Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of the ambit of breast cancer with a modified ResNet analysis using machine learning approach

Breast Cancer has been one of the most common reasons for mortality and morbidity among the females around the world especially in developing countries. In this regard, Mammography is a popular screening technique for breast cancer diagnosis so as to label the existence of cancerous cells. The present work encompasses the design and development of a M-ResNet (Modified ResNet) approach so as to classify the breast cancer into benign and malignant conditions with the inclusions for supervised classification models with the training of both upper as well as the lower layers of the designed networks. The efficacy of the developed approach was evaluated using various performance evaluators such as those of sensitivity, specificity, accuracy and F1-Score. Bi-Rads score was used as a basis for the classification process wherein a score of 0-3 correlated to benign and it is non-cancerous nature of tissues whereas malignancy was denoted by a score of 4 and above. InBreast dataset, a publicly available online dataset with 112 breast images were used for the evaluation of the developed paradigm. The present paradigm portrayed an accuracy of 96.43% with Area Under the Curve (AUC) of 95.63%.
mRNA Expressions of Methylation Related Enzymes and Duration of Thermal Conditioning in Chicks

DNA methylation regulates gene expression by modifying the nucleosome structure of DNA, without altering the gene sequence. It has been reported that DNA methylation reactions are catalyzed by several enzymes. In chickens, thermal conditioning treatment affects the central DNA methylation levels. The purpose of this study was to clarify the changes in DNA methylation and demethylation factors during thermal conditioning in the hypothalamus of 3-day-old chicks. Male chicks (3-days old) were exposed to 40±0.5°C as a thermal conditioning treatment for 1, 2, 6, 9, or 12 h. The control chicks were kept in a thermoneutral zone (30±0.2°C). After thermal conditioning, the mRNA levels of DNA methyltransferase (DNMT)-1, -3a, -3b, and ten-eleven translocation (TET)-1, -2, and -3 in the hypothalamus were measured by q-PCR. The mRNA levels of DNMT-3a and TET-1 were increased by thermal conditioning. Moreover, the expression level of TET-1 increased with the loading time of the thermal conditioning. The gene expressions of DNMT-1, DNMT-3b, TET-2, and TET-3 were not affected by thermal conditioning. Since DNMT-3a is a catalyst for de-novo DNA methylation and TET-1 catalyzes the oxidation of methylated cytosine, it is suggested that the thermal conditioning increased the activation of DNA methylation and demethylation factors, which occur in the hypothalamus of neonatal chicks.
Feasibility of Nanotechnology in the Application of Cancer Therapy

The application of nanotechnology in medicine is one of the hot spots now. In this paper, the tumor treatment has carried on the detailed elaboration, from three major treatments called surgery, radiotherapy and chemotherapy. The past treatments and the existing defects of each methods were illustrated, respectively. Then by referring to the relevant literature, what changes the nanotechnology will exert on the three methods were analyzed. In the end, this article presented some shortages and challenges of nanotechnology. According to the research results, nanotechnology can effectively improve the therapeutic effect of the three methods from the following aspects: Firstly, it can improve the accuracy and safety of surgery; Secondly it can enhance the sensitivity of tumor tissues to radiotherapy; Thirdly, it can improve the therapeutic effect of chemotherapy with nano-drugs. In contrast, the low safety and non-standardization of product quality are the main limitations of this technology.
Illumination-driven Light Probe Placement

We introduce a simpliﬁcation method for light probe conﬁgurations that preserves the indirect illumination distribution in scenes with diverse lighting conditions. An iterative graph simpliﬁcation algorithm discards the probes that, according to a set of evaluation points, have the least impact on the global light ﬁeld. Our approach is simple, generic and aims at improving the repetitive and often non-intuitive and tedious task of placing light probes on complex virtual environments.
Digital Parent Training RCT Meta-Analysis and Systematic Review

Background. Disruptive behavior disorders significantly increased family disruption and children are at higher rates of child maltreatment, which have increased following the pandemic. While parent training interventions are a best-practice intervention to treat a range of disruptive behavior disorders and family dysfunction concerns, there is limited and mixed findings on the efficacy of telehealth or digital parent training interventions. Methods. Therefore, we conducted a systematic review and meta-analysis (k = 24, total number of intervention participants = 1469 and control participants = 800) of the impact of digital parent training interventions on parent skill, parent mental health, and child externalizing mental health outcomes from 2000 to 2020, among children 2-12 years old, across four databases. Exclusionary criteria include programs targeted for parents of children with intellectual disabilities, autism, brain injury, nutrition/health/dental needs or primary medical diagnosis. Results. Across outcomes, digital parent training interventions had a modest effect size (g = .22 to .30), compared to controls. The effects of digital parent training on parent skills and child outcomes were stronger if the intervention was evidence-based, combined interactive platforms with a therapist and was compared to an inactive control. Digital parent training effects compared to an active control (e.g., in-person therapy or psychoeducation modules), were improved with increased therapy contacts. Conclusions. Together, these findings suggest digital parent training interventions provide an important role in stepped care models. We call on future studies to provide standardized demographics to aide future knowledge synthesis and we provide templates for shared measurement. Preregistration and open data files: https://osf.io/e35bt/.
Examining the Role of Quasi-biennial Oscillation on Rainfall patterns over Upper Blue Nile Basin of Ethiopia

A composite analysis is used to evaluate the teleconnections between the long term (June- August) rainfall anomalies with east and west phases of quasi-biennial oscillation (QBO) in the stratospheric zonal winds from 1979–2017. Applying the lower equatorial stratospheric zonal wind index in JJA rainfall prediction is based on its tendency to persist for several months after the phase change from easterly to westerly and vice versa. Below normal condition rainfall used to coin drought. This study is important because, the Upper Blue Nile region is one of the most inviting areas for different activities like agriculture and hydroelectric power; therefore, timely prediction of June-August rainfall serves farmers and other concerned sectors. The aim of this analysis is to establish the global signal quasi-biennial oscillation contribution alone at different time lags and its association among Southern Oscillation Index (SOI) for estimation June-August rainfall of the Upper Blue Nile. The rainfall used as predictand while quasi-biennial oscillation & SOI datasets are used as predictors in regression model after testing collinearity of these two independent variables. Performance of regression model and actual value is tested by using statistical techniques: Root Mean Square Error, Mean Absolute Error and bias. The performance is seen reasonably high between actual and estimated values show strong agreement.
Risk-Constrained Minimization of Combined Event Detection and Decision Time for Online Transient Stability Assessment

This paper addresses the problem of ‘quickest possible’ online transient stability assessment, by minimizing the decision time of combined event detection that might lead to a system split and unstable generator group prediction, from real-time wide area power system measurements. More importantly it does so by respecting predefined probabilistic error constraints for the prediction. The statistical theory of optimal detection is applied, firstly to choose the detection threshold and secondly to select a flexible assessment time, after using probabilistic neural networks to provide a temporal representation of the data. On simulated wide area measurements from the interconnected New England test system and New York power system this approach is between two and three times faster on average than strategies based on fixed assessment times, despite having comparable error rates.
Measuring the Benefits of Diversification Across Portfolios

A portfolio diversification index is defined as the ratio of an equivalent number of independent assets to the number of assets. The equivalence is based on either attaining the same diversification benefit or spread reduction. The diversification benefit is the difference in value of a value maximizing portfolio and the maximum value of the components. The spread reduction is the percentage reduction attained by a spread minimizing portfolio relative to the smallest spread for the components. Asset values, bid and ask, are given by conservative valuation operators from the theory of two price economies. The diversification indices fall with the number of assets in the portfolio and it they are explained by a measure of concentration applied to normalized eigenvalues of the correlation matrix along with the average level of correlation. Diversification across global indices is not as strong as diversification across an equal number of domestic assets, but rises substantially for longer horizons of up to three years.
Cryptocurrencies as facilitators of cybercrime

The aim of the article is to show cryptocurrencies as facilitators of crime, especially cybercrime. While investing in cryptocurrencies is publicly discussed, their role in the criminal world is more hidden from the public, however, causes a lot of problems for law enforcement and regulatory authorities around the world. Criminals are interested in cryptocurrencies as targets for of their attacks, means of payment and as a method of money laundering. In this article, we discuss why cryptocurrencies have become a means of payment for the criminal underworld, what benefits they have from them, and what major challenges law enforcement is facing in that regard. The survey was conducted based on reports from authorities involved in the prosecution of cybercrime. We can conclude that the organized criminal underworld has a strong interest in cryptocurrencies and their popularity among ordinary, honest citizens, as in this way it is much easier for the criminals to conceal their activities and the origin of their assets.
Manufacture and application of lignin-based carbon fibers (LCFs) and lignin-based carbon nanofibers (LCNFs)

Environmental issues and constantly diminishing petroleum resources are considerable barriers inhibiting modernization, and vast efforts have been exerted to address these problems. Carbon fibers (CFs) are carbon materials with high mechanical strength and functionality for applications in construction, electronics, transportation, and aviation. Currently, most CFs are produced from polyacrylonitrile, a petroleum-based, unsustainable, and non-renewable chemical of relatively high price. Interestingly, lignin is an inexpensive, highly accessible, and renewable resource. It has been utilized to fabricate lignin-based carbon fibers (LCFs), which have met rapid development during the past two decades. In this review, LCFs are generalized by focusing on their steps of manufacture. Resource types and corresponding pretreatments ensure the processability of spinning and thermal treatments. Fibers are formed via spinning methods, including melt-spinning, wet-spinning, dry-spinning, and electrospinning. The next step is the most significant process of stabilization, in which fibers are oxidized, crosslinked, and thermally stabilized for pyrolysis. Subsequent to carbonization and/or additional processes (activation and graphitization), LCFs are obtained. Each step can influence the terminal performance of LCFs, which is discussed in detail. Recently produced LCFs of sub-micron size, also known as lignin-based carbon nanofibers (LCNFs), are detailed. Furthermore, attributed to the excellent performance and low cost of LCFs and LCNFs, they have been applied in various fields, predominantly for electronic devices such as batteries and supercapacitors. Our review is concluded with opinions on the potential for further advancement of this promising material.
Effectiveness of Human Resource Information System (HRIS) in Banking Industry in India

Human Resource Information Systems (HRIS) plays an important part in banking industry. Due to this, the main objective of this study is to examine the effectiveness of determining factors across HRIS effectiveness in chosen commercial banks in India. In five dimensions HRIS was measured (Human Resource, Environmental, Technological, Organizational, and Security Factors). Likert scale which has five points of 28 statements is used by the whole HR department. The data was evaluated and analyzed with the help of package of statistical data analysis, SPSS (Statistical Package for the Social Sciences version 23.0) along with the single variant and bi-variant methods. The investigations of the survey declares that 91.7% of HRM (Human Resource Management) effectiveness variance is explained by HRIS and investigated the significant difference between determining factors acrossHRIS of the bank employees concluded that human resource, technological, organizational, environmental and security factors significantly difference with HIRS of bank employees.
Numerical modelling of chemical vapour deposition reactors

In this thesis we study the chemical reactions and transport phenomena which occur in a microwave power assisted chemical vapour deposition (MPA-CVD) reactor which facilitates diamond growth. First we introduce a model of an underlying binary gas flow and its chemistry for a hydrogen gas mixture. This system is heated by incorporating a microwave frequency electric field, operating in a resonant mode in the CVD chamber. This heating facilitates the dissociation of hydrogen and the generation of a gas discharge plasma, a key component of carbon deposition in industrial diamond manufacture. We then proceed to summarise the discontinuous Galerkin (DG) finite element discretisation of the standard hyperbolic and elliptic partial differential operators which typically occur in conservation laws of continuum models. Additionally, we summarise the non-stabilised discontinuous Galerkin formulation of the time harmonic Maxwell operator. These schemes are then used as the basis for the discretisation method employed for the numerical approximation of the MPA-CVD model equations. The practical implementation of the resulting DG MPA-CVD model is an extremely challenging task, which is prone to human error. Thereby, we introduce a mathematical approach for the symbolic formulation and computation of the underlying finite element method, based on automatic code generation. We extend this idea further such that the DG finite element formulation is automatically computed following the user's specification of the convective and viscous flux terms of the underlying PDE system in this symbolic framework. We then devise a method for writing a library of automatically generated DG finite element formulations for a hierarchy of partial differential equations with automatic treatment of prescribed boundary conditions. This toolbox for automatically computing DG finite element solutions is then applied to the DG MPA-CVD model. In particular, we consider reactor designs inspired by the AIXTRON and LIMHP reactors which are analysed extensively in the literature.
Top Five Cancer Health Disparities in Florida: Race, Ethnicity, Geographic Location and Socio-Economic Predictors

Background: In 2019, cancer was found to be the second leading cause of death with an economic cost of over $90 billion in the United States. Cancer affects all population groups in the United States; however, certain populations may bear a disproportionate burden of cancer compared with other populations. In this study, we have examined cancer data from 1981-2015 on the top five cancers in Florida for predictors of advanced stages of diagnosis of each cancer. Materials & Methods: This study is a secondary analysis via data from the Florida Cancer Data System database. The odds for advanced stages of cancer regressed with demographic, insurance, and socioeconomic predictors. Results from the last 34 years and the last 15 years were compared to see the changes during this time. Results: Considerable differences were found in multiple factors for each type of cancer in this study. Most notably, breast cancer yielded a discrepancy for every category, including insurance status, race, and socioeconomic status. In contrast, the least number of identifiable disparities existed with melanoma of the skin. Conclusion: Although many interventions over the past 15 years have been aimed at reducing disparities in cancer outcomes, it appears that social determinants such as race, ethnicity, insurance, income, and geographic location still play a significant role as predictors of the advanced stage of a cancer diagnosis for lung, breast, prostate, colorectal, and melanoma of skin at initial diagnosis for Florida residents.
Dentist Awareness about Basic Life Support in Dental Colleges of NCR

Aim: This study aimed to assess Dentist Awareness of Basic life Support (BLS) among Dental colleges of NCR U.P India. Materials and Methods: A cross-sectional questionnaire survey was carried out in randomly selected 3 dental colleges out of 6 pursuing post-graduation courses in NCR. A prior permission was obtained from the concerned college authorities. The study was conducted by assessing responses to 20 selected basic questions regarding BLS among M.D.S Staff, P.G Student, and B.D. S Staff. A questionnaire with 20 questions regarding the awareness and skills involved in BLS was used to assess the levels of awareness to BLS and its practical knowledge. The aspects on which they were interrogated were about the abbreviation of BLS, AED and EMS (Emergency Medical Service), sequential steps in BLS, assessment and resuscitation techniques with regard to airway, breathing, circulation in unresponsive victims of different age groups, techniques regarding removal of foreign body obstruction, recognition of early signs of stroke and acute coronary syndrome. Results: The findings of present study are somewhat similar to Chandrashekaran S et al., [1] who stated that medical, dental, nursing students & faculty in the study group were severely lacking in the awareness of BLS whereas in the present study BDS faculty and postgraduates of dental were same but MDS faculty were somewhat aware about BLS. On comparison MDS Faculty showed more awareness as compared to PG student and BDS faculty in this study. Conclusions: It is also equally important that teachers, school children, public and all lay persons from the community be taught the facts of basic life support and first aid.
Barriers and measurement of work/life balance of managers and other employees

Due to major changes and challenges in the way of conducting business in recent decades, establishing work/life balance of employees and managers has become a very important topic. The aim of this paper is to emphasize the obstacles to successfully establishing this balance, the most important of which being the supportive organizational culture and superiors’ communication. Another goal of this paper is to introduce the Standards of Excellence Index as a measure for determining the success of the companies’ work/life balance programs for employees and managers within 7 components: leadership, strategy, infrastructure, accountability, relationship building, communication, and measurement. In this regard, this paper presents research results on this index in companies in America, where this index was created.
Effects of weekly hippotherapy frequency on gross motor function and functional performance of children with cerebral palsy: a randomized controlled trial

Objective: To verify whether hippotherapy once or twice a week has a different effect on gross motor function and functional performance in children with cerebral palsy. Methods: This trial had 20 children (age 2 to 5 years and 11 months) with cerebral palsy who were assigned to the groups once a week (n = 9) or twice a week (n = 11) and underwent 30-minute hippotherapy sessions for 16 weeks. The instruments used were the Gross Motor Function Measure (GMFM) and the Pediatric Evaluation of Disability Inventory (PEDI), assessed at baseline and after 16 weeks. Results: A significant time effect was observed for both groups without significant interactions between groups. Conclusions: Hippotherapy improved the gross motor function and functional performance of children with cerebral palsy, regardless of the weekly frequency of the sessions. This result has relevant clinical implications, since hippotherapy has a high cost and the prescription of weekly sessions could make this treatment more available for this population. Key-words: Equine-assisted therapy, Cerebral Palsy, Heavy Motor Function, Functional Performance
Surrogate-Assisted Cooperation Control of Network-Connected Doubly Fed Induction Generator Wind Farm With Maximized Reactive Power Capacity

This article aims to realize a cooperative active power control of doubly fed induction generator (DFIG)-based wind farm (WF) to maximize the total reactive power capacity while maintaining the active power supply-and-demand balance. Difficulties lie in that the accurate PQ-curve expressions of wind turbines therein are unknown and nonuniform, thereby putting an obstacle to distributed optimization. To address the problem, PQ-curve inaccuracy caused by expression simplification is analyzed through the bridge of rotor current frame, rotor overspeeding control prioritized operation is recommended, and a surrogate-assisted distributed optimization (SADO) scheme is proposed from the WF perspective. The proposed method iteratively uses measured operating data to prompt a surrogate model to fit the accurate model, and then the optimal control action is guaranteed by online exploitation-and-exploration process with demonstrated availability through convergence analysis. Further, coordination with offline pretraining ensures that convergence can be obtained within shortened iteration steps. Case studies on 150-MW DFIG WF demonstrate the effectiveness of the proposed SADO scheme regarding shortening the iteration number, a full extraction on reactive power capacity and the better performance for voltage support.
Mapping the Local Community: Factors Influencing the Purchase Intention of Community based Entrepreneur Halal Products in Malaysia

This research is designed to get the analysis of purchase intension of the customer for the local community-based products in Kelantan with focus on the impact of products halal certification and product hygiene on the consumers purchase intention. 100 respondents were recruited in convenient sampling. This quantitative study using survey and questionnaire as a tool of data collection. Results found that the purchasing intention of the Muslims regarding the local community-based halal products is dependent mainly on the halal logo and certification and also the hygienic factor. This study addresses an important knowledge gap in the local community-based product literature, proposing and clarifying the relationship between Halal logo and certification, hygienic factors and purchase intention.