and requirements modeling. All these are carried out by keeping ISO 25000 standards for software engineering at the core. The proposed REF will be impactful in implementing modern-day projects which are disruptive and becoming more and more context-aware systems because of machine/ deep learning, data engineering to deal with structured and unstructured data, sensor technologies, interactive technologies, 5G technologies, and control-related technologies. The framework also will address the limitations of CMM-based or agile-based approaches.
Authentication Technique based on Image Recognition: Example of Quantitative Evaluation by Probabilistic Model Checker
Authors: Nokovic Bojan
Published: August 2023

A probabilistic model checker is a software tool for formal modeling and analysis of systems that exhibit random or probabilistic behaviour. Over probabilistic models, we analyze an innovative online authentication process based on image recognition. For true positive identification, the user needs to recognize the relationship between identified objects on distinct images which we call an outer relation, and the relation between objects in the same image which we call an inner relation. We use probabilistic computational tree logic formulas (PCTL) to quantify false-negative detection and analyze the proposed authentication process. That helps to tune up the process and make it more convenient for the user while maintaining the integrity of the authentication process.
Optimizing Estimation Accuracy: Leveraging the Winner-Takes-All Approach
Authors: Wu FuChe , Dellinger Andrew
Published: August 2023

This paper proposes an algorithm for improving estimation accuracy in industrial applications. Traditionally, a weighted sum method is used to map two views, but this approach often leads to blurry results. Instead, the winner-take-all approach is suggested as a means of achieving better accuracy. Three criteria are introduced for evaluating image quality, including sharpness (which measures the effect of motion artifacts from the RGB camera), flatness (which estimates the number of parts in the depth image that belong to plane parts), and fitness (which checks the match between the current view and existing map). While depth images provide 3D structure of the environment, they typically lack sufficient resolution to deliver accurate results. However, by estimating a plane, accuracy can be improved and a more precise boundary can be obtained from the higher resolution of the RGB image.
Neural Networks
Authors: Chandrasekaran Arvind
Published: August 2023

The neural networks review the categories, explaining the organization algorithm techniques required to improve the generalization performance and the Feedforward Neural Network (FNN) learning speed. They are needed to discover the research trends changes under the six categories of the optimization algorithms for the learning rate, learning algorithms which are gradient-free. Metaheuristic algorithms collectively and new research directions are recommended for the researchers to facilitate the algorithm's understanding of the natural world applications to solve the complex engineering, management, and problems in the health sciences. FNN gained research attention for making an informed decision. The literature survey focuses on optimization technology and learning algorithms. The optimization techniques and the FNN learning algorithms identified are segregated into six categories based on the mathematical model, problem identification, proposed solution, and technical reasoning. FNN contributions rapidly increase the ability to make informed decisions reliably.
Improved Student Learning Experience in Large Programming Classes Using Pseudo-Flipped Method
Authors: Chaturvedi Ritu
Published: August 2023

In an effort to improve student engagement in large programming classes, this study proposes a pseudo-flipped (PF) method of teaching that combines the core principles of two popular teaching methods, traditional and flipped (or inverted), thereby mitigating the drawbacks of these methods. In traditional teaching, class time is mostly used by instructors to teach a class using pre-prepared lecture slides and smartboards or similar alternatives, whereas students, mostly passively, listen to the lecture and take notes. In a purely flipped class, all resources traditionally taught in classroom are moved outside the classroom, either as text, video, audio, students are expected to read or view lectures before class, and the instructor uses class time in solving problems. In the proposed PF method, students are taught in a traditional way for half the allocated time. For the other half, students solve problems in class with the instructorÃ¢â‚¬â„¢s assistance. Similar to the flipped method, in PF, students learn concepts on their own outside the classroom using an interactive textbook. To fill gaps in their knowledge, instructors spend time teaching those core concepts in class by solving problems. PF promotes active learning by engaging students towards solving problems on learnt concepts. A survey is done in a programming class to find student opinion on how useful this pseudo-flipped method is on student engagement as opposed to traditional teaching. Both quantitative and qualitative analysis of the survey responses strongly favour the proposed method, with more than 70% of students in favour of it.
A Novel Framework for Privacy-Preserving Data Publishing with Multiple Sensitive Attributes
Authors: Al-Otaibi Saud , Al-Qurashi lujain
Published: August 2023

The world is now experiencing a great technological revolution, as many fields have become dependent on it. The use of technology by members of society has become daily. Data is collected on individuals by using smart technology applications in hospitals or companies. These organizations are managed through databases that record data about their customers. The collected data may include sensitive data (e.g., personal data) that individuals do not want to disclose. In order to continue development , we sometimes need to publish this data for the purposes of research, statistical studies or decision-making. The publication of this data constitutes a threat to the privacy of the customer as it can be exploited by the intruder. This research focuses on trying to provide Privacy-Preserving Data Publishing algorithm that preserves customer privacy with the possibility of publishing this data with less information loss.
Professional Certification Benchmark Dataset: The First 500 Jobs for Large Language Models
Authors: Noever David , Ciolino Matt
Published: August 2023

The research creates a professional certification survey to test large language models and evaluate their employable skills. It compares the performance of two AI models, GPT-3 and Turbo-GPT3.5, on a benchmark dataset of 1149 professional certifications, emphasizing vocational readiness rather than academic performance. GPT-3 achieved a passing score (>70% correct) in 39% of the professional certifications without fine-tuning or exam preparation. The models demonstrated qualifications in various computer-related fields, such as cloud and virtualization, business analytics, cybersecurity, network setup and repair, and data analytics. Turbo-GPT3.5 scored 100% on the valuable Offensive Security Certified Professional (OSCP) exam. The models also displayed competence in other professional domains, including nursing, licensed counseling, pharmacy, and teaching. Turbo-GPT3.5 passed the Financial Industry Regulatory Authority (FINRA) Series 6 exam with a 70% grade without preparation. Interestingly, Turbo-GPT3.5 performed well on customer service tasks, suggesting potential applications in human augmentation for chatbots in call centers and routine advice services. The models also score well on sensory and experience-based tests such as wine sommelier, beer taster, emotional quotient, and body language reader. The OpenAI model improvement from Babbage to Turbo resulted in a median 60% better-graded performance in less than a few years. This progress suggests that focusing on the latest model's shortcomings could lead to a highly performant AI capable of mastering the most demanding professional certifications. We open-source the benchmark to expand the range of testable professional skills as the models improve or gain emergent capabilities.
Timor-Leste's Mikrolet Vehicle Multi-Class Classification Performance Evaluation Using Deep Learning Models
Authors: Boavida Abreu Andre
Published: August 2023

This research uses a multiclass deep learning model to identify images containing different mikrolet vehicles. In addition, we have studied multiclass classification research by assessing the performance of mikroletpictures with the same color and comparing the classification performance of several proposed deep learning models. The objectives of this study are two-fold: first, to identify images containing different mikrolet vehicle lanes, and second, compare four deep learning models for evaluation of the accuracy of performance precision, recall, f1-measure, micro and macro average ROC curves areas.
A Deep Learning System for Domain-Specific Speech Recognition
Authors: Jia Yanan
Published: August 2023

As human-machine voice interfaces provide easy access to increasingly intelligent machines, many state-of-theart automatic speech recognition (ASR) systems are proposed. However, commercial ASR systems usually have poor performance on domain-specific speech especially under low-resource settings. The author works with pre-trained DeepSpeech2 and Wav2Vec2 acoustic models to develop benefit-specific ASR systems. The domainspecific data are collected using proposed semi-supervised learning annotation with little human intervention. The best performance comes from a fine-tuned Wav2Vec2-Large-LV60 acoustic model with an external KenLM, which surpasses the Google and AWS ASR systems on benefit-specific speech. The viability of using error prone ASR transcriptions as part of spoken language understanding (SLU) is also investigated. Results of a benefit-specific natural language understanding (NLU) task show that the domain-specific fine-tuned ASR system can outperform the commercial ASR systems even when its transcriptions have higher word error rate (WER), and the results between fine-tuned ASR and human transcriptions are similar
GPT-3 Models are Few-Shot Financial Reasoners
Authors: Padua Raul Salles de , Qureshi Imran , U. Karakaplan Mustafa
Published: August 2023

Financial analysis is an important tool for evaluating company performance. Practitioners work to answer financial questions to make profitable investment decisions, and use advanced quantitative analyses to do so. As a result, Financial Question Answering (QA) is a question answering task that requires deep reasoning about numbers. Furthermore, it is unknown how well pre-trained language models can reason in the financial domain. The current state-of-the-art requires a retriever to collect relevant facts about the financial question from the text and a generator to produce a valid financial program and a final answer. However, recently large language models like GPT-3 [1] have achieved state-of-the-art performance on wide variety of tasks with just a few shot examples. We run several experiments with GPT-3 and find that a separate retrieval model and logic engine continue to be essential components to achieving SOTA performance in this task, particularly due to the precise nature of financial questions and the complex information stored in financial documents. With this understanding, our refined promptengineering approach on GPT-3 achieves near SOTA accuracy without any fine-tuning.
Automatic Discovery of Multiword Nouns Based on Syntactic-Semantic Representations
Authors: Hu Xiaoqin
Published: August 2023

This research aims to explore a deeper representation of the internal structure and semantic relationship of multiword nouns (MWNs) for improving MWN discovery. This representation focuses on MWN formations, which follow a series of categorical and semantic constraints. Linguistically motivated semantic features are defined by computing the internal semantic relations of MWNs. The internal structures are represented by describing categorical combinations in a hierarchy, and the internal semantic relations are represented with the help of semantic combinations of constituents. The results show that combining linguistically motivated semantic features with statistically motivated semantic features improves MWN discovery.
Identifying the Bank Personnel involved in Fraudulent Activities
Authors: Duman Ekrem
Published: August 2023

Binary classification is about predicting which one of the two class values if more likely for a given instance. To learn such a model it is important to have enough number of examples from both class values. When this is not the case, which is known to be class imbalance problem, building strong predictive models becomes a very challenging task. In this study we pick up one such problem: predicting the bank personnel which might commit fraud (stealing money from customer accounts). For this problem, in order to have a strong enough predictive model, we decided to combine the powers of descriptive and predictive modeling techniques where we developed several descriptive models and used them as an input of a predictive model at the last stage. The results show that our solution approach perform quite well.
A Crowdsourcing-Based Analytical Engine for Virus and Malware Detection using Artificial Intelligenceand Machine Learning
Authors: Zhang Zonglin , Chang Marisabel
Published: August 2023

In recent years, cybersecurity has grown increasingly salient in people's lives [8]. With the spread of various newmalware, the security risks of executable network installation packages are dramatically increasing, so problemspersist, rising with the growth of web users. This research work, aimed at a Crowdsourcing-based Analytical Engine for Virus and Malware Detection, prevents malware by examining MS Windows Portable Executable (PE) headers. YARA, a database from Kaggle, and data extracted from actual malware files were combined to createafinal dataset [9]. Comparing each section of the PE header to improve the detection accuracy, the final absoluteaccuracy is between 98% and 99%, and the front end displays the final prediction results through PythonGUI.
Examining Accuracy Heterogeneities in Classification of Multilingual
Authors: Subramaniam Raghav
Published: August 2023

Tools for detection of AI-generated texts are used globally, however, the nature of the apparent accuracy disparities between languages must be further observed. This paper aims to examine the nature of these differences through testing OpenAIâ€™s â€œAI Text Classifierâ€ on a set of various AI and human-generated texts in English, Swahili, German, Arabic, Chinese, and Hindi. Current tools for detecting AI-generated text are already fairly easy to discredit, as misclassifications have shown to be fairly common, but such vulnerabilities often persist in slightly different ways when non-English languages are observed: classification of human-written text as AI-generated and vice versa could occur more frequently in specific language environments than others. Our findings indicate that false positives are more likely to occur in Hindi and Arabic, whereas false negative labelings are more likely to occur in English. Other languages tested had a tendency to not be confidently labeled at all.
Pengaruh Program Darsul Iḍāf Terhadap Mahāratul Qira'ah Mahasiswi Intensif Semester 1 IDIA Prenduan 2021/2022
Authors: Asmania  , Aniq Rasida
Published: August 2023

The Darsul Iḍāf program is a language program that has been running for a long time at IDIA Prenduan Sumenep Madura, adapted to the needs of students at the highest level, namely being able to read Arabic texts as stipulated by boarding school. The researchers focused on Mahāratul Qira'ah (reading skills). In this case, we need to know whether the Darsul Iḍāf program has had an impact on intensive Mahāratul Qira'ah second semester IDIA Prenduan for the 2021-2022 academic year. This type of research is quantitative research using simple linear regression with a total of 71 populations as respondents who use observation, questionnaires, and tests as data collection. Linear regression Ha = there is a significant effect between variable X (Darsul Iḍāf program) and Y variable (Mahāratul Qira'ah) while Ho = there is no significant effect between variable X (Darsul Iḍāf program) and variable Y (Mahāratul Qira'ah) . From the results of research with the help of SPSS 22 software. The effect of the Darsul Iḍāf  program on Mahāratul Qira'ah intensive 1st semester students of IDIA Prenduan Sumenep Madura 2021-2022 can be seen from the coefficient of determination with a total R square of 0.028 which indicates that the Darsul Iḍāf program has a very large influence weak, namely 28% with conclusions not reaching linearity and can be said to be very low.
Ta’ṡīru Kitāb al-Syāmil Fī Mahārāti al-Qirā’ah ladā al-Ṭulabi al-Mukaṡṡafi bi al-Jāmiʻah Al-Āmīn Al-Islāmiyyah Prenduan Sumenep Madura
Authors: Mahrus  , Saiful Anam
Published: August 2023

Both modern and Salafi Islamic boarding schools. Almost all boarding activities use the Arabic language, and every Islamic boarding school cannot be separated from learning the Yellow Book using the rules of grammar and morphology, all of which are inseparable from the Arabic language. To facilitate students' learning of the Arabic language, Kiahi Bastami Tebyan Master, wrote a book titled Kitab Al-Syamil. As a guide or an easy way for students to learn Arabic. This study investigates how learning the Book of Fasting affects reading skills of the Yellow Book. The purpose of this research is to find out the method of implementing the learning of the book Al-Syamil in reading the yellow book, and to know the factors of the extent of the effectiveness of the book Al-Samail in reading the yellow book. In this study using the quantitative research method, since this research is a type of quantitative research, the variables involved in this research are the X variable and the Y variable, for the X variable here, which is “the effect of learning a comprehensive book, while the Y variable is the ability to read the book As for the results of this study, the researchers found that there was an additional agenda for the students at the Institute of Al-Ameen Islamic University, which included learning about the basic rules of syntax and morphology.The first semester of the Idea Brendawan Institute.
Al-Anāşir al-Adabiyah fῑ al-Qişşah al-Qaşῑrah “Wa Kānat al-Dunya” lῑ Taufῑq al-Hākim: Dirāsah al-Nażariyah al-Bunyawiyah lῑ Aḥmad Al-Syā’ib
Authors: Rania Khoiru Nisa  , Abdul Latif
Published: August 2023

This study aims to determine the intrinsic elements such as Aṭifah, Khayāl, Fikrah, and Şūrah using Ahmad al- Al-Syā’ib 's structuralism theory in the short story Wa Kānat al-Dunya by Taufik Al-Hakim. The type of research used is a qualitative approach. The qualitative type used is descriptive qualitative with data collection methods, namely research through short story texts. The data sources in this study are primary and secondary data sources such as analyzing the data obtained, namely short stories, discussing the problems obtained in the short stories and applying them to the problems to be discussed. Drawing conclusions from the results of the study, the results obtained are that Aṭifah has five parts, namely suduq al-aṭifah ’emotional authenticity’, quwwatu al-aṭifah ‘emotional strength’, sabat al-aṭifah ‘emotional toughness’, tanawwu’u al-aṭifah ‘emotional diversity’ and sumuw al-aṭifah ‘emotional level’. Khayāl, has three parts namely Ibtikāri ’Innovative’, Ta'lifi ’compositional’, and Bayāni ’graphic’. Fikrah  type Sihah Al-Afkār ‘correct thinking’ and Şūrah there are three parts namely al-wuduh ’ clarity’, al-quwwah ‘strength’, and al-jamal ‘beauty’.
Ta’śīru Niẓāmi al-Luġati fī Mahārati al-Kalām al-ʿArabī ladā Talāmīżi al Madrasati al-Mutawassiṭati
Authors: Sufandi  , Yakin Ainul
Published: August 2023

Discipline is something that can provide therapy through existing rules for students, especially in terms of developing language skills. From their activities, it is hoped that later they will feel motivated to continuously grow, learn to speak and be independent. Finally, there will be awareness of them, In this study, we want to describe whether there is an influence of language discipline on students' Arabic speaking skills at MTs. Nurulhuda Pakandangan Barat Kec. Bluto Kab. Sumenep and how much influence Language Discipline has on students' Arabic speaking skills at MTs. Nurulhuda Pakandangan Barat Kec. Bluto Kab. Sumenep. The research used correlational quantitative research with the number of students at MTs Nurulhuda Pandandang Kec. Bluto Kab. Sumenep 80 students. In an effort to obtain, explore and collect the data needed in the process of presenting and analyzing accurate data, the authors use questionnaires, tests, and documentation. The data analysis used in this study is the Product Moment statistical analysis technique. The results of the research can be concluded that there is an influence of language discipline on students' Arabic speaking skills at MTs. Nurulhuda Pakandangan Barat Kec. Bluto Kab. Sumenep. This can be proven by looking at the critical price table of r product moment with N = 80 with a significance level of 95% = 0.213 and a significance level of 99% = 0.278, it turns out that r work (0.636), is greater than the value of the critical price either at the significant level 95% and 99% and from the calculation results in it can also be concluded that the students' Arabic speaking skills at MTs. Nurulhuda Pakandangan Barat Kec. Bluto Kab. Sumenep is determined or influenced by language discipline by 40.45% while the remaining 59.55% is determined by other factors.
Al-Istirātījyyat fī Takwīn al-Bī’ah al-Luġawiyyah li Rafʿi Qudrah al-Țalabah ʿalā Mahārah al-Kalām al-ʿArabī
Authors: Izzat Amini  , Mohammad Arif Nurmuzib
Published: August 2023

The purpose of this study is to understand the strategies strategy of creating the language environment to raise the ability of students to speak and know how the language environment affects the Arabic language skills. This study adopts qualitative research methods and collects data in the form of interviews, observations and documents. The data analysis method used by researchers in the research is to analyze nonverbal data to verify the effectiveness of the data used by researchers. These data are undoubtedly original, and are widely used for participation, persistence, observation and triangulation. As for the results of this study, As for the strategy in creating the language environment in all institutes, it is to find a program that is implemented continuously every day, week, monthly or yearly. From a procedural point of view, the language center of the institution coordinates the language centers in all the institutes. As for the effect of the formation of the linguistic environment, it is that the students in the Islamic Teacher Education and the Arabic Language Tahfi Institute for the Qur'an are able to communicate. The language center has special goals, which are to make students fluent in speaking the Arabic language.
Development of antigen-capture ELISA using monoclonal antibodies for the detection of brucellae in milk
Authors: Gürbilek S. E. , Keskin O. , Tel O. Y.
Published: August 2023

In this study, a Brucella antigen-capture ELISA (Ag-cELISA) prototype was developed. To study the validity of the developed Ag-cELISA, milk samples collected from Brucella-positive goats (n=120) and cattle (n= 64), as well as from unknown Brucella-status cattle (n=105) and sheep (n=65) herds were tested by Ag-cELISA, I-ELISA, and culture method. All Brucella-positive samples were confirmed using PCR. It was found that the developed Ag-cELISA could detect 50-100 bacteria per well (equivalent to 103 to 2×103 cells per mL) as the lowest limit of detection (LOD) and was therefore considered moderately sensitive to detect brucellae in milk. In an infected goat herd, out of 120 milk samples, 41, 32, and 17 were positive by Ag-cELISA, I-ELISA, and culture, respectively. Ag-cELISA detected 15 positive cases out of 17 culture-positive milk samples. Two culture-positive milk samples were not detected in Ag-cELISA. The relative sensitivity and specificity between Ag-cELISA and I-ELISA were 78% and 100%, respectively. In an infected cow herd, out of 64 milk samples, 32, 23, and 11 were found positive by Ag-cELISA, I-ELISA, and culture, respectively. Ten out of 11 culturally positive milk samples were found positive by Ag-cELISA. The relative sensitivity and specificity between the Ag-cELISA and I-ELISA were 71.9% and 100%, respectively. From randomly collected 105 cow and 110 sheep milk samples from herds of unknown Brucella-infection status, three (2.85%) and five (4.5%) samples were found positive using Ag-cELISA, respectively. These results showed that Ag-cELISA could be used to detect brucellae in milk more practically and safely than bacterial culture. On the other hand, this information re-affirms that milk can be an important source of brucellosis and creates a public health risk in humans; therefore, increased public awareness is of utmost importance.
EARNINGS MANAGEMENTAND DIVIDEND POLICY OF LISTED COMMERCIAL BANKS IN NIGERIA
Authors: Mopho, July Philip (Ph.D. Candidate)  , Prof. A. O. OKOLIE (Ph.D.)
Published: August 2023

The aim of this study is to examine the association between dividend policy and earnings management of listed commercial banks in Nigeria. The study adopted ex-post-facto research design and stratified random sampling technique to select all commercial banks quoted on the Nigerian Exchange Group that span from 2013 to 2022 financial years. Secondary data were extracted from the annual reports of the commercial banks in Nigeria. The collected data were analyzed using descriptive statistics, correlation analysis, and multivariate regressions analysis. The results revealed that, earnings per share have a coefficient value of -0.03 and probability value of 0.006 indicating that Earnings per share has inverse significant effect on accrual earnings management at 1% level and a coefficient value of -0.007 and p- value of 0.025 indicating a corresponding inverse significant effect on real earnings management of the commercial banks in Nigeria. Again Price earnings ratio has coefficient value of-0.008 and p- value of 0.114 indicating an inverse significant effect on accrual earnings management but has coefficient value of 0.003 and p-value of 0.219 indicating a positive significant effect on real earnings management. Also dividend yield has coefficient value of 0.018 and p-value 0f 0.001 indicating that dividend yield has statistical significant effect on both accrual earnings and real earnings management of the commercial banks studied. The study recommends amongst others that commercial banks should   engage the chief executive officers that are goal getters to enhance the operating profitability of the banks, which would play down on the quest to make up their deficiencies through earnings manipulations. Pertinently, the commercial banks are also encouraged to ensure regular payment of dividend to shareholders which will motivates other investors rather than opportunistic behaviors and manipulations through earnings management.

Keywords: Earnings Management, Dividend Policy, Commercial Banks, Nigeria.
The Prevalence of Visual Acuity Impairment among Children in Nigeria – A Systematic Review
Authors: Nasiru Kangiwa , Basiru Shuaibu , Buhari Aliyu , Isiyaku Gwarzo , Kabiru Ladan , Shahzad Ahmad , Kamaldeen Sanusi , Kasimu Ibrahim , Murtala Abubakar
Published: August 2023

Background: Blindness is a major health problem, and there is an increasing trend of visual acuity impairment among children in developing countries. Vision loss in childhood has serious implications in all stages of a child's growth and development. It poses social, educational and occupational challenges, with affected children being at greater risk of developing behavioural, psychological and emotional problems, lower self-esteem and poorer social integration. The study aimed to assess the prevalence of visual impairment among children in Nigeria. Method: A systematic review of papers published on the prevalence of visual acuity impairment among children in the country was carried out. We covered works published in Google Scholar, PubMed, ResearchGate, ScienceDirect, and African Journals Online. Primary search terms included the combination of the following keywords; “prevalence”, “visual acuity”, “visual impairment”, “children”, “Nigeria”. The database search for published articles was done without date restriction till 1st December 2021. The review was restricted to primary research published in English and peer-reviewed journals. Results: Fourteen studies met the inclusion criteria out of the 56 studies reviewed. In Nigeria, the prevalence of visual acuity impairments ranged from 1.7% to 26.1%. Conclusion: The prevalence of visual acuity impairment among children in Nigeria is in epidemic proportions. There is a need to pay attention to proper health education; early detection and appropriate management of impaired vision to fight against this health disorder.
Nutritional Status of Under-five Children in Sokoto, Nigeria
Authors: Jiya Fatima , Mohammad Ango , Adamu Isah , Tukur Umar , Auwal Usman , Muhammad Bello , Adamu Asma'u , Isezuo Khadijat
Published: August 2023

Background: Malnutrition is the largest risk factor in the world for disability and premature mortality among young children, especially in developing countries. A myriad of socio-economic, cultural, and environmental factors have been identified to either improve or negatively affect a child's nutritional status. Objectives: To assess the nutritional status of children under-five years of age in Sokoto, Nigeria, and determine the associated factors. Methods: A cross-sectional survey of children aged 6-59 months selected through multistage random sampling. Data was obtained using pretested semi-structured questionnaire and the nutritional indices were determined using WHO anthro v3.2.2. Data was analyzed using SPSS version 25. Results: Subjects comprised a total of 353 children with a mean (±S.D) age of 26.8 ±14.9 months. Majority 214(60.6%) were females. Most 330(93.5%) of the caregivers were married majority 180(51.0%) were of low socio-economic status. Two hundred and two (57.2%) of the under-fives had normal weight for age, 144(40.8%) of them were severely stunted, most 290 (82.2%) of them had normal weight for height, and 199(56.7%) had normal mid upper arm circumference. Mother/caregiver's age (p=0.012), marital status (p= 0.007), and child's immunization status (p=0.015) were associated with weight for age, marital status (p=0.028) was associated with the weight for height/length, Child's age group category (p<0.001), social class (p=0.036), and community setting (p=0.031) were associated with the height for age, Marital status (p=0.025), child's age group category (p<0.001), history of recent illness (p=0.046), and community setting (p<0.001) were associated with the mid-upper arm circumference. Conclusion: Under nutrition was the main form of malnutrition among the under-fives, with severe stunting predominating. The nutritional status were influenced by some maternal or caregivers' socio-demographic factors, as well as inadequate child immunization and treatment of acute illnesses.
Prevalence of Iron Deficiency Anaemia (IDA) among Pregnant Women Attending a Tertiary Health Care Facility in North-eastern Nigeria
Authors: Hadiza Idi , Awwalu Sani , Mamman Aisha , Aliyu Babadoko , Hassan Abdulaziz , Halifa Ibrahim
Published: August 2023

Background: Iron Deficiency Anaemia (IDA) is the most frequent nutritional deficiency in the world and it is most prevalent in African countries including Nigeria. In pregnant women, IDA is associated with high morbidity and mortality. Aim: This study was to determine the prevalence and some associated risk factors for IDA in the third trimester. Materials and methods: This was a cross-sectional descriptive study involving 88 women in the third trimester of pregnancy attending Antenatal Clinic (ANC) of Federal Medical Centre in Nguru, Yobe State, North-East, Nigeria. Complete Blood Count (CBC) and serum ferritin were analysed and relation of serum ferritin with some variables were determined. Results: The mean age, parity, last child birth, haematocrit and ferritin of the study participants were 26.72±6.12years, 3.58±3.43, 1.89`±1.85 years, 32.51±7.41% and 68.87±151.88ng/ml respectively. Overall prevalence of anaemia was 22/88(25%) with the prevalence of iron deficiency (ID) being 53/88(60.2%); 10/88(11.4%) had IDA while ID without anaemia was present in 43/88(48.9%). There were no statistically significant correlations between maternal ferritin levels and age, surprisingly to note that ferritin levels were not significantly associated with parity, LCB and GA. Conclusion: We concluded that there was a high burden of third trimester ID among the study population. Maternal age and other assessed risk factors do not have any relationships with third trimester ferritin levels.
Assessment of Plasma Glucose and Lipid Profile Dysregulation among Patients on Antipsychotics in Sokoto
Authors: Muhammad AbdulRahman , Emordi Emeka , Abdullahi Mainasara , Abdulfatahi Bakare , Jibril El-Bashir , Aminu Bello , Abubakar Fakku , Kasimu Saidu , Aminu Abdullahi , Mohammed Dalili , Nasir Madandola , Modupe Ugege , Makun Babazhitsu
Published: August 2023

Background: Antipsychotic drugs used in the treatment of psychotic disorders have been implicated in negative effects on the blood glucose and lipid profile levels of patients. Methods: We studied the anthropometric parameters and then the plasma glucose and lipid profile levels of one hundred and seventy-two (172) patients between the ages of 18 and 45 years; who are on various oral antipsychotics. Also, forty (40) treatment-naïve psychiatric patients and forty (40) healthy controls were included in the study. The results were analysed using standard methods. Results: The mean plasma glucose level was significantly higher (p<0.05) in psychiatric patients on oral antipsychotic drugs compared to controls. The mean plasma glucose level of treatment-naïve psychiatric patients was also significantly higher (p<0.05) compared to that of healthy controls. Furthermore, there was a significant increase in plasma glucose levels of patients on second-generation antipsychotic drugs compared to those on first-generation antipsychotic drugs. The lipid profile of patients on antipsychotic drugs showed a similar trend. There were significant increases in the plasma levels of Total Cholesterol (TC), Low-Density Lipoprotein (LDL), Triglycerides (TG) and a significant decrease in the plasma level of High-Density. However, the plasma TG levels were significantly higher in the typical antipsychotic drugs group. Lipoprotein (HDL) levels of individuals that were on antipsychotics were significantly decreased when compared to healthy controls Conclusion: The lipid profile and plasma glucose concentration were altered by oral antipsychotic drugs in Sokoto, Nigeria. Therefore, it may be clinically expedient to vigorously assess the plasma glucose and lipid profile levels of all patients that are on oral antipsychotic drugs and interventions planned as appropriate. Keywords: Antipsychotic drugs, lipid profile, glucose, Cholesterol, Lipoprotein
Prevalence of Proteinuria among Type 2 Diabetic Patients Attending Usmanu Danfodiyo University Teaching Hospital, Sokoto, Nigeria
Authors: Muhammad B. AbdulRahman , Saidu Kasimu
Published: August 2023

Background: Diabetes mellitus has been reported to be the primary cause of end-stage renal disease in some Asian and American countries. However, no such data were available among type 2 diabetic patients in North-Western Nigeria. This study was aimed to assess the prevalence and associated risk factors of proteinuria among type- 2 diabetic patients by measuring the total protein-to-creatinine ratio (TPCR) and to provide some possible recommendations to enhance the level of health care rendered to the patients. Methods: This was a cross-sectional study. Spot urine TPCR was performed on 182 diabetic patients who attended the diabetic clinic at Usmanu Danfodiyo University Teaching Hospital, Sokoto, Nigeria, from January 2018 to December 2018. Other relevant parameters were extracted from the Chemical Pathology Department register, and the patients' case folders. The data were statistically analysed using SPSS version 23.0 (Chicago IL). Results: Among the total of 182 diabetic patients recruited during the study period, 66(36.3%) were males and 116(63.7%) were females. Out of the patients, (82)45.1% had hypertension; and (105)57.7% of the study population were obese. The overall prevalence of pathological proteinuria (TPCR ≥ 150 mg/mmol creatinine) was found in 116 (63.7%) of the study population. Conclusions: The prevalence of proteinuria is high in the study subjects (63.7%). The high prevalence observed might be a result of kidney disease in a primary healthcare setting. However, this study is a hospital-based finding with a small sample size, therefore, a larger study population size is recommended for future studies. Keywords: prevalence, proteinuria, type 2 diab
Surgical Management of Huge Uterine Fibroids in a Northern Nigerian Teaching Hospital
Authors: Bawa Umma , Zubairu Usman , Sarkin-Pawa Zulaihatu , Madugu Nana , Abdul Muhammad
Published: August 2023

Background: Uterine fibroids are the most common tumor of the uterus worldwide, especially in blacks. While surgery remains the goal standard for definitive treatment, huge uterine fibroids pose a peculiar surgical challenge, with a possibly higher risk of complications such as hemorrhage and deep surgical site infection. Methods: A 5-year retrospective review of patients' folders who had surgical treatment for huge uterine fibroids from January 2015 to December 2019 was done. Huge uterine fibroids were defined as uterine size of ≥16 weeks. The patients' sociodemographic profiles, surgical procedure performed, early and delayed post-operative complications were all documented on a structured proforma. Data was analyzed using SPSS version 21. Results: A total of 245 patients had surgical treatments for uterine fibroids. However, 152 case notes were retrieved, of which 135 had huge uterine fibroids. The mean age of the patients was 37.85 ± 7.05 years. Abdominal myomectomy was performed in 108 (80%) of patients, while others had abdominal hysterectomy. Early post-operative complications included 10 (7.2%) with surgical site infection (SSI), 4 (3%) with febrile morbidity, and 3 (2.2%) requiring blood transfusion. Late complications included 6 (4.4%) with delayed SSI, 5 (3.7%) with uterine synechiae, and 2 (1.5%) with endometritis. There was no peri-operative mortality. Uterine sizes, and type of surgery performed showed no differences in complication rates. Nulliparity, and age <40 years showed higher odds of having myomectomy. Conclusion: The most common surgical treatment for huge uterine fibroids is abdominal myomectomy. Surgical treatment is generally safe with low morbidity.