bluuebunny/crossref_metadata_2025 huggingface dataset:
An Intelligent Sensor based Automatic Attendance Management System Using IoT
Authors: Meenakshi A. , Leelarani K. , Shopika S. , Rajasekaran M.
Published: January 2023

The need for intelligent and distributed monitoring systems based on sensor networks of diverse application systems is growing as a result of the field of industrial control in network applications developing so quickly. It is required to check the body temperatures and attendance when students and staffs visit schools and colleges during this COVID 19 pandemic. A solution is developed here for the purpose of tracking temperatures and attendance management using a smart thermometer without being in contact in order to keep social distance. The person (both staff and student) faces are captured by the ESP32 Camera for training and testing purposes. After the training is over, the ESP32 Micro Controller board registers the student or faculty facial image. For attendance purposes, the MLX90614 IR Temperature Sensor will measure the body temperature of students or instructors. Both the collected data and the email-based attendance notification will be transferred to the cloud using IoT. The message "Please leave the college and take care of your health" will be communicated to the person if their temperature exceeds the threshold level.
Credibility Evaluation of User-generated Content using Novel Multinomial Classification Technique
Authors: Gayakwad Milind , Patil Suhas , Joshi Rahul , Gonge Sudhanshu , Pande Sandeep Dwarkanath
Published: January 2023

Awareness about the features of the internet, easy access to data using mobile, and affordable data facilities have caused a lot of traffic on the internet. Digitization came with a lot of opportunities and challenges as well. One of the important advantages of digitization is paperless transactions, and transparency in payment, while data privacy, fake news, and cyber-attacks are the evolving challenges. The extensive use of social media networks and e-commerce websites has caused a lot of user-generated information, misinformation, and disinformation on the Internet. The quality of information depends upon various stages (of information) like generation of information, medium of propagation, and consumption of information. Content being user-generated, information needs a quality assessment before consumption. The loss of information is also necessary to be examined by applying the machine learning approach as the volume of content is extremely huge. This research work focuses on novel multinomial classification (based on multinoulli distribution) techniques to determine the quality of the information in the given content. To evaluate the information content a single algorithm with some processing is not sufficient and various approaches are necessary to evaluate the quality of content.  We propose a novel approach to calculate the bias, for which the Machine Learning model will be fitted appropriately to classify the content correctly. As an empirical study, rotten tomatoes’ movie review data set is used to apply the classification techniques. The accuracy of the system is evaluated using the ROC curve, confusion matrix, and MAP.
Affect Recognition in Human Emotional Speech using Probabilistic Support Vector Machines
Authors: Nelapati Ratna Kanth , Selvarajan Saraswathi
Published: January 2023

The problem of inferring human emotional state automatically from speech has become one of the central problems in Man Machine Interaction (MMI). Though Support Vector Machines (SVMs) were used in several worksfor emotion recognition from speech, the potential of using probabilistic SVMs for this task is not explored. The emphasis of the current work is on how to use probabilistic SVMs for the efficient recognition of emotions from speech. Emotional speech corpuses for two Dravidian languages- Telugu & Tamil- were constructed for assessing the recognition accuracy of Probabilistic SVMs. Recognition accuracy of the proposed model is analyzed using both Telugu and Tamil emotional speech corpuses and compared with three of the existing works. Experimental results indicated that the proposed model is significantly better compared with the existing methods.
Crptography based Lifi for Patient Privacy and Emergency Health Service Using IOT
Authors: Vithya V. T. , Chandrasekar M. P. , Suganthy M. , Hephzipah J. Jasmine , Sarala B. , Praveena N. G. , Perarasi M.
Published: January 2023

Medical care is one such region, where WIFI is as yet not utilized as the electromagnetic waves influences patients with sicknesses like neurological problems, diseases and so forth. Accordingly, LIFI can be respected the following large thing, as it represents no gamble to patients and offers more advantages than WIFI, such as faster speeds and a larger spectrum. The only issue that hospitals have while exchanging data through it is ensuring confidentiality. The methodology proposed here leverages Secure Hash Algorithms to give maximum security as a solution to this challenge. The Secure Hash Algorithm is a bonus feature that is mostly utilised for authentication. IoT connects physical devices such as sensors and actuators to networks. The programming routines can be visualised from any location thanks to cloud storage. These algorithms can be employed in a variety of applications, including smart homes, digital technologies, and banking systems. This research presents a model that takes into account a human's heart rate, glucose level, and temperature. In the even to fan emergency, adjacent hospitals are alerted to the patient's condition, allowing them to provide timely and correct care. This will save you from having to go to the hospital. Temperature, blood pressure, heart rate, gas sensor, and fall detection are among the vital signs monitored by the system. An Arduino controller and a GSM900Amodule make up the system design. The monitored values can be supplied via mobile phones, and if an abnormal state is detected, the buzzer is activated, and the information is communicated to the concerned members via the mobile app.
A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks
Authors: K Priyadarsini , G Saranya V , S Karthik
Published: January 2023

The wireless sensor network (WSN) consists of a large number of randomly distributed nodes capable of detecting environmental data, converting it into a suitable format, and transmitting it to the base station. The most essential issue in WSNs is energy consumption, which is mostly dependent on the energy-efficient clustering and data transfer phases. We compared a variety of algorithms for clustering that balance the number of clusters. The cluster head selection protocol is arbitrary and incorporates energy-conscious considerations. In this survey, we compared different types of energy-efficient clustering-based protocols to determine which one is effective for lowering energy consumption, latency and extending the lifetime of wireless sensor networks (WSN) under various scenarios.
Analysing the Security Aspects of IoT using Blockchain and Cryptographic Algorithms
Authors: Verma Rajat , Dhanda Namrata , Nagar Vishal
Published: January 2023

Technological advancement is a never-ending field that shows its evolution from time to time. In 1832, with the invention of the electromagnetic telegraph, the era of the Internet of Things (IoT) began. Within the time of 190 years, this technological domain has revolutionized IoT and made it omnipresent. However, with this evolved and omnipresent nature of IoT, many drawbacks, privacy, interoperability, and security issues have also been generated. These different concerns should be tackled with some newer technologies rather than the conventional ones as somehow, they are only the generator of those issues. Outdated Security could be an appropriate issue of IoT along with the centralized point of failure. It also possesses more concerns and challenges to tackle. On the other side, there is a visible solution to address the challenges of IoT in this developing domain of technology. The visible approach is Blockchain which acted as the backbone in securing Bitcoin in 2008, which was created by the pseudo group named Satoshi Nakamoto. Blockchain has evolved from Blockchain 1.0 to Blockchain 4.0 as the latest one depicts its amalgamation with another component of Industry 4.0 i.e., Artificial Intelligence (AI). AI will give the ability to think logically and like humans. In addition to this SMART solution, there is also an advanced cryptographical technique known as the Elliptic Curve Digital Signature Algorithm (ECDSA) which can enhance the security spectrum of IoT if applied appropriately. This paper produces a vision to enhance and optimize the security of IoT using a network peer-to-peer technology Blockchain along with advanced cryptography.
Machine Learning-Based Hybrid Recommendation (SVOF-KNN) Model For Breast Cancer Coimbra Dataset Diagnosis
Authors: Barwal Ravi Kumar , Raheja Neeraj , Bhiyana Malika , Rani Dimple
Published: January 2023

An effective way to identify breast cancer is by creating a prediction algorithm using risk factors. Models for ML have been used to improve the effectiveness of early detection. This article analyses a KNN combined with singular value decomposition and Grey wolf optimization(GWO) method to give a detection of breast cancer(BC) at the early phase depending on risk metrics. The SVD technique was utilized to eliminate the reliable feature vectors, the GW optimizer was used to select the feature vectors, and while KNN model was used to diagnose the BC status. The proposed hybrid recommendation model (SVOF-KNN) for BC prediction's main objective is to give an accurate recommendation for BC prognosis through four different steps such as;BCCD dataset collection, data pre-processing, feature selection, and classification/recommendation. It is implemented to classify the consequence of risk metrics connected withregular blood analysis(BA) in the BCCD database. The aspects of the BC dataset are insulin, glucose, HOMA, Leptin, resistin, etc. The error categories such as RMSE and MAE are used to calculate the exception values for each instance of the BC dataset. It hybrid model has recommended the best score instance having the minimumexception rateas the defined features for BC prediction. It improves significance in automatic BC classification with the optimum solution. The hybrid recommendation model (SVOF-KNN) also recommends the accurateclassification method for BC diagnosis. The results of this work shall enhance the QoS in BC care.
Machine Learning Approach for Prediction of the Online User Intention for a Product Purchase
Authors: Kumar Anubhav , M Dileep Kumar , Macedo Víctor Daniel Jiménez , Mohan B R , N Achyutha Prasad
Published: January 2023

The deployment of self-learning computer algorithms that can automatically enhance their performance via experience is referred to as machine learning in ecommerce and is a crucial trend of the retail digital transformation. Machine learning algorithms can be unambiguously trained by analysing big datasets, identifying repeating patterns, relationships, and anomalies among all of this data, and creating mathematical models resembling such associations. These models are improved when the algorithms analyse ever-increasing amounts of data, providing us with useful insights into specific ecommerce-related events and the links between all the variables that underlie them. A tool that has been quite effective in studying current affairs, predicting future trends, and making data-driven decisions. The present work investigates the implementation of machine learning algorithms to predict the user intention for purchasing a product on a specific store's website. An Online Shoppers Purchasing Intention data set from the UC Irvine Machine Learning Repository was used for this investigation. In this study, two classification-based machine learning algorithms i.e. Stochastic Gradient Descent (SGD) algorithm and Random Forest algorithm were used. SGD algorithm was used for first time in prediction of the online user intention. The results showed that the Random Forest resulted in the highest F1-Score of 0.90 in contrast to the Stochastic Gradient Descent algorithm.
The 2020 Constitutional Reform: An Independent Constitutional and Legal Status of Commercial (Arbitrazh) Courts being fixed for the First Time
Authors: Sviridenko O. M.
Published: January 2023

The paper analyzes the interim results of the 2020 constitutional reform, which affected the foundations of the judiciary in the territory of the Russian Federation. The author assumes and justifies that there is a change in priorities and vectors of legislative work in the field of commercial (arbitrazh) procedural legislation. Based on the analysis of the history of the creation of commercial (arbitrazh) courts, the author makes a conclusion about the formation and development of commercial (arbitrazh) courts as an independent procedural form of the exercise of judicial power in modern Russia. An assessment of the role of Professor V.F. Yakovlev in the creation of commercial (arbitrazh) courts in Russia is given. The author notes the importance of fixing the constitutional and legal status of the system of commercial (arbitrazh) courts. The author shares the opinion, which is of enormous theoretical and practical importance, that the activity of commercial (arbitrazh) courts is a form of exercising judicial power both in the sphere of civil and administrative proceedings. In the context of the problem of a possible «absorption» by the unified Civil Procedure Code of the Russian Federation, including the Commercial (Arbitrazh) Procedure Code, the adoption of amendments to the Constitution reduces such a threat. The author concludes that the rules of commercial (arbitrazh) procedural law, being improved, undergoing different editions, allowing for disputes and discussions at the scientific and practical level, have been preserved as an independent branch of law. At the same time, these rules are, along with the Constitution of the Russian Federation, the fundamental basis of the independent legal status of the commercial (arbitrazh) courts system.
The Use of Catastrophe Theory in Forensics
Authors: Korma V. D.
Published: January 2023

The modern theory of catastrophes contributes to the understanding of dynamic situations that govern the evolutionary development of natural phenomena, society, and man, as well as the prediction of the instability of various dynamic systems that can have catastrophic consequences. The results of the development of this theory are widely used in various fields of knowledge: in physics, biology, economics, medicine, psychology, linguistics, ecology and other sciences. The paper attempts to use the theory of catastrophes in forensic science, in particular, in the investigation of criminally relevant incidents of a man-made nature related to professional activities, which are inherently a destructive product of the functioning of various dynamic systems. First, the theoretical aspects of the theory of catastrophes are briefly outlined, the main concepts and their classifications are considered (catastrophe, man-made disaster, man-made emergency, emergencies, man-made sources of increased danger, etc.), which are important for developing a methodology for investigating man-made crimes related to professional activities. In order to improve the efficiency of the investigator’s recognition activity in establishing the cause of the crime under investigation (man-made disaster), the author proposes to use schemes (probabilistic models) obtained using the techniques for constructing the so-called fault and event trees, addressed primarily to specialists associated with the operation of technical systems and supervision behind them. According to the author, this will contribute to the effectiveness of putting forward investigative leads in a criminal case and their verification.
The results of treatment of newborns with right-sided and left-sided intrathoracic localization of the liver with diaphragmatic hernia
Authors: Mokrushina Olga G. , Razumovskiy Alexandr Yu. , Yudina Elena V. , Afukov Ivan I. , Shumikhin Vasiliy S. , Smirnova Svetlana V. , Zilbert Elena V. , Petrova Lubov V. , Erokhina Nadezhda O. , Halafov Rashid V. , Svetlichnaya Tatyana O.
Published: January 2023

BACKGROUND: The right-sided congenital diaphragmatic hernia is the rare pathology. Results of diagnostics, prognosis and treatment usally published as a collection of cases.
AIM: Comparition of treatment results of congenital diaphragmatic hernia with the liver as its content in dependancy of the side.
MATERIALS AND METHODS: We present a retrospective analysis of 50 newborn patients with congenital diaphragmatic hernia. Patiens were divided in two groups, first with right-sided (19 patients), and second with left-sided hernia (31 patients). Groups were compared by gender and weigth. Comparition criteria was the results of prenatal and postnatal diagnostics, intraoperative data, postoperative period, complications and outcomes.
RESULTS: We found predominance of prenatal diagnosis in the second group (48% vs 84%, p = 0,001). The lung-to-head circumference ratio were the same in both groups (0,52 in first, 0,46 in second, p = 0,058). Chance to use thoracoscopic approach in the second group was higer in 5,7 times (48% vs 84%). Postoperative period was easier in the group of right-sided congenital diaphragmatic hernia: artificial ventilation lasted on average 8 days (min 3; max 28) versus 11 (min 4; max 50) days in the first group (p = 0,036).
Hospital stay was significantly lower in the second group 18 days (min 12; max 28), versus 50 days in the first group (min 13; max 64), p = 0,011. Recovery chance in patients with right-sided hernia was higher (45% vs 79%, confidence interval 0,0590,814).
CONCLUSIONS: Every type of diaphragmatic hernia, including right-sided location, need to be the subgect of research of high compitantive center. Prognostic criteria for right-sided congenital diaphragmatic hernia require furter advanced study, wich is possible only in case of concentration of patients in the same center.
Pneumothorax in newborns with multisystem inflammatory syndrome associated with COVID-19: a case reports
Authors: Shangareeva Roza K. , Absalyamova Nursilya T. , Fedorova Regina R. , Tikhonova Irina V. , Mukhamedova Rano Kh. , Alibaev Aibulat K. , Minibaeva Gulfiya I.
Published: January 2023

Currently, there is more and more data on new manifestations of COVID-19, such as multisystem inflammatory syndrome in children, which occurs with severe complications, among which cases of pneumothorax have been recorded.
The article presents the experience of treating 4 newborns with a new coronovirus infection who were admitted to the clinic during 2021. In all clinical cases, children were born to mothers with a burdened obstetric history. All children had a positive RNA polymerase chain reaction for SARS-CoV-2. Children were admitted with signs of respiratory, cerebral insufficiency, gastrointestinal syndrome and metabolic disorders. The clinical picture and laboratory data corresponded to the definition of a multisystem inflammatory syndrome and was characterized not only by lung damage, but also by changes in other organs. Pneumothorax was diagnosed on days 1521. In all children, a tension pneumothorax developed on the right, in the first two cases against the background of mechanical ventilation, in the remaining two with spontaneous breathing with additional oxygenation. In one case, the pneumothorax was bilateral. Drainage of the pleural cavity in three children was carried out according to Bulau and in one case with active aspiration. Pneumothorax resolved after 414 days. Computed tomography of the chest, performed during the period of rehabilitation treatment, shows pronounced sclerotic and bullous changes in the lung parenchyma. All patients were discharged from the hospital in a satisfactory condition.
Since in all the above cases, pneumothorax occurred in newborns with a burdened obstetric history of mothers, it is difficult to differentiate the occurrence of pneumothorax associated with the underlying disease, the course of labor, complications of therapy, from the disease associated with COVID-19. Stronger evidence is needed from larger datasets and rigorous analysis.
Health related behaviour changes in pregnant women during COVID-19 pandemic
Authors: Dutta Indrani , Usha Madhulika Horo
Published: January 2023

Background: Pregnancy associated anxiety and depression is very well known for its prevalence. Pandemic like COVID-19 all the more is additive to the levels of anxiety and depression during pregnancy, especially for mothers who are concerned about feto-maternal wellbeing. This study makes an effort to analyze the health-related behavior changes and psychological impact of pregnant women after COVID-19 outbreak.
Methods: Cross sectional, questionnaire-based study conducted on pregnant ladies visiting labor room and out-patients department RIMS, Ranchi from April 2020 to September 2020.
Results: Most patients were primigravida and turned up only in third trimester. Pregnancy complications like heart disease, GDM, jaundice, PIH were present in 28% of participants. 48% participants had no family income during pandemic. The 92% women wore masks, 80% practiced social distancing, 72% practiced frequent handwashing, 72% practiced frequent handwashing during pandemic, 80% had no regular antenatal check-up. Almost 64% participants showed mild to moderate anxiety, 34% had moderate depression and 40% had moderate stress. Four percentages had severe anxiety, 2% had severe depression and 12% had severe stress. Usage of mask was inversely related to GAD7 scores, but had no correlation with EPDS scores. Rest parameters like frequent handwashing, social distancing, stressful behavior, not going out and frequent handwashing were directly related to GAD 7 and EPDS score.
Conclusions: Mental health and preventive behavior of respondents could be attributed to socio demographic, social, situational, economic status, family conditions and perception of severity of Covid19.
First metatarsal bone reconstruction using Masquelet’s technique after bone loss in open III B injury
Authors: Tanveer Ahmed Bhat  , Pallav Gupta  , Lone Zubair Ahmad Lone , Mohammed Farooq Butt  , Abdul Ghani  , Sanjeev Gupta
Published: January 2023

Background: Masquelet technique involves two stages for reconstruction of bony defects. During stage one decontamination and debridement is performed. The bone defect is filled by a spacer made of bone cement. After a gap of around 6 weeks, a bio-membrane is established around the cement spacer. During stage two, the cement spacer is removed and cancellous autologous bone graft is used to fill the space that was previously occupied by the cement spacer. However, there is a huge scarcity of literature on reconstruction of bone defects in foot metatarsals, especially open injuries that require soft tissue coverage also.
Methods: This prospective study involved 25 patients with a minimum follow-up of 12 months. Masquelet’s technique was used to reconstruct large bony defects in metatarsals of foot in a staged manner. The primary outcome variable was union and consolidation of the bone. The secondary outcome variables included complications and functional outcome using Maryland foot score. 
Results: One of the patients needed a below knee amputation for extensive bone and soft tissue infection. Pin site infection was the commonest indication observed and deep infection was observed on table at the time of second stage in two patients. Both the patients needed a re-do of stage one and a new cement spacer was placed which was removed at six weeks. Hallux varus deformity was observed in two patients at the final follow-up. Excluding the patient that needed amputation, all the patients had consolidation and union at the final follow-up and the mean Maryland foot score was 79.45±8.8. Good to excellent functional outcome was observed among 91.66% patients.    
Conclusions: Masquelet’s induced membrane technique is a potentially fruitful method to deal with bone defects created by open fractures of metatarsals of feet. However, due to limited sample size and lack of control group, we recommend large scale randomized control trials be conducted on the subject.
Knowledge, attitude and practice of health care workers towards COVID-19 vaccination
Authors: Sharma Kavita , Raina Alok , Sharma Preeti
Published: January 2023

Background: A sound knowledge about vaccination against coronavirus disease-2019 (COVID-19) among health professionals is of great importance in spreading right information to general population. Aim of the study was to find the level of knowledge, attitude and practice (KAP) of health professionals towards COVID-19 vaccination.
Methods: This observational study based on questionnaire done in two district hospitals of North India. Following questionnaire’s content validity, printouts of questionnaire were distributed among the healthcare workers. The assessment was made by a scoring scheme for KAP. The statistical analysis done using SPSS software and Spearman’s rank co-relation used to calculate the correlation between KAP.
Results: Total 300 subjects participated in study. Social networking platform was the major source for acquiring information about COVID-19 vaccination among paramedical staff while the source of knowledge for doctors was mainly scientific websites.62.67% had moderate knowledge, 88% had positive attitude towards vaccination and 73% showed good practice. There was significant difference of KAP towards vaccine between doctors and paramedics.
Conclusions: In most of health care workers level of knowledge towards COVID-19 vaccination was found to be moderate and attitude was predominantly positive. Adequate knowledge and positive of health professionals are very important for increasing the acceptance of vaccination in general population.
Academic stress and coping in high school adolescents
Authors: Pillai Jitesh , Jose Soumya , A. Velukutty Bijumon , Riyaz A.
Published: January 2023

Background: Education stress is widely recognized as one of the most important precursors leading to depression in adolescent life. This study explores the prevalence of academic stress among high school going adolescents, contributing factors and the coping strategies used by students. The finding of this study aids the teaching institutes to better the understanding of the stress due to present teaching methods.
Methods: A cross-sectional study was conducted in 2020 at both private and government schools of Kozhikode, Kerala. 371 students were selected randomly. A questionnaire was developed incorporating educational stress scale for adolescent (ESSA), academic stress scale (ASC) and simplified coping styles questionnaire (SCSQ).
Results: 70.8% students have minimal stress, 25.8% moderate stress, 0.002% high stress, 0.02 did not have stress. Female participants experienced more stress compared to male participants (p value=0.04). Participants with less educated father (p value <0.001) and with less educated mother (p value <0.001) experienced more stress. Last year final exam grade (p value=0.005) and parental pressure (p value=0.008) were important factors contributing to stress. With regard to deployment of coping strategies 0.5% never used any coping strategies, 53.6% students used coping occasionally, 45% often used coping, 0.8% used coping frequently.
Conclusions: Most of the children studying in high school have minimal to moderate stress. The main factors that contribute to stress more are female gender, low parental education level, and poor final exam grade. Positive association for factors like parental pressure with increasing age was present. Most of the students used different coping strategies to cope with the education stress. Students often use active coping strategies compared to passive coping strategies.
Breastfeeding practices among mothers attending a tertiary care hospital in Kashmir
Authors: Ain Syed Najmul , Qulsum Reyana , Rizwan Amtul
Published: January 2023

Background: According to world health organization (WHO), exclusive breastfeeding (EBF) for the first 6 months of life is vital for optimal growth and development of a child. During this period, other liquids or breastfeeding substitutes should not be given to infants except for medicine or oral rehydration solution.
Methods: This cross-sectional study was conducted in the child health clinic of the department of community medicine, SKIMS. The study participants were mothers accompanying their infants coming for immunisation at the child health centre. A semi-structured, questionnaire was used to interview the mothers regarding breast feeding practices of their infants. The data was entered in Microsoft excel 2010 and analysed using SPSS Version 20.
Results: The prevalence of EBF was 38.7%. Mixed feeding was received by 54% and 7.3% were formula-fed. Variables that were significantly associated with EBF include residence and mother’s education. Infants from rural area were more likely to be exclusively breastfed compared to those from urban area (OR=0.365; 95% CI=0.166-0.802; p=0.012). Mothers with up to 9 years of formal education were more likely to exclusively breastfed their children than those with more than 9 years of formal education (OR=0.300;95% CI=0.121-0.744, p=0.009).
Conclusions: To ensure that the rate of EBF among the mothers is increased, all the stakeholders (spouse, family and government) as well as the people at work place must play their part to the best extent.
Study on adverse events following immunizations among COVID-19 vaccine recipients at a tertiary care hospital in Kashmir valley
Authors: Shah Rohul Jabeen , Qulsum Reyana , Ahmad Javeed
Published: January 2023

Background: Adverse events following immunization (AEFI) is an event of unexpected medical emergency occurring after vaccination without any causal association with vaccination. It can be any unintended, abnormal laboratory finding or anything. The present study was conducted to evaluate the incidence and severity of AEFI associated with the COVID-19 vaccines.
Methods: All the beneficiaries who had received two doses of Covishield and Covaxin vaccine from SKIMS Soura and provided consent were included in this prospective study. Each beneficiary was contacted telephonically. A self- designed questionnaire was used to interview them. The beneficiaries were contacted twice. The data was entered into and analysed using SPSS version 20.
Results: A total of 267 participants (52.3%) reported at least one of the AEFI following Covaxin vaccine. It was found that participants with AEFIs following the first dose had more chances to develop them following its second dose and this difference was found to be statistically significant (OR=6.8, p=0.0001). A total of 670 participants (38.0%) reported at least one of the AEFI following Covishield vaccine. The incidence of AEFIs was more after the first dose (31.6%) than that of the second dose (6.4%) and this difference was found to be statistically significant (p<0.0001).
Conclusions: Most of the AEFI are minor and can be managed symptomatically. Therefore, these AEFIs should not be a hurdle for vaccination.
La resiliencia climática en el sector de agua y saneamiento en América Latina y su relación con la emisión de bonos verdes
Authors: Concha Paulina , Aguilera Julio César
Published: January 2023

El objetivo de esta nota técnica es dar visibilidad a los requisitos, importancia y beneficios que tiene la planeación e inversión en proyectos centrados en la adaptación climática y el aumento de resiliencia para las empresas prestadoras de servicios de agua y saneamiento (referidas aquí como empresas de AyS).
Estudio exploratorio sobre la ansiedad por la salud en universitarios colombianos durante el confinamiento por la pandemia del COVID-19 en el segundo semestre del 2020
Authors: Castañeda-Quirama Tatiana , Restrepo Jorge Emiro , Zambrano-Cruz Renato
Published: January 2023

Introducción: la ansiedad por la salud es un estado psicológico caracterizado por cierto tipo de creencias, emociones y actitudes hacia la posibilidad de contraer una enfermedad. La ansiedad por la salud ha sido considerada un mediador de la respuesta psicológica ante la pandemia generada por el COVID-19. Objetivo: determinar el nivel de ansiedad por la salud de una muestra de estudiantes universitarios colombianos, discriminando y comparando en función de ciertas variables sociodemográficas, y describir sus principales características durante el confinamiento social en el segundo semestre del 2020. Metodología: se realizó un estudio cuantitativo, no experimental, de nivel descriptivo y corte transversal en una muestra de 1004 estudiantes de pregrado de 3 instituciones de educación superior de la ciudad de Medellín. Se utilizó el Inventario Breve de Ansiedad por la Salud. Resultados: el valor de la media para la ansiedad por la salud estuvo por encima del valor reportado por otros estudios. Se encontraron altos porcentajes de preocupación por la salud (39,64 %), consciencia del malestar/dolor (63,3 %), miedo de tener una enfermedad grave (20,01 %), interés por las sensaciones o cambios corporales (68,92 %), riesgo de padecer una enfermedad grave (30,33 %) y consecuencias sobre la vida (35,75 %). No se encontraron diferencias estadísticamente significativas en ninguna de las comparaciones entre grupos. Conclusiones: la preocupación por la salud y la ansiedad durante las epidemias/pandemias pueden tener un impacto psicológico importante, además de estar relacionadas con un comportamiento preventivo ineficaz y tener consecuencias adversas en el largo plazo.
Accidente lonómico leve atribuido a la oruga de la especie Lonomia obliqua en el departamento de Santander, Colombia, 2021
Authors: Villabona-Rosales Sergio Alberto , Amaya-Muñoz María Camila , Amaya-Muñoz María Juliana , Acero-Gomez Joaquin Alonso , Rodriguez-Vega Kevin Armando
Published: January 2023

Las orugas del género Lonomia, del orden Lepidoptera y familia Saturnidae, son de interés médico en Sudamérica por ser causantes del lonomismo, tipo de envenenamiento que aumenta cada vez más en Colombia, con tasas de mortalidad de 2,5 %. La severidad es variable y los casos no son de notificación obligatoria, lo que lleva a un subregistro de estos eventos. Se presenta el caso de una mujer adulta joven, quien acude a urgencias por la picadura de 20 orugas Lonomia en la palma de la mano izquierda; presentó signos locales inflamatorios, dolor y limitación de la movilidad de la mano. Se hospitalizó por tres días, se clasificó como leve y se trató con analgesia y antihistamínico endovenoso, lo que logró favorable evolución. El envenenamiento por oruga Lonomia es una urgencia que puede ser mortal, por tanto, es importante que se conozcan estos eventos en la literatura para su adecuado abordaje.
“Here it was waiting for me:” Diabetes Diagnosis Pathways and Implications for Health Policy
Authors: Chard Sarah , Girling Laura , Harris‐Wallace Brandy , Henderson Loren , Roth Erin G. , Eckert J. Kevin
Published: January 2023

Diabetes in older adults is a growing public health concern with nearly 30% of Americans 65 and older having diabetes. This includes 2.6 million older adults with undiagnosed diabetes who are at high risk of microvascular and cardiovascular complications (Centers for Disease Control and Prevention, 2022). The majority of cases are Type‐2 diabetes. The past decade has witnessed an expansion in screening recommendations in an effort to reduce rates of undiagnosed older adults. Drawing on the sociology of diagnosis, we suggest further attention to the social factors that shape the diagnosis process is needed. We examine the diabetes diagnosis process from the perspective of older adults with type 2 diabetes. The data derive from diabetes illness narrative interviews with non‐Hispanic White and African American older adult men and women (age ≥50) with type 2 diabetes (N=83). Our thematic analysis reveals four pathways to diagnosis: 1. Annual wellness exam, 2. Workplace screening, 3. Community‐based opportunities, and 4. Health event or alarm. Diabetes' early symptoms are often normalized within daily life, with health insurance gaps, providers' dismissal of symptoms, and nonprescription medications reinforcing efforts to address initial symptoms within the home. Wellness visits, as well as worksite and community‐based screening, critically intercede in the unfolding of symptoms. In contrast, diagnosis in connection with a health event or alarm carries an additional toll on social and emotional well‐being. These findings have implications for national screening policies and local diabetes control efforts.
Improving the Performance of Organic Photovoltaic Panels by Integrating Heat Pipe for Cooling
Authors: Magdi Joseph , Samy Irene , Mina Ehab
Published: January 2023

A new photovoltaic technology is manufactured from an organic material that easily degrades in nature. Unfortunately, organic photovoltaics suffer from low thermal stability and lower power conversion efficiency compared with silicon-based photovoltaics. Cooling is critical in this type of photovoltaic because of these factors. This research investigates a new method to cool this organic photovoltaic with a heat pipe to achieve a minimum operating temperature and maximum temperature uniformity, the heat pipe design is fixed, and the number of cells served by a single heat pipe is studied. For each case, the temperature distribution is plotted, and the maximum and the range in the temperature distribution are recorded, respectively, as a measure of the cell's performance. The temperature of the cell is evaluated numerically using COMSOL 5.6 Multiphysics™ software with and without the heat pipe. The electrical performance was estimated in both cases using GPVDM™ software. Consequently, the combined system of panel and cell reaches a maximum thermal stability at a minimum temperature of 33.4℃ instead of 52℃ without a heat pipe, which improves the electrical performance and the power conversion efficiency by 0.24%.
Mixed Convection Flow and Heat Transfer of Two Rotating Cylinders in a Trapezoidal Enclosure Filled with Porous Medium
Authors: Alshuraiaan Bader
Published: January 2023

The goal of this research is to investigate numerically mixed convection flow and heat transfer characteristics from two rotating cylinders in a trapezoidal enclosure filled with porous material for a variety of factors including rotation speed and direction, Richardson number, and the location of the cylinders. The results of this presentation were checked against accessible data and determined to be very similar. The heat transmission properties within the trapezoid were found to be substantially dependent on the Richardson number, speed, and direction of the spinning cylinders, as well as the location of the cylinders according to the findings of this study. Furthermore, it was discovered that the CW-CW casing produced more heat transfer as compared to the CCW-CW scenario for various Richardson numbers when the cylinders placed vertically. Furthermore, this research revealed that, for higher Richardson values, the rotation speed has no effect on the heat transfer increase inside the trapezoidal enclosure. The effect of the cylinders’ location on the average Nusselt number was also studied in this investigation. It was found the placing the cylinders in the vertical direction produced higher heat transfer compared with horizontal location for a trapezoid heated from below.
NOx Emission Prediction Based on SSA-DELM via CFD and DCS Data Fusion
Authors: Lv Manli , Zhao Jianping , Cao Shengxian , Tang Zhenhao
Published: January 2023

The objective of this study was to obtain NOx emission prediction model at the inlet selective catalytic reduction (SCR) reactors, which was the basis of combustion optimization and denitrification treatment. A deep extreme learning machine (DELM) optimized by the sparrow optimization algorithm (SSA) was adopted to establish the NOx model based on data fusion of Computational Fluid Dynamics (CFD) simulation and Distributed Control System (DCD). The mechanism analysis and XGBoost algorithm was used to select input variables. The results show that the XGBoost-SSA-DELM-based prediction model has high prediction accuracy with mean absolute error of 2.54 mg/m3. The results of this study have important implications for research on improving combustion efficiency and reducing pollutant emissions.
Chemical Reaction Effects on of Nanofluid Past a Permeable Stretching Sheet with Slip Boundary Conditions and MHD Boundary Layer Flow
Authors: Vijaya Kolli , Lavanya Bommanna
Published: January 2023

The overall exploration is excited to investigate the MHD limit layer float of a nanofluid with the results of attractive field, slip limit situation, warm radiation and synthetic reaction has been researched. Closeness change is utilized to change over the administering non-straight limit layer conditions into coupled better request non-direct normal differential conditions. those conditions are mathematically addressed utilizing fourth request R-k technique alongside shooting strategy. An assessment has been accomplished to explain the outcomes of overseeing boundaries like assorted materially conditions. Mathematical results are gotten for the speed, temperature and mindfulness, as well as, for the pores and skin rubbing, close by Nusselt reach and neighborhood Sherwood range for a few benefits of overseeing boundaries. The mathematical results are talked about through graphically and referenced subjectively.
Prevention of Occupational Diseases in Small and Medium-Sized Manufacturing Enterprises in Quebec (CANADA)-Portrayal of Elements Influencing OHS Performance
Authors: Randrianarivelo Fara , Badri Adel , Gauthier François , Boudreau-Trudel Bryan
Published: January 2023

Unlike workplace accidents, occupational diseases are often underestimated and underreported since their effects appear gradually over time. They are even on the increase in the province of Quebec (Canada), especially in small and medium-sized enterprises (SMEs), where they are less likely to receive medical attention. The aim of this four-stage study is therefore to describe how prevention of occupational disease is practiced in this type of business and identify a way forward to improve the protection of worker health and well-being in Quebec. The present article focuses on the first two stages, namely reviewing the literature to catalog the elements of prevention and identifying the most relevant elements. Stages 3 and 4, in which gathered field data on the application of these elements and analyzed their relative effectiveness using descriptive statistics, are reported in Part 2 [1]. Despite the limitations of this research method, we portray in detail the elements that appear to have the most influence on occupational disease prevention in small to medium-sized manufacturing enterprises, and thus identify the strengths and weaknesses of occupational health and safety performance in this setting.
Technologies for Responding to the Main Challenges of Ensuring the Safety of the Engineering Migrant Workers in the System of Migration Security
Authors: Lesko Nataliia , Lukianova Halyna , Rym Olena , Ranevych Orest , Buk Myroslava
Published: January 2023

The engineering sector of the economy is growing rapidly and in many Eastern European countries, supply and demand are only going up. The terrible events of the pandemic and military actions in the very center of Europe led to mass labor migration of the population. For scientists and practitioners, the question arose of finding ways to ensure safety for them and the formation of proper safe working conditions in new regions with new challenges. This determined the relevance of the research topic. The main goal of the study is the application of mathematical technologies to counteract the main challenges that negatively affect engineering migrant workers in terms of security. The methodology implies the use of modeling methods with the flexibility to change the basic parameters. Based on the results of the analysis, we presented several models to counteract the negative impact of the main challenges faced by engineering labor migrants in modern conditions. The study has a number of limitations and concerns the use of modeling technology for only one region as an example. Further research should concern not only an individual worker in the field of engineering but also entire engineering enterprises.
Fake News Detection in the Medical Field Using Machine Learning Techniques
Authors: Murugesan Sudhakar , Pachamuthu Kaliyamurthie
Published: January 2023

In today's world, fake news is the biggest and most challenging problem in the natural world environment. This type of fake news will create many problems in society, especially in the medical field. This research aims to detect automatic phoney news in the news. The following machine learning algorithm will help us to see phoney medical information based on dataset 1. KNN, 2. Naive Bayes, 3. Support Vector Machine, 4. BERT and 5. Decision tree, but the Decision tree will provide better accuracy. Findings: Performance measures such as accuracy, precision, recall, and f1-score showed 98.5% accuracy of our proposed Adaboost & Decision Tree algorithm. In this research work, we introduced and implemented the Proposed Ensembling (Adaboost & Decision tree) and achieved better accuracy. We collected and trained the dataset to identify misinformation in the medical area.
Analytical and FEM Methods for Line Start Permanent Magnet Synchronous Motor of 2.2kW
Authors: Duc Hung Bui , Minh Dinh Bui , Quoc Vuong Dang
Published: January 2023

This paper has developed electromagnetic equations based an analytical model to design a three-phase line start permanent magnet synchronous motor (LSPMSM) of 2.2 kW. In order to enhance the torque and efficiency of this machine, an optimized slot shape of rotor permanent magnet is proposed. The analytical model is first presented to evaluate the magnetic characteristics, and then analytical expressions are derived under the open circuit condition. The influence of the magnet size variables on the analytical model is considered to investigate the magnetic leakage flux and flux density distribution in air gaps. Moreover, the variation of design has a significant impact on the steady-state performance characteristics of this motor. In addition, in order to check the output results from the analytical model, a finite element method is developed to evaluate these solutions. Finally, experimental and simulation results have been compared and analyzed to validate the development of method.
Optimization and Performance Analysis of Fractional Order PID Controller for DC Motor Speed Control
Authors: Ibrahim Entidhar K. , Issa Abbas H. , Gitaffa Sabah A.
Published: January 2023

Multi-Agent System (MAS) technology is one of the cores and promising areas in the field of Artificial Intelligence (AI) as well as in the stream of Computer Science. The technology is comprised of multiple decision-making agents that exist in an environment to achieve common or conflicting goals. Multi-Agent System technology has a rapid growth and evolution due to its marvelous features such as flexibility and intelligence that are very useful when solving complex distributed problems. This paper focuses on the history and evolution of MAS technology, present applications, and future trends by addressing more detailed explanations about the foundations or key principles of Multi-Agent System technology such as agents, agent taxonomy, agent communication approaches, MAS development frameworks as well as the history of agent technology. The goal of this paper is to provide broad and comprehensive knowledge about Multi-Agents System technology.