Miracle-dz/UniFAR-FTUs huggingface dataset:
Pre-operative and peri operative predictors of acute renal failure after cardiac surgery

Background: Acute kidney injury (AKI) is one of the most serious complications during the postoperative period of cardiac surgery. Multiple variables predict the ARF after cardiac surgery. Objective of this study was to evaluate the significance of pre and peri-operative variables which may help in predicting the chances of developing ARF after cardiac surgery.Methods: This study was an observational, prospective study conducted among patients who were scheduled to undergo open heart surgery under cardiopulmonary bypass.Results: In total, 50 patients who underwent open-heart surgery, ARF was seen in 5 patients, with the incidence rate of 10%. Acute renal failure was present in one patient with ejection fraction <35, 2 patients had ejection fraction between 35 to 50 and 2 patients with ejection fraction >50. It was seen in 4 patients with 1-2 hrs of cardiopulmonary bypass and in 1 patient with >2 hrs of cardiopulmonary bypass. ARF was also seen in 4 patients with hematocrit between 22-26% and in 1 patient with >26%. Conclusions: The study provided a clinical variable score that can predict ARF after open-heart surgery. The score enhances the accuracy of prediction by accounting for the effect of all major risk factors of ARF.
A graph‐based method for social sensing of infrastructure disruptions in disasters

Damages in critical infrastructure occur abruptly, and disruptions evolve with time dynamically. Understanding the situation of critical infrastructure disruptions is essential to effective disaster response and recovery of communities. Although the potential of social media data for situation awareness during disasters has been investigated in recent studies, the application of social sensing in detecting disruptions and analyzing evolutions of the situation about critical infrastructure is limited. To address this limitation, this study developed a graph‐based method for detecting credible situation information related to infrastructure disruptions in disasters. The proposed method was composed of data filtering, burst time‐frame detection, content similarity calculation, graph analysis, and situation evolution analysis. The application of the proposed method was demonstrated in a case study of Hurricane Harvey in 2017 in Houston. The findings highlighted the capability of the proposed method in detecting credible situational information and capturing the temporal and spatial patterns of critical infrastructure events that occurred in Harvey, including disruptive events and their adverse impacts on communities. The proposed methodology can improve the ability of community members, volunteer responders, and decision makers to detect and respond to infrastructure disruptions in disasters.
State Estimation and Error Analysis of a Single State Dynamic System with Sensor Data Using Kalman Filter

Kalman Filter is used in system estimation applications today like state estimation, load flow analysis, harmonic estimation, digital signal processing, sensor integration, Navigational Systems, etc. In using a Kalman Filter the user has to give the parameters relating the estimates of process and measurement noise along with system state modeling. The values of process and measurement noise covariance are usually not available beforehand and have to be estimated, usually by hit or trial method. This involves heavy computation, as two variables have to be estimated for optimal filtering independently. For multi-state systems this value further increases the computation time. This paper presents the application of Kalman Filter to a simple one state problem. This paper, through using simulations, finds relationships between the two different parameters Q (Process Noise Covariance) and R (Measurement Noise Covariance). This results in reduction of computation time. The proposed scheme’s low complexity and robustness makes it practical for real implementations.
ATYPICAL HYPERPACHYMORPH TRYPANOSOMA ( NANNOMONAS ) CONGOLENSE FOREST-TYPE IN A DOG RETURNING FROM SENEGAL

Trypanosoma congolense forest-type was identified by PCR in France, in a dog returning from Senegal. This paper describes the morphological features of the parasite on Giemsa-stained smears. Slender forms and “latent bodies” represent 30.4 % and 20.4 %, respectively. Some rosettes have been observed (0.8 %). The predominant form (48.4 %) is stumpy, close to “montgomeryiform”, but it is unusually broad, with a width/length ratio (WLr) of 0.40-0.55, while that of “montgomeryi-forms” is close to 0.3. To the best of our knowledge, this is the first description of such a form of T. (Nannomonas). Also unusual, the shape of the cytoplasm appears to be tightened by an “S-” or “C-” shaped flagellum. We propose naming this peculiar morphotype “hyperpachymorph”, and adding its description to that of T. congolense forest-type. Thus T. (Nannomonas) forms would include: sphaeromorph or “latent bodyform” (globular), hyperleptomorph (rodhaini-form, very long and slender, with a free flagellum); leptomorph (simiae-form, slender, with a free flagellum); isomorph (congolense-form, short, generally without a free flagellum); pachymorph (montgomeryi-form, short and stout; 0.25 < WLr < 0.34, without a free flagellum), and hyperpachymorph (“hyper-montgomeryi-form”, short and very stout; 0.35 < WLr < 0.7, without a free flagellum).
Effects of fermented potato protein supplementation in drinking water on growth performance, carcass characteristics, small intestinal morphology and expression of IGF-1 and GHR genes in the liver of broiler chickens

We investigated the effects of fermented potato protein (FPP), supplied through drinking water, on growth performance of broiler chickens. A total of 288 male broiler chickens were divided into two groups: a control group and an experimental group supplemented with 0.01% FPP in drinking water. The FPP group had a significantly higher BWG and ADG (P less than 0.01) and significantly improved FCR (Pless than 0.05). The percentage of breast was significantly higher (P less than 0.05) in fermented potato protein (FPP) group. The FPP group had an increased villus height (P less than 0.05) in duodenum and jejunum. Expression of IGF-1 gene in the liver was significantly higher in the FPP group than in the control group (P less than 0.05), whereas GHR gene expression did not differ between the groups at 37 days. This study suggests that FPP supplementation in drinking water improves growth performance of broiler chickens by stimulating IGF-1 gene expression in the liver and improving the intestinal morphology.
Restoration and rehabilitation potential of the remnant natural forests of Himchari National Park (HNP) in Cox’s Bazar, Bangladesh

Abstract. Hossen S, Hossain MK, Uddin MF. 2019. Restoration and rehabilitation potential of the remnant natural forests of Himchari National Park (HNP) in Cox’s Bazar, Bangladesh. Asian J For 3 : 25-30. The present study was conducted by taking 51 stratified random sample quadrats (20 m x 20 m), where, naturally occupied vegetation (dbh ≥ 5cm) was found in maximum (16 plot, 31%) number of plots. The highest number of regenerated seedlings was accounted for Grewia nervosa 12.37 % followed by Acacia auriculiformis 8.95%. For regeneration study, 5 m × 5 m subplots were taken at the centre of each of the 51 sample quadrats and thus a total of 51 regeneration subplots were studied. The maximum Importance Value Index (IVI) of regenerated seedlings was found for Grewia nervosa (26.43) followed by Acacia auriculiformis (20.27). Different biological diversity indices such as species diversity index, Shanon-Wiener’s diversity index, Shanon’s maximum diversity index, species evenness index, Margalef’s diversity index and Simpson’s diversity index were 0.054, 3.166, 3.714, 0.853, 6.03 and 0.057 respectively. Maximum natural regeneration was observed in the sample plots of Natural and plantation forest type rather than remnant natural forests or patches. Based on result, the following research outputs are also recommended: (i). Evaluation of forest harvesting impacts on the forest ecosystems, (ii). Development of rehabilitation methods on logged-over forests and degraded forest lands, (iii). Development of silvicultural techniques on plantation and degraded lands, (iv). Network on the restoration and rehabilitation of degraded forest ecosystems.
ScalaBLAST 2.0: rapid and robust BLAST calculations on multiprocessor systems

Motivation: BLAST remains one of the most widely used tools in computational biology. The rate at which new sequence data is available continues to grow exponentially, driving the emergence of new fields of biological research. At the same time, multicore systems and conventional clusters are more accessible. ScalaBLAST has been designed to run on conventional multiprocessor systems with an eye to extreme parallelism, enabling parallel BLAST calculations using >16 000 processing cores with a portable, robust, fault-resilient design that introduces little to no overhead with respect to serial BLAST. Availability: ScalaBLAST 2.0 source code can be freely downloaded from http://omics.pnl.gov/software/ScalaBLAST.php. Contact: christopher.oehmen@pnl.gov
Critical operations capabilities in a high cost environment: a multiple case study

Operations capabilities have been a popular research area for many years and several frameworks have been proposed in the literature. The current frameworks do not take specific contexts into consideration, for instance a high cost environment. This research gap is of particular interest since a manufacturing relocation process has been ongoing the last decades, leading to a huge amount of manufacturing being moved from high to low cost environments. The purpose of this study is to identify critical operations capabilities in a high cost environment. The two research questions were: What are the critical operations capabilities dimensions in a high cost environment? What are the critical operations capabilities in a high cost environment? A multiple case study was conducted and three Swedish manufacturing firms were selected. The study was based on the investigation of an existing framework of operations capabilities. The main dimensions of operations capabilities included in the framework were: cost, quality, delivery, flexibility, service, innovation and environment. Each of the dimensions included two or more operations capabilities. The findings confirmed the validity of the framework and its usefulness in a high cost environment and a new operations capability was revealed (employee flexibility).
Family Involvement And Academic Self Efficacy as a Factors in Children’s Academic Engagement

The main goal of the present study is to examine the effect of family involvement and academic self efficacy toward children academic engagement. Sample of this research 97 children from 5rd to 6th grade of elementary school. Data collection tool used was questionaire form of academic engagement scale (35 items), family involvement scale (28 items), and academic self efficacy scale (40 items). Based on the analysis of research data, it was found that the obtained R square value of 0.35 with a significance level of p<0.01. It can be concluded that there are significant effect of family involvement and academic self efficacy toward children academic engagement. In general, we found the positive impact of student’s academic self-efficacy and parents involvement on student’s school engagement. But their impact differ in the respondent, their parents personal and their parents involvement characteristics also. As an example, gender status, specifically being as female, made their academic engagement better.
A wireless precoding technique for millimetre-wave MIMO system based on SIC-MMSE

A communication method is proposed using Minimum Mean Square Error (MMSE) precoding and Successive Interference Cancellation (SIC) technique for millimetre-wave multiple-input multiple-output (mm-Wave MIMO) based wireless communication system. The mm-Wave MIMO technology for wireless communication system is the base potential technology for its high data transfer rate followed by data instruction and low power consumption compared to Long-Term Evolution (LTE). The mm-Wave system is already available in indoor hotspot and Wi-Fi backhaul for its high bandwidth availability and potential lead to rate of numerous Gbps/user. But, in mobile wireless communication system this technique is lagging because the channel faces relative orthogonal coordination and multiple node detection problems while rapid movement of nodes (transmitter and receiver) occur. To improve the conventional mm-wave MIMO nodal detection and coordination performance, the system processes data using symbolized error vector technique for linearization. Then the MMSE precoding detection technique improves the link strength by constantly fitting the channel coefficients based on number of independent service antennas (M), Signal to Noise Ratio (SNR), Channel Matrix (CM) and mean square errors (MSE). To maintain sequentially encoded user data connectivity and to overcome data loss, SIC method is used in combination with MMSE. MATLAB was used to validate the proposed system performance.
Analysis of fault of insulation aging of oiled paper of a large‐scale power transformer and the prediction of its service life

Insulation aging of oiled paper is a common malfunction of transformers. It is of great value to recognize the insulation aging status of oiled paper and predict the service life of transformers using appropriate methods. In this study, an aging state recognition method based on partial discharge was proposed. Partial discharge signals were collected, the feature values were obtained through analysis of the principle component factor, and the state was identified by using a support vector machine. A Weibull distribution‐based method was proposed for the prediction of service life, and the residual life of transformers was determined using failure rate function. Through analysis, it was found that the fault analysis method had an accuracy rate of 80.55% in the recognition of the aging state, which was higher than that of Hidden Markov Model (HMM). In the case analysis, the accuracy rate of the method in recognizing the aging state of 100 transformers reached 82.06%. The accuracy of the failure rate function was also verified in the prediction of service life. This study provides some new ideas for the effective recognition of insulation aging of oiled paper in transformers and the prediction of service life. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
ASSESSMENT ON THE POTENTIAL BENEFIT OF IMPLEMENTATION OF COUNTRY BY COUNTRY REPORT TO TACKLE BEPS IN INDONESIA

Base Erosion and Profit Shifting (BEPS) spillover effect jeopardizes developing countries due to inexperience and lack of legislative resources. To deal with the BEPS, a robust implementation of BEPS Action Plan should be guarded. The common theme among study in this field is whether Country by Country Report (CbCR) is an effective tool to tackle BEPS. This paper highlight the potential value could be taken by developing countries in adopting CbCR handbook of effective tax risk assessment. Whether the high cost of CbCR implementation could be paid by employing CbCR effective tax risk assessment. The results suggest that in the CbCR tax risk assessment could be used to increase income tax revenue in the developing country such as Indonesia by combining it with domestic regulations as implementation on other BEPS action plan recommendations. However, there are certain problems of CbCR, confidentiality and minimalist information, need to be clear up to maximise the effectivity.
Interacting with AR / VR Objects in Natural Ways

Smart Wristband [1] consists of a flexible touch screen panel and IMU sensor to capture multiple input sources outside of the camera’s field of view. My research explores novel natural user interface technologies that aim to overcome challenges in interactions between humans and computers in a wearable AR/VR environment, specialising in understanding human behaviours, understanding scene and identifying users based on visual computing and mobile & wearable computing. Besides my research background in computer science, I draw on a diverse set of skills, including machine learning (particularly Deep Learning (CNN), Random Forest), computer vision, video processing (including IR, colour, and depth images), AR&VR, and biometrics.
The Leucine-rich domain of RGNEF: a modifier of TDP-43 toxicity in Drosophila melanogaster.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the progressive degeneration of motor neurons. Rho Guanine Nucleotide Exchange factor (RGNEF), like other RNA-binding proteins, has been observed to form inclusions in the spinal cord motor neurons of both sporadic and familial cases of ALS. RGNEF has been determined to be a prosurvival factor under stress conditions. When comparing expression of different constructs of RGNEF in HEK293T cells, a Leucine-rich domain containing fragment of RGNEF (L-Rich), was found to form aggregates under metabolic stress that co-aggregated with TDP-43, another ALS-linked RNA-binding protein. In this thesis, I used both in vivo and in vitro techniques to further characterize the role of L-Rich in the pro-survival effect of RGNEF. In vitro analysis examined whether L-Rich was needed against osmotic or oxidative stress for improved cell survival. Immunofluorescence determined whether RGNEF, RGNEF lacking the Leucine-rich domain (RGNEFΔL), or L-Rich alone were capable of colocalizing with TDP-43 positive granules following stress. Immunoprecipitation examined whether the Leucine-rich domain was essential for the interaction between RGNEF and TDP-43. A Drosophila model was included to examine the impact of L-Rich in modulating the toxic effect of human wildtype TDP-43 in Drosophila. My findings support the hypothesis that L-Rich of RGNEF is important in the cytoprotective effect of full length RGNEF in vitro. This effect varies depending on the type of cellular insult present. My findings also support the hypothesis that L-Rich of RGNEF is a protective modifier of TDP43 toxicity in Drosophila.
High genetic diversity and differentiation of the Babesia ovis population in Turkey.

Babesia ovis is a tick-transmitted protozoan haemoparasite causing ovine babesiosis in sheep and goats leading to considerable economic loss in Turkey and neighbouring countries. There are no vaccines available, therapeutic drugs leave toxic residues in meat and milk, and tick vector control entails environmental risks. A panel of eight mini- and micro-satellite marker loci was developed and applied to study genetic diversity and substructuring of B. ovis from western, central and eastern Turkey. A high genetic diversity (He = 0.799) was found for the sample of overall B. ovis population (n = 107) analyzed. Principle component analysis (PCoA) revealed the existence of three parasite subpopulations: (a) a small subpopulation of isolates from Aydin, western Turkey; (b) a second cluster predominantly generated by isolates from western Turkey; and (c) a third cluster predominantly formed by isolates from central and eastern Turkey. Two B. ovis isolates from Israel included in the analysis clustered with isolates from central and eastern Turkey. This finding strongly suggests substructuring of a major Turkish population into western versus central-eastern subpopulations, while the additional smaller B. ovis population found in Aydin could have been introduced, more recently, to Turkey. STRUCTURE analysis suggests a limited exchange of parasite strains between the western and the central-eastern regions and vice versa, possibly due to limited trading of sheep. Importantly, evidence for recombinant genotypes was obtained in regionally interchanged parasite isolates. Important climatic differences between the western and the central/eastern region, with average yearly temperatures of 21°C versus 15°C, correspond with the identified geographical substructuring. We hypothesize that the different climatic conditions may result in variation in the activity of subpopulations of Rhipicephalus spp. tick vectors, which, in turn, could selectively maintain and transmit different parasite populations. These findings may have important implications for vaccine development and the spread of drug resistance.
Energy-efficiency fog computing resource allocation in cyber physical internet of things systems

Cyber physical internet of things systems (CPIoTs), taking advantages of cyber physical systems, have been considered as a promising technology to provide better interaction and interoperability among various machines. However, the development of CPIoTs suffers severely from big data. In this context, fog computing is proposed to handle the big data bottleneck of CPIoTs. In this study, the authors focus on the joint optimisation of the communication resources and computation resources in fog computing-based CPIoTs to maximise the overall system energy efficiency, in which multiple fog nodes and end users are taken into consideration. Moreover, since the channel estimation error will become serious with the expanding scale, the imperfect channel state information is considered in this study. The formulated optimisation problem is a mixed integer non-linear problem which is indeed non-deterministic polynomial hard, hence a probability distribution method is proposed to reformulate the problem into a non-probability form, and the resource allocation algorithm based on Dinkelbach algorithm and Lagrange duality approach is adopted to tackle the problem efficiently. The simulation results confirm the effectiveness of the proposed scheme, especially when the scales are enormous.
The Effects of Tillage-Induced Soil Disturbance
on Soil Quality

The aim of this paper was to investigate the tillage-induced changes in soils in 2010-2017, and rank tillage management in the present climate situation. The study was carried out on Chernozems, where five ploughless tillage treatments – loosening (L), tine tillage (a deeper T, and a shallower, ST), disk tillage (D) and direct drilling (DD) – were compared with ploughing (P). Soil condition was evaluated in accordance with the crumb ratio, the soil moisture range for workability, the extension of compacted tillage pan, the crust formation and number of earthworms. The higher ratio of crumbs was found at the treatments where cover ratio reached at least 20% after sowing (at T, ST, and DD). Significant differences were found between soil moisture ranges for the workability of different tillage operations (p<0.05). The T treatment proved to be an adaptable solution to the extreme soil moisture contents. Extension of the compacted pan was moderated under ST, T and L. The crust occurrence was lower under ST, T and DD with residue cover. DD, ST and T had a significantly higher number of earthworms compared to other treatments. Soil condition ranking revealed the suitability of the tillage managements for alleviating the farming and the climate hazards.
Determination of the Median Effective Concentration of Nano-Zero Valent Iron to the Marine Phytoplankton Species Isochrysis galbana

Nano zero valent iron (nZVI) is often used in the remediation of organic and inorganic contaminant and has been hailed as an emerging remediation tool. Unfortunately, were few studies has been done on the toxicity of nZVI on organisms especially aquatic organisms. In this study, the toxicity of commercial forms (uncoated, organic coating, and iron oxide coating) of nano zero-valent iron (nZVI) to the marine phytoplankton Isochrysis galbana is revisited in terms of the determination of the EC50 or median effective concentration using nonlinear regression. Based on the four-parameter logistics equation, the median effective concentration for Nanofer 25S, Fe2+ and Fe3+ were 5.46 mg/L (95% confidence interval of 4.84 to 6.16), 70.89 mg/L (95% confidence interval of 37.26 to 134.9), 64.29 mg/L (95% confidence interval of 44.92 to 92.02). The results indicate that Nanofer 25S was the most toxic.