bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifikasi proses berpikir siswa dalam menyelesaikan masalah aljabar dengan menggunakan representasi graf
Authors: Lailiyah Siti , Kusaeri Kusaeri , Rizki Wenda Yulian
Published: May 2022

Representasi graf banyak digunakan, salah satunya untuk menggambarkan proses berpikir siswa. Caranya dengan melihat hubungan antara langkah penyelesaian satu dengan lainnya dalam menyelesaikan masalah matematika. Penelitian ini bertujuan untuk merepresentasikan proses berpikir siswa dalam menyelesaikan masalah aljabar dengan bantuan representasi graf. Subjek penelitian ini adalah 3 dari 38 siswa kelas IX-A SMP Negeri 26 Surabaya, yang diambil dengan teknik snowball sampling. Teknik pengumpulan data menggunakan metode wawancara berbasis tugas. Tugas atau masalah yang diberikan berupa dua soal open onded dan hasilnya dianalisis serta direpresentasikan melalui graf: graf pohon biner, graf pohon rentang, dan graf pohon keputusan. Hasil penelitian menunjukkan bahwa melalui graf pohon biner, representasi proses berpikir siswa masih sederhana dan tidak sistematis dengan langkah-langkah penyelesaian yang dilakukan masih sedikit. Melalui graf pohon rentang, proses berpikir siswa direpresentasikan secara praktis, lengkap, dan tepat. Melalui graf pohon keputusan, proses berpikir siswa direpresentasikan secara teratur, rinci, dan terurut. AbstractOne of the uses of graph representation was to describe students’ thinking. Processes by identifying the relationship between one completion step and another completion step in doing mathematics problems. This qualitative descriptive research aimed to describe the representation of students’ thinking processes in solving algebraic questions with the help of graph representation. The subjects of this study were 3 from 38 students of class IX-A at SMP Negeri 26 Surabaya, Indonesia selected through snowball sampling. Data was collected from task-based interview methods. The task or problem given was two open-ended questions and the results were analyzed as well as represented through graphs: binary tree graph, spanning tree graph, and decision tree graph. The results showed that through the binary tree graph, the representations of students’ thinking processes were still simple and not systematic with few steps to complete. Through the spanning tree graph, students’ thinking processes were represented practically, completely, and precisely. Through the decision tree graph, students’ thinking processes were represented in an orderly, detailed, and consecutive.
Inisiasi Kahoot! sebagai variasi pembelajaran kalkulus bagi mahasiswa teknik lingkungan
Authors: Fauzan Achmad , Safira Muthia Citra , Sulistyo Elita Nurfitriyani
Published: May 2022

Penelitian bertujuan untuk menguji perbedaan hasil belajar antara mahasiswa yang mengikuti pembelajaran Kalkulus menggunakan media Kahoot! dengan yang tidak menggunakan Kahoot! serta tingkat kesesuaian dari penggunaan media pembelajaran Kahoot!. Penelitian ini merupakan penelitian kuantitatif dengan subjek penelitian adalah mahasiswa baru Prodi Teknik Lingkungan Tahun Angkatan 2019/2020 sebanyak 82 orang dan Angkatan 2018/2019 sebanyak 40 orang. Digunakan t-test dan Wilcoxon test untuk menguji perbedaan signifikansi rata-rata dari dua grup yang saling bebas. Tingkat kesesuaian dianalisis menggunakan Importance-Performance Analysis (IPA) yang menggambarkan antara kinerja dengan harapan. Sebagai bahan evaluasi diberikan feedback yang dianalisis menggunakan text mining dengan sentiment analysis yang divisualisasikan menggunakan word cloud berbantuan Program R. Hasil penelitian menunjukkan bahwa secara keseluruhan tidak terlalu berbeda rata-rata hasil belajar dari kedua kelompok. Namun, jika menggunakan media Kahoot!, suasana pembelajaran lebih menyenangkan dan tidak tegang, serta tercipta komunikasi dua arah dari pendidik kepada mahasiswa atau antar mahasiswa. Tingkat kesesuaian antara kinerja dan harapan adalah baik dengan nilai rata-rata 95.05%. Selain itu, mahasiswa memberikan respon positif terhadap penggunaan media Kahoot! pada perkuliahan Kalkulus dengan berbagai kelebihan dan kekurangannya.Initiate Kahoot! as a variation of calculus learning for environmental engineering studentsAbstractThis study aimed to examined differences in learning outcomes between students who take Calculus courses using Kahoot! and those who didn’t use Kahoot! as well as the level of suitability of using Kahoot! learning media. This study was quantitative research. The subjects were 82 new students in 2019/2020 and 40 students in 2018/2019 from the Environmental Engineering Study Program, Universitas Islam Indonesia, Indonesia. We used the t-test and the Wilcoxon test to examine mean differences in the two independent groups. The level of suitability uses Importance-Performance Analysis (IPA), which describes performance and expectations. As an evaluation material, the feedback was given, analyzed using text mining with sentiment analysis, which was visualized using word cloud assisted by the R program. The results showed that overall the learning outcomes of the two groups were not significantly different. However, if Kahoot! media was used, the learning atmosphere was more fun and less tense, and created two-way communication from educators to students or between students. The level of suitability between performance and expectations was good, with an average value of 95.05%. Also, students gave a positive response to the use of Kahoot! in Calculus courses with its various advantages and disadvantages.
Analisis kemampuan berpikir kritis ditinjau dari gaya belajar matematika siswa
Authors: Setiana Dafid Slamet , Purwoko Riawan Yudi
Published: May 2022

Penelitian ini bertujuan untuk mendeskripsikan kemampuan berpikir kritis ditinjau dari gaya belajar matematika siswa. Jenis penelitian ini adalah penelitian deskriptif kualitatif. Subjek penelitian adalah siswa kelas XII SMA Negeri Punung, Kabupaten Pacitan. Subjek penelitian sebanyak enam siswa dengan masing-masing dua siswa untuk gaya belajar visual, auditorial, dan kinestetik. Data penelitian diambil melalui angket gaya belajar, tes kemampuan berpikir kritis, dan wawancara. Data angket dianalisis untuk menentukan jenis gaya belajar siswa, sedangkan data hasil tes dianalisis berdasarkan aspek kemampuan berpikir kritis matematis yaitu FRISCO – Focus, Reason, Inference, Situation, Clarify, and Overview. Hasil penelitian menunjukkan bahwa kemampuan berpikir kritis siswa pada masing-masing gaya belajar memiliki tingkatan yang berbeda. Siswa dengan gaya belajar visual memiliki kemampuan berpikir kritis pada kriteria sangat baik, siswa dengan gaya belajar auditorial memiliki kemampuan berpikir kritis pada kriteria cukup, sedangkan siswa dengan gaya belajar kinestetik memiliki kemampuan berpikir kritis pada kriteria baik.  Namun demikian ketiganya mempunyai potensi kuat untuk mengembangkan kemampuan berpikir kritis dalam matematika melalui stimulasi dari guru. Analysis of critical thinking skills in terms of students' mathematics learning stylesAbstractThis study aimed to describe critical thinking skills in terms of students’ mathematics learning styles. It was a qualitative descriptive study. The study subjects were twelfth-grade students of SMA Negeri Punung (Public Senior High School), Pacitan Regency, Indonesia. The subjects were six students, with two students each for visual, auditory, and kinesthetic learning styles. The data were taken through learning style questionnaires, critical thinking skills tests, and interviews. The questionnaire data were analyzed to determine the type of student learning style, while the test result data were analyzed based on aspects of mathematical critical thinking skills, namely FRISCO – Focus, Reason, Inference, Situation, Clarify, and Overview. The results showed that students’ critical thinking skills in each learning style had different levels. Students with visual learning styles have the critical thinking skills on very good criteria, students with auditory learning styles have the critical thinking skills on moderate criteria, while students with kinesthetic learning styles have the critical thinking skills on good criteria. However, all three have strong potential to develop critical thinking skills in mathematics through stimulation from the teacher.
Pengembangan film animasi aritmetika sosial berbasis ekonomi syariah untuk meningkatkan minat belajar siswa MTs
Authors: Safitri Wilda Yumna , Retnawati Heri , Rofiki Imam
Published: May 2022

Penelitian ini bertujuan untuk menghasilkan film animasi aritmetika sosial berbasis ekonomi syariah yang valid, praktis, dan efektif untuk meningkatkan minat belajar siswa. Penelitian pengembangan ini menggunakan model Plomp yang terdiri dari tiga fase, yaitu fase penelitian pendahuluan, fase pembuatan prototype, dan fase penilaian. Uji coba prototype dilakukan kepada 21 siswa kelas VIII MTs di Sidoarjo, Indonesia. Instrumen penelitian terdiri dari lembar validasi ahli untuk menilai kevalidan, angket respons siswa untuk menilai kepraktisan, dan angket minat belajar siswa untuk menilai keefektifan film animasi. Penelitian ini menghasilkan film animasi aritmetika sosial berbasis ekonomi syariah untuk meningkatkan minat belajar siswa MTs terhadap pembelajaran matematika yang terintegrasi dengan ilmu keislaman. Meskipun peningkatan minat belajar siswa masih tergolong rendah, namun secara keseluruhan film animasi yang dikembangkan dinilai valid, praktis, dan efektif, sehingga layak digunakan dalam pembelajaran matematika di MTs. Development of social arithmetic animation film based on sharia economic to increase MTs students' interest in learningAbstractThis study aimed to produce an animated film of social arithmetic based on sharia economics that was valid, practical, and effective to increase students’ interest. The study was development research using Plomp’s model, which consisted of three stages: the preliminary research stage, the prototyping stage, and the assessment stage. Prototype trials were conducted on grade-eight students (n = 21) of MTs (Islamic Junior High School) in Sidoarjo, Indonesia. The instruments consisted of the expert validation sheet to assess the validity, the students' response questionnaire to assess the practicality, and the students' interest questionnaire to assess the effectiveness of the animated film. This study produced an animated film of social arithmetic based on sharia economics to increase MTs students' interest in learning mathematics integrated with Islamic science. Although the increase in student interest in learning was still low, overall, the animated film developed was considered valid, practical, and effective, so it was proper to use in mathematics learning in MTs.
Deep Neural Networks for Simultaneously Capturing Public Topics and Sentiments During a Pandemic: Application on a COVID-19 Tweet Data Set
Authors: Boukobza Adrien , Burgun Anita , Roudier Bertrand , Tsopra Rosy
Published: May 2022

Background

Public engagement is a key element for mitigating pandemics, and a good understanding of public opinion could help to encourage the successful adoption of public health measures by the population. In past years, deep learning has been increasingly applied to the analysis of text from social networks. However, most of the developed approaches can only capture topics or sentiments alone but not both together.

Objective

Here, we aimed to develop a new approach, based on deep neural networks, for simultaneously capturing public topics and sentiments and applied it to tweets sent just after the announcement of the COVID-19 pandemic by the World Health Organization (WHO).

Methods

A total of 1,386,496 tweets were collected, preprocessed, and split with a ratio of 80:20 into training and validation sets, respectively. We combined lexicons and convolutional neural networks to improve sentiment prediction. The trained model achieved an overall accuracy of 81% and a precision of 82% and was able to capture simultaneously the weighted words associated with a predicted sentiment intensity score. These outputs were then visualized via an interactive and customizable web interface based on a word cloud representation. Using word cloud analysis, we captured the main topics for extreme positive and negative sentiment intensity scores.

Results

In reaction to the announcement of the pandemic by the WHO, 6 negative and 5 positive topics were discussed on Twitter. Twitter users seemed to be worried about the international situation, economic consequences, and medical situation. Conversely, they seemed to be satisfied with the commitment of medical and social workers and with the collaboration between people.

Conclusions

We propose a new method based on deep neural networks for simultaneously extracting public topics and sentiments from tweets. This method could be helpful for monitoring public opinion during crises such as pandemics.
Acceptance and Effect of Continuous Glucose Monitoring on Discharge From Hospital in Patients With Type 2 Diabetes: Open-label, Prospective, Controlled Study
Authors: Depczynski Barbara , Poynten Ann
Published: May 2022

Background

Continuous glucose monitors (CGM) can provide detailed information on glucose excursions. There is little information on safe transitioning from hospital back to the community for patients who have had diabetes therapies adjusted in hospital and it is unclear whether newer technologies may facilitate this process.

Objective

Our aim was to determine whether offering CGM on discharge would be acceptable and if CGM initiated on hospital discharge in people with type 2 diabetes (T2DM) would reduce hospital re-presentations at 1 month.

Methods

This was an open-label study. Adult inpatients with T2DM, who were to be discharged home and required postdischarge glycemic stabilization, were offered usual care consisting of clinic review at 2 weeks and at 3 months. In addition to usual care, participants in the intervention arm were provided with a Libre flash glucose monitoring system (Abbott Australia). An initial run-in phase for the first 20 participants was planned, where all consenting participants were enrolled in an active arm. Subsequently, all participants were to be randomized to the active arm or usual care control group.

Results

Of 237 patients screened during their hospital admission, 34 had comorbidities affecting cognition that prevented informed consent and affected their ability to learn to use the CGM device. In addition, 21 were not able to be approached as the material was only in English. Of 101 potential participants who fulfilled eligibility criteria, 19 provided consent and were enrolled. Of the 82 patients who declined to participate, 31 advised that the learning of a new task toward discharge was overwhelming or too stressful and 26 were not interested, with no other details. Due to poor recruitment, the study was terminated without entering the randomization phase to determine whether CGM could reduce readmission rate.

Conclusions

These results suggest successful and equitable implementation of telemedicine programs requires that any human factors such as language, cognition, and possible disengagement be addressed. Recovery from acute illness may not be the ideal time for introduction of newer technologies or may require more novel implementation frameworks.
Comparison Between the 24-hour Holter Test and 72-hour Single-Lead Electrocardiogram Monitoring With an Adhesive Patch-Type Device for Atrial Fibrillation Detection: Prospective Cohort Study
Authors: Kwon Soonil , Lee So-Ryoung , Choi Eue-Keun , Ahn Hyo-Jeong , Song Hee-Seok , Lee Young-Shin , Oh Seil , Lip Gregory Y H
Published: May 2022

Background

There is insufficient evidence for the use of single-lead electrocardiogram (ECG) monitoring with an adhesive patch-type device (APD) over an extended period compared to that of the 24-hour Holter test for atrial fibrillation (AF) detection.

Objective

In this paper, we aimed to compare AF detection by the 24-hour Holter test and 72-hour single-lead ECG monitoring using an APD among patients with AF.

Methods

This was a prospective, single-center cohort study. A total of 210 patients with AF with clinical indications for the Holter test at cardiology outpatient clinics were enrolled in the study. The study participants were equipped with both the Holter device and APD for the first 24 hours. Subsequently, only the APD continued ECG monitoring for an additional 48 hours. AF detection during the first 24 hours was compared between the two devices. The diagnostic benefits of extended monitoring using the APD were evaluated.

Results

A total of 200 patients (mean age 60 years; n=141, 70.5% male; and n=59, 29.5% female) completed 72-hour ECG monitoring with the APD. During the first 24 hours, both monitoring methods detected AF in the same 40/200 (20%) patients (including 20 patients each with paroxysmal and persistent AF). Compared to the 24-hour Holter test, the APD increased the AF detection rate by 1.5-fold (58/200; 29%) and 1.6-fold (64/200; 32%) with 48- and 72-hour monitoring, respectively. With the APD, the number of newly discovered patients with paroxysmal AF was 20/44 (45.5%), 18/44 (40.9%), and 6/44 (13.6%) at 24-, 48-, and 72-hour monitoring, respectively. Compared with 24-hour Holter monitoring, 72-hour monitoring with the APD increased the detection rate of paroxysmal AF by 2.2-fold (44/20).

Conclusions

Compared to the 24-hour Holter test, AF detection could be improved with 72-hour single-lead ECG monitoring with the APD.
Establishing Requirements for Technology to Support Clinical Trial Retention: Systematic Scoping Review and Analysis Using Self-determination Theory (Preprint)
Authors: Gamble Eoin , Linehan Conor , Heavin Ciara
Published: May 2022

BACKGROUND

Retaining participants in clinical trials is an established challenge. Currently, the industry is moving to a technology-mediated, decentralized model for running trials. The shift presents an opportunity for technology design to aid the participant experience and promote retention; however, there are many open questions regarding how this can be best supported. We advocate the adoption of a stronger theoretical position to improve the quality of design decisions for clinical trial technology to promote participant engagement.

OBJECTIVE

This study aimed to identify and analyze the types of retention strategies used in published clinical trials that successfully retain participants.

METHODS

A systematic scoping review was carried out on 6 electronic databases for articles published from 1990 to September 2020, namely CINAHL, The Cochrane Library, EBSCO, Embase, PsycINFO, and PubMed, using the concepts “retention,” “strategy,” “clinal trial,” and “clinical research.” This was followed by an analysis of the included articles through the lens of self-determination theory, an evidence-based theory of human motivation.

RESULTS

A total of 26 articles were included in this review. The motivational strategies identified in the clinical trials in our sample were categorized into 8 themes: autonomy; competence; relatedness; controlled motivation; branding, communication material, and marketing literature; contact, tracking, and scheduling methods and data collection; convenience to contribute to data collection; and organizational competence. The trials used a wide range of motivational strategies. Notably, the trials often relied on controlled motivation interventions and underused strategies to support intrinsic motivation. Moreover, traditional clinical trials relied heavily on human interaction and “relatedness” to support motivation and retention, which may cause problems in the move to technology-led decentralized trials. We found inconsistency in the data-reporting methods and that motivational theory–based approaches were not evident in strategy design.

CONCLUSIONS

This study offers direction and a framework to guide digital technology design decisions for future decentralized clinical trials to enhance participant retention during clinical trials. This research defines previous clinical trial retention strategies in terms of participant motivation, identifies motivational strategies, and offers a rationale for selecting strategies that will improve retention. It emphasizes the benefits of using theoretical frameworks to analyze strategic approaches and aid decision-making to improve the quality of technology design decisions.
Supporting Public Health Research Capacity, Quality, and Productivity in a Diverse Region (Preprint)
Authors: AlHamawi Rana , Saad Randa K , Abdul Rahim Hanan F , Mir Islam Saeed Khwaja , Husseini Abdullatif , Khader Yousef , Al Nsour Mohannad
Published: May 2022

UNSTRUCTURED

Public health research plays a critical role in strengthening health systems and improving their performance and impact. However, scholarly production in public health coming from the Eastern Mediterranean Region (EMR) remains well below the world average and lacks a tangible growth trend over time. During the seventh Eastern Mediterranean Public Health Network Regional Conference, a roundtable session brought together a panel of public health experts representing Global Health Development/Eastern Mediterranean Public Health Network affiliates, universities or academia, and research institutions from the region, where they shared insights on the current situation of public health research; challenges and barriers to research facing the different countries in the EMR and the region in general; and how research agendas, productivity, and quality can be supported through strengthening research capacity in the region. Although the region is diverse in terms of health system capacity and socioeconomic development, several common challenges were identified, including a lack of strategic prioritization to guide health research, insufficient funding, ineffective transfer of knowledge to policy and practice, limited availability of research facilities, and limited national and international research collaboration. Occupied countries and countries in a state of conflict, such as Palestine, face additional barriers, such as personal and social security, lack of control of borders and natural resources, travel and movement restrictions, and confidentiality challenges because of the continuing war conditions and occupation. However, there have been success stories in the EMR regarding research publications and their positive and effective impact on policy and decision-makers. To improve research resilience and public health care in the region, a collaborative approach involving institutions, policymakers, and relevant stakeholders is critical.
Explainable machine learning for decision support in healthcare: A scoping review (Preprint)
Authors: Shulha Michael , Rahimi Samira , Sandhu Amrita , Sharma Gauri , D'Souza Vinita , Harmouche Rola , Hovdebo Jordan
Published: May 2022

BACKGROUND

The uptake of machine learning based decisions support has faced challenges in real world clinical scenarios. A key reason has been that clinicians lack trust in black box machine learning models. One approach to this challenge is through the use of explainable approaches to machine learning, which ideally allow an end user to understand why a specific prediction is being made.

OBJECTIVE

The study aimed to describe the scope of explainable machine learning (XML) research in clinical decision support, and identify approaches and frameworks that have been used to study end-user perceptions of explainability.

METHODS

Following PRISMA guidelines, a search protocol was developed and executed in Ovid MEDLINE ALL(R), EMBASE Classic + EMBASE, Web of Science Core Collection, CINAHL Cochrane Library CENTRAL (Trials) to identify eligible articles. Studies describing the testing, piloting, or implementation of explainable machine learning tools designed to support clinical decision making were eligible for synthesis. We summarized the scope of machine learning methods, the clinical scope, intended end user, and decision focus. In a sub analysis, we also summarized the design and visual elements employed by researchers and the associated methodological approaches used to assess end-user perceptions of explainability. Finally, we conducted a thematic analysis to better understand the perceived potential health system benefits, and clinical end-user benefits with explainable machine learning based decision support.

RESULTS

We found the majority of studies focused on the development of tools for doctors as the intended users (85%) for diagnostic support (45%) in the context of secondary care (55%). Explainability methods were highly varied with the majority of studies using a unique explainability model (76%). Only 12% discussed some type of testing phase to assess the suitability of explainability methods with clinical end users. Improved end-user trust in machine learning and AI tools was the most common cited potential benefit.

CONCLUSIONS

The majority of research appears focused on the mechanics of developing explainable machine learning models, with little attention paid to the clinical end-user experience. While increased trust in machine learning tools is often cited as a potential outcome of well implemented explainability, there is little discussion of how this can be effectively measured and operationalized.

Ultimately, improved alignment between research, implementation, and medical education will serve to benefit the advancement of XML for clinical decision support and the capacity of these types of tools to benefit healthcare.
Akurasi dimensi produk filamen 3d printing berbahan polipropilen menggunakan mesin ekstrusi
Authors: Ramadhan Mochamad Edoward , Darsin Mahros , Akbar Sains Ilham , Yudistiro Danang
Published: May 2022

Additive manufacturing (AM) has been trending topic in industrial revolution 4.0. One technique and the most widely used AM is fused deposition modeling (FDM), which uses a melted filament and deposited it layer by layer. The common filaments used are made of PLA, PP, and ABS, which are available at the online market with variety of prices depend on the quality. It is an advantage if we can make these filaments. In filament manufacturing, the dimensional accuracy is one of the most important factors to comply with the existing 3D printers. The aim of this research is to fabricate a filament made of PP, then assessed the quality based on the accuaray of the targeted diameter of 1.75 mm. The manufacturing process used a self-made plastic extrusion machine. Variations were made on three variables with three levels each. There are (i) heater band temperature with a minimum and maximum range (150/170 oC, 155/175 oC and 160/180 oC), (ii) winding speed (13 mm/s, 16 mm/,s and 19 mm/s), and (iii) roll distance to the nozzle set point (200 mm, 500 mm and 700 mm). Taguchi L9 design was used to design the experiments and analysis.Minitab 19 was employed to find the S/N ratio and analysis the variance (ANOVA). The results of the analysis state that two parameters have a significant effect on the dimensions of the filament, i.e. temperature and roll distance to the nozzle, while, the winding speed has no dominat effect. The best accuracy of filaments diameter was achieved when applying a combination of temperature (160/180 ⁰C), the distance between the nozzle to the roll of 700 mm, and winding speed of 13 mm/s.
Editorial
Authors: Siswomihardjo Widowati
Published: May 2022

Jurnal Teknosains merupakan salah satu jurnal di bawah Sekolah Pascasarjana UniversitasGadjah Mada yang memiliki minat serta program studi yang beragam. Dengan berangkatdari keilmuan lintas disiplin, Jurnal Teknosains edisi Juni ini juga mengemban semangat yangberagam dalam menerbitkan suatu hasil atau karya ilmiah dari beragam disiplin ilmu. Selain itu,penerbitan di edisi ini telah memilih delapan artikel dari lintas institusi. Hal tersebut dilakukanuntuk menambah diversifikasi penulis dari Jurnal Teknosains agar semakin memberikan dampakyang luas dalam bidang publikasi, khususnya dalam bidang sains dan teknologi secara nasional.
College English Language Teaching Reform and EFL Lecturers’ Reflection on Teaching: A Case Study in China
Authors: Sun Zhiyong
Published: May 2022

With the rapid development of newly improved colleges and universities across China, there was a commensurate need for English as a Foreign Language teaching and learning (EFL). As a result, China’s Ministry of Education initiated the College English Language Teaching Reform (CELTR) to improve English language teaching and learning at tertiary institutions in the country. The purpose of this article was to look into EFL lecturers’ perceptions of the CELTR and see how much the CELTR had improved their teaching reflection, which in turn influenced the CELTR’s effect and implementation. A total of 92 EFL lecturers from a newly renovated university in Nanyang City, Central China, participated in the study. Purposive sampling was used to obtain data for the study, which included a questionnaire and semi-structured interviews with eight EFL lecturers. The findings revealed that EFL lecturers had a reasonable degree of awareness and knowledge of the CELTR, that lecturers’ reflection on teaching had improved slightly since the CELTR was implemented, and that EFL lecturers’ intents and use of reflection on teaching had increased under the CELTR. They used many ways to undertake reflection on teaching. The findings revealed that EFL lecturers constantly reflected on their teaching contents, methods, and events during the CELTR implementation process in order to improve their teaching practice and better meet the students’ specific needs, and they believed that reflection on teaching could not be separated from teaching practice.
EVALUATION OF ANTAGONIST ACTIVITY OF IFENPRODIL AND THEIR ANALOGOUS AGAINST GLUN1/GLUN2B USING IN SILICO MOLECULAR DOCKING AND ABSORPTION-DISTRIBUTIONMETABOLISM- EXCRETION TOXICITY
Authors: PRAVEEN MALLARI
Published: May 2022

Objectives: High Ca2+ permeability represents a characteristic feature of N-methyl-D-aspartate (NMDA) receptors that in extreme amounts affects physiological functions such as reduced neural development, synaptic plasticity, and learning and memory. The study aims to elucidate the potent inhibitory ifenprodil and their eleven analogues, retrieved from the PubChem database, which act as ligands to the target Glun1/GluN2B subunit of the NMDA receptor.
Methods: In silico methods such as molecular docking performed using AutoDock Vina and absorption-distribution-metabolism-excretion-toxicity (ADMET) were SwissADME and OSIRIS carried out to elucidate the potent antagonist ligand against the target.
Results: Molecular docking showed that six of the compounds had significant binding affinities (7.8–9.0 kcal/mol) for the target. The ADMET study revealed that three (PubChemID: 12613159, 12613162, and 6604117) of six compounds with good binding affinity obeyed Lipinski’s rule of five.
Conclusion: This study revealed three good antagonists of GluN1/GluN2B, namely, 4- [(1R, 2R)-2-(4-benzylpiperidin-1-yl)-1- hydroxy propyl] phenol (A2), 4-[2-(4-benzylpiperidin-1-yl)-1-hydrooxypropyl] phenol hydrobromide (A4), and 4- [(1R, 2S)-2-(4-benzylpiperidin-1-yl)-1-hydroxypropyl] phenol (A7) that can be further exploited for wet lab studies.
COMBINED PERICAPSULAR NERVE GROUP AND OBTURATOR NERVE BLOCKS (PARTHA’S COMBO BLOCK) FOR EMERGENCY REDUCTION OF DISLOCATED PROSTHETIC HIP: A CASE REPORT
Authors: KALSAD ANUSHA , S PARTHASARATHY
Published: May 2022

The perioperative management of hip fractures and dislocation of hips with already fixed hardware are challenging in the elderly because of poor physiological reserve and multiple comorbidities. Previously, general anesthesia and a few regional anesthetic techniques were used to reduce dislocated hip. The pericapsular nerve group block (PENG) was first described in 2018, especially for total hip arthroplasties for a near-complete perioperative analgesia with motor sparing. In this case, a 75-year-old male with a history of hemiarthroplasty 15 days prior presents with a repeat fall and hip injury. We used a combined PENG and obturator nerve (ON) block to treat a dislocated prosthetic hip with a fractured pubic ramus. PENG was given with 20 ml of 0.375% bupivacaine and 6 ml each was administered for the anterior and posterior branches of ON. Following this Partha’s combo block (PENG block+obturator), pain score reduced to 1/10 in around 20 min and closed reduction was done successfully in 4 min. The reduction was successful, painless, and without any major side effects. This is the first such report of reduction of dislocation of prosthetic hip. We surmised that a good pain relief of pubic fracture and the relief of associated adductor spasm targeted by the ON block may be the key to our success.
SCREENING OF NEROLI OIL ON PARACETAMOL INDUCED HEPATOTOXICITY IN RATS
Authors: PATIL ANNASAHEB , SHIVATHAYA NEHA
Published: May 2022

Objective: The objective of the study was to evaluate the hepatoprotective effect of Neroli oil against Paracetamol induced liver injury in Wistar rats.
Methods: Changes in the serum biomarker enzymes, namely, alanine transferase (ALT), aspartate transferase (AST), alkaline phosphatase (ALP), direct bilirubin, total bilirubin, total cholesterol, and albumin were estimated. Oxidative stress parameter such as MDA, SOD, GSH, and catalase levels was also estimated along with the liver weight and volume.
Results: Neroli oil showed significant reduction in all elevated biochemical parameters (namely, ALT, AST, ALP, direct bilirubin, total bilirubin, and total cholesterol), and significant increase in reduced level of albumin. Oil showed significant increase in GSH and catalase level and decreased in LPO level. Histopathological determinations confirmed biochemical findings.
Conclusion: Neroli oil showed a significant hepatoprotective effect against Paracetamol induced hepatic damage as depicted by its protective activity on functional, physical, biochemical, antioxidant, and histological changes in liver.
WEIGHT-BASED DOSING OF ENOXAPARIN AND ANTIFACTOR XA LEVELS FOR VENOUS THROMBOEMBOLISM PROPHYLAXIS IN MEDICALLY-ILL PATIENTS
Authors: K SOURIS , B SWATHI , SAINATH ENP , V LAHARI
Published: May 2022

Objective: The objective of the study was to evaluate peak antifactor Xa (aFXa) levels in low-weight patients receiving enoxaparin for VTE prophylaxis.
Methods: Retrospective cohort of adult patients weighing <55 kg who was hospitalized at tertiary care Center between January 2019 through February 2020. All patients received enoxaparin for VTE prophylaxis with a peak aFXa level drawn. The primary end point was the proportion of patients achieving peak aFXa levels within the goal range of 0.2–0.5 units/ml.
Results: Of 65 patients receiving enoxaparin for VTE prophylaxis with an appropriately timed peak aFXa level, 74% achieved goal peak aFXa levels and the median daily dose of enoxaparin was 30 mg. The mean weight was about 44 kg. No significant correlations between aFXa level and body mass index or body weight were found.
Conclusion: A lower dose of enoxaparin may be reasonable in low-weight patients for VTE prophylaxis. There appears to be no safety concerns with reduced enoxaparin dosing in low-weight patients. More robust data are needed to confirm these findings.
mRNA vaccines against emerging infectious diseases; A challenging approach of novel vaccine discovery
Authors: Samantaray Utkalendu Suvendusekhar , Khuntia Rudra Prasad
Published: May 2022

Basic human biology is dealt with by mRNA, which creates instructions for making proteins that may aid in the fight against infectious illnesses using our bodies' own mechanisms. mRNA therapies are neither tiny compounds nor huge biological such as recombinant proteins or monoclonal antibodies. These are a series of instructions that assist our cells' machinery in producing proteins that protect us against a certain virus. Our bodies would be unable to perform their activities if mRNA was not introduced. mRNA, or messenger ribonucleic acid, is an important component of the living world, especially in the process of protein synthesis. mRNA is a single-stranded molecule that transmits genetic instructions from a cell's nucleus DNA to the ribosomes, which are the cell's protein-making machinery. The synthesis of an RNA copy from the coded sequence of DNA leads in the production of a particular protein. This copy of mRNA moves from the nucleus of the cell to the cytoplasm, where ribosomes reside. Ribosomes are a sort of sophisticated machinery organelle that aids and begins protein synthesis in cells. Ribosomes ‘read' the mRNA sequence and follow the instructions, progressively adding on various needed amino acids to make the intended protein during the translation process. The protein is subsequently expressed by the cell, and it goes on to execute its role in the cell or in the body. The use of mRNA as a medication offers up a whole new universe of possibilities in terms of illness treatment and prevention. This review contributes to the growing body of knowledge in the field of mRNA therapeutic delivery and the identification of appropriate antigens for mRNA target locations. Two major mRNA vaccines for protection against SARS-CoV-2 have recently been developed and approved for use in the general population by international health authorities. They've been demonstrated to defend against the SARS-CoV-2 virus, which is still active and evolving. This will draw attention to a variety of mRNA vaccines now being evaluated for infectious diseases in clinical studies. mRNA vaccines offer a number of advantages, including speedy design, fabrication, manufacturing, and administration, and they hold a lot of potential for future use against a wide range of diseases.
Age Estimation and Gender Recognition Technique Using Deep Learning
Authors: Arya Shailesh , Khan Mubashir , Agarwal Anirudh , Gaur Ayush , Mallick Dr. Bhawna
Published: May 2022

Abstract: Using a neural convolution network, this research presents an automatic system for recognising age and gender based on a person's face. In recent years, one of the most effective research subjects has been collecting information from a person's face. The human face has facial features such as eyes, ears, nose, chin, and other aspects that can be examined based on our requirements. The detection of age and gender begins with facial recognition. Detection is the process of identifying many features based on a single input. Our system makes use of OpenCV and includes a few deep convolutional emotional networks that have been trained to detect faces from inserted images and predict their age and gender using either a webcam or an image. Not only are deep neural convolutional networks costly, but they are also difficult to implement. Keywords: Age Estimation, Gender Detection, Deep Learning, Webcam, Convolutional neural network, OpenCV.
Identification and Mitigation of Blackspots and Implementation of An Advanced Traffic Management System on NH-216A (A Spur of National Highway-16)
Authors: Ramakrishna Maanyam , Ramesh Bandaru
Published: May 2022

Abstract: As the population is increasing day by day the number of vehicles is also increasing. As the number of vehicles is increasing, the number of accidents also increases. Analysis of previous data indicates that 66% of the accidents occur due to human error and 33% due to road parameters such as road and vehicle interaction, other road users, and environmental factors. Road safety has recently become a major concern in most modern societies. The identification of sites (black spots) that are more dangerous from an accident point of view can help in better scheduling road safety policies. The study includes the collection of accident data and prioritizing the accident-prone locations by using the Weighted Severity Index (WSI) method. This study includes the identification of Accidental Black Spots and improving these Accidental Black Spots by using ATMS. This project emphasizes accident studies on the National Highway-216A (Diwancheruvu to Siddantham) in East Godavari District, State of Andhra Pradesh, India. So the main aim of this study is, therefore, to identify the major accident black spots on National Highway -16 and mitigation of Accidental Black Spots by using Advanced Traffic Management System. Keywords: Accident, National Highway, Black Spots, Advanced Traffic Management System (ATMS), Weighted Severity Index (WSI).
A Memory Based Current Algorithm for Pole-to-Pole Fault Detection in Microgrids
Authors: Srinivas Nirupama P , Modi Sangeeta
Published: May 2022

Abstract: The world’s growing attention to sustainable energy and development can be causal to the recently observed disrupt in the existing global power system networks. Moreover, an additional incentive towards this change are the challenges associated with the traditional power grid, including its rigid structure, aging architecture, and ecologically profligate nature. Modern power systems have observed a rapidly growing trend of decentralized energy generation in the recent past. A prominent structure incorporating decentralized energy generation and renewable energy are microgrids. While microgrids promote on-site generation and distributed energy resources (DERs), their unique characteristics of bidirectional flow of power, renewable generational intermittency, and varying levels of current causes challenges uncommon to the traditional grid. One of the vital challenges associated with microgrids is the protection of microgrids against faults and disturbances that can cause impairment to life and property. Conventional protection algorithms are ineffective in protecting the system from faults due to the unconventional topology of the microgrid. This paper attempts to contribute to work in the sector related to the protection of microgrids. This paper presents the pole-to-pole fault analysis of a hybrid photovoltaic system and presents a current based algorithm for the detection of DC pole-to-pole faults in the system under study. The protection algorithm is further verified on a hybrid Photovoltaic-Wind-Battery microgrid. Keywords: DC Faults, Hybrid Microgrids, Power Systems, Protection Algorithm, DERs
Real-time Driver Drowsiness Detection with Android
Authors: Pansare Dr. Jayshree , Deshpande Ranjeet , Shingare Shubham , Deokar Harshal , Manwar Piyush
Published: May 2022

Abstract: Major causes for the road accidents are Driver Fatigue and Distraction. Recently many driver monitoring systems have been proposed for monitoring driver activities to avoid accidents. Almost all the systems which exists till date are in the specialized embedded or hardware form, which are present in expensive and luxurious cars. This research paper presents a cost efficient approach to detect driver fatigue and monitor dizziness/drowsiness in real-time. An intelligent android app to monitor driver fatigue and distraction during travel using Adaptive Template Matching and Adaptive Boosting is achieved and implemented. Developing of technologies for preventing drowsiness is quite challenging in the area of accident avoiding systems. Preventing drowsiness during driving requires a method to accurately detect lowering of driver attentiveness and a method for alerting and to forewarn the driver. In this detection approach, we developed an android app that utilizes image processing technology and analyse all the images captured through the user’s phone camera. Drop of alertness is detected based on the degree to which the driver's eyes are open or closed. This application provides a non-contact method for judging various levels of driver awareness and enables an early detection of a reduction in attentiveness while driving. Keywords: Drowsiness Detection, Google vision API, Face detection, Eye Detection, Android application
Pengaruh Investasi, Angkatan Kerja, Pengeluaran Pemerintah dan Tingkat Pendidikan Terhadap PDRB Jawa Timur
Authors: Febrianto Alvaro Dimas , Arifin Zainal
Published: May 2022

Gross Regional Domestic Product (GRDP) is a reference of GRDP in a region, where if a GRDP value in a region increases, it indicates an increase in the production process of items and services. Investment, labor force, government expenditure, and educational level are some of the indicators that can influence the changes of GRDP value in a region. The aim of this study is to analyze how the influence of Investment, Labor Force, Government Expenditure (Capital Expenditure, and High School Education Level. This study was a quantitative study using multiple linear regression analysis with time series, which was analyzed with SPSS 26 software. The results of this study show that simultaneously, variables of Investment, Labor Force, Government Expenditure (Capital Expenditure), and High School Education Level significantly influence the GRDP in East Java Province in 1990-2020. The coefficient of determination (R2) shows that 80.3 percent of variables influence employment, and the remaining 19.7% is explained by other variables not examined in this study. Partially, Investment, Labor Force, Government Expenditure (Capital Expenditure), and High School Education Level significantly influence the GRDP in East Java Province.

Keywords: Investment, Labor Force, Government Expenditure (Capital Expenditure), High School Education Level
DISCIPLINE AND RESPONSIBILITIES CHARACTERS OF SENIOR HIGH SCHOOL(SMA) STUDENTS THROUGH PROBLEM BASED LEARNING ON TRANSPORT SYSTEM MATERIAL
Authors: Hanim Nafisah , Risna Irda , Putri Auriza Satria
Published: May 2022

The research aimed to know the development of discipline and responsibility character ofthe students at SMA Negeri 1 Suka Makmur Nagan Raya in biology subject on transport system concept through a problem based learning model. This research used descriptive qualitative method. The samples were students of class XI. Character values obtained from observations using a questionnaire instrument. Data were analyzed using the percentage formula. The result showed that there was a student's character development at each meeting, namely the value of discipline character at the first meeting with a percentage of 65 increased to 88 at the second meeting while the value of responsibility character at the first meeting with a percentage of 63 increased to 90 at the second meeting. It can be concluded that the problem based learning model can increase the value of discipline and responsibility character of the students at SMA Negeri 1 Suka Makmur Nagan Raya.
Implementasi Customer Service BRI Dengan Pemanfaatan News Media (Instagram) Untuk Meningkatkan Kepuasan Nasabah Dalam Masa Pandemi Covid 19
Authors: Iman Eki Chandra Nur , Natasya Adibah , Ramadhani Dita Pranawengkapti
Published: May 2022

The purpose of this study was to determine the application of BRI customer service by utilizing news media (Instagram) to increase customer satisfaction during the Covid-19 pandemic. The research approach used in this study is a quantitative approach. This research was conducted at Bank BRI. The sampling technique of this research is random sampling. Respondents in this study were 100 people who are customers of Bank BRI. The data analysis used a structural approach to the Equation Model (SEM) assisted by the smart PLS application. The results of this study are that customer service has a significant positive effect on customer satisfaction, customer service can increase engagement on social media/news media, Instagram news media has a significant positive effect on customer satisfaction.