Miracle-dz/UniFAR-FTUs huggingface dataset:
The Intraoperative Finding of a Large Atrial Septum Defect Pre-Liver Transplantation: A Case Report

The case report discusses a significant discrepancy between the pre-transplant cardiac evaluation and post-induction transesophageal echocardiography, leading to aborting the surgical procedure. The transthoracic echocardiography [TTE] pre-liver transplant indicated only a minor intracardiac shunt, while the post-induction transesophageal echocardiography [TEE] showed a large atrial septal defect with a more significant left to right shunt. The attempt to close the defect with a transcatheter closure device failed and the perioperative care team decided not to proceed with the liver transplantation. Later cardiac evaluation with cardiac magnetic resonance imaging demonstrated a secundum atrial septum defect in the inferior border of the interatrial septum with 43 ml flow difference between systemic and pulmonary circulation. The failure to identify a large atrial septal defect/inferior venosus defect in the preoperative screening process for liver transplantation resulted in failing to optimize the patient pre transplant. Although complications related to large atrial septal defects are rare during liver transplant (paradoxical embolisms, malignant arrhythmias, myocardial infarctions or cerebrovascular complications), they can be potentially fatal. The preoperative cardiac assessment should have included optimization of this congenital defect. The case report discusses implications of atrial septal defects for liver transplant and why the screening process may have missed the defect. The findings of a positive bubble study during the transthoracic echocardiography should not be trivialized and may require further workup.
The current state of validated small molecules inhibiting SARS-CoV-2 nonstructural proteins

The current COVID-19 outbreak has had a profound influence on public health and daily life. Despite all restrictions and vaccination programs, COVID-19 still can lead to fatality due to a lack of COVID-19-specific treatments. A number of studies have demonstrated the feasibility to develop therapeutics by targeting underlying components of the viral proteome. Here we reviewed recently developed and validated small molecule inhibitors of SARS-CoV-2’s nonstructural proteins. We described the validation level of identified compounds specific for SARS-CoV-2 in the presence of in vitro and in vivo supporting data. The mechanisms of pharmacological activity, as well as approaches for developing improved SARS-CoV-2 NSP inhibitors have been emphasized.
A Study on The fun Elements of Physical Interactive Game

In this study, the non-face-to-face industry is highlighted due to Corona 19 and the rapidly changing matters of the global game industry are observed, and the fun factor of tangible functional games is derived through prior research. Nowadays, living in the inner residence rather than outside activities has become a daily routine, and it is becoming fashionable to make a healthy body through home training. However, through personal counseling, I learned that it is difficult to continue using tangible Physical Serious games. We conducted an 8-week experiment with a ring pit adventure game with 40 students at our school, and gave up about 50% of them halfway through. Through this experiment, it was found that in the case of tangible functional games, the sustained use time is much insufficient compared to other games such as online or console games. Three fun theories were derived by conducting an interview with a group of experts to find out the cause of continuous use, and after analyzing the most popular Nintendo Ring Fit adventure game, I would like to present a fun factor model.
Using the Outputs of Different Automatic Speech Recognition Paradigms for Acoustic- and BERT-Based Alzheimer's Dementia Detection Through Spontaneous Speech

Exploring acoustic and linguistic information embedded in spontaneous speech recordings has proven to be efﬁcient for automatic Alzheimer’s dementia detection. Acoustic features can be extracted directly from the audio recordings, however, linguistic features, in fully automatic systems, need to be extracted from transcripts generated by an automatic speech recognition (ASR) system. We explore two state-of-the-art ASR paradigms, Wav2vec2.0 (for transcription and feature extraction) and time delay neural networks (TDNN) on the ADReSSo dataset containing recordings of people describing the Cookie Theft (CT) picture. As no manual transcripts are provided, we train an ASR system using our in-house CT data. We further investigate the use of conﬁdence scores and multiple ASR hypotheses to guide and augment the input for the BERT-based classiﬁcation. In total, ﬁve models are proposed for exploring how to use the audio recordings only for acoustic and linguistic information extraction. The test results on best acoustic-only and best linguistic-only are 74.65% and 84.51% respectively (representing a 15% and 9% relative increase to published baseline results).
Seed Quality as Related to Harvest Time in Three Key Perennial Grasses Native to Puna Tussock Rangelands of Peru

Seed-based rehabilitation programs represent a primary foundation for rangeland recovery, which requires high-quality seed of key native species. The objective of this research was to determine the seed quality at different harvest times for three key perennial grasses native to puna tussock rangelands of Peru: Festuca dolichophylla, Festuca humilior, and Calamagrostis vicunarum. Seeds of each species were harvested at 21, 28, and 35 days after anthesis and evaluated by standard tests to determine the purity, size, viability, and germinability. On average, the seed purity of the studied species ranged between 23% and 44%, hundred-seed weight between 34 mg and 73 mg, seed viability between 24% and 60%, and the seed germination between 18% and 34% over the harvest dates. The highest seed quality was observed in C. vicunarum. Seed quality parameters of the studied species did not show a consistent variation over the harvest times. Overall, the species studied presented relatively low seed quality; therefore, when using it in rehabilitation programs for rangeland recovery, it is important to carry out a previous cleaning process (to reduce nonviable seeds and inert matter) and to use a sufficient quantity of seed for effective establishment of these key grasses.
Cross-lingual Low Resource Speaker Adaptation Using Phonological Features

The idea of using phonological features instead of phonemes as input to sequence-to-sequence TTS has been recently proposed for zero-shot multilingual speech synthesis. This approach is useful for code-switching, as it facilitates the seamless uttering of foreign text embedded in a stream of native text. In our work, we train a language-agnostic multispeaker model conditioned on a set of phonologically derived features common across different languages, with the goal of achieving cross-lingual speaker adaptation. We first experiment with the effect of language phonological similarity on cross-lingual TTS of several source-target language combinations. Subsequently, we fine-tune the model with very limited data of a new speaker's voice in either a seen or an unseen language, and achieve synthetic speech of equal quality, while preserving the target speaker's identity. With as few as 32 and 8 utterances of target speaker data, we obtain high speaker similarity scores and naturalness comparable to the corresponding literature. In the extreme case of only 2 available adaptation utterances, we find that our model behaves as a few-shot learner, as the performance is similar in both the seen and unseen adaptation language scenarios.
Potential of the Biomass of Plants Grown in Trace Element-Contaminated Soils under Mediterranean Climatic Conditions for Bioenergy Production

Phytomanagement of trace element-contaminated soils combines sustainable soil remediation with the use of plant biomass for different applications. Consequently, phytostabilization using plant species useful for bioenergy production has recently received increasing attention. However, the water requirement of most of these species is a limitation for their use under Mediterranean climatic conditions. In this work, eight plant species growing naturally in mine soils contaminated by trace elements were evaluated for their use as bioenergy crops using thermochemical (combustion) and biochemical (anaerobic digestion) methods. The higher heating values of the biomass of the plants studied were all within a narrow range (16.03–18.75 MJ kg−1), while their biochemical methane potentials ranged from 86.0 to 227.4 mL CH4 (g VS)−1. The anaerobic degradation was not influenced by the presence of trace elements in the plants, but the mineral content (mainly Na) negatively affected the potential thermal energy released by combustion (HHV). The highest annual energy yields from biogas or combustion could be obtained by the cultivation of Phragmites australis and Arundo donax, followed by Piptatherum miliaceum. Both options can be considered to be suitable final destinations for the biomass obtained in the phytostabilization of trace element-contaminated soils and may contribute to the implementation of these remediation techniques in Mediterranean areas.
Beyond effective approaches: A rapid review response to designing professional learning

ABSTRACT Professional learning (PL) in education is thought to be a key mechanism for improving classroom instruction and student achievement. Yet despite decades of research into PL, the impact of this investment is not well understood, with reports of limited change in both research and practice. As part of a large-scale investigation focusing on practitioner use of evidence in education, the authors undertook a rapid review to understand what is known about effective PL for K-12 school-based educators. Based on analysis and synthesis of 12 included studies, the review identified eight features of effective PL: collaboration; active learning and reflection; content and pedagogy in context; sustained duration; coaching; external expertise; models and modelling; and, audience and alignment. It also highlighted additional considerations for effective PL, including workplace conditions, PL providers, and online and blended approaches. This paper argues that though there is a consensus around effective PL features, there is a need to go beyond ‘effective approaches’ and consider the broader conditions and methodological limitations that impact improved and sustained change. Overall, this paper has implications for understanding the research landscape around effective PL, and applying an evidence-informed approach to designing PL programmes.
Kinematics modeling and grasping experiment of pneumatic four-finger flexible robotic hand

To solve the complex structure, poor flexibility, and heavyweight of the rigid robotic hand, a pneumatic four-finger flexible robotic hand is developed in this paper. The robotic hand is about 1.3 times as large as that of a human hand and each finger is composed of a single multi-drive bending joint. The kinematic model of the robotic hand is established by using homogeneous coordinate transformation matrix. Through the simulation experiment of the robotic hand structure, the trajectory, and workspace of the robotic hand are established. According to the experimental results of grasping performance of the robotic hand, the grasping forces of different geometric positions along the finger axis are obtained. The results show that the robotic hand can realize a variety of grasping modes, has flexible action and strong adaptive ability; it can grasp, hold, and pinch, as well as stably grasp objects such as cylinder, box, and sphere. In pinch grasp mode, the robotic hand can grip objects as thin as 1 mm and the diameter of the grasped object varies from 28 mm to 160 mm; the maximum mass that the robotic hand can grasp an object with a diameter of 90 mm under 0.35 MPa is 1386 g.
EFFECT OF CORPORATE GOVERNANCE PRACTICES ON R&D AND INNOVATION COSTS: A CASE STUDY ON BORSA İSTANBUL

This study aimed to reveal the impact of corporate governance practices (CGP) on research and development (R&D) expenses and innovation costs. The businesses registered in Borsa Istanbul (BIST), with complete data regarding R&D and innovation costs for 2009–2017, were analyzed. The panel regression analysis performed through the STATA 15.0 program revealed that the board size, number of independent board members, gender diversity in the board of directors, chairman’s tenure, board meeting frequency, and business scale had a statistically significant and positive effect on the realized R&D expenses. Furthermore, it was determined that the number of foreign members of the board of directors, board ownership, and the organizational age had a statistically significant and negative effect on the nominal R&D expenses. However, it was also discovered that the role duality and business scale had a statistically significant and positive impact. In contrast, the foreign member ratio on the board of directors and organizational age had a statistically significant and negative effect on innovation costs.
Identifying Conflict Escalation and Primates by Using Ensemble X-Vectors and Fisher Vector Features

Computational paralinguistics is concerned with the automatic identiﬁcation of non-verbal information in human speech. The Interspeech ComParE challenge features new paralinguistic tasks each year; this time, among others, a cross-corpus conﬂict escalation task and the identiﬁcation of primates based solely on audio are the actual problems set. In our entry to ComParE 2021, we utilize x-vectors and Fisher vectors as features. To improve the robustness of the predictions, we also experiment with building an ensemble of classiﬁers from the x-vectors. Lastly, we exploit the fact that the Escalation Sub-Challenge is a con-ﬂict detection task, and incorporate the SSPNet Conﬂict Corpus in our training workﬂow. Using these approaches, at the time of writing, we had already surpassed the ofﬁcial Challenge base-lines on both tasks, which demonstrates the efﬁciency of the employed techniques.
Intelligent Decision Support System for Predicting Student’s E-Learning Performance Using Ensemble Machine Learning

Electronic learning management systems provide live environments for students and faculty members to connect with their institutional online portals and perform educational activities virtually. Although modern technologies proactively support these online sessions, students’ active participation remains a challenge that has been discussed in previous research. Additionally, one concern for both parents and teachers is how to accurately measure student performance using different attributes collected during online sessions. Therefore, the research idea undertaken in this study is to understand and predict the performance of the students based on features extracted from electronic learning management systems. The dataset chosen in this study belongs to one of the learning management systems providing a number of features predicting student’s performance. The integrated machine learning model proposed in this research can be useful to make proactive and intelligent decisions according to student performance evaluated through the electronic system’s data. The proposed model consists of five traditional machine learning algorithms, which are further enhanced by applying four ensemble techniques: bagging, boosting, stacking, and voting. The overall F1 scores of the single models are as follows: DT (0.675), RF (0.777), GBT (0.714), NB (0.654), and KNN (0.664). The model performance has shown remarkable improvement using ensemble approaches. The stacking model by combining all five classifiers has outperformed and recorded the highest F1 score (0.8195) among other ensemble methods. The integration of the ML models has improved the prediction ratio and performed better than all other ensemble approaches. The proposed model can be useful for predicting student performance and helping educators to make informed decisions by proactively notifying the students.
Overcoming the Challenges of Freestanding Tin Oxide‐Based Composite Anodes to Achieve High Capacity and Increased Cycling Stability

Freestanding electrodes are a promising way to increase the energy density of the batteries by decreasing the overall amount of electrochemically inactive materials. Freestanding antimony doped tin oxide (ATO)‐based hybrid materials have not been reported so far, although this material has demonstrated excellent performance in conventionally designed electrodes. Two different strategies, namely electrospinning and freeze‐casting, are explored for the fabrication of ATO‐based hybrid materials. It is shown that the electrospinning of ATO/carbon based electrodes from polyvinyl pyrrolidone polymer (PVP) solutions was not successful, as the resulting electrode material suffers from rapid degradation. However, freestanding reduced graphene oxide (rGO) containing ATO/C/rGO nanocomposites prepared via a freeze‐casting route demonstrates an impressive rate and cycling performance reaching 697 mAh g−1 at a high current density of 4 A g−1, which is 40 times higher as compared to SnO2/rGO and also exceeds the freestanding SnO2‐based composites reported so far. Antimony doping of the nanosized tin oxide phase and carbon coating are thereby shown to be essential factors for appealing electrochemical performance. Finally, the freestanding ATO/C/rGO anodes are combined with freestanding LiFe0.2Mn0. 8PO4/rGO cathodes to obtain a full freestanding cell operating without metal current collector foils showing nonetheless an excellent cycling stability.
Timing of Kidney Support Therapy in Acute Kidney Injury: What Are We Waiting For?

The optimal timing of kidney support therapy (KST) in critically ill patients with acute kidney injury (AKI) without life-threatening complications related to AKI is controversial. Recent multicenter randomized controlled studies have questioned the need for earlier initiation of therapy, despite one study showing a benefit in survival and others with no differences in mortality based on the timing of KST initiation. These findings reflect the uncertainties in decisions to initiate KST that should ideally be individualized according to the patient's comorbidities, severity of illness, trajectory of kidney function and urine output, as well as requirements for fluid balance and solute removal. A delayed approach could translate into potential reduced burden of dialysis-dependence in addition to saving health resources. However, we must ascertain what constitutes the waiting period and the benefits and risks associated with this approach. The purpose of this article is to review the concept of timing of dialysis in AKI, perform a critical assessment of the most important clinical trials in this topic, discuss ongoing research and knowledge gaps, and define key research issues to address in the future.
The Utility of MALDI-TOF-Mass Spectrometry, Analytical Profile Index (API) and Conventional-PCR for the Detection of Foodborne Pathogens from Meat

The rich nutrient composition of meat and its sufficient water activity supports the growth of both spoilage and pathogenic bacteria. The microbial quality of 150 raw meat samples (50 chicken, 50 pork and 50 beef) were evaluated for foodborne pathogens using Analytical Profile Index (API Staph-Ident kit, API-20E strips and API-20A), MALDI-TOF-MS, and conventional PCR. Thirty isolates (30) were identified using biochemical tests and Confirmatory biochemical test (API). All 30 isolates were confirmed by 16S rDNA PCR and sequencing. Detected isolates are Macrococcus caseolyticus 57%, Enterococcus faecalis 23%, Bacillus cereus 3%, Enterococcus mundtii 3%, Escherichia coli 3%, Citrobacter freundii 3%, and Clostridium subterminale 3%. Seven (23%) isolates were correctly identified using MALDI-TOF MS, whilst 18 (60%) isolates were misidentified, and 5 isolates were not detected (No peaks). Seventy three percent 73% (22) of the organisms showed high degree of resistance to tetracycline, followed by sulphonamide with 13% (4/30), and ciprofloxacin 3% (1/30). However, Bacillus cereus, Citrobacter freundii were not resistant to any of the antibiotics. All the isolates were susceptible to streptomycin. Furthermore, some bacteria exhibited multiple antibiotic resistances with tetracycline. Due to the presence and potential hazard of pathogens in meat samples, the detection of these pathogens in different types of meat is vital to maintain public health.
A New Evaluation of Skin Factor in Inclined Wells with Anisotropic Permeability

Oil and gas well productivity can be affected by a number of different skin factors, the combined influences of which contribute to a well’s total skin factor. The skin caused by deviated wells is one such well-known factor. The present study aimed to investigate skin effects caused by deviated well slants when considering vertical-to-horizontal permeability anisotropy. The research employed computational fluid dynamics (CFD) software to simulate fluid flows in inclined wells through the injection of water with Darcy flow using 3D geometric formations. The present work investigates the effects of four main characteristics—namely, the permeability anisotropy, wellbore radius, reservoir thickness, and deviation angle—of open-hole inclined wells. Additional investigations sought to verify the effect of the direction of perforations on the skin factor or pressure drop in perforated inclined wells. In the case of an inclined open hole well, the novel correlation produced in the current study simplifies the estimation of the skin factor of inclined wells at different inclination angles. Our comparison indicates good agreement between the proposed correlation and available models. Furthermore, the results demonstrated a deviation in the skin factor estimation results for perforated inclined wells in different perforation orientation scenarios; therefore, existing models must be improved in light of this variance. This work contributes to the understanding and simulation of the effects of well inclination on skin factor in the near-wellbore region.