Miracle-dz/UniFAR-FTUs huggingface dataset:
Placenta Accreta spectrum (pas) disorders: A 10-year study at tertiary care center, Ahmedabad, western India

Background: The last 30 years have witnessed the dramatic increase in the incidence of placenta accreta spectrum (PAS) disorders from 0.12% to 0.31%. The spectrum of abnormal placental invasion ranges from the subclinical findings of adherent placental basal plate with the myometrial fibres to the substantial presentation of placenta percreta. Methods: In this retrospective study of 10 years, there were 81,650 deliveries at our tertiary care center and 28 patients were diagnosed with PAS disorders. The placental localization and diagnosis of placental spectrum disorders were confirmed with ultrasound and color doppler. Results: Total deliveries during the 10 years study were 81,650, out of which 27 cases met the diagnostic criteria of PAS with ultrasound and 1 case diagnosed intraoperatively resulting incidence of PAS to 0.035%. There is increase in incidence of PAS from 0.0125% in 2010 to 0.1% in 2019. All these patients were planned for elective cesarean section at 35 weeks gestation, but 2 of them presented in emergency with bouts of bleeding and required immediate intervention. Massive hemorrhage was reported in 12 (42.8%) cases and 26 (92.9%) cases required blood transfusion. Bladder injury was reported in 6 (21.4%) case. Maternal mortality has been noted in 1(3.5%) case which was complicated with disseminated intravascular coagulation and acute renal failure. Conclusions: Favorable outcome in PAS disorders can only be achieved with preoperative multidisciplinary input and perioperative measures require adequate time in order to be instituted.
Modeling Affordances and Functioning for Personalized Robotic Assistance

A key aspect of robotic assistants is their ability to contextualize their behavior according to different needs of assistive scenarios. This work presents an ontology-based knowledge representation and reasoning approach supporting the synthesis of personalized behavior of robotic assistants. It introduces an ontological model of health state and functioning of persons based on the International Classification of Functioning, Disability and Health. Moreover, it borrows the concepts of affordance and function from the literature of robotics and manufacturing and adapts them to robotic (physical and cognitive) assistance domain. Knowledge reasoning mechanisms are developed on top of the resulting ontological model to reason about stimulation capabilities of a robot and health state of a person in order to identify action opportunities and achieve personalized assistance. Experimental tests assess the performance of the proposed approach and its capability of dealing with different profiles and stimuli.
On the Unbalanced Atmospheric Environmental Performance of Major Cities in China

As the largest emitter of CO2, China has also serious air pollution issues. Is it possible to catch these two rabbits under heterogenetic conditions of urbanization? To answer this, this study examines atmospheric environmental performance (SO2, NOx, and PMs) of 30 major cities in China using streaming data from 2011 to 2017. A non-radial SBM-DEA approach is adopted with a meta-frontier model to evaluate regional heterogeneity in atmospheric environmental management. Our results suggest that pollution prevention and regulation policies encouraged synergic development of most cities in the economy and atmospheric environment. On average, atmospheric environmental efficiency of the cities improved from 0.556 to 0.691. However, significantly unbalanced development exists in the regions, requiring customized policies. Eastern cities achieved continuing improvement owing to stringent air pollutant emission policies. Central cities showed a strong improvement but lacked momentum after they achieved certain targets. Western cities lagged behind in the studying period due to both technology gap as well as weak regulation. Furthermore, we identify heterogeneous paths for inefficient cities to enhance their performance using benchmark information. Economically developed eastern cities, such as Beijing, Fuzhou, are facing an over-supply issue. Reshaping their economic structure may be necessary to attain better environmental performance. Central cities face diversified issues. The emphasis of different cities may vary from stringent emission policies to proactive supply-side transition to achieve strong atmospheric management performance. For under-developed cities, preferential policies for investment and tax incentives may be needed to improve their production scale for higher efficiency.
Sustainable Approach for Linz-Donawitz Slag Waste as a Replacement of Cement in Concrete: Mechanical, Microstructural, and Durability Properties

Linz-Donawitz (LD) slag, solid waste produced during steel manufacture in basic oxygen furnace, is difficult when it comes to handling and disposal and has very limited utilization. To increase its reusability, the suitability of supplanting cement with LD slag in concrete was examined. To study the impact of partially replacing cement with LD slag on strength, microstructure, and durability of concrete, more than 150 samples were cast. The test results reveal that the highest compressive and flexural strengths were attained at 20% LD slag replacement and, beyond that, the strength decreased. The hydration products detected by X-ray Diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) were calcium silicate hydrate (C-S-H), ettringite, and calcium aluminosilicate hydrate (C-A-S-H). The scanning electron microscope (SEM) images of binary cement concrete showed denser microstructure and lesser voids. The sulphuric acid resistance, electrical resistivity, and carbonation resistance tests done reveal that acceptable durability could be achieved when cement is replaced by LD slag. It is deduced that LD slag can be utilized in partially replacing cement to achieve the desired strength. This research gives another comprehension of simultaneously managing steel industry waste for sustainable development and contributing added advantages to the economy.
Effect of nutrient management through organic sources on yield and quality of garlic (Allium sativum L.) under organic farming

An experiment was conducted on medium black calcareous soil at Junagadh (Gujarat) to evaluate FYM, biofertilizers and botanicals for organic cultivation of garlic (var. Gujarat Garlic 4) during Rabi season of 2017-18 and 2018-19. The results revealed that the growth parameters, yield attributes and yield were significantly influenced by the various organic treatments in both years and pooled results. The experimental results revealed that the application of FYM @ 10 t/ha + Panchgavya as foliar spray @ 3% at 30 and 60 DAS (T1) produced significant effect on growth parameters, yield attributes and yield obtained significantly higher bulb yield (68.04, 71.28 and 68.99 q/ha) and straw yield (8.63, 9.47 and 8.87 q/ha) in 2018, 2019 and pooled results, respectively.
Uses and Gratifications of YouTube: A Comparative Analysis of Users and Content Creators

Drawing on the classic media theory of uses and gratifications, this paper comparatively analyzes the uses of YouTube and the rewards obtained by consumers and content of this video sharing platform. The aim of this research is two-fold: 1. to identify the main uses and gratifications that determine consumers and content creators to use YouTube, and 2) to examine the reasons behind the decision to become a content creator on YouTube. Based on a qualitative research method, the paper highlights how YouTube is used from the perspective of consumers and content creators and the types of needs it gratifies. The research consists of 20 in-depth interviews with YouTube consumers and content creators from Romania. While for content consumers YouTube is mainly a means of relaxation and information, for content creators this platform becomes a source of recognition and social validation. The study also indicates that vlogging can provide job-specific gratifications. Moreover, the research reveals essential aspects behind the decision to become a content creator.
A Technique for Frequency Converter-Fed Asynchronous Motor Vibration Monitoring and Fault Classification, Applying Continuous Wavelet Transform and Convolutional Neural Networks

In this article, a type of diagnostic tool for an asynchronous motor powered from a frequency converter is proposed. An all-purpose, effective, and simple method for asynchronous motor monitoring is used. This method includes a single vibration measuring device fixed on the motor’s housing to detect faults such as worn-out or broken bearings, shaft misalignment, defective motor support, lost phase to the stator, and short circuit in one of the phase windings in the stator. The gathered vibration data are then standardized and continuous wavelet transform (CWT) is applied for feature extraction. Using morl wavelets, the algorithm is applied to all the datasets in the research and resulting scalograms are then fed to a complex deep convolutional neural network (CNN). Training and testing are done using separate datasets. The resulting model could successfully classify all the defects at an excellent rate and even separate mechanical faults from electrical ones. The best performing model achieved 97.53% accuracy.
Risk Factors and Perinatal Outcome of Meconium Stained Amniotic Fluid

Introduction: Meconium Stained Amniotic Fluid (MSAF) is a frequent finding during deliveries and is a cause for perinatal morbidity and mortality. Meconium Aspiration Syndrome (MAS) in neonates is an association in these deliveries with some infants requiring mechanical ventilation. This study was done with the aim of finding the risk factors for MSAF and its perinatal outcome. Methods: This was a hospital based, cross-sectional study. All the inborn babies delivered with MSAF were included in the study. Antenatal risk factors and perinatal outcomes like mode of delivery, Apgar score, NICU admission and neonatal morbidities mainly MAS were noted. Results: MSAF was seen in 202 (13.6%) neonates out of which 30 (15%)developed MAS. Antenatal risk factors were present in 97 (48%) cases. Mode of delivery was caesarean section in 78 (39%) and instrumental in 25 (13%) cases. Twenty three percent of the neonates required resuscitation at birth while 34% required respiratory support. Morbidities observed were meconium aspiration, pneumonia, septicaemia, perinatal asphyxia, shock, meconium gastritis and persistent pulmonary hypertension. Neonatal mortality amongst all neonates with meconium was 1.5%. Conclusion: Meconium stained amniotic fluid leading to aspiration is a significant cause of neonatal mortality and morbidity. Most of the risk factors for MAS are preventable.
Attributes Reduction in Big Data

Processing big data requires serious computing resources. Because of this challenge, big data processing is an issue not only for algorithms but also for computing resources. This article analyzes a large amount of data from different points of view. One perspective is the processing of reduced collections of big data with less computing resources. Therefore, the study analyzed 40 GB data to test various strategies to reduce data processing. Thus, the goal is to reduce this data, but not to compromise on the detection and model learning in machine learning. Several alternatives were analyzed, and it is found that in many cases and types of settings, data can be reduced to some extent without compromising detection efficiency. Tests of 200 attributes showed that with a performance loss of only 4%, more than 80% of the data could be ignored. The results found in the study, thus provide useful insights into large data analytics.
Machine Learning applied on Poincaré Analyisis to discriminate different cardiac issues

Poincare plot analysis has been recognized to provide valuable information in the prognostic stratification of cardiac patients. The parameters provided by the analysis can be used as input for machine learning algorithms in order to distinguish patients in Health, Hypertension, Post-myocardial infarction, Congestive heart failure, Heart transplanted classes. Knime analytics platform was employed to implement decision tree and random forests algorithms. Some evaluation metrics (accuracy, sensitivity and specificity) were computed to assess the final performance. The best accuracy was 86% while the highest specificity was 98.8%. The analysis proved the feasibility of machine learning in predicting patients with different cardiac issues based on parameters extracted through a Poincare analysis.
Ensemble Modeling of the Impact of Climate Warming and Increased Frequency of Extreme Climatic Events on the Thermal Characteristics of a Sub-Tropical Lake

Lake ecosystems are impacted by changes in climatic conditions. Climate changes forecasted to occur are reflected in models by slow gradual changes over extended periods of time. Output from weather generators, on the other hand, can simulate short-term extreme conditions and weather patterns. In order to evaluate the likely impact of climate changes on a large sub-tropical lake, specifically the thermal regime of the lake, we constructed climate scenarios using a weather generator. The 30-year scenarios included no change in climate conditions, a gradual change, increased frequency of heat waves and a merging of the latter two. The projected impact on the lake’s physical properties was evaluated using an ensemble of 1-D hydrodynamic lake models. The gradual increase scenario had the largest impact on annual temperatures and stratification period; however, increased heat waves had a large effect on the summer lake conditions and introduced a larger degree of variability in water temperature. The use of the ensemble of models resulted in variability in the projected impacts; yet, the large degree of similarity between projected trends and patterns increased confidence in the results. The projected effect the heat waves will have on the lake conditions highlights the need to include heat waves in climate studies and the need for impact studies in order to better understand possible consequences for lake ecosystems.
Transparency Promotion with Model-Agnostic Linear Competitors

We propose a novel type of hybrid model for multi-class classiﬁcation, which utilizes competing linear models to collaborate with an existing black-box model, promoting transparency in the decision-making process. Our proposed hybrid model, Model-Agnostic Linear Competitors (MALC), brings together the interpretable power of linear models and the good predictive performance of the state-of-the-art black-box models. We formulate the training of a MALC model as a convex optimization problem, optimizing the predictive accuracy and transparency (deﬁned as the percentage of data captured by the linear models) in the objective function. Experiments show that MALC offers more model ﬂexibility for users to balance transparency and accuracy, in contrast to the currently available choice of either a pure black-box model or a pure interpretable model. The human evaluation also shows that more users are likely to choose MALC for this model ﬂex-ibility compared with interpretable models and black-box models.
Bringing the war home: the strategic logic of ‘North Caucasian terrorism’ in Russia

ABSTRACT Terrorism connected to the North Caucasus has been pervasive in Russia between 1992 and 2018. Based on an original dataset, this article presents statistics on rates of terrorist attacks outside of the North Caucasus, their geography and targets, and the tactics used. It argues that terrorism by North Caucasian insurgents has long retained a strategic logic despite their conversion to radical Islamism. Accordingly, the end of North Caucasian terrorism was determined by the erosion of its strategic character as an increasingly vague ideological project replaced concrete political goals among the insurgents.
Determination of a stress-dependent rock-physics model using anisotropic time-lapse tomographic inversion

In the petroleum industry, time-lapse (4D) studies are commonly used for reservoir monitoring, but they are also useful to perform risk assessment for potential overburden deformations (e.g., well shearing, cap-rock integrity). Although complex anisotropic velocity changes are predicted in the overburden by geomechanical studies, conventional time-lapse inversion workflows only deal with vertical velocity changes. To retrieve the geomechanically induced anisotropy, we have adopted a reflection traveltime tomography method coupled with a time-shift estimation algorithm of prestack data of the baseline and monitor simultaneously. For the 2D approach, we parameterize the anisotropy using five coefficients, enough to cover any type of anisotropy. Before applying the workflow to a real data set, we first study a synthetic data set based on the real data set and include velocity variations between baseline and monitor found in the literature (vertical P-wave velocity decrease in the cap rock and isotropic P-wave velocity change in the reservoir). On the synthetics, we measure the angular ray coverage necessary to retrieve the target anisotropy and observe that the retrieved anisotropies depend on the offset range. Based on a synthetic experiment, we believe that the acquisition of the real case study is suitable for performing tomographic inversion. The anisotropic velocity changes obtained on three inlines separated by 375 m are consistent and show a strong positive anomaly in the cap rock along the 45° direction (the [Formula: see text] parameter in Thomsen notation), whereas the vertical velocity change is surprisingly almost negligible. We adopt a rock-physics explanation compatible with these observations and geologic considerations: a reactivation of water-filled subvertical cracks.
Liquid micronized CaCO3: an alternative to correct the pH of an acidic soil and improve pineapple development

Objective: to determine the effect of liquid micronized CaCO3 on soil pH and pineapple vegetative development in acidic soils at Isla, Veracruz. Design/Methodology/Approach: randomized blocks with four replications and four treatments: Non-liming control (T1), 2.0 t ha-1 of dolomite (T2), 10.0 (T3) and 20.0 (T4) L ha-1 of liquid CaCO3. The soil pH was measured, before liming and at 30, 60, 90 and 120 days after sowing, at depths of 0-5, 5-15 and 15-30 cm, and the biomass was determined at the 60, 90 and 120 dds. Analysis of variance and the 5% Fisher test were performed to separate means. Results: up to 90 dds, with dolomite, optimal pH values were reached for pineapple, significantly higher than those of CaCO3 in both doses. At 120 dds, with 20 L ha-1 CaCO3 the pH was higher than 5.0, similar to that of dolomite and higher than those of the low dose of CaCO3 and the control. At the last date, with 20 L ha-1 of CaCO3 1,346 g plant-1 biomass were produced, an amount similar to dolomite and the low dose of CaCO3 and significantly higher than that of the control. Findings/Conclusions: up to 120 dds, with 20 L ha-1 of liquid CaCO3, the optimum pH for pineapple was reached in the three strata, the values were similar to those of dolomite and higher than those of the low dose of CaCO3 and the control. CaCO3 (20 L ha-1) and dolomite (2 t ha-1) produced 33.1 and 20.9% more biomass than the control.
Internal audit function and real earnings management practices in an emerging market

This study aims to investigate the monitoring role of internal audit function (IAF) on real earnings management (REM) practices. It examines the effect of investment in IAF (IIAF) and IAF sourcing arrangements on REM, unlike prior literature which has mainly examined the effects of IIAF on accrual-based earnings management. ,This study uses a sample of 1,056 observations from an emerging market, Malaysia, between 2013 and 2016. Feasible generalised least square (FGLS) regression is used to analyse the data. To corroborate the results of this study, the authors use an ordinary least square (OLS) regression model with robust standard errors adjusted and also consider alternative REM measures. ,The results of this study suggest that IIAF has a significant negative relationship with REM practices. Further, in-house IAF sourcing has a significant negative association with REM. The additional analysis supports the main results confirming the essential role of IAF in reducing REM in the Malaysian market. ,The evidence relates to the important role of IAF in mitigating REM practices. High-quality of IAF impairs managers’ ability to manage earnings in their own interests. The findings may be useful in informing regulators, managers, shareholders and other investors, as well as researchers, about improving the role of IAF. ,This study contributes to the existing literature by providing the first evidence of the significant role of IIAF and IAF sourcing arrangements in mitigating REM in an emerging country.
Physiological and histological alterations in fishes induced by pollution in Lake Nasser and the potential human risk assessment

Lake Nasser is one of the longest man-made lakes in the world; it was formed after the construction of Aswan High Dam. Furthermore it considered the fundamental water bank of Egypt; which provides more than 95% of freshwater needs (Ali et al., 2016). The total surface area is 6276 km 2 , 5237 km 2 represents Lake Nasser and 1039 km 2 in the northern part of Sudan is known as Lake Nubia (Heikal, 2010). The lake bank is extremely irregular with several terminal extensions known as khors that is representing about 79% of total lake surface. Khors are the favorite habitat for fish; therefore Khors are important in fish production (El-Shabrawy and Dumont, 2003). Many previous studies investigated the ecology and morphology of Lake Nasser (Latif, 1984; Khalifa et al., 2000; El-Shabrawy, 2014). The Water quality of the Lake Nasser is influenced by many factors such as; water levels, thermal stratification, water circulation and pollutants (El-Shabrawy, 2014). ARTICLE INFO ABSTRACT Article History: Received: June 4, 2020 Accepted: June 30, 2020 Online: July 2020 _______________
Analysis of Expansion Mesenchymal Stromal Cells in patients with low risk myelodysplastic syndrome

Myelodysplastic syndromes (MDS) comprise a heterogeneous group of clonal hematopoiet­ic disorders characterized by ineffective hematopoiesis, cytopenias and dysplasia and one or more lineages. The stratification of MDS is made based on the percentage of bone marrow blasts, number of cytopenias and karyotype at diagnosis. Somatic mutations in the p53 tu­mor suppressor gene are found in approximately 50% of all human tumors, making it the most commonly mutated gene. The expression of p53 protein and the study of mutations is especially needed in the prognosis of MDS. In this context, the study aims to evaluate the expansion of mesenchymal stromal cells (MSCs) and the expression of p53 protein in pa­tients with SMD, low risk, according to the International Prognostic System (IPSS), in order to demonstrate the importance of these evaluations also diagnostics. This is a cross-sectional analytical study with review 3 adult patients of both sexes, the diagnosis of low-risk MDS receiving outpatient treatment at the University Hospital Walter Cantidio (HUWC). MSCs were characterized by immunophenotyping and screening of mutation of the p53 gene by Real Time PCR System (Applied Biosystems). For data analysis, the statistical software was used GraphPadPrism 5.0. Statistical differences between groups were checked by Student t or Mann-Whitney’s test significance level was p < 0.05 for all analyzes. The results showed a smaller expansion of MSCs in the bone marrow of patients with MDS compared with a control group. A survey of mutation of the p53 gene was negative in all patients. The results demonstrate an impairment in the growth of MSCs in patients with MDS, collaborating with the hypothesis that medullary microenvironment in MDS may be compromised contributing greater understanding of disease mechanisms. However studies with larger sample should be conducted in order to establish the best results.