Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of hypertensive disorders of pregnancy and its maternal outcome in a tertiary care hospital, Salem, Tamil Nadu, India

Background: Hypertensive disorders complicate 5-10% of all pregnancies and together forms the deadly triad- along with hemorrhage and heart disease that contributes greatly to maternal morbidity and mortality. Objective of this study was to determine the prevalence of hypertensive disorders of pregnancy and its maternal complications in patients attending obstetrics and gynaecology department, Government Mohan Kumaramangalam Medical College Hospital, Salem.Methods: This is a prospective study conducted from August 2018 to July 2019 in the department of obstetrics and gynaecology. Patients diagnosed with hypertensive disorders of pregnancy was evaluated and data were collected.Results: A total of 19,383 pregnant women visited obstetrics and gynaecology department over a period of one year, out of which 2028 were diagnosed with hypertensive disorders of pregnancy. Hence the prevalence of hypertensive disorders in pregnancy is 10.4%. Among 2028 hypertensive disorder cases, Gestational hypertension were 962 cases (47.4%), pre-eclampsia 661 cases (32.6%), chronic hypertension 166 cases (8.2%) and pre-eclampsia superimposed on chronic hypertension 239 cases (11.8%). The prevalence was highest among primigravida (54%) compared to multigravida (46%). Hypertensive disorders were highest among the age group of 18-22 years in our study. Most common maternal complication in our study was HELLP syndrome.Conclusions: Prevalence of hypertensive disorders was high in our study. Early detection and timely intervention decrease the maternal complications.
Determinants of capital structure; a sector-level analysis for Indian manufacturing firms

PurposeThe purpose of this paper is to empirically analyze the determinants of capital structure and their long-run equilibrium relationships with firm-specific and macroeconomic indicators for Indian manufacturing firms.Design/methodology/approachThe study is conducted using the panel semi-parametric and non-parametric regression models to identify the key determinants of capital structure. Panel cointegration models are also employed for analyzing the long-run equilibrium association of capital structure with its determinants.FindingsThe study finds that each manufacturing sector has unique determinants of capital structure. The debt level is significantly affected by asset tangibility, growth opportunity, effective tax rate, non-debt tax shield, cash flow, profitability, firm size, foreign investment, government borrowing, economic growth, and interest rate. All these firm-specific and macroeconomic variables have strong long-run equilibrium relationship with capital structure as a whole.Practical Implication of the StudyThe study analyzes the determinants of capital structure for eight manufacturing sectors of India, which helps firm managers and policy-makers to identify appropriate factors that maximize firm value. The sector-specific features of firms may lead to a new path with regard to corporate governance and ownership structure to enhance stakeholder's satisfaction.Originality/valueThe use of semi-parametric and non-parametric panel regression models to analyze the determinants of capital structure, and the use of panel cointegration approach to explore the long-run equilibrium relationship between the determinants and its factors are the unique contributions of the present research.
Utility Grid Interfaced Solar WPS Using PMSM Drive With Improved Power Quality Performance for Operation Under Abnormal Grid Conditions

Owing to the intermittency issue associated with renewable energy sources, a solar photovoltaic (PV) array fed grid interfaced encoder-less permanent magnet synchronous motor (PMSM) based solar water pumping (SWP) system is presented in this paper. The grid integration enables a continuous water flow regardless of available solar insolation. However, it has been observed that the grids in developing and underdeveloped countries are mostly weak. Moreover, as SWP systems are typically established at remote locations, which are generally the grid radial ends, therefore, prone to various grid abnormalities. Such abnormalities affect the SWP system performance. Therefore, a hybrid multi-resonant generalized integrator-frequency locked loop (HMRGI-FLL) control structure is presented in this paper to deal with the abnormalities in grid voltage and makes the SWP system operational even under weak grid condition. The proposed structure not only rejects the dc-offset but it also eliminates the dominant lower order harmonic with its selective harmonic elimination capability. A boost converter is used on the grid side to facilitate the power transfer from the grid. In condition of grid failure, the output water flow is regulated in accordance with available solar insolation. The speed of the PMSM is regulated using sensor-less vector control. Performance of the proposed system is experimentally validated using a laboratory prototype under varying solar insolation, during grid failure, during voltage sag, voltage swell, and distorted grid voltage conditions.
A study of principal components analysis for mixed data

Analyzing data requires statistical tools to interpret the data information, which helps to improve the process. This is the interpretation of the qualitative and quantitative status of mixed data. The objective of this paper was to study the implementation of principal component analysis on mixed data and explain how to handle this type of databases and to make it possible to extract statistical information over a population under study. The effectiveness of principal component analysis on mixed data was studied using data sets available in the R package and simulated data.
Multimodal Personality Trait Recognition Using Wearable Sensors in Response to Public Speaking

Personality traits are fundamental parameters to characterize an individual’s behavior. Recently physiological signals are used to recognize personality traits in response to emotional videos, but gives good accuracies only for few traits. In this study, personality traits are statistically analyzed and recognized using physiological signals (electroencephalography (EEG), galvanic skin response (GSR), and photoplethysmogram (PPG)) in response to public speaking. The proposed framework consists of data acquisition, pre-processing, feature extraction, feature selection, and classification stages. The subject is labeled into two classes of each personality trait based on the mean value of big five personality trait questionnaire score. The physiological signals of twenty-eight participants are recorded while performing a public speaking task in front of a real audience. These signals are statistically analyzed to examine the behavior of different personality traits. Time domain features from GSR and PPG data and frequency domain features from EEG data are extracted. A wrapper based method for feature selection is applied to select an optimum set of features from each modality, which are then fused for personality trait recognition. An average F1-score of 0.86, 0.96, 0.64, 0.75, and 0.86 is achieved by the proposed framework for openness to experience, extroversion, neuroticism, conscientiousness, and agreeableness traits respectively. It is observed that the personality trait recognition using physiological signals in response to public speaking task outperforms the existing methods.
Social Learning in Transnational Spatial Planning Processes: An Analysis of the ‘V4+2’ Cooperation on Spatial Development

ABSTRACT Social learning can offer a useful lens to analyse multi-actor cooperation processes and their outcomes. In this paper, a conceptual framework based on learning theories is applied to a recent transnational spatial planning process in Central Europe to analyse how the cooperation agenda was shaped, a joint strategy developed, and to understand the possible policy effects of this process. The findings allow a reflection on the potentials of, and challenges for, multi-actor cooperation on spatial planning in large regions covering several countries.
Exploring the Underlying Dimensions of Job Satisfaction in Quality Management Practices

Humans issues involved in quality management are an important determinant of operational performance as it is crucial for quality improvement. Accordingly, the relationships between quality management (QM) and job satisfaction (JS) have recently received an attention in the QM literature. However, the available researches tried to study such relationships by merely relating their respective factors, obtaining critically dispersed findings and contributing in fragmented knowhow about the issue. The main objective of the present study is to examine the mechanics of relationships between QM & JS and create understandings on how one is constituted within the corpus of the other. A case study was carried out in the manufacturing organizations of Ethiopia. Data triangulation was used in the form of questionnaire survey and focus group interviews of shop floor workers. The study identified the underlying dimensions that are believed to realize JS. All of the dimensions were cross-checked with the fundamental ideas in the QM theory and shown to be constituted in it. It augments the existing understanding of the connection between QM and JS. Through the increased knowledge from this study, managers can maximize organizational gains via human resource perspectives. Keywords: Quality management; job satisfaction; Ethiopia. Keywords: Claims, Delivery, Administration DOI : 10.7176/IEL/9-2-03 Publication date :March 31 st 2019
Effect of fish scale texture on friction performance for reciprocating pair with high velocity

Purpose This paper aims to study the frictional performance of reciprocating pair with high velocity by using hydrodynamic lubrication principle and fish scale textured piston model. Design/methodology/approach Based on the idea of function characteristic approximation and coordinate change, a mathematical representation model of imitating fish scale texture pit section is established. According to the principle of dynamic pressure lubrication of the textured fluid, a three-dimensional numerical model of flow field for fish scale texture is established without considering cavitation. Numerical analysis of the model carp scale texture unit by orthogonal experimental design and FLUENT software is carried out. Findings Effects of fish scale pit texture on friction properties for a reciprocating pair piston surface with high velocity (impact piston) are acquired. Effects of texture characterization parameters and flow rate on the surface friction performance for impact piston are found. Effects of different characteristic parameters combination of imitating fish scale texture on friction performance for impact piston surface are obtained. Originality/value The model is an effective tool to study the friction and wear of reciprocating pair with high velocity. The effects of fish scale textured piston pair supply a theory lead to design the reciprocating pair with better friction performance. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2019-0398
BLADE: An in-Cache Computing Architecture for Edge Devices

Area and power-constrained edge devices are increasingly utilized to perform compute intensive workloads, necessitating increasingly area and power-efficient accelerators. In this context, in-SRAM computing performs hundreds of parallel operations on spatially local data common in many emerging workloads, while reducing power consumption due to data movement. However, in-SRAM computing faces many challenges, including integration into the existing architecture, arithmetic operation support, data corruption at high operating frequencies, inability to run at low voltages, and low area density. To meet these challenges, this article introduces BLADE, a BitLine Accelerator for Devices on the Edge. BLADE is an in-SRAM computing architecture that utilizes local wordline groups to perform computations at a frequency 2.8x higher than state-of-the-art in-SRAM computing architectures. BLADE is integrated into the cache hierarchy of low-voltage edge devices, and simulated and benchmarked at the transistor, architecture, and software abstraction levels. Experimental results demonstrate performance/energy gains over an equivalent NEON accelerated processor for a variety of edge device workloads, namely, cryptography (4x performance gain/6x energy reduction), video encoding (6x/2x), and convolutional neural networks (3x/1.5x), while maintaining the highest frequency/energy ratio (up to 2.2 Ghz@1V) of any conventional in-SRAM computing architecture, and a low area overhead of less than 8 percent.
A Chemotherapeutic Efficacy of Some antibiotics and Punica Grantum L. Extracts against Propionibacterium Acnes Isolated from Acne Vulgaris Cases

Acne is a major skin problem among the youth, and is usually initiated by androgen and propagated by bacterial flora of hair follicles such as Propionibacterium acnes and Staphylococcus epidermidis (1). Pomegrantum extracts are extensively used throughout the world as a traditional beverage, which contain many chemical compounds like tannins, mainly catechins, flavonol, and alkaloid substances. Pomegrantum extracts are used as an antibacterial, antioxidant, and immune-modulating agent (2).
Can the intermediate disturbance hypothesis explain grazing–diversity relations at a global scale?

In the context of grazing, the intermediate disturbance hypothesis (IDH) predicts that plant diversity peaks under moderate grazing, resulting in a hump‐shape pattern for the grazing–diversity relationship. Although this has been debated due to contradictory empirical results, the IDH is still widely accepted among rangeland ecologists. The Milchunas–Sala–Lauenroth (MSL) model predicts that in arid areas grazing affects diversity negatively regardless of grazing intensity, whereas in mesic areas grazing effects on plant diversity are the same as predicted by the IDH. Very few studies have attempted to specifically evaluate the applicability of the IDH and MSL to grazing systems at a global scale, accounting for the possible effects of climate. We conducted a meta‐analysis and vote‐counting analysis to evaluate these two hypotheses. The results of both analyses show that the IDH cannot be applied globally and that its application largely depends on aridity. The IDH prediction of a hump‐shape curve is supported in wet areas, while in dry areas there is a slight decrease in species richness with increasing grazing intensity. Overall, the MSL model correctly predicted grazing–diversity relations in both wet and dry areas. Looking at specific ecosystem types, we found that these results hold in grasslands, but not in woodlands. Differences between livestock types, not considered by the MSL model, were found to be important. Mixed sheep and goat grazing in dry areas resulted in a significant decline of species richness with grazing intensity, while grazing by sheep only had little effect on species richness. Cattle grazing and yak grazing in wet areas yielded a clear hump‐shape pattern. Therefore, we conclude that the climate‐specific MSL model better predicts the impact of grazing on diversity than the IDH in rangelands, and that the response patterns of plant richness to grazing are dependent on aridity, grazing intensity and grazer type.
“Just for fun?”: An exploration of digital games’ potential for eudaimonic media experiences among Flemish adolescents

ABSTRACT Research shows that media entertainment can induce eudaimonic or meaningful experiences, such as being emotionally moved or being stimulated to reflect about oneself. While these studies have primarily focused on adults’ eudaimonic media entertainment experiences, the current study explores whether games can lead to eudaimonic experiences amongst adolescents, for instance, via characteristics like emotionally deep stories and moral choices. Games are very popular among adolescents, while eudaimonic experiences may possibly fulfill key needs of identity development and peer relatedness as well as prove to be beneficial for adolescents’ well-being and overall development. To explore adolescents’ eudaimonic game experiences, we performed a qualitative study existing of six focus groups (N = 33) and 20 individual in-depth interviews (total N = 53). Results indicate that adolescents do experience eudaimonic game moments. Specifically, they experienced socially bonding, reflective (about oneself and society), emotionally moving, and elevating moments. These were considered particularly meaningful when they were somehow connected to real life. Finally, adolescents mostly mentioned narrative aspects (i.e., the game’s story, characters, moral choices), other real players, and audiovisual aspects like graphics and soundtrack as important elicitors of eudaimonic game experiences. Limitations and future research suggestions are further discussed.
Vocell: A 65-nm Speech-Triggered Wake-Up SoC for 10- $\mu$ W Keyword Spotting and Speaker Verification

The use of speech-triggered wake-up interfaces has grown significantly in the last few years for use in ubiquitous and mobile devices. Since these interfaces must always be active, power consumption is one of their primary design metrics. This article presents a complete mixed-signal system-on-chip, capable of directly interfacing to an analog microphone and performing keyword spotting (KWS) and speaker verification (SV), without any need for further external accesses. Through the use of: 1) an integrated single-chip digital-friendly design; b) hardware-aware algorithmic optimization; and c) memory- and power-optimized accelerators, ultra-low power is achieved while maintaining high accuracy for speech recognition tasks. The 65-nm implementation achieves 18.3-<inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> worst case power consumption or 10.6-<inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> power for typical real-time scenarios, <inline-formula> <tex-math notation="LaTeX">$10\times $ </tex-math></inline-formula> below state of the art (SoA).
Gifted Students’ Adjustment and Underachievement in University: An Exploration From the Self-Determination Theory Perspective

Successful transition from school to university is essential for the academic success of any student. Gifted students might encounter unique challenges due to their characteristics, and there is an evidence that a failure to adjust to the demands of university environment has a negative effect on gifted students’ academic performance, leading to underachievement. This qualitative study aimed at exploration of gifted students’ adjustment to university and issues they face within this process. We use the lenses provided by self-determination theory to further interpret the role of both internal and external motivation forces contributing to gifted students’ adjustment and achievement in higher education settings. It was identified that the gifted school and university learning environments, as well as the influence of key people (parents, peers, and teachers) played a crucial role in facilitating or impeding gifted school graduates’ sense of self-determination and consequently their adjustment and achievement. This study offers interesting insights for the understanding of gifted (under)achievement in a context where giftedness is predominantly conceived as high intelligence and academic achievement, gifted students are identified via performance-based measures, specialized schools are the preferred means for gifted education, and young people’s talents are considered invaluable for the development of the national economy and the society.
Parent–Child Relationship Satisfaction: The Influence of Family Communication Orientations and Relational Maintenance Behaviors

This study examined emerging adults’ satisfaction with parent–child relationships as a function of family communication orientations and relational maintenance behaviors. Two hundred and eleven emerging adults completed measures assessing family communication orientations (conversation and conformity), relational maintenance behaviors (shared tasks, shared networks, positivity, openness, and assurances), and satisfaction with parent–child relationships. Results demonstrated that family conversation orientation and relational maintenance behaviors were positively associated with relationship satisfaction; family conformity orientation was not related to relationship satisfaction. Furthermore, findings indicated support for a model in which positivity and openness mediated the association between family conversation orientation and children’s satisfaction with parent–child relationships.
Complete mitogenome of the chlorophyte green alga Marsupiomonas sp. NIES 1824 (Pedinophyceae)

Abstract The 25,137-bp mitogenome of the green alga Pedinomonas minor (Pedinomonadales, Pedinophyceae), which belongs to a basal class of the core Chlorophyta, is unusual in displaying a reduced gene content as well as other derived traits. Here, we present the mitogenome of Marsupiomonas sp. NIES 1824 (Marsupiomonadales, Pedinophyceae). Despite its smaller size, this 24,252-bp genome encodes twice as many genes (39) as its P. minor homolog. Besides gradual gene erosion, our comparative analyses revealed that major changes in GC content and codon usage led to the gain of distinct, noncanonical genetic codes during evolution of the mitogenome in the Pedinophyceae.
A metaheuristic optimization approach for energy efficiency in the IoT networks

Recently Internet of Things (IoT) is being used in several fields like smart city, agriculture, weather forecasting, smart grids, waste management, etc. Even though IoT has huge potential in several applications, there are some areas for improvement. In the current work, we have concentrated on minimizing the energy consumption of sensors in the IoT network that will lead to an increase in the network lifetime. In this work, to optimize the energy consumption, most appropriate Cluster Head (CH) is chosen in the IoT network. The proposed work makes use of a hybrid metaheuristic algorithm, namely, Whale Optimization Algorithm (WOA) with Simulated Annealing (SA). To select the optimal CH in the clusters of IoT network, several performance metrics such as the number of alive nodes, load, temperature, residual energy, cost function have been used. The proposed approach is then compared with several state‐of‐the‐art optimization algorithms like Artificial Bee Colony algorithm, Genetic Algorithm, Adaptive Gravitational Search algorithm, WOA. The results prove the superiority of the proposed hybrid approach over existing approaches.