Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Risk Factor Analysis model for Heart Disease Classification and using Convolution Neural Network

In the recent years, the number of people passing away due to heart attack has increased a lot. The lifestyle changes of the 20 th century have made people more prone to heart attacks. This paper presents a heart disease classification system using deep learning. The individual parameters causing the heart attack are analysed in terms of risk factor. The risk factor analysis has helped to access the role of each parameter at a personal patient level. The risk factor analysis has led to discovery of redundancy present in the datasets and thereby providing input on how accuracy can be increased. The proposed model used Convolution Neural Network (CNN) to classify the heart data. The UCI heart dataset is used to validate the proposed method. A custom dataset is constructed with new real-time parameters which has been recently discovered. The proposed method has achieved better accuracy when compared to the existing counterparts.
Hardware Abstractions for targeting EDDO Architectures with the Polyhedral Model

Unlike cache-based load-store architectures, Explicit De-coupled Data Orchestration (EDDO) architectures are programmed using decoupled but synchronized programs running at various units on the hardware, moving data between storage units and/or performing computations. As such, they present a unique programming challenge. In this paper, we propose a set of hardware abstractions to represent EDDO architectures, enabling them to be targeted with the polyhedral model for statically analyzable work-loads. The abstractions are rich enough to support EDDO architectures with arbitrarily deep storage hierarchies, hierarchical parallelism and support for temporal and spatial reuse exploitation via multicast, peer-to-peer communications, and spatial reduction. We also frame the abstractions within the context of an in-progress project called PolyEDDO, which is a mapping analysis and code-generation framework for EDDO architectures.
Mitigation Factors for Multi-domain Resilient Networked Distributed Tessellation Communications

—Numerous technical calls have converged upon an overarching goal of Resilient Networked Distributed Tessellation Communications (RNDTC) so as to provide long-range communications through the notion of “tessellation” antennas, which are comprised of spatially distributed low Size, Weight, Power, and Cost (SWaP-C) transceiver “polygons. ” At its core, this approach supplants higher powered amplifiers and large directional antennas with various tessellations of spatially dispersed transceiver polygons. In essence, the transmit power is spatially distributed amongst the polygons, and gain is achieved, via signal processing rather than the use of, by way of example, an antenna aperture so as to concentrate energy. Therefore, signal processing functions enable the various polygons to self-form into an array and enable beamforming, among other techniques, thereby enhancing the desired signals and somewhat obviating intentional/unintentional interference. However, the algorithmic approaches to date have varied pros and cons (e.g., the attainment of reduced sidelobes at the expense of the mainlobe, wherein interference suppression is achieved at the cost of the resolution of the signals). There are promising interference mitigation factor pathways, such as adaptive weight shifting, during the analyzing, transforming, and synthesizing of such signals. However, despite the advantages of adaptive weighting techniques, the computational complexity is extremely high, and the ensuing complexity reduction processes are subject to adversarial exploitation. Accordingly, this paper proposes mitigation factors by way of Artificial Intelligence (AI)-centric Genetic Algorithm (GA) approaches amidst the analysis, transformation, and synthesis amalgam. In particular, preliminary experimental results (to be furthered in future work) indicate promise for the auto-tuning of the Steady State Genetic Algorithm (SSGA) compression factor 𝜻 for more optimal convergence
Detecting Scenes in Fiction: A new Segmentation Task

This paper introduces the novel task of scene segmentation on narrative texts and provides an annotated corpus, a discussion of the linguistic and narrative properties of the task and baseline experiments towards automatic solutions. A scene here is a segment of the text where time and discourse time are more or less equal, the narration focuses on one action and location and character constellations stay the same. The corpus we describe consists of German-language dime novels (550k tokens) that have been annotated in parallel, achieving an inter-annotator agreement of gamma = 0.7. Baseline experiments using BERT achieve an F1 score of 24%, showing that the task is very challenging. An automatic scene segmentation paves the way towards processing longer narrative texts like tales or novels by breaking them down into smaller, coherent and meaningful parts, which is an important stepping stone towards the reconstruction of plot in Computational Literary Studies but also can serve to improve tasks like coreference resolution.
Microwave-assisted extraction of lactones from Ligusticum chuanxiong Hort. using protic ionic liquids

Traditional Chinese medicine is still the main source for medical treatment in China. Extraction processes are usually adopted to separate bioactive ingredients from local plants. However, volatile traditional organic solvents are commonly used in the extraction process, which would lead to solvent loss and environment pollution. In this work, in order to improve the extraction process and develop a greener process, a microwave-assisted extraction (MAE) method was investigated to extract senkyunolide I, senkyunolide H and Z-ligustilide from Ligusticum chuanxiong Hort. Two ionic liquids, N,N-dimethyl-N-(2-hydroxyethoxyethyl)ammonium propionate (DMHEEAP) and N,N-dimethyl(cyanoethyl)ammonium propionate (DMCEAP), were employed as extractants. Important factors such as system temperature, extraction time, solid-to-solvent ratio and particle size were studied. The results show the system temperature was main factor which affects the microwave assisted extraction process. The extraction equilibrium could be reached in a short period of time. The extraction efficiency was not affected by the phase ratio within a certain solid/solvent ratio range. The particle size of Ligusticum chuanxiong powder had no remarkable effect on extraction efficiency. The back-extraction of protic ionic liquids using n-hexane was realized, and the concentration of senkyunolide I and senkyunolide H hardly decreased, but the concentration of Z-ligustilide decreased by 39.7%. The extraction mechanism of the investigated microwave assisted ionic liquid extraction was the same as traditional organic solvent extraction.
Cultural Diversity Management Strategies and Efficiency of Multinational Companies in Rivers State

This examination researched the connection between cultural diversity management strategies and efficiency of multinational firms in Rivers State. The study is designed as a cross sectional survey and draws data using the structured questionnaire from 70 workers from a population of 77 staff within the multinational firms. The study, using the Spearman’s rank order correlation coefficient tested the relationship between – investiture, assimilation and divestiture; and efficiency. Results revealed significant relationships; hence a rejection of all previously stated hypotheses. In conclusion it was stated that investiture, assimilation and divestiture enhances the relationship between workers within the organization and also affords them sound supportive grounds upon which they become more aware and are able to improve the efficiency of multinational companies in Rivers State. Thereafter it was recommended that organizations should develop structures that support and facilitate practices such as investiture, assimilation and divestiture within their workplace in a way that facilitates and drives the learning and value alignment of groups within the organization. Such should focus on the values, expectations and norms of the organization especially as regards ethical actions and practices within the
Supplementary Material:Interpretable Neural Networks Decoupling

As shown in Fig A, we collect filters in the last convolutional layer of VGG16 on ImageNet 2012 after network decoupling and present the results of the number of times they are activated. ImageNet 2012 contains 50,000 validation images, so the number of times each filter is activated falls in the interval [0, 50000]. The leftmost bar represents the number of filters that never been activated (i.e., silent filters), and the rightmost bar represents the number of filters that are activated every time (i.e., energetic filters). The middle bars represent the number of filters, which respond to specific inputs (i.e., dynamic filters). For instance, the rightmost bar represents that there are 60 filters, which are activated 50,000 times during evaluating on ImageNet 2012, in the last convolutional layer of
Prey selection by Sparrowhawks Accipiter nisus and characteristics of vulnerable prey

Prey selection of the Sparrowhawk (Accipiter nisus) was studied in northern Finland during 1982-1993. A total of 540 prey items (all birds) were recorded from the surroundings of 12 nests. For each prey species a vulnerability index was calculated as the ratio between its proportion in the Sparrowhawk's diet and its proportion in the land bird community (data from the whole of the Oulanka National Park, and spruce forests only). The average prey individual weighed 52 g, whereas the average breeding bird weighed 36 g in the spruce forests and 24 gin the whole of the Oulanka National Park area . Prey vulnerability increased with increasing prey body mass . The result could be interpreted in the light of the optimal foraging theory, large prey being the most profitable among the Sparrowhawks' prey-size range. In the whole of Oulanka data, open habitat species were caught relatively more frequently than forest species, and prey vulnerability correlated negatively with prey abundance . Foraging behaviour and the nest site of the prey species were not related to their vulnerability . Phylogenetic analyses revealed a significant correlation between prey vulnerability and plumage brightness, after the effects of body mass and abundance of prey species were controlled for. Higher relative predation risk of bright species give support to the `sexual selection' hypothesis but not to the `unprofitable prey' hypothesis explaining prey vulnerability .
Quake ML: Earthquake Forecasting

Earthquakes have the potential to cause catastrophic structural, emotional, and economic damage. The problem of predicting earthquakes is a decades-old problem, yet this crucial problem is incredibly difficult to tackle. The problem of earthquake forecasting can be broken down into three key subproblems: when an earthquake will occur, where an earthquake will occur, and what is the magnitude of the earthquake. In this paper, we will focus on the problem of predicting when an earthquake will occur using statistical and deep learning methods. We present numerical results using earthquake acoustic data collected in a laboratory simulated experiment.
Genomic Heterogeneity of the Naga and Kuki Tribal Populations of Manipur, Northeast India

ABSTRACT Manipur, one of the northeastern states of India, lies on the ancient silk route and serves as a meeting point between Southeast Asia and South Asia. The origin and migration histories of Naga and Kuki tribal populations are not clearly understood. Moreover, Kukis have been traced to two different ancestries, which has created confusion among the people. The present study examined genomic affinities and differentiation of the Naga and Kuki tribal populations of Manipur, Northeast India. Twenty autosomal markers (8 Alu insertion-deletions, 12 restriction-fragment-length polymorphisms) were analyzed. Findings show genetic differences between Naga and Kuki tribal populations with respect to the allele distribution pattern, which was substantiated by genetic differentiation (GST = 5.2%) and molecular variance (AMOVA), where the highest percentage of among-group variances was observed between Naga and Kuki tribal groups (7.09%). However, genetic similarities with respect to allele distribution patterns in most of the loci were seen among their respective groups (Rongmei and Inpui, Thadou and Vaiphei). Rongmei and Inpui tribal populations (Naga group) belong to the Naga-Bodo linguistic group, and Thadou and Vaiphei (Kuki group) belong to the Northern Kuki-Chin linguistic group, suggesting that genetic similarities may not be independent of linguistic affinities. Despite differential genetic affinities, both Naga and Kuki tribal populations in Manipur show more proximity with Southeast Asian populations and Northeast Indian populations than with other Indian populations and global populations taken for comparison.
Review of Various IoT Standards and Communication Protocols

: With tremendous growth in IoT devices in last few years, research has also geared up in finding solutions to make cloud related services more scalable. The present paper is focusing on study and survey of object-to-object communication protocols enabling Internet of Things (IoT) environment. The paper also covers range of various existing networking communication protocols, routing protocols, data transfer protocols and security protocols. These protocols are adopted in IoT based environment, with layer based taxonomy. Security is one of the main concerns of IoT based environment. So many security and lightweight protocols also have been detailed out. Few of the protocols proposed by researchers have been adopted very successfully in IoT enabled environment. Various IoT enabling standards and technologies have also been reviewed in this paper. Further this paper also highlights the properties, characteristics and specialties of these protocols. Last but not least, the comparative analysis of various messaging protocols has also has been presented on the basis of their performance.
Diversity Narratives: How Color-blindness Shapes Diversity Beliefs and Actions in the U.S. Workplace

Following increased calls for racial justice spurred by the death of George Floyd, many organizations have pledged to support the Black community and play their part in dismantling systemic racism. One common step that leaders take is to invest in diversity programs. Despite bold claims to value diversity and billions of dollars invested in related efforts, workplace discrimination continues to be a major factor in the lives of racial and ethnic minorities. Further, the American public remains substantially divided in their views of diversity programs. Many Americans value diversity, while others believe diversity efforts have gone too far. The current study employed a mixed-methods survey to explore attitudes about diversity efforts and how these beliefs shape workplace decision-making. Our analysis of open-ended responses reveal that many individuals support organizational diversity in theory, yet subtly resist inclusion. This resistance reflects abstract liberalism, the foundational frame of color-blind racial ideology. Compared to those who acknowledge discrimination, those expressing abstract liberalism are more likely to believe Blacks are responsible for their own poor outcomes in the workplace and less likely to recommend a Black male for a promotion. Our findings also reveal that even those who both openly acknowledge discrimination and believe diversity is an important goal rarely take action to counter structural inequality. We discuss these findings in the context of shifting racial attitudes and whether such a shift will lead to broader systemic change that benefits Black employees.
Effect of Nickle Nanoparticles Solution on Staphylococcus aureus Contaminated Open Wounds Healing in Mice

The bacteria have been noted as the main cause of late wound healing. The greatest common pathogen causing the wound contaminations is Staphylococcus aureus. The current study was carried out to isolate and diagnose the staphylococcus aureus which causes of open wound inflammation after surgery in mice process and to study the effect of nickle nanoparticles solution on bacterial isolated and evaluating the molecular and pathological techniques. The study included the collection of 60 cotton swabs from the Office of the Consultant of the Faculty of Veterinary Medicine Tikrit University and from the external veterinary clinics (from November 2018 to March 2019) from the areas of contaminated wounds or inflamed after surgery. The results of the laboratory cultural of 60 cotton swabs used showed to isolated 50(83.3%) Staphylococcus aureus isolated. And all bacterial isolates were resistant to Doxycycline hydrochloride, Penicillin, CO-Trimoxazole, Ciprofloxacin, Cephalosporin and Penicillin. The study showed that the NFNPS used to inhibit the growth of bacterial isolated by using different concentrations the MBC killer concentration was 256μg / L and the lowest inhibitory concentration to Staphylococcus aureus was MIC 64 microgram / L). Molecular studies included the observation of the most important molecular changes at the level of DNA prior to and treatment with nanoparticles. Many variations were observed on the studied bacterial isolated Including the appearance and disappearance of DNA and its different numbers when treated with nanoparticles. As for the results of the histopathological, it was found that the injury of mice with Staphylococcus aureus antibiotic resistance emerged after about five days and the symptoms were heat, redness and swelling of the skin and the release of yellow and green purulent secretions from the place of injury. When treated mice infected with nanoparticles and antibiotics together the time of the healing was faster than the time of the healing of nanoparticles treated only.
The Socio-Economic Determinants of Child Educational Attainment in Pakistan

The main purpose of conducting this study was to explore the socioeconomic determinants of child educational attainment in Pakistan. Data on selected variables is extracted from nationally representative survey of Pakistan Social and Living Standards Measurement (PSLM) 2013-14. The study considers the children of age 5-18 years who ever attended any or currently attending any educational institution. Censored Ordered Probit model is employed. The results at aggregate level reveal that child’s gender, child’s age, age of household’s head, parental education, household assets and availability of private schools positively affect child educational attainment in Pakistan. Children belong to Baluchistan province and urban region of Pakistan also get more education as compare to reference categories. Gender of household head and distance to school has negative effect on child educational attainment. To explore the inconsistency in effect of these factors across region and across gender, separate analysis is conducted for urban, rural, male and female sample. The results of gender specific analysis indicate that income of the household, region of residence (urban) and annual school fee are the main factors causing gender disparity whereas estimates at regional level analysis show that parental education, agricultural land ownership and, distance to school are the factors responsible for regional disparity in child educational attainment. Keywords
Multi-parametric characterization of drug effects on cells

We present here a novel multi-parametric approach for the characterization of multiple cellular features, using images acquired by high-throughput and high-definition light microscopy. We specifically used this approach for deep and unbiased analysis of the effects of a drug library on five cultured cell lines. The presented method enables the acquisition and analysis of millions of images, of treated and control cells, followed by an automated identification of drugs inducing strong responses, evaluating the median effect concentrations and those cellular properties that are most highly affected by the drug. The tools described here provide standardized quantification of multiple attributes for systems level dissection of complex functions in normal and diseased cells, using multiple perturbations. Such analysis of cells, derived from pathological samples, may help in the diagnosis and follow-up of treatment in patients.
Environmental stresses and transcriptional responses for safe chloroplast operation

Higher plants are exposed to various environmental stresses which affect their survival and growth. Organellar perturbation which is caused by environmental stresses results in modulation of nuclear gene expression as a feedback regulation to relieve these stresses. To understand mechanisms of environmental adaptation that is achieved in part through the chloroplast signaling, or retrograde signaling, we are analyzing the transcriptional network that orchestrates stress responses in higher plants. Determination of cis-regulatory elements in the promoter region is an old subject in plant science but still provides essential information on the transcriptional network, and, it is now much more easily and more comprehensively conducted with the aid of our recently developed methodologies of bioinformatics. Functional analysis of synthetic promoters that contain only one or two cis-regulatory elements provides precise information on the upstream signals driving the cis-elements, which is also necessary to understand the network. In addition, biochemical analysis of DNA-protein interaction that is scalable with the aid of oligo DNA and a cDNA resource of Arabidopsis transcription factors (TFs) enables empirical determination of a middle-scale transcriptional network, which is under trial in our laboratory.
Heterogeneous Treatment Effects of Place-based Policies: Which Cities Should be Targeted?

In this paper, we empirically assess the treatment effects of a Japanese place-based policy known as the urban revitalization zone (URZ) program. on regional economies. We propose socially desirable assignment rules for the URZ program. The mixed results of previous empirical studies on place-based policies suggest that the treatment effects are regionally heterogeneous. In order to account for such heterogeneity across regions, this study estimates the conditional average treatment effect (CATE) for each region using a marginal treatment effects framework. We then use the estimated CATE parameters to construct empirically welfare-maximizing treatment rules based on the following three types of regional characteristic variables: demographic variables, suburbanization variables, and local production-network variables. Our results indicate that the treatment choice rule based on the suburbanization variables is the most successful. In particular, we find that cities with high numbers of cars per household and low percentages of large-scale stores should be targeted for URZ.
Synthesis and Antifungal Property of Mg Doped Zinc Oxide Nanocubes on the Glass Substrate Using Solution-Evaporation Method at Low Temperature

This in this paper, we report the synthesis of Mg doped ZnO nanocubes on the glass substrate by using solution-evaporation method at low temperature for the first time. Samples are characterized by means of scanning electron microscopy (SEM) and X-ray diffraction (XRD). The samples have a pure phase and no characteristic peaks are observed for the other impurities, such as Mg and MgO. It was observed that the length and width of the ZnO nanocubes are about 100nm and morphology of the samples is cube-shape. A blue-shift is observed in the band-edge with introduction of Mg into zinc oxide structure. The anti-fungal results indicate that ZnO nanocubes arrays exhibit stable properties after two months and play an important role in growth inhibitory of Candida albicans.