Miracle-dz/UniFAR-FTUs huggingface dataset:
INFLUENCE OF DEMOGRAPHIC FACTORS ON THE CONSUMERS' AWARENESS OF FMCG PRODUCTS A CASE OF CONSUMERS IN KRISHNAGIRI DISTRICT OF TAMILNADU

Fast moving consumers goods (FMCG) market is highly competitive due to innumerous players in the field. It is true to all kind of FMCG products. Yet only few brands are firmly foot in the mind of customers. If a company suceed in making aware of a product brand, it ensures the major success of its marketing campaign. The awareness about a particular brand exixtence is caused by many factors. The existing customers as unpaid ambassodors, the reach of marketing communications and the receptive nature of the consumers are the factors generally influence the awareness level of the customers. The demographic factors such as age, education and gender predominantly playing a vital role in receiving portion of any communication due to communicational influesors like selective perception etc. Hence the study focuses on the influence of demographic factors on the Consumers' Awareness of FMCG products. The study is very significant due to lack of studies that identifie the influence of demaographic factors on the consumers’ awareness. To achieve the stated objectivea a self administered questionnairre was designed and developed to measure the consumers’ awareness level of the FMCG customers. There are 150 samples of respondents; resposes were collected from the FMCG consumers of Krishnagiri district. Convinience sampling technique was applied to collect the data. Retail stores in the city and nearby villages were selected to collect the repsonses from the respondents who are the consumers of FMCG products from the geographic study area Krishnagiri District of Tamilnadu state. The collected data were properly edited coded and computed in excel sheet. Statistical tests such as mean, standard devaition, ANOVA were exexcuted using Ms-office excel data analysis tool. The results have indicated clearly that the consumer awareness level is influenced by the age and income level of the customers.
The Effects Of Early Menarche On Sexual And Reproductive Health: A Scoping Review

Early menarche in adolescent girls has an effect on how quickly they come into contact with sexual life. This may have an impact on the increased incidence of unintended pregnancy, increased childbirth and abortion in adolescents. The condition of adolescents who are too young at menarche and poor reproductive health status will create problems with their menstruation, especially when the right sources of reproductive health information are not fully utilized. The aim of this scoping review is to interpret the effects of early menarche on sexual and reproductive health. The Scoping Review method was carried out using the following steps; 1) identifying research questions; 2) identifying relevant studies, through the Pubmed, Ebsco, and Wiley databases. In the search for articles, the keywords used are Effect OR Outcomes AND Menarche OR Menstruation OR Menstrua * OR menses OR "Early Menarche" AND "Reproductive Health" OR sexual reproduction * AND sexual behavior * OR "sexual debut" OR "Sexual Partners OR" unsafe sex "OR" unprotected sex ". The article criteria used are articles published from 2009 to 2019 and discussing the effects of early menarche on sexual and reproductive health; 3) the selection of articles was described using the Prisma Flow Chart where in full text search results, 18 articles were obtained and 9 articles was used for the review as these have quality assessment and according to population, methods, and results; 4) carrying out data charting; and 5) carrying out the compilation of results reports. The nine articles used as review materials discussed sexual health and early sexual reproduction in 101 respondents (21%) among sexually active students, 15 out of 89 students (16.9%) had low use of contraception, diseases of sexual health and reproduction (herpes simplex type-2, that is, women aged 14 who have experienced menarche have had sexual intercourse, HIV, which is 5.6% positive, as well as factors that affect sexual and reproductive health (45% education, 81.4% knowledge, economy due to low income, 60% sexual desire at the age of 14 years and only 11% who have not been sexually active at the age of 17 years). Early menarche and high sexual desire are health problems that have serious implications for adolescents. Provision of appropriate information and education on sexual and reproductive health for adolescents is urgently needed. It is hoped that the findings from the articles that have been reviewed can contribute to the importance of providing sex education from an early age.
Treatment of difficult-to-treat depression – clinical guideline for selected interventions

Abstract Background Difficult-to-treat-depression (DTD) is a clinical challenge. The interventions that are well-established for DTD are not suitable or effective for all the patients. Therefore, more treatment options are highly warranted. We formulated an evidence-based guideline concerning six interventions not well-established for DTD in Denmark. Methods Selected review questions were formulated according to the PICO principle with specific definitions of the patient population (P), the intervention (I), the comparison (C), and the outcomes of interest (O), and systematic literature searches were performed stepwise for each review question to identify relevant systematic reviews/meta-analyses, and randomized controlled trials. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was used to assess the methodological quality of the included studies. Clinical recommendations were formulated based on the evidence, the risk-benefit ratio, and perceived patient preferences. Results We found sufficient evidence for a weak recommendation of repetitive transcranial magnetic stimulation (rTMS) and cognitive behavioural analysis system of psychotherapy (CBASP). The use of bright light therapy in DTD was not sufficiently supported by the evidence, but should be considered as good clinical practice. The interventions should be considered in addition to ongoing antidepressant treatment. We did not find sufficient evidence to recommend intravenous ketamine/esketamine, rumination-focused psychotherapy, or cognitive remediation to patients with DTD. Conclusion The evidence supported two of the six reviewed interventions, however it was generally weak which emphasizes the need for more good quality studies. This guideline does not cover all treatment options and should be regarded as a supplement to relevant DTD-guidelines.
A constraint method for supersaturation in a variational data assimilation system

The reproducibility of precipitation in the early stages of forecasts, often called a spin-down or spin-up problem, has been a significant issue in numerical weather prediction. This problem is caused by moisture imbalance in the analysis data, and in the case of the Japan Meteorological Agency’s (JMA’s) mesoscale data assimilation system JNoVA, we found that the imbalance stems from the existence of unrealistic supersaturated states in the minimal solution of the cost function in JNoVA. Based on the theory of constrained optimization problems, we implemented an exterior penalty function method for the mixing ratio within JNoVA to suppress unrealistic supersaturated states. The advantage of this method is the simplicity of its theory and implementation. The results of twin data assimilation cycle experiments conducted for the Heavy Rain Event of July 2018 over Japan show that—with the new method—unrealistic supersaturated states are reduced successfully, negative temperature bias to the observations is alleviated, and a sharper distribution of the mixing ratio is obtained. These changes help to initiate the development of convection at the proper location and improve the fractions skill score (FSS) of precipitation in the early stages of the forecast. From these results, we conclude that the initial shock caused by moisture imbalance is mitigated by implementing the penalty function method, and the new moisture balance has a positive impact on the reproducibility of precipitation in the early stages of forecasts.
PolSAR Image Land Cover Classification Based on Hierarchical Capsule Network

Polarimetric synthetic aperture radar (PolSAR) image classification is one of the basic methods of PolSAR image interpretation. Deep learning algorithms, especially convolutional neural networks (CNNs), have been widely used in PolSAR image classification due to their powerful feature learning capabilities. However, a single neuron in the CNN cannot represent multiple polarimetric attributes of the land cover. The capsule network (CapsNet) uses vectors instead of the single neuron to characterize the polarimetric attributes, which improves the classification performance compared with traditional CNNs. In this paper, a hierarchical capsule network (HCapsNet) is proposed for the land cover classification of PolSAR images, which can consider the deep features obtained at different network levels in the classification. Moreover, we adopt three attributes to uniformly describe the scattering mechanisms of different land covers: phase, amplitude, and polarimetric decomposition parameters, which improves the generalization performance of HCapsNet. Furthermore, conditional random field (CRF) is added to the classification framework to eliminate small isolated regions of the intra-class. Comprehensive evaluations are performed on three PolSAR datasets acquired by different sensors, which demonstrate that our proposed method outperforms other state-of-the-art methods.
Research on Digital Skills that Accountants Should Possess in the Intelligent Era

The intelligent era is also known as the fourth industrial revolution. One of the features of the intelligent era is that people use digital technologies such as artificial intelligence, block chain, 5G, cloud computing and mobile animal networking to carry out production, operation and management activities. At present, digital technology is an important factor in promoting social and economic development around the world. Representative digital technology gradually empowers the fields of financial accounting, management accounting, corporate financial management, audit and corporate governance. In this paper, we study and discuss the digital technology that a qualified accountant should possess in the intelligent era, which also provides a directional guidance for the training of intelligent accounting talents in the future.
Influence of Body Mass Index, Waist Circumference, and Physical Activity on Age of Menarche in Female Adolescent

Background: The age of menarche which was referred to first time of teenagers had men­strua­tion can be affected by anthropometric index, including body mass index, and waist circumference. Differences in measurement of body mass index, waist circumference, and intensity of physical activity will make some differences in age of menarche. This research aimed to determine the influence of body mass index, waist circumference and physical activity with age of menarche in late adolescent girls in Surakarta. Subjects and Method: The data collected by observed 359 adolescent girls aged 15 until 18 years old in Surakarta during September to October 2016 using observational analytic with cross sectional methods. The independent variables were body mass index, waist circum­fe­rence, and physical activity. The dependent variable is age of menarche. Body mass index is measured using BW (kg)/BH² (m²) formula, in which: BW is Body Weight (measured using digital standardized scales) and BH is Body Height (measured using standardized micro­toise). Students asked to fill in the questio­n­naire that contain questions regarding repro­duc­tive health especially menarche and phy­sical activity questionnaire (IPAQ). The data is processed using SPSS for Windows 23.0 and are analyzed using multiple regression analysis. Results: From the 359 respondents, the mean of age of menarche is 12.6 years (Mean= 12.6; SD= 1). Mean of body mass index is 21.42 kg/m² (Mean= 21.42; SD= 4.44). Mean of waist circum­ference is 70.41 cm (Mean= 70.41; SD= 7.47). There are 87 respondents (24.2%) with low physical activity, 100 respondents (29.5%) with mode­rate physical activity, and 166 res­pondents (46.2%) with high physical activity. Physical activity has significant influence posi­tively (OR= 1.98; 95% CI= 0.39 to 4.72; p= 0.017) on the age of menarche. Conclusion: Physical activity has significant influence on the age of menarche in adolescent girls in Kota Surakarta, Indonesia. Keywords: endocrinology, body mass index, waist circumference, physical activity, menar­che, female student Correspondence: Ulfa Puspita Rachma. Faculty of Medicine, Uni­versitas Sebelas Maret. Jl. Ir. Sutami 36A Sura­karta 57126, Central Java. Email: ulfapr96­@­gmail.com. Mobile: 0823293­42­140. Journal of Maternal and Child Health (2021), 06(04): 400-408 https://doi.org/10.26911/thejmch.2021. 06.04. 02
Could Avatar Therapy Enhance Mental Health in Chronic Patients? A Systematic Review

The use of avatars in the psychological treatment of some chronic diseases is in their infancy, and it represents a growing field of research with many possibilities for innovation. However, there is a lack of studies seeking to determine if avatar-based therapies could improve mental health in chronic care settings. In fact, to the best of our knowledge, this is the first systematic review addressing this research topic. The objectives of this study were to review the scientific literature on those studies involving avatar-based therapies for chronic patients, as well as different ways to develop them and their efficacy on mental health outcomes. Two main questions were addressed: (1) Are avatar-based strategies useful to improve mental health in chronic patients? (2) Which is the best way to develop avatar-based strategies regarding chronic diseases? A systematic review of the peer-reviewed literature was conducted in March 2021. The results were, not only useful for establishing suitable ways to develop avatar-based strategies to improve mental health in chronic care, but also for providing an ad hoc taxonomy regarding this research topic. Five modalities were established according to technological complexity and avatar presentation. Most of the studies were effective (61.1%) in enhancing mental health in chronic care.
Como o uso de aplicativos móveis educacionais impacta o cotidiano de crianças autistas? Uma avaliação por meio de diários de usuário

O Transtorno do Espectro Autista (TEA) pode ser classificado como um tipo de transtorno global do desenvolvimento, caracterizado por prejuízos em diferentes áreas do desenvolvimento do indivíduo, como interação, socialização, concentração e principalmente na comunicação. Pesquisas relacionadas ao uso de tecnologias educacionais para o público autista no Brasil ganhou destaque após a publicação da Lei N° 12.674, que institui a Política Nacional de Proteção dos Direitos da Pessoa com TEA. A vasta gama de tecnologias disponíveis e a pouca quantidade de estudos empíricos, dificulta a identificação de aplicações úteis e alinhadas aos interesses de mães, pais e profissionais que lidam com crianças autistas. Por esta razão, decidiu-se investigar sobre o uso de aplicativos educacionais móveis na aprendizagem e nas atividades diárias de crianças autistas. Para explorar a experiência de uso dos aplicativos pelas crianças em seu cotidiano, foi conduzido um estudo com o uso de diários. Os participantes do estudo foram crianças autistas cujas mães participam de uma associação de mães do município de Jaguaruana no estado do Ceará. Os aplicativos utilizados promoveram boa experiência de uso, incluindo benefícios no aprendizado e desenvolvimento da comunicação. Esta pesquisa visa contribuir no contexto acadêmico e social, pois os resultados são relevantes tanto para pessoas que convivem com crianças autistas, como para profissionais da área.
Predicting student performance using data mining and learning analysis technique in Libyan Higher Education

The Technology has an increasing impact on all areas of life, including the education sector, and requires developing countries to emulate developed countries and integrate technology into their education systems. Recently schools in Libya are facing an issue trying to figure out why students perform poorly in certain subjects and how can they know how they will perform next in the future in coming semesters in perspective subject. There are several methods proposed to predict the student’s performance, using data mining techniques. In this paper, there are plans to create Data Mining Techniques in Education (i.e., DME) prediction model clustering, classification and association rule mining in many universities and schools in order to provide students and teachers with the most advanced platform. Although relatively late, the Libyan government finally responded to this challenge by investing heavily in rebuilding the education system and launching a national plan to presented method in terms of predicting students’ performance based on their grades in Math and English. The results are divided in to three main sections clustering analysis using k-mean algorithm, classification analysis was done using two rounds first using Gain Ratio Evaluations to find out the top attributes that used by J84 algorithm in second round of classification, and rule association analysis using A priori algorithm. Rule association analysis is applied for the clusters generate by clustering analysis to generate the rules associated with each cluster. For each section, a list of inputs is presented with the scale used for the values followed by the results of the algorithm and explanation for the finding.
Takting the Sustainability of Construction Processes: An Environmental Assessment Method

The building sector is key to achieving global sustainability targets due to its significant resource consumption, associated emissions, and waste generation. Life cycle assessment (LCA) evaluates the environmental quality of buildings to identify improvement possibilities. However, current research activities limit their focus on a few life cycle phases, while the construction phase receives none to little attention. At the heart of the problem lies the lack of information about on-site processes and the lack of tools to evaluate the environmental quality of construction processes. The authors developed a conceptual framework to assess this aspect using an interdisciplinary approach. The proposed solution is based on two main methods, namely LCA and Takt Planning (TP). Based on literature research we identified the main categories for environmentally relevant in- and outputs of construction processes. This allows a structured, standardized, and scalable assessment of each single process step from an environmental perspective We anticipate this method to be a starting point for a holistic sustainability approach for construction process assessment. Further development of this framework aims to broaden the current environmental evaluation in the building sector and to improve both, the construction process and the building product from an environmental point of view.
Evaluation of the Impact of Queue Trucks with Navigation Alerts Using Connected Vehicle Data

Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could be transmitted to navigation systems such as Waze. This study reports on the deployment and impact evaluation of digital alerts on motorist’s assistance patrols and 19 Queue trucks in Indiana. The motorist assistance patrol evaluation is provided qualitatively. A novel analysis of queue warning trucks equipped with digital alerts was conducted during the months of May-July in 2021 using connected vehicle data. This new data set reports locations of anonymous hard-braking events from connected vehicles on the Interstate. Hard-braking events were tabulated for when queueing occurred with and without the presence of a queue warning truck. Approximately 370 hours of queueing with queue trucks present and 58 hours of queueing without queue trucks present were evaluated. Hard-braking events were found to decrease approximately 80% when queue warning trucks were used to alert motorists of impending queues.
Comparison of the Health Cost of Organic and Conventional Vegetable Cultivation in Getasan Sub-district, Semarang, Indonesia

Environmental damage will disrupt the ecosystem to support life. Unsustainable agriculture can be a source of environmental degradation. Conventional agriculture may have an effect on the environment, thus the participation of various parties in sustainable agriculture is needed. Organic agriculture is developed as an environmentally friendly agricultural cultivation with many benefits. Compared to the attention on occupational health, safety and environmental problems, economic motives receive less attention. This study aims to calculate the costs arising from the health impacts of vegetable cultivation. There were 314 respondents interviewed in this study. There were significant differences in the sickness complaints felt by respondents; organic farmer groups have the potential to incur health costs of Rp. 30,333.33, while the conventional group is higher, with a cost of Rp. 103.303. 57 (US$ 7.38). Organic farming has a better impact because it uses natural ingredients and is not bad for health. The potential losses arising from health cases also show a high and significant number (p <0.001).
Infections in CSF Shunts and External Ventricular Drainage

Infection in those with hydrocephalus shunts or external drains (EVDs) can cause serious central nervous system damage with lasting sequelae. The infections usually involve bacterial colonisation and biofilm formation in the catheters. The nature and sources of pathogens and preventive measures are discussed. The risks of infection in shunts and EVDs is different. Infection in shunts is almost always initiated at their insertion or revision (exceptions are described). In contrast, in EVDs, the risk of infection persists throughout their use. The pathogen profile is also different. These factors are important considerations when planning preventive measures. Newer strategies such as antimicrobial catheters are discussed. Diagnosis of EVD infections in an already ill patient is difficult but guidelines can be useful. Treatment of the shunt and EVD infections are also addressed, with reference to modes and routes of antibiotic administration.
Semantic Segmentation Based on Temporal Features: Learning of Temporal–Spatial Information From Time-Series SAR Images for Paddy Rice Mapping

Synthetic aperture radar (SAR) can be used to obtain remote sensing images of different growth stages of crops under all weather conditions. Such time-series SAR images can provide an abundance of temporal and spatial features for use in large-scale crop mapping and analysis. In this study, we propose a temporal feature-based segmentation (TFBS) model for accurate crop mapping using time-series SAR images. This model first extracts deep-seated temporal features and then learns the spatial context of the extracted temporal features for crop mapping. The results indicate that the TFBS model significantly outperforms traditional long short-term memory (LSTM), U-network, and convolutional LSTM models in crop mapping based on time-series SAR images. TFBS demonstrates better generalizability than other models in the study area, which makes it more transferable, and the results show that data augmentation can significantly improve this generalizability. The visualization of the temporal features extracted by the TFBS shows that there is a high degree of intraclass homogeneity among rice fields and interclass heterogeneity between rice fields and other features. TFBS also achieved the highest accuracy of the four deep learning models for multicrop classification in the study area. This study presents a feasible way of producing high-accuracy large-scale crop maps based on the proposed model.