Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive Factors For The Successful Implantation and Live Birth After Euploid Blastocyst Transfer: A Single Center Study

Background : Pre-implantation Genetic Testing for Aneuploidy (PGT-A) has enabled IVF specialists to screen embryos for abnormalities in chromosome number and structure. Subsequently, healthy embryos are selected for transfer, decreasing the rate of spontaneous miscarriages and improving pregnancy outcomes. In spite of this, almost only half of the PGT-determined euploid embryos result in a pregnancy. Objective : This study aimed to determine what other factors among euploid embryo transfers will have an association with successful implantation and live birth. Methods : This study retrospectively analyzed 159 IVF-PGS cycles performed in CARMI SLMC-GC from January 2017 to December 2019. Of these, a total of 231 euploid embryos (86 single embryo transfers and 73 double embryo transfers) were assessed. The relationship of eight predictive variables (maternal age, maternal BMI, etiology of infertility, history of failed IVF, blastocyst expansion stage, ICM grade, TE grade and endometrial thickness on transfer) with regard to the outcome of successful implantation and live birth among single or double euploid blastocyst transfers were determined via logistic regression analysis. Results : Overall, the implantation rate was significantly lower when using B-grade ICM or C-grade ICM blastocysts as compared to A-grade ICM blastocysts (OR 0.54, 95% CI 0.356-0.815, p = 0.003). With regard to live birth rate, the success of transfer is statistically lower when using a B-grade or C-grade ICM blastocysts as compared to A-grade ICM blastocysts (OR 0.55, CI 0.354-0.863, p = 0.009). Other predictive factors such as maternal age, maternal BMI, etiology of infertility, number of previous IVF, blastocyst expansion stage, trophectoderm grade and endometrial thickness had no apparent effect on the outcome of implantation and live birth. Conclusion : Present study results suggest that only the ICM grade of euploid blastocysts correlates with implantation and live birth in IVF-FET cycles. Therefore, the selection of euploid blastocysts based on the presence of a higher grade ICM is the most predictive factor that determines success among those undergoing IVF with PGT-A.
Design and Simulation of a DC Microgrid for a Small Island in Belize

A microgrid based on direct current (DC) was designed and simulated for a small island in Belize. The energy generated in the microgrid will come from DC sources and the loads on the island will also be DC. Therefore, it was proposed to design a microgrid based on DC to reduce the amount of conversion losses between AC-DC. A microgrid based on DC will have no power factor losses, less corona discharges due to the absence of the skin effect and allow for a cheaper and simpler system. DC microgrids are already widespread in the telecoms industry for data centres, airplanes, submarines and remote locations. MATLAB/Simulink was used to design and simulate the individual components of the microgrid. Power electronic converters were designed and simulated for use with photovoltaic (PV) modules and maximum power point trackers (MPPT) in order to extract maximum power from the solar resource. The perturb and observe (P&O) algorithm was coded into the MATLAB environment for the MPPT. A bidirectional converter (BDC) was also designed to allow power to flow from/to the battery which was controlled by a PI controller. A traditional buck or boost converter could not be used for the bidirectional converter due to the presence of diodes in their designs. The charge controller successfully controlled the bidirectional converter allowing power to flow from/to the battery to achieve voltage stabilization. A lead-acid battery was found to be the most cost effective option for integration into the microgrid. The solar and wind resources for the island were modelled along with the predicted load profiles of the island. A financial analysis was conducted using the Hybrid Optimization Model for Electric Renewables (HOMER) software. It was found that a DC microgrid could meet the load requirements with 20% less generation than an AC microgrid due to the absence of losses in inverters reducing the costs. An AC microgrid with diesel only generation which is currently in use resulted in the highest overall costs, an AC hybrid microgrid resulted in a cheaper system than the diesel only system and a DC microgrid resulted in the lowest costs. A long term, medium term and short term analysis of the DC microgrid was conducted. A 100% renewable microgrid was found to generate excess electricity throughout a year because the system needs to be sized to meet the load on periods of low renewable energy generation. Batteries can be used to decrease the excess electricity but they eventually increase the cost of the system and create battery disposal problems. The medium and short term analysis verified the functionality of the charge controller on a good day and bad day for renewable energy generation. Both simulations shown that the voltage was stabilized and the bidirectional converter functioned correctly. The microgrid would require 15.7% island cover from PV panels and 10 containers for the batteries. Therefore, it was proposed to size the solar generation to meet the base load and diesel generators to meet the peak load with hydrogen storage. Hönnun og hermun á DC örneti fyrir litla eyju í Belize.
The Confirmatory Factor Analysis of the Spiritual Wellbeing Scale of a Sample of Students from Iraq and Algeria

The current study aims at confirming the factor structure of the Arabized image of the SPIRITUALITY INDEX OF WELL BEING scale through the confirmatory factor analysis. The study was conducted on a sample consisting of (187) students (male and female) at the level of the two universities of Anbar in Iraq and Saida in Algeria. To achieve the aims of the study, a descriptive approach was used based on the scale of the quality of spiritual wellbeing: Spirituality Index of Wellbeing by Daaleman & Frey (2004) and translated by researchers. The confirmatory factor analysis of the translated Arabic version of the Scale was conducted on the study model that has found out, according to the results of the analysis, that the model has a good fit. The study recommends the necessity of paying attention to the issue of the spirituality of the students.
Gamers’ Self-Efficacy When Using English in School and When Gaming

: The aim of this study is to examine the relationship between gamers’ and non-gamers’ self-efficacy when using English while playing video games at home and using English in the classroom. Data were collected through an online questionnaire distributed to 79 first-year upper-secondary students in Norway. The participants were divided into groups of self-reported gaming time per day: Frequent gamers (>3 h), Gamers (2–3h), Casual gamers (1–2h), and Non-gamers (0 h). The results show a statistically significant difference between Gamers ( n = 11), Casual gamers, and Non-gamers in terms of self-efficacy. Gamers show a higher sense of self-efficacy when using English in the classroom (M = 39.45) and while playing video games (M = 39.9) than those who play either more or less. Higher self-efficacy correlates with higher grades in both settings (Classroom setting p = <.001; Gaming setting p = .010). There was no connection between being a gamer and their given grades ( p = .337). The findings suggest that playing a moderate amount of video games in English can affect students’ self-efficacy positively in relation to using the language, both while playing and in the classroom. The findings also suggest that even though spending excessive time on video games might increase self-efficacy while playing, it cannot be transferred to the classroom. Background variables could not account for this difference. A secondary finding reveals clear gender differences in the amount of time spent on video games; further research is required in this field.
Purdue e-Pubs Purdue e-Pubs

Building energy predictions are in critical need in many fields. The conventional physic model-based approach (via EnergyPlus or similar tools) does decent work to predict energy consumptions. However, it is limited to single predefined building analysis and requires an extensive amount of time and labor to build models. Nevertheless, decision-makers usually need to quantify the energy savings of large building clusters within a short time. The thriving of big data and machine learning techniques enables predicting energy consumptions accurately for different applications within reasonable time frames. This study aims at developing data-driven models for generalized building energy predictions. The models can be used for establishing counter-factual baselines to validate the efficacy of energy-saving measures and energy production and usage planning. The former is usually for medium to long-term durations, while the latter is for short-term durations. We used real-world open data sets from ASHRAE, which covers energy consumptions of about 1,500 buildings for two years. We then preprocessed the data following the industry's standard practice. Multiple approaches of missing values imputations, outlier detections, and feature engineering were explored, based on which the best methods are suggested for building energy predictions. Gradient boosting (GB) based model has been developed for medium to long-term predictions, while the long short-term memory (LSTM) based model has been developed for short term predictions. Hyperparameter tuning was performed on model structures and parameters. We used root mean squared error (RMSE) between the predicted and true energy consumptions to evaluate performances. The results show that the GB based model achieves RMSE of 0.49 for electricity, 1.10 for chilled water, 1.25 for steam, and 1.32 for hot water. The LSTM model performs better with shorter prediction days and longer input days. However, further increasing input days beyond a week does not increase the performance. The LSTM model has about 38% lower prediction errors than the baselines, which are averages of energy consumptions from similar historical days. The study demonstrates the development process of data-driven models for general purpose building energy predictions, from data preparations, model selections, development, and evaluations.
Bureaucracy politicization and its effects on human rights

Bureaucracy represents the infrastructural power of a State, and by studying its configuration one can determine how effective the government can be on carrying on with its goals and promises. In this research, I explore if a bureaucracy controlled by politicians, and not by a professionalized civil service, is less conducive to better protection and fulfillment of human rights. I test a hypothesis that proposes that the higher the levels of politicization of bureaucracy, the higher the violations of human rights. To test this hypothesis a mix-method analysis was selected. First I run a Large-N Analysis of 100+ countries using OLS regression models of cross-sectional data to measure the strength of this focal relationship. I found it to be significant: Bureaucracy politization affects negatively human rights outcomes, even in democratic countries with high GDP per capita. I then conducted a case-study analysis on El Salvador, a developing country that appears to be very well explained by the linear regression models. Using interviews with country experts, academic research, and official statistics I was able to identify key causal mechanisms undermining the state capacity to better protect and fulfill human rights.
Wind Farms Predictive Maintenance Based on Condition Monitoring System

— This article focuses on a new methodology based on fuzzy logic to predict the maintenance of wind farms. In wind systems, Vibrations present the main cause of the occurrence of failures. The prediction of these failures can be ensured by correct processing of the set of vibration signals collected by the Condition Monitoring System (CMS) and declaration of the appropriate maintenance action by the connected management system SCADA (Supervisory Control And Data Acquisition). In this paper, fuzzy logic is used as a new approach to processing vibration signals by exploiting their features for the generation of probabilities of occurrence of failures. The probabilities generated correspond to alarms (Green, Orange and Red) and the alarms correspond to maintenance actions to be applied.
Task-Adaptive Negative Envision for Few-Shot Open-Set Recognition

We study the problem of few-shot open-set recognition (FSOR), which learns a recognition system capable of both fast adaptation to new classes with limited labeled exam-ples and rejection of unknown negative samples. Traditional large-scale open-set methods have been shown in-effective for FSOR problem due to data limitation. Current FSOR methods typically calibrate few-shot closed-set clas-sifiers to be sensitive to negative samples so that they can be rejected via thresholding. However, threshold tuning is a challenging process as different FSOR tasks may require different rejection powers. In this paper, we instead propose task-adaptive negative class envision for FSOR to integrate threshold tuning into the learning process. Specifically, we augment the few-shot closed-set classifier with additional negative prototypes generated from few-shot examples. By incorporating few-shot class correlations in the negative generation process, we are able to learn dynamic rejection boundaries for FSOR tasks. Besides, we extend our method to generalized few-shot open-set recognition (GF-SOR), which requires classification on both many-shot and few-shot classes as well as rejection of negative samples. Extensive experiments on public benchmarks validate our methods on both problems.11Code available at https://github.com/shiyuanh/TANE
The Routledge International Handbook of Thinking and Reasoning

well-known two-faculty view of the human mind that underlies most assumptions about intuitive thinking. In the second section, we show that sorting processes into faculties does not remedy the problem that intuitive processes sometimes differ strikingly from each other. We discuss two processes in more detail in the third section and argue that the diversity of processes should be acknowledged on a theoretical level. In the fourth section, we consider some topics much discussed in the literature, such as neural correlates of intuition, the accuracy of intuitive thought, and the role of learning and emotions. We close with a remark on the nature of intuition.
TEAM 59: LEAP MOTION HAND GESTURE CLASSIFICATION

Hand gesture recognition forms a foundation for low-level Human-Computer Interaction (HCI). In this paper, Hand Gesture Recognition Database from Kaggle with ten different gestures is used to train a model. We implemented a Convolutional Neural Network (CNN) with data augumentation and used a 3-phase training technique to increase training throughput and reduce overﬁtting. The ﬁnal testing accuracy obatined is 99.9%. We also leveraged transfer learning to train a model for American Sign Language (ASL) dataset with 3-phase training technique and achieves a testing accuracy of 99.6%.
Th e Eff ect of Rat Adipose-derived Stem Cells in Bone Tissue Regeneration Yağ Dokusu Kökenli Kök Hücrelerin Kemik Dokusu

: Stem cell approaches has been increasing in the conventional medicine. Th is study was planned to determinate the efficacy of adipose-derived stem cells (ADSCs) on the bone fracture’s regeneration by histologically, morphologically and radiologically. Primarily isolated cells were cultivated and identified for the obtaining of the third passage mesenchymal stem cells in the cell culture laboratory. Th e right tibias (applicated ADSCs) were planned as experimental group and the left tibias were studied as control on the clinically healthy 10 rats. Th e middle diaphysis of the right and left tibias was transversally cut by a thin saw and then fixed by intramedullary pin. Before surgical closure of the incised area, 10 6 ADSCs were injected on an absorbent material, which covered the cut site of the right tibia, in experimental group. At postoperative 45 th day, cranio-caudal and lateral radiographs of the tibias pointed out that there was callus formation in the caudal and lateral parts of the right tibia. After sacrification of the animals, preparations were made for histological examinations. Th e results indicate that there were clear diff erences in the mitotic activity; and also, the experimental tibias were found to be rich in blood vessel network. As a conclusion, it was found that ADSCs can have a positive potential effect on osteogenesis in bone tissue.
M EDIEVAL T HEORIES ON THE C ONCEIVABILITY OF THE I MPOSSIBLE : A S URVEY OF I MPOSSIBLE P OSITIO IN A RS O BLIGATORIA DURING THE 13 TH –14 TH C ENTURIES

: During the 13 th century, several logicians in the Latin medieval tradition showed a special interest in the nature of impossibility, and in the different kinds or ‘degrees’ of impossibility that could be distinguished. This discussion resulted in an analysis of the modal concept with a fineness of grain unprecedented in earlier modal accounts. Of the several divisions of the term ‘impossible’ that were offered, one became particularly relevant in connection with the debate on ars obligatoria and positio impossibilis : the distinction between ‘intelligible’ and ‘unintelligible’ impossibilities. In this article, I consider some 13 th century tracts on obligations that provide an account of the relation between impossibility and intelligibility and discuss the inferential principles that are permissible when we reason from an impossible – but intelligible – premise. I also explore the way in which the 13 th century reflection on this topic survives, in a revised form, in some early 14 th -century accounts of positio , namely, those of William of Ockham, Roger Swineshead and Thomas Bradwardine.
Dynamics of stochastic Lotka-Volterra predator-prey models driven by three independent Brownian motions

This article concerns the permanence and extinction of stochastic Lotka-Volterra predator-prey models perturbed by three independent white noises. We establish some criteria and present some numerical simulations that illustrate our theoretical results. It is shown that the presence of strong noise on either the intra-specific interaction rate or the inter-specific interaction rate may lead to complete different dynamical behaviors from the deterministic case.
Analysis of emotions in the hotel destination choice: using a valence and arousal affective space

This paper explores emotional perceptions extracted from online consumer reviews posted on TripAdvisor. More specifically, the study analyzes valence and arousal using the Affective Norms for English Words and a database of 10,000 comments in two languages (English and Spanish) on budget and premium hotels on a worldwide scale. An emotional analysis of tourist comments allows us to summarize the features highlighted by customers, identifying those which are more important for hotels aiming to offer better services. The results are presented in four linguistic categories to allow a closer focus on the emotional value of tourist reviews. The categorization shows a general use of words with high valence and arousal, allowing a classification within a dimensional affective space. The use of positive, negative, and exciting words is discussed, explaining the importance of a cohesive transmission of emotion depending on hotel category. The study analyses emotions of reviews word by word, avoiding a dichotomic classification of comments. This offers a brand-new approach into touristic reviews, knowing what clients really pays attention to.
The iron spin transition of deep nitrogen-bearing mineral Fe 3 N 1.2 at 2 high pressure 3

Nitrogen is an essential element for life, one of the most abundant volatiles in the 21 atmosphere, and an important component in the Earth’s interior, where iron nitride is an 22 essential host of deep nitrogen. Here, we investigate the pressure-induced electronic 23 spin-pairing transition of iron in siderazot (Fe 3 N 1.2 ) at pressures to 45.8 GPa at room 24 temperature, using diamond-anvil cell techniques coupled with synchrotron x-ray emission 25 spectroscopy. The integrated intensity of the satellite emission peak ( K β ′) decreases once 26 upon compression and remains unchanged at pressures greater than 30.5 GPa. In other words, 27 the high-spin to low-spin transition of iron in Fe 3 N 1.2 starts immediately at very low pressures 28 and completes at ~ 30.5 GPa. The iron spin transition completion pressures increase with the 29 nitrogen concentration of hexagonal close-packed iron nitrides (i.e., Fe 3 N 1.2 , Fe 7 N 3 , and 30 Fe 2 N). Moreover, the identity and concentration of light elements, together with their crystal 31 structure, could affect the iron spin transition pressure of binary iron-rich compounds such as 32 Fe 3 N, Fe 3 C, Fe 3 P, Fe 3 S, Fe 7 C 3, and Fe 7 N 3 . The spin transition of iron-rich alloys could alter 33 the bonding nature and the physical properties including the thermal and electrical 34 conductivity, influencing the thermal state and evolution of planetary interiors in turn.
An online counseling intervention for Nigerian undergraduates with academic burnout

A growing problem among university students is academic burnout, and it has become more prevalent in recent years. With the increasing demand for school mental health services, online counseling interventions are gradually being regarded as a reasonable way to provide assistance to students with regard to burnout reduction. It was the researcher's aim to find out whether an online counseling intervention would be able to reduce academic burnout in a Nigerian undergraduate sample. A total of 80 Nigerian undergraduates were participants of this study. In this study, the participants were randomly assigned to the intervention group (n=40) and to the control group (n=40) by using a simple randomization procedure. For the collection of data, the Oldenburg Burnout Inventory for Students and the Students School Burnout Inventory were utilised. The researcher applied repeated measures ANOVA to examine within and between groups' mean differences, reported η² to establish treatment effect size, and conducted posthoc analyses where mean differences existed using Holm's approach. The results of the study demonstrate that the online counseling intervention for academic burnout was effective in reducing the level of academic burnout among Nigerian undergraduates.As online counseling can help students reduce academic burnout, this finding opens the door to reach a larger number of burned-out students, such as those who live off-campus or are afraid of social stigma when seeking mental health care. This intervention has the potential to significantly improve student mental health related to burnout in other higher education settings like polytechnics. It is recommended that students should be encouraged to receive psychological supports and care from the university's counseling centre, not just during crises, but as a regular process of mental health support.