A Pattern and Incidence Study of Complications after Emergency Laparotomy

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Background and Objectives: The study of emergency laparotomies are being carried out prospectively at the Department of General Surgery at a tertiary care facility affiliated with the Parul Institute of Medical Science and Research (Parul Sevasharam Hospital).

Methods: A tertiary care teaching hospital’s Department of General Surgery conducted a prospective study involving 100 emergency laparotomy cases from July 2020 to May 2021. Every patient underwent surgery using a midline vertical incision.

The main aim of the study is to identify various complications occurring following emergency laparotomies and various factors influencing them.

All patients followed up at least for a period of 6 months after surgery.

Results: 60 patients developed one or more complications postoperatively, 19 (31.7%) patients had abdominal complications; 34 (56.7%) had wound complications; 12 (20%) had chest complications and 4 (6.7%) had limb complications

Conclusion: Even with the availability of safe anaesthetic, broad range of antibiotics, and advanced experimental or investigational devices, the risk of complications and mortality from emergency laparotomies remains significant. Chest problems were associated with a higher postoperative mortality rate than wound, limb, or abdomen complications.

Narrative Paradigm in Da’wah Text within the Realm of Persuasive Approach

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This research aims at revealing persuasive messages that are conveyed through narratives constructed by the preachers. Employing the theory of persuasion, narrative paradigm proposed by Fisher, this research analyzed three transcribed da‘wah texts that are originally have been researched by Hairus, et al from different tools of persuasion. The analysis results that there have been found ten narratives within the three sources of da’wah texts, comprising six narratives from da’wah text (DT) 1, one narrative from DT 2, and three from DT 3. In each DT, the story about the first president of Indonesia, Soekarno, is found. Other narratives’ themes are about the prophet Yusuf, Umar bin Khottob, King Fir’aun, Indonesian alim Buya Hamka, and unnamed characters. They are all assumed to be “good reasons” in the narratives because their story presents narrative probability and fidelity that the theory requires. Additionally, the foremost persuasive message is embracing iman, which is then followed by ridding them of their worries about being poor either in wealth and social power, because God will save one’s life based on their worship and their practices of good deeds.

Design and Construction of Thermal Overload Relay (Siemens 3ua50) Based on Arduino Uno

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A Thermal Overload Relay (TOR) is a device in an electric motor protection system designed to safeguard the motor from damage due to overheating or overcurrent. This research discusses the design and implementation of a Thermal Overload Relay (TOR) based on Arduino Uno, which is a popular and flexible microcontroller platform. This design includes the PZEM-004T sensor to detect the electrical current and temperature of the electric motor. The design integrates the advantages of the PZEM-004T sensor in accurately measuring current and voltage with the flexibility and programming capabilities of Arduino in control and data processing. This system utilizes Arduino’s communication capabilities to transmit current and temperature data in real-time, enabling remote monitoring and quick response to potentially hazardous conditions. The result of this project is a tool that can replace the function of the TOR itself, where the characteristics produced are close to those of conventional TORs, and the thermal principle in the TOR is regulated with a time delay disconnection in the Arduino program.

Synergetic Approach Model for Improving Vocational Education: Characteristics, Guidelines and Applications

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The main purpose of vocational education is to prepare students for their future professional development, including the acquisition of skills and competencies necessary for the labor market. The research aims to present a model that gains effectiveness of applying a synergetic approach for improving vocational education. The synergetic approach could be an innovative pedagogical concept in VET that creates an open educational environment utilizing the application of different approaches and teaching methods. Basically the model proposed combines the change in curricula, the use of learning resources for practical teaching and the change in the way of assessment as kernel guideines for achieving better student outcomes. The ensuing benefits of applying a synergetic approach in VET are related to the possibility that vocational education is required to meet the needs of the contemporary labor market, as well as it answers to the expectations of society to prepare young people for their successful employment in industry. Other benefits are related to the possibility of restructuring the learning content, using various teaching methods, formative assessment, acquisition of permanent knowledge, as well as acquisition of skills for critical evaluation of information and self-evaluation of the achieved results to increase motivation. In synergetic learning, the content of the learning materials differs significantly from those traditionally used in vocational training, and the teacher has the opportunity to adapt the learning content to the needs of the specific student.

Semantic Components of English Directive Speech Act Verbs (Order, Command, Instruct)

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This research focuses on synonymous English speech act verbs that mean “giving order” (directive). The verbs analyzed in this study are those with very close synonymy, namely order, command, and instruct. The aim of this research is to describe in more detail the semantic behavior of the directive English speech act verbs through their semantic component. This semantics study is qualitative descriptive research. The data in this study were collected by using corpus linguistics and observation methods with note-taking techniques. The data source is the Corpus of Contemporary American English (COCA). There are 300 citations for each verb analyzed, which making in total 900 citations analyzed in the study. The study found that the verbs order, command, and instruct has eight semantic features/components that differentiate those three verbs, namely the components of authority, the way of saying, form of order, the duration of orders, level of urgency, actor and undergoer positions, domain of use, compliance level.

Establishing the program to predict Shirt Sizes with Fuzzy Logic

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This paper presents a program for prediction shirt size with a fuzzy logic technique. The Mamdani model is applied to a MISO fuzzy system with two inputs and one output. Neck girth and sleeve length are chosen as the primary dimensions, serving as input variables for this simulation model. In this study, fuzzy logic is used to select the size of the Min-Max rule. The IF-THEN structure is applied to execute commands effectively within this model. The outcome is an appropriate size. The program’s fuzzy rule matrix consists of 45 rows and 5 columns. Each row is a fuzzy rule. The first column represents the 9 sizes of necklaces. The second column represents the 5 groups of sleeve lengths. The third column represents the 9 predicted sizes in the output. The fourth column is the weight coefficient. The last column represents the logical connection type. The fuzzy logic approaches significantly reduces the time required. This approach provides an alternative method for prediction sizes that more accurately align with individual body measurements, offering a personalized fit.

MSMEs Bookkeeping Capabilities for Accounting Information Transparency

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MSMEs contribute 60% to gross domestic income, MSMEs also absorb labor and collect investment. However, of the total percentage of banking credit, MSMEs only get 20%. Banks experience difficulties in disbursing credit due to a lack of information on debtors who are worthy of financing. Difficulties are caused by the absence of financial reports as a parameter for credit worthiness. Through accounting transparency, it will be easy for MSMEs to know the policies that will be and have been taken. Transparency means the availability of sufficient, accurate and timely information about accounting policies and reporting. It is hoped that this research will be able to provide considerations for MSMEs to improve their accounting capabilities in accordance with SAK EMKM. The research was conducted in Denpasar, involving 100 questionnaire respondents and 10 informants in FGD. The data analysis technique used in this research is interpretive descriptive qualitative analysis technique.

As a result, MSMEs do not yet have the capability to prepare financial reports. MSMES players consider that the important aspects in starting a business are capital, skills and innovation or products, not accounting. Low accounting capability has an impact on neglecting the preparation of financial reports. Transparency can increase funding opportunities from banks or investors as well as opportunities for collaboration. There are still many MSMEs that have not prepared financial reports due to limited human resources and costs. However, MSMES players want to prepare financial reports.

MSMEs in the medium business category have prepared financial reports in accordance with SAK EMKM, only some in the small business group and not in the small business group. SAK EMKM requires a statement of financial position at the end of the period (balance sheet), a profit and loss statement for the period and notes to the financial statement. MSMEs focus more on recording expenses and income for profit and loss projections but ignore the balance sheet and Calc. The compiled profit and loss is still not relevant, there are still many accounts that have not been taken into account. Preparing a complete report in accordance with SAK EMKM will provide much more relevant and credible information.

Comparative Analysis of Machine Learning Algorithms for Used Car Price Prediction

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After 2021, over 90 million passenger automobiles were produced, marking a significant increase in auto production. This growth has led to a flourishing used car market, which has become a highly lucrative sector. One of the most critical and fascinating areas of research within this market is automobile price prediction. Accurate price prediction models can greatly benefit buyers, sellers, and businesses in the used car industry. This paper presents a detailed comparative analysis of two supervised machine learning models: K-Nearest Neighbour and Support Vector Machine regression techniques, to predict used car prices. We utilized a comprehensive dataset of used cars sourced from the Kaggle website for training and testing our models. The K Nearest Neighbour algorithm is known for its simplicity and effectiveness in regression tasks. On the other hand, the Support Vector Machine regression technique uses a different approach, finding the optimal hyperplane that best fits the data. Both methods have their strengths and weaknesses, which we explored in this study. Our results indicated that both KNN and SVM models performed well in predicting used car prices, but with slight variations in accuracy.  Consequently, the suggested models fit as the optimum models and have an accuracy of about 83 percent for KNN and 80 percent for SVM. The results indicate that the KNN model slightly outperforms the SVM model in predicting used car prices.

Exploring the Frontiers: A Comprehensive Review of Augmented Reality and Virtual Reality in Manufacturing and Industry

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Augmented reality (AR) and virtual reality (VR) are revo- lutionizing manufacturing practices by offering immersive and interactive experiences. This review paper synthesizes current research on AR and VR’s applications, benefits, and challenges in manufacturing, covering design, training, maintenance, and quality control. Key findings highlight the applications and positive impact of AR/VR on efficiency, cost management, and quality control in manufacturing processes. Industries are in- creasingly adopting these technologies to enhance productivity and reduce errors. However, challenges such as cost, techno- logical infrastructure, and integration into existing workflows remain significant barriers. In conclusion, integrating AR and VR in manufacturing holds immense potential to transform traditional methods and improve operational efficiency. This paper advocates for broader implementation and research to harness the full benefits of immersive technologies in manufacturing.

Grid Search Optimized Machine Learning based Modeling of CO2 Emissions Prediction from Cars for Sustainable Environment

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Carbon emissions have increased dramatically because of industrialization, trapping heat in the atmosphere and hastening climate change. This is a serious threat to the wealth, security, and well-being of the world. The effects are extensive, ranging from severe weather, disease outbreaks, and economic disruption to food insecurity and water scarcity. The World Health Organization (WHO) has determined that climate change poses the greatest threat to public health in the twenty-first century. Thus, precise CO2 emissions have emerged as a crucial concern in recent times. Several studies have tried to forecast the amount CO2 from industry and power plant using statistical analysis. Efficiency, robustness and diverse application was the limitation of the study.  In this study, we have proposed an AI based model that is able to predict the amounts of CO2 emissions from cars. We applied a grid search-optimized machine learning approach using the publicly available Canadian dataset. Incorporation of different statistical analyses and preprocessing techniques such as duplicate data management, outlier rejection, scaling contributed to enhance the quality of the dataset. Later, grid search techniques were applied to tune the KNN, RF, and SVR models. The approach has enhanced the performance of CO2 emissions prediction. In the study, we further used the explainability of the random forest model to check the bias and fairness of predictability. MSE, RMSE, and R-squared metrics of the proposed approach were the highest as the state of the art.