bluuebunny/crossref_metadata_2025 huggingface dataset:
Correlaciones y análisis de sendero entre características del fruto y la semilla de Benincasa hispida [(Thunb.) Cogn.]
Authors: Espitia Camacho Miguel M. , Araméndiz Tatis Hermes , Cardona Ayala Carlos E.
Published: May 2022

Las correlaciones y el análisis de sendero son estrategias importantes para mejorar la selección de características agronómicas de interés comercial en diversos cultivos. El objetivo de este trabajo fue estimar las correlaciones entre 14 características biométricas del fruto y la semilla, y el análisis de sendero para el peso del fruto en B. hispida. Se evaluaron 10 familias de hermanos medios, en un diseño completamente aleatorizado con cinco repeticiones. El peso del fruto mostró correlaciones fenotípicas significativas directas con grosor de la pulpa, largo del fruto, ancho del fruto, número de semillas, cavidad semilla y peso de semillas, cuyos coeficientes oscilaron entre 0,64* y 0,91**, respectivamente. El largo de semilla presentó asociación directa significativa con volumen de una semilla y el peso de una semilla, con registros de 0,66* y 0,83**, respectivamente. El ancho de semilla y el volumen de una semilla acusaron correlación de 0,88**, mientras que la densidad de una semilla presentó correlación inversa significativa con el ancho de semilla y el volumen de una semilla, con registros de -0,73* y -0,89**. Los efectos indirectos explicaron principalmente la correlación significativa del peso del fruto con las variables ancho del fruto, cavidad semilla, peso de semillas y número de semillas. El largo del fruto presentó los mayores efectos directos e indirectos sobre el peso del fruto. El peso del fruto y largo del fruto, pueden ser usados en la selección de B. hispida para la obtención de genotipos con mayor peso y número de semillas por fruto.
Effect biological life factors on pregnant woman
Authors: Nathem Rashed Rawya
Published: May 2022

Define anemia is the low concentration in the amount of hemoglobin according to age, sex and trimester pregnancy. The pregnant has three trimesters and has an exceptional hemoglobin range in every trimester. The pregnant has 124-135 g/dl in the 1st trimester, 110-117 g/dl in the 2nd trimester and 106-109 g/dl in the 3rd trimester. Many pregnant females had been found with anemia because of a low level of Iron. This leads to megaloblastic anemia because of iron deficiency anemia and B12 Vitamin, diet, gastrectomy, malabsorption, blood loss and physiological demand (pregnancy infancy and adolescence). The blood consists of Hemoglobin (Heam + globin) Heam and Iron protoporphyrin ring. Globin is the type of protein with a specific length of amino acid and a specific type of A, maybe 2 Alpha 2 Beta called A1 or 2 Alpha and 2 Bata called A2 or 2Alpha and Gamma called F Fetal. The production of hemoglobin depends on the previously mentioned factors. In this study, we focused on some factors associated with the amount of blood and how these factors affected anemia, which is the most important in Iron treatments, with considering other factors such as food, diversity, Economic situation, social status, number of the fetus, and number of pregnancies. Statistical analysis was used to detect the effect factors of anemia in pregnant. This study refers to 23.2% of anemia because of Iron deficiency during pregnancy. So, treatment of Iron deficiency reduces anemia during pregnancy time.

Keywords. Anemia; Hemoglobin; Pregnant Woman
Understanding Whole-Person Health and Resilience During the COVID-19 Pandemic and Beyond: A Cross-sectional and Descriptive Correlation Study
Authors: Rajamani Sripriya , Austin Robin , Geiger-Simpson Elena , Jantraporn Ratchada , Park Suhyun , Monsen Karen A
Published: May 2022

Background

The COVID-19 pandemic has prompted an interest in whole-person health and emotional well-being. Informatics solutions through user-friendly tools such as mobile health apps offer immense value. Prior research developed a consumer-facing app MyStrengths + MyHealth using Simplified Omaha System Terms (SOST) to assess whole-person health. The MyStrengths + MyHealth app assesses strengths, challenges, and needs (SCN) for 42 concepts across four domains (My Living, My Mind and Networks, My Body, My Self-care; eg, Income, Emotions, Pain, and Nutrition, respectively). Given that emotional well-being was a predominant concern during the COVID-19 pandemic, we sought to understand whole-person health for participants with/without Emotions challenges.

Objective

This study aims to use visualization techniques and data from attendees at a Midwest state fair to examine SCN overall and by groups with/without Emotions challenges, and to explore the resilience of participants.

Methods

This cross-sectional and descriptive correlational study surveyed adult attendees at a 2021 Midwest state fair. Data were visualized using Excel and analyzed using descriptive and inferential statistics using SPSS.

Results

The study participants (N=182) were primarily female (n=123, 67.6%), aged ≥45 years (n=112, 61.5%), White (n=154, 84.6%), and non-Hispanic (n=177, 97.3%). Compared to those without Emotions challenges, those with Emotions challenges were aged 18-44 (P<.001) years, more often female (P=.02), and not married (P=.01). Overall, participants had more strengths (mean 28.6, SD 10.5) than challenges (mean 12, SD 7.5) and needs (mean 4.2, SD 7.5). The most frequent needs were in Emotions, Nutrition, Income, Sleeping, and Exercising. Compared to those without Emotions challenges, those with Emotions challenges had fewer strengths (P<.001), more challenges (P<.001), and more needs (P<.001), along with fewer strengths for Emotions (P<.001) and for the cluster of health-related behaviors domain concepts, Sleeping (P=.002), Nutrition (P<.001), and Exercising (P<.001). Resilience was operationalized as correlations among strengths for SOST concepts and visualized for participants with/without an Emotions challenge. Those without Emotions challenges had more positive strengths correlations across multiple concepts/domains.

Conclusions

This survey study explored a large community-generated data set to understand whole-person health and showed between-group differences in SCN and resilience for participants with/without Emotions challenges. It contributes to the literature regarding an app-aided and data-driven approach to whole-person health and resilience. This research demonstrates the power of health informatics and provides researchers with a data-driven methodology for additional studies to build evidence on whole-person health and resilience.
The Accuracy of Artificial Intelligence in the Endoscopic Diagnosis of Early Gastric Cancer: Pooled Analysis Study (Preprint)
Authors: Chen Pei-Chin , Lu Yun-Ru , Kang Yi-No , Chang Chun-Chao
Published: May 2022

BACKGROUND

Artificial intelligence (AI) for gastric cancer diagnosis has been discussed in recent years. The role of AI in early gastric cancer is more important than in advanced gastric cancer since early gastric cancer is not easily identified in clinical practice. However, to our knowledge, past syntheses appear to have limited focus on the populations with early gastric cancer.

OBJECTIVE

The purpose of this study is to evaluate the diagnostic accuracy of AI in the diagnosis of early gastric cancer from endoscopic images.

METHODS

We conducted a systematic review from database inception to June 2020 of all studies assessing the performance of AI in the endoscopic diagnosis of early gastric cancer. Studies not concerning early gastric cancer were excluded. The outcome of interest was the diagnostic accuracy (comprising sensitivity, specificity, and accuracy) of AI systems. Study quality was assessed on the basis of the revised Quality Assessment of Diagnostic Accuracy Studies. Meta-analysis was primarily based on a bivariate mixed-effects model. A summary receiver operating curve and a hierarchical summary receiver operating curve were constructed, and the area under the curve was computed.

RESULTS

We analyzed 12 retrospective case control studies (n=11,685) in which AI identified early gastric cancer from endoscopic images. The pooled sensitivity and specificity of AI for early gastric cancer diagnosis were 0.86 (95% CI 0.75-0.92) and 0.90 (95% CI 0.84-0.93), respectively. The area under the curve was 0.94. Sensitivity analysis of studies using support vector machines and narrow-band imaging demonstrated more consistent results.

CONCLUSIONS

For early gastric cancer, to our knowledge, this was the first synthesis study on the use of endoscopic images in AI in diagnosis. AI may support the diagnosis of early gastric cancer. However, the collocation of imaging techniques and optimal algorithms remain unclear. Competing models of AI for the diagnosis of early gastric cancer are worthy of future investigation.

CLINICALTRIAL

PROSPERO CRD42020193223; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=193223
A Computerized Audiovisual Training on Letter Naming in School Environment: a Feasibility Study (Preprint)
Authors: Luciani Léa , Payne Magali , Manera Valeria , Robert Philippe , Gros Auriane , Leloup Gilles
Published: May 2022

BACKGROUND

Reading disorder is one of the most common learning disabilities affecting children's learning. Difficulties in letter identification is fundamental to be screened, in order to detect children "at risk" of developing difficulties in word identification. It will allow to propose a targeted and intensive first-line intervention in kindergarten. We developed a ludic computerized program targeting letter identification as an initial response to the management of these children "at risk". It also allows to distinguish, according to their resistance to this type of intervention, those children who will benefit from more specific interventions. These intervention programs and the way in which children and teachers perceive them are still poorly evaluated in France.

OBJECTIVE

The aim of our study is to evaluate a longitudinal first-line intervention’s implementation in a kindergarten class in a French school. This intervention focuses on letter naming as a strong predictor of developing a written language learning disability risk.

METHODS

For this intervention, two 3-week training sessions were proposed, one during the last trimester of kindergarten, the other during the first trimester of first grade. In order to evaluate the feasibility of this intervention and to measure the feedbacks, questionnaires were filled by participants, children and teachers.

RESULTS

The majority of teachers founds that the intervention was easy and relevant. All the children enjoyed participating to the program, especially those that were enrolled in the training. Trained children felt more excitement about participating than their peers.

CONCLUSIONS

These results indicate that a first-line intervention based on letter naming is perfectly feasible in kindergarten, allowing teachers to identify children with difficulties and direct those for whom more specific help seems necessary. A real partnership between school and care may be created.

CLINICALTRIAL

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Social support, social media and life satisfaction with BD during the COVID-19 Pandemic (Preprint)
Authors: Pollock Star Ariel , Bachner Yaacov G. , Cohen Bar , Haglili Ophir , O'Rourke Norm
Published: May 2022

BACKGROUND

Reliable and consistent social support are associated with the psychological well-being of those with severe mental illness, including bipolar disorder (BD). Yet the COVID-19 pandemic and associated social distancing measures (e.g., shelter-in-place) have reduced access to regular social support. Concomitantly, use of social media during the pandemic has increased (i.e., social, non-social, passive social media usage).

OBJECTIVE

We set out to identify associations between BD symptoms, social support and social media use (SMU) during the pandemic.

METHODS

Using micro-targeted Facebook advertising, we recruited 102 adults with BD, most lived in North America (Canada = 45, USA = 15), Western Europe (e.g., UK=18, Ireland=10), South Africa (4) and Oceania (e.g., Australia=4, New Zealand=3). On average, participants were 53.96 years of age (SD = 13.22, range 20-77 years); they completed questionnaires online 32 months after the World Health Organization declared COVID-19 a global pandemic.

RESULTS

Consistent with previous research, symptoms of hypo/mania and depression are correlated; and symptoms of depression predict loneliness, social support and life satisfaction. Social support predicts social Facebook usage whereas passive Facebook use predicts life satisfaction. Symptoms of depression emerged as indirect predictors of SMU via social support.

CONCLUSIONS

Most participants (60.8%) reported accessing social media several times a day during the pandemic, and 36% reported using social media more often since the emergence of COVID-19. Our findings suggest bidirectional associations between social media use and well-being with BD. Longitudinal data collection is required to identify associations between BD symptoms, social media use and well-being over time.
Pain reduction with an immersive digital therapeutic in women suffering from endometriosis-related pelvic pain: a randomized, controlled, open-label, two-parallel-group, interventional study (Preprint)
Authors: Merlot Benjamin , Dispersyn Garance , Husson Zoé , Chanavaz-Lacheray Isabella , Dennis Thomas , Greco-Vuilloud Juliette , Fougère Maxime , Potvin Stéphane , Cotty-Eslous Maryne , Roman Horace , Marchand Serge
Published: May 2022

BACKGROUND

Chronic pelvic pain is a frequent debilitating condition in women suffering from endometriosis. Pharmacological and surgical treatments are not always efficient in controlling pain and present important restriction. Digital Therapeutics (DTx) are emerging as major non-pharmacological alternatives, aiming to extend the analgesic therapeutic arsenal of the patients.

OBJECTIVE

In this randomized controlled trial (RCT), we aimed to measure the immediate and 4 hours persisting effects of a single use 20-minutes long DTx (Endocare) on pain in women suffering from pelvic pain related to endometriosis.

METHODS

Forty-five women suffering from endometriosis participated in a randomized controlled study comparing the analgesic effect of a single use of a virtual reality digital treatment (Endocare, n = 23) to a 2D digital control (n = 22). Perceived pain and pain relief were measured before the treatment and 15-, 30-, 45-, 60-, and 240-minutes after the end of the treatment.

RESULTS

The clustered post-treatment pain is significantly reduced compared to the pretreatment for both Endocare and the control group (all P<.01). Endocare was significantly more efficient than the control group (all P<.01). When comparing each post-treatment measures to the pretest, Endocare significantly reduces pain perception for all times up to 4 hours post-treatment. The differences didn’t reached significance for the control group. Moreover, Endocare was significantly superior to the control group for 15-, 30- and 45-minutes after the treatment (all P<.001). The mean perceived pain relief was significantly higher for Endocare compared to the control for all the post-treatment measurements (all P>.05).

CONCLUSIONS

To our knowledge, our study is the first to test the effects of a single use of a DTx treatment on reported pain at different time points in patients diagnosed with endometriosis perceiving moderate-to-severe pelvic pain. Importantly, our result supports that Endocare, a VR immersive treatment, significantly reduce pain perception compared to a digital control in women suffering from endometriosis. Interestingly, we are the first to notice the effect persisted up to 4 hours post-treatment.

CLINICALTRIAL

ClinicalTrials.gov NCT04650516
A Systematic Review and Meta-analysis of Hyperuricemia Prevalence in Chinese Patients With Bipolar Disorder (Preprint)
Authors: Tao Hejian , Shen Dong , Zhou Yong , Sun Fengli , Li Guorong , Jin Weidong
Published: May 2022

BACKGROUND

How about the prevalence of hyperuricemia in Chinese patients with bipolar disorder because the increasing level of uric acid in bipolar disorder patients was conformed.

OBJECTIVE

To study prevalence of hyperuricemia in Chinese patients with bipolar disorder.

METHODS

The Chinese and English literature related to the study in prevalence of hyperuricemia in Chinese bipolar disorder were searched,among which results such as comments, letters, reviews and case reports were excluded. The prevalence of hyperuricemia in Chinese patients with bipolar disorder was synthesized and discussed by meta-analysis.

RESULTS

A total of 1040 subjects were included in 10 studies. The prevalence of hyperuricemia in bipolar disorder was 32.6%(95%CI=0.26-0.38.),which was higher significantly than normal control(9.18%).It is also found that prevalence of hyperuricemia in bipolar mania,depression and mixed respectively were 27.11%,20.16%,30.88%.The UA level of male patients was higher significantly than that in female (Z=4.87,P<0.00001).The results showed that the serum level of UA before treatment was higher significantly than that after treatment in patients with bipolar disorder(Z=2.14, P=0.03).

CONCLUSIONS

The prevalence of hyperuricemia in bipolar disorder was 32.6%(95%CI=0.26-0.38),which was higher significantly than normal control(9.18%). It also different among bipolar mania,bipolar depression,bipolar mixed.It also be proposed that higher level maybe a biological marker for bipolar disorder.

CLINICALTRIAL

No
Provider Perspectives on Telemental Health Usage After COVID-19: A Retrospective Analysis (Preprint)
Authors: Wilczewski Hattie , Paige Samantha R , Ong Triton , Soni Hiral , Barrera Janelle F , Welch Brandon M , Bunnell Brian E
Published: May 2022

BACKGROUND

Mental health care pivoted to telemedicine during COVID-19, and there is uncertainty around the sustainability of this rapid shift.

OBJECTIVE

This study examined how intentions to continue using telemedicine post-COVID are influenced by provider perceptions of usefulness, ease of use, professional social influence, and facilitating organizational conditions.

METHODS

We conducted a web-based, cross-sectional survey of 369 telemental health providers between February and March 2021. A hierarchical linear regression analysis was conducted to predict intentions to continue using telemedicine post-COVID.

RESULTS

Most providers began using telemedicine March 2020 or later (257/369, 69.6%) and saw ≥50% of their clients via telemedicine (299/369, 81.0%). Analyses revealed that intention to continue using telemedicine post-COVID was predicted by telemedicine caseload ( = .10; P = .005), perceived usefulness in general ( = .10; P = .008), ease-of-use ( = .08; P = .04), social influence ( = .68; P < .001) and facilitating conditions ( = .08; P = .047).

CONCLUSIONS

Exploration into predictors of telemedicine usage beyond COVID-19 aids in surveillance of telemedicine usage, integration with future clinic workflows, and the shaping of public policy. It is important to consider telemedicine services not only as a response to a crisis, but as an effective and useful solution for everyday life. Our results suggest widespread, sustainable telemedicine adoption.

CLINICALTRIAL

N/A
The Influence of Civil Society on Welfare Expansion in East Asia: A Comparative Study of Singapore and South Korea
Authors: Yeo Qin-Liang
Published: May 2022

East Asian countries are often characterized as productivist welfare states whose social policies are subordinated to economic growth. However, in the past decade, public pressure for welfare expansion (or welfarism) has built up across all East Asian countries – including China, Japan, South Korea, Taiwan, and Singapore. Therefore, this paper asks: How has pro-welfare civil society influenced welfare expansion in East Asia over the past decade? Addressing this research question will help fill the theoretical gap on the relationship between contemporary pro-welfare civil society activism and welfare state expansion in East Asian countries. I address this theoretical gap by devising the New Power Approach which argues that pro-welfare civil society is the main driver of welfare expansions when the incumbent government is conservative. By implication, the stronger the pro-welfare civil society in generating political impetus for reforms, the greater the extent of welfare expansion in the country with a conservative government.
Hospitals as confinement?
Authors: - Anon
Published: May 2022

None
Changes in the Tragic daily Life of those who Experience Intimate Partner Violence: A Collective Discourse of Women
Authors: Oliveira Jeany Freire de , Lira Margaret Olinda de Souza Carvalho e , Oliveira Lucia Marisy Souza Ribeiro de , Rodrigues Vanda Palmarella , Ribeiro Rafaella Ayanne Alves dos Santos
Published: May 2022

Intimate partner violence is a complex problem that harms the lifestyle with profound changes in women's daily lives. This is an interdisciplinary research, with a qualitative approach, developed between July 2019 and February 2020, in a Reference Center for Women's Care in the city of Petrolina, Pernambuco, Brazil, with data collected through semi-structured interviews, applied to twelve women who experienced intimate partner violence. The results were systematized by the Collective Subject Discourse method and interpreted by methodological theoretical resources of Comprehensive Sociology and Everyday Life in Michel Maffesoli's sociological thought. The collective subject was between 32 and 56 years old, Black and Brown, low income, evangelical religion and complete higher school level. The content of the narratives originated three central synthesis ideas that comprised three collective discourses about the daily life of women before violence, daily life during violence and daily life after partner violence. The discourses describe daily transformations resulting from the tragic represented in childhood and adolescence by intrafamily violence and adulthood by intimate partner violence that resulted in the loss of freedom, autonomy, individuality, social relationships and material goods and gave rise to needs that transcend traditional care.
A Comparative and Contrastive Analysis of the Emerson Philosophical Essays and Ghaani's Distress
Authors: Elyasi Faramarz
Published: May 2022

In this study, Mirza Habibollah Shirazi’s (Ghaani) Distress was compared with Ralph Waldo Emerson’s two philosophical essays “Nature” and “Self-Reliance” in light of philosophical and moral views. The study aimed at comparison of these two contemporaneous poets and writers to trace the similarity, differences and source of their teachings, because the rearcher assumed the two thinkers have many ideas in common. To perform the study, the main ideas in the selected works of the two poets were analyzed in length and then their works were compared and contrasted. Results of the analysis indicated that In Emerson’s “Nature,” God is present in nature and man is not separable from metaphysical order. “Self-Reliance” emphasized non-conformity and dependence of the individual self. Ghanni’s Distress was described as a window to Eastern metaphysics that specified didactic implications. Emerson uses a general idea of philosophy of nature’s utility and then focuses on deductive reasoning. In addition, Emerson philosophy of transcendental and metaphysical philosophy represents perception of nature and self in an independent philosophy and strengthened diverse education of Eastern philosophy and poetry. Ghaani is merely advocator of Sa’di’s style and educational teachings.
Understanding Actions and Motives: The Ideal ‘I’ and Signifiers in Lacanian Psychoanalysis
Authors: Karamchandani Poorva
Published: May 2022

The Mirror Stage (1949) and The Formation of the Unconscious (1957) by Jacques Lacan are important concepts in the field of Psychoanalysis. This paper understands the arguments put forth in the concepts and concludes their importance in literary criticism. They also help determine the factors that influence Lacan’s theories. Through this paper, we understand the argument of The Mirror Stage, its role in literary criticism and analyze The Picture of Dorian Gray (1891) in context to The Mirror Stage. Later we look at the Formation of the Unconscious, its structure similar to that of the language, and the role of signifiers in the human psyche.
Nuestras huellas y cicatrices
Authors: de Agüero Servín María de las Mercedes
Published: May 2022

En este número, de los meses de mayo y junio, la Revista Digital Universitaria les comparte un interesante grupo de artículos que me llevan directamente a pensar en las huellas que dejamos los seres humanos en nuestro vivir en el planeta y las interacciones entre personas con el medio ambiente y la naturaleza.
Trazabilidad en los productos de origen animal y su papel para desalentar las malas prácticas
Authors: Gamboa-Delgado Julián , Pacheco-Vega Juan Manuel , Ponce-Campos Paulino , Márquez-Reyes Julia Mariana
Published: May 2022

El comercio de productos de origen animal es cada vez más intensivo a nivel nacional e internacional. Esto conlleva la necesidad de una serie de verificaciones y certificaciones que pueden ir desde los aspectos sanitarios hasta la denominación de origen y la protección de especies vulnerables. La trazabilidad de los productos de origen animal asiste en las comprobaciones de los productos ofertados y comercializados. Productos tales como los mariscos, miel de abeja, pieles, quesos y carnes de diversos animales están sujetos a protocolos de trazabilidad que aseguran que el consumidor final recibirá un producto auténtico y seguro. Mediante un buen seguimiento, es posible generar información confiable sobre el origen, forma de producción y la especie de la cual se obtuvo el producto final. Tales sistemas de trazabilidad frecuentemente se apoyan en evaluaciones analíticas, ya sea para confirmar el origen o autenticidad de un producto o como una medida para definir acciones penales ante delitos tales como adulteraciones y etiquetados fraudulentos. La ciencia forense de los alimentos juega un importante papel en este contexto. El presente artículo aborda algunos casos y aplicaciones de técnicas analíticas usadas para reforzar la trazabilidad y autenticidad de los productos de origen animal.
A Comprehensive Survey on Plant Disesases Detection
Authors: Gohil Mr. Kathan , Tailor Prof. Amita , Solanki Prof. Anjali
Published: May 2022

Abstract: India is an agricultural country. The life and economy of a farmer depends on agriculture. If any disease occurs in his crop, his entire crop goes into loss. Therefore, timely identification and diagnosis of the disease in the crop is very important. With this idea, we have created this product. So that the farmer can know whether the plant is diseased or not by inputting the photo of the leaf in this software. And if so, he can get information about the disease. This whole process he can do from his home just through a Smartphone. Keywords: plant disease, artificial neural network, deep learning, Support Vector Machine
Voice Isolation Using Artificial Neural Network
Authors: Kumar Vikash , Gupta Shivam Kumar , Sharma Harsh , Bhadauriya Uchit , Varma Chandra Prakash
Published: May 2022

Abstract: The paper reflects the use of Artificial Neural Networks with the help of various machine learning algorithms for voice isolation. In particular, we consider the case of a voice sample recognition by analyzing the speech signals with the help of machine learning algorithms such as artificial neural networks, independent component analysis, activation function. The strategies by which our central nervous network decodes the network stimuli same as artificial neural network will analyze the given speech sample. After first step, a set of machine learning algorithms will be used like independent component analysis algorithm and gradient function algorithm for processing. After the processing, a decision statement will be applied to generate the desired output. Keywords: Artificial Neural Network, Voice Isolation, Fast Independent Component Analysis, Gradient Descent
AI Based False Positive Analysis of Software Vulnerabilities
Authors: Patil Priya
Published: May 2022

Abstract: Programming measurements and shortcoming information having a place with a past programming variant are utilized to assemble the product issue expectation model for the following arrival of the product. Notwithstanding, there are sure situations when past issue information are absent. As such foreseeing the shortcoming inclination of program modules when the issue marks for modules are inaccessible is a difficult assignment oftentimes arised in the product business There is need to foster a few strategies to assemble the product issue forecast model in light of unaided realizing which can assist with anticipating the shortcoming inclination of a program modules when shortcoming names for modules are absent. One of the strategies is utilization of grouping methods. Solo methods like grouping might be utilized for issue expectation in programming modules, all the more so in those situations where shortcoming names are not accessible. In this review, we propose a Machine Learning grouping based programming shortcoming forecast approach for this difficult issue
Bacterial Concrete
Authors: Das Prayash , Das Indrajeet , Kumar Mithilesh , Pradhan Jagannath , Sahoo Chitrabhanu
Published: May 2022

Abstract: Cement mortar durability is the function of its internal pore structure and distribution, porosity and its permeation properties. Research has shown that some specific bacterial species isolatedfrom soil can tolerate harsh and challenging alkaline environment and can be used in remediating cracks in cement mortar structures. This state of-the-art microbial based crack healing mechanism is one such phenomenon on which studies were carried out to investigate the role of calcite mineral precipitation in improvement of durability in bacteria integrated cement mortar. Keywords: Bacteria, Bacillus Subtilis, Self-Healing
Mathematical and Stochastic Growth Models
Authors: Kumari V. Pavan , Musala Venkataramana , Naidu M. Bhupathi
Published: May 2022

Abstract: Many statistical and mathematical models of growth are developed in the literature and effectively applied to various conditions in the existent world involves many research problems in the different fields of applied statistics. Nevertheless, still, there are an equally a large number of conditions, which have not yet been mathematically or statistically modeled, due to the complex situations or formed models are mathematically or statistically inflexible. The present study is based on mathematical and stochastic growth models. The specification of both the growth models is depicted. A details study of newly modified growth models are mentioned. This research will give substantial information on growth models, such as proposed modified exponential growth models and it’s specifications clearly motioned which gives scope for future research.
Scan For Notes
Authors: Nargude Miss. Nikita , Shambhushetti Miss. Srushti , Kagale Miss. Shreya , Parit Miss. Prajakta , Kanase Prof. Mahesh. J.
Published: May 2022

Abstract: QR code (abbreviated from Quick Response Code ) is the trademark for a type of matrix bar code first designed for the automotive industry. Today the QR code is widely used in all industries. In our paper we present an implementation of an Android device using libraries is and combined algorithms in order to be able to scan any QR code fast accurate and easy. The devices that we targeted for our application are the Google Glasses and an Android operated phone. The implementation for each of the devices was slight different, but the core algorithms and libraries were the same. Keywords: Generate QR Code for Notes, Android device using libraries
Covid-19 Face Mask Detection and People Count
Authors: S. B Nithyashree. , R Ramya Bharathi. , Monaa. A Poe Pyae Hay Thar , Durgadevi M.
Published: May 2022

Abstract: During this pandemic the problems faced was shortage of testing services, vaccines and poor medical care all these lead to lockdown for a long run which affected our daily lives. During this pandemic the problems faced were shortage of testing services, vaccine and poor medical care all these lead to lockdown for the long run which affected our daily lives. The prevention for this problem was to wear masks in public areas. Facemask detection had seen remarkable growth in the image processing and deep learning domain. Facemask detection is already an existing concept in which they had used different algorithms and techniques to show better results. The proposed system in this project is developed to avoid mask-less people from entering the desired places by detecting face-mask, and sending a signal to an Arduino device that connects to the sensors and counts the people while entering and exiting. This helps to maintain the social distancing inside those places and limit the Total number of persons. If the total number of people count increases, the Arduino microcontroller will give the buzzer alarm to notify the person. In This project, we use live detection and identify either the person wears a mask or not. Therefore, this proposed approach will make a significant change in the public healthcare system. Keywords: Deep Learning, Sensors, Computer Vision, Convolutional Neural Networks (CNNs), public Safety, face mask detection, OpenCV, COVID-19.
Animal Specie Detection Using Deep Convolution Neural Network
Authors: Bhandari Shubham , Gautam Shruti , Sharma Shubham , Srivastav Neelam
Published: May 2022

Abstract: India is a diverse country in term of wild life, all kind of wild life animal in north and southern part of India like Bengal Tiger, Rhino, Leopard are some of them and many of them are in stage of extinct, only few of them are remaining so to check their population continuous monitoring and research is important. To monitor in forest one to one is very tedious and time consuming job so technology have evolved which include installing cameras in animal living areas and acquire videos and pictures, hence save time and money. The images received in camera's not recognisable in general as pictures are blurred , without animals, or difficult to detect, resulting in doubt and error. To cater this obstacle, we suggest a database driven network captured images with dataset of different animal species stored from spatiotemporal domain and pictures with animal are captured from forest are compared with the dataset, identify if a graph matches the animal or not. This animal detection model have developed by us based on self training by Deep Neural Network (DCNN). The technology is used for classification using ML and AI algorithms, support vector machine, k-mean nearest neighbour, and ensemble tree. This suggest system can accurately classify pictures up to 91% accuracy. Keywords: Installed Camera, Animal detection ·Camera images·DCNN, ·Deep learning ·SVM ·KNN
Prediction of Kidney Stones Using Machine Learning
Authors: G. P Vishnu Prasad , Reddy Kurapati Vishnu Sai , Kiruthik A. M. , Nehru Dr. J. Arun
Published: May 2022

Abstract: Kidney stones are a prevalent disease all over the world, resulting in many of us being rushed to the hospital in excruciating pain. Calculus illness is diagnosed using a variety of imaging modalities. For the interpretation and thorough diagnosis of the photos, specialists are required. Computer-aided diagnosis systems are practical ways that can be utilized as supplemental tools to aid clinicians in their diagnosis. During this project, the deep learning (DL) technique was used to propose an automatic diagnosis of kidney stones using coronal X-ray (CT) pictures, which has made a great advances in the field of AI. Keywords: Kidney stone, medical image, Deep learning, Computed tomography
Real-Time Communication over Blockchain
Authors: Gupta Tushar , Dhyani Harshit , Kumar Piyush , Gupta Vishesh , Sharma Ankita
Published: May 2022

Abstract: Blockchain Technology becoming popular with time giving rise to Web 3.0 and this technology will change the way we see the Internet. Blockchain is a decentralized, digitally dis- tributed immutable ledger that allows real-time communication to happen securely; this is the reason we need blockchain in a social networking websites as these websites keep the data on centralized servers that can be risky as the data can easily be stolen and can easily be distributed with third parties without the need of users consent. But with the help of Blockchain and DApps, we can create a reliable and efficient way to share messages and media on secured networks without any third party interference. In this paper, we are going to discuss how we make use of smart contracts and peer-to-peer networks like Ethereum to create such applications and allow users to share their messages and other forms of information without any fear of data getting lost or being shared without user consent, we also going to discuss how this method is different from the current method which social networking websites use to secure users data, and how Web 3.0 is going to be different from current Web 2.0 in terms of a social network. Index Terms: decentralization, blockchain, Apps(Decentralized applications), Ethereum
Design and Fabrication of Marigold Flower Hydrosol Extraction Machine and Manure Making
Authors: Vanalkar Prof. A. V. , Dhodre Mahesh , Anwane Pratik , Mantinwar Prajwal , Kanade Ritesh , Kalbande Shivam , Mohite Aniket
Published: May 2022

Abstract: India is the religious country with a huge population. And their are lots of hindu temple present here. This devotion towards god comes with price in the from of flower. And this flower create a lot of pollution in solid from and due to improper management of this waste create air pollution and other types of pollution which harms the nature critically. In an average in India their are 60 cores tons of marigold flower are devoted to the god and create such a problems as we discuss. Hence to tackle such a situation in such a way to create some revenue from those waste and also reduce pollution we design and fabricated marigold flowers hydrosol and manure extracting machine. This machine works on water distillation process and represent thermodynamic cycle. Here flowers get boiled with water and it create steam of flower essences and get cold down into liquid from in condenser and by this process we get hydrosol and manure (in boiler). Their are also other process to extract these items from flower but water distillation process is more easy, effective and simple than other process and it create absolutely low or no pollution
Boat Detection and Tracking Using RSSI Signal in A Device-Free Environment
Authors: GP Rajeshwari , Vasan G Prathick , C Ramanarayanan , K Elango
Published: May 2022

Abstract: This project presents a device-free human detection method for using Received Signal Strength Indicator (RSSI) measurement of Wireless Sensor Network (WSN) with packet dropout based on ZigBee. Packet loss is observed to be a familiar phenomenon with transmissions of WSNs. The packet reception rate (PRR) based on a large number of data packets cannot reflect the real-time link quality accurately. So, it raises a real-time RSSI link quality evaluation method based on the exponential smoothing method. Then, a device-free human detection method is proposed. Compared to conventional solutions which utilize a complex set of sensors for detection, the proposed approach achieves the same only by RSSI volatility. The experimental measurements are conducted in laboratory. A high-quality network based on ZigBee is obtained, and then, RSSI can be calculated from the receiver sensor modules. Experimental results show the uncertainty of RSSI change at the moment of human through the network area and confirm the validity of the detection method. Keywords: RSSI Signal, Detection and tracking
Demographic evaluation of Post-Concussion Syndrome in referrals to Bandar Abbas Forensic Medical Center, South of Iran from March 2020 to August 2021
Authors: Mohammadi Saeed , Mirhadi Seyed Javad , Javadi Vasigh Hosein , Asadi Khatere , Memarian Azadeh , Nikkhah Farahnaz
Published: May 2022

Objectives: The aim of the present study is the demographicassessment of PCS in referrals to forensic medical centersin Bandar Abbas.

Methods: This cross-sectional and descriptive study was performed on 72 patients with mild brain trauma who were referred to Bandar Abbas forensic medical center. PCS was confirmed according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria. Information on age, sex, mechanism of trauma, the time interval between the first visit to the forensic medical center, level of consciousness, number of hospitals stays days, number of days in ICU, and symptoms at initial referral were recorded in the designed form.

Results: The mean age of patients was 30.81 Â± 13.39 years. There was a significant difference in sex and mechanisms of trauma (P < 0.001).  The average time interval of the first referral to forensic medical center was 9.44 Â± 18.37 days.87.5% were hospitalized and only 9.7% were hospitalized at ICU. The consciousness level of all patients was in the range of 12 to 15 (mild range).Among symptoms, headache (87.5%) and dizziness (81.9%) were the most significant prevalent symptoms. 70.8% of patients had no symptoms one month after the accident but 12.5% still had symptoms and only 9.7% still had symptoms of concussion after3 months.

Conclusion: According to the results, PCS mostly happened in the male gender and the main mechanism of trauma was an accident. Headache and dizziness were the main symptoms. Only a small percentage of patients have symptoms after one month and three months, post-injury.
Safety and efficacy of COVID-19 Vaccines in special populations
Authors: Alattas Sana , Ibrahim Ibrahim M , Ali Ahmed S. , Barakat Jehan M , A Shaker Assmaa , Momen Tasneem N , S. Mohamed Abir , Alfadil Abdalbabgi , Alharbi Amani E
Published: May 2022

Coronavirus disease 2019 (COVID-19), is a pandemic that resulted in extreme human and economic losses.  A higher incidence of morbidity and mortality to COVID-19 was demonstrated in a special population. Factors that impact the disease severity include old age, obesity, pregnancy, diabetes mellitus, cancer, and immunosuppressive drugs. Fortunately, several COVID-19 vaccines were developed such as Pfizer-BioNTech, Moderna, Oxford-AstraZeneca, and Johnson & Johnson among others. These vaccines have shown good efficacy and safety profiles in the general population, but serious rare adverse effects were reported related to specific vaccines. Several studies are undergoing to test the efficacy in special populations. Reduced efficacy or delayed immunological response to COVID-19 vaccines were suggested for patients with autoimmune disorders or organ transplant patients, especially those receiving certain medications such as rituximab. There is a concern about organ rejection in organ transplant patients. Despite these facts, there is an agreement among health care providers to consider prioritization of the above-mentioned groups for receiving vaccinations with the same precautions followed for the general population. It is recommended to ongoing studies determine the efficacy and safety of COVID-19 vaccines in patients with comorbidities based on clinical data.
Ultrasonografía y descripción fisiológica de eventos esenciales para el manejo reproductivo en ganado lechero. Revisión
Authors: Torres-Lechuga María Elena , González-Maldonado Juan
Published: May 2022

The ultrasound allows to visualize the female reproductive tract and helps to understand some of the most relevant reproductive events such as follicular and corpus luteum development, ovulation, pregnancy diagnosis, uterine infections, embryo and fetal growth, among others. Nowadays, there is a massive amount of information regarding the physiology and ultrasonography of the reproductive events mentioned above. However, the overwhelming number of available papers review technical aspects of ultrasonography, physiology and reproductive management separately. Therefore, the objective of the present review is to merge a physiological description with reproductive management and technical aspects of original ultrasound pictures of the most relevant reproductive events in dairy cattle to promote ultrasound use during dairy cattle reproductive management by practitioners and researchers.
Estrés por calor en ganado lechero con énfasis en la producción de leche y los hábitos de consumo de alimento y agua. Revisión
Authors: Correa-Calderón Abelardo , Avendaño-Reyes Leonel , López-Baca M. Ángeles , Macías-Cruz Ulises
Published: May 2022

El impacto negativo del estrés por calor (EC) en la ganadería lechera repercute en cuantiosas pérdidas económicas a nivel mundial, dado que reduce la producción de leche, la eficiencia reproductiva y la vida productiva de las vacas. Adicionalmente, el mejoramiento genético continuo resulta en vacas muy productivas, pero menos tolerantes al EC debido a que producen mayor calor metabólico. Esto en conjunto con el calentamiento global convertirá al EC en un reto difícil de controlar para la industria lechera. Como respuesta dependiente del grado de EC, el ganado lechero realiza una serie de ajustes fisiológicos, metabólicos y conductuales como mecanismos de termorregulación para disipar el exceso de calor corporal y reducir la producción endógena del mismo, todo dirigido a mantener la normotermia. Sin embargo, la secreción láctea y la fertilidad se reducen por efecto directo de la hipertermia e indirectamente por la reducción en el consumo de nutrientes dietéticos. Los consumos de alimento y de agua están asociados estrechamente con la reducción de la productividad en ganado lechero expuesto a EC. Cabe mencionar que el impacto del EC en la productividad del ganado lechero varía entre razas, siendo las razas Bos taurus menos tolerantes al EC, particularmente la raza Holstein. Actualmente, se investiga en la identificación de genes asociados con la termotolerancia, los cuales son empleados en programas de selección por marcadores genéticos para producir vacas altas productoras de leche en climas cálidos. Por lo tanto, el objetivo de esta revisión es hacer un análisis comprensivo de los efectos del EC sobre la producción de leche, activación de mecanismos de termorregulación y conducta de ingesta en ganado lechero.
Concentrado de proteína de papa: una posible alternativa al uso de antibióticos en las dietas para lechones destetados. Revisión
Authors: Parra Alarcón Erick Alejandro , Hijuitl Valeriano Teresita De Jesús , Mariscal Landín Gerardo , Reis de Souza Tércia Cesária
Published: May 2022

El periodo del destete es crítico en la vida de los lechones y puede generar trastornos gastrointestinales y un bajo crecimiento, que son aminorados con el uso de antibióticos en los alimentos iniciadores. Sin embargo, debido a la necesidad de eliminar los antibióticos de la nutrición animal, se mencionan algunas posibles alternativas a su uso. En la presente revisión bibliográfica, se describen los péptidos antimicrobianos y compuestos inhibidores de proteasas de origen vegetal, sobre todo los provenientes de la papa, que han sido tradicionalmente reconocidos por su potencial aplicación biomédica y actividad contra bacterias patógenas y hongos. Se revisaron las características y aplicaciones del concentrado de proteína de papa (CPP) proveniente de la industria del almidón, que se distingue por su perfil de aminoácidos y alta digestibilidad. Se destacan en el CPP moléculas que están presentes en la fracción proteica y que pueden contribuir a la salud intestinal de los lechones, por lo que se perfila como un ingrediente con potencial para ser utilizado en dietas libres de antibióticos. Sin embargo, es necesario tener más información bibliográfica sobre el CPP para verificar si la respuesta sanitaria es consistente o no, y recomendar su inclusión en las dietas iniciadoras para lechones recién destetados como una alternativa a los antibióticos.