Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence from Characteristics and Comorbidities Suggesting That Asperger Syndrome Is a Subtype of Autism Spectrum Disorder

The current version of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-V) does not consider Asperger syndrome a diagnostic category. This study was undertaken to see if there is evidence that this diagnosis should be reinstated. An online survey was conducted to examine symptoms and behaviors associated with the current diagnostic criteria of autism spectrum disorders (ASD) (DSM-V), and those associated with Asperger syndrome based on the previous version (DSM-IV-TR). The study also examined other characteristics historically associated with autism, as well as impairments often reported in infancy/young childhood and medical comorbidities frequently associated with autism. The sample included 251 individuals who had received a diagnosis of Asperger syndrome and 1888 who were diagnosed with autism or ASD. Numerous similarities and differences were found between the two groups. The findings are discussed in relation to reestablishing Asperger syndrome as a valid diagnostic category as well as a subtype of ASD.
Viabilitas Benih Melon (Cucumis Melo L.) pada Kondisi Optimum dan Sub-Optimum Setelah Diberi Perlakuan Invigorasi Viability of Invigorated Melon (Cucumis melo L.) Seed in Optimum and Sub-optimum Conditions

The purpose of this research was to find out the effect of invigoration treatments using GA3 and coconut water on viability of high and low quality melon seeds in optimum and sub-optimum (drought) conditions. The research was conducted in Seed Science and Technology Laboratory, Bogor Agricultural University, from February until December 2012. The research was consist of two experiments, invigoration in optimum condition and sub-optimum (drought) condition. The experiments were arranged in a Randomized Completely Block Design with two factors and three replications. The first factor was seed quality i.e low quality and high quality with 60%-75% and 80%-95% germination percentage respectively. The second factor was invigoration treatment (control, coconut water, GA3 80 ppm, GA3 100 ppm, combination of coconut water and GA3 80 ppm, and combination coconut water and GA3 100 ppm). Variables observed were vigor index, germination percentage, speed of germination, the maximum grow potential and dry weight of normal seedling. Results of the experiment showed that in optimum condition all of invigoration treatment could increase vigor index from 16.67% to 30.67%-48% except GA3 100 ppm treatment. Coconut water treatment could increase germination percentage of low quality melon seed from 72% to 85.33%-88%. In sub-optimum condition there were no invigoration treatment could increase viability of melon seeds. Key word : GA3, coconut water, drought condition, invigoration ABSTRAK
Variational Bayesian Inference in High-Dimensional Linear Mixed Models

In high-dimensional regression models, the Bayesian lasso with the Gaussian spike and slab priors is widely adopted to select variables and estimate unknown parameters. However, it involves large matrix computations in a standard Gibbs sampler. To solve this issue, the Skinny Gibbs sampler is employed to draw observations required for Bayesian variable selection. However, when the sample size is much smaller than the number of variables, the computation is rather time-consuming. As an alternative to the Skinny Gibbs sampler, we develop a variational Bayesian approach to simultaneously select variables and estimate parameters in high-dimensional linear mixed models under the Gaussian spike and slab priors of population-specific fixed-effects regression coefficients, which are reformulated as a mixture of a normal distribution and an exponential distribution. The coordinate ascent algorithm, which can be implemented efficiently, is proposed to optimize the evidence lower bound. The Bayes factor, which can be computed with the path sampling technique, is presented to compare two competing models in the variational Bayesian framework. Simulation studies are conducted to assess the performance of the proposed variational Bayesian method. An empirical example is analyzed by the proposed methodologies.
The Forward Slice Core: A High-Performance, Yet Low-Complexity Microarchitecture

Superscalar out-of-order cores deliver high performance at the cost of increased complexity and power budget. In-order cores, in contrast, are less complex and have a smaller power budget, but offer low performance. A processor architecture should ideally provide high performance in a power- and cost-efficient manner. Recently proposed slice-out-of-order (sOoO) cores identify backward slices of memory operations which they execute out-of-order with respect to the rest of the dynamic instruction stream for increased instruction-level and memory-hierarchy parallelism. Unfortunately, constructing backward slices is imprecise and hardware-inefficient, leaving performance on the table. In this article, we propose Forward Slice Core (FSC), a novel core microarchitecture that builds on a stall-on-use in-order core and extracts more instruction-level and memory-hierarchy parallelism than slice-out-of-order cores. FSC does so by identifying and steering forward slices (rather than backward slices) to dedicated in-order FIFO queues. Moreover, FSC puts load-consumers that depend on L1 D-cache misses on the side to enable younger independent load-consumers to execute faster. Finally, FSC eliminates the need for dynamic memory disambiguation by replicating store-address instructions across queues. Considering 3-wide pipeline configurations, we find that FSC improves performance by 27.1%, 21.1%, and 14.6% on average compared to Freeway, the state-of-the-art sOoO core, across SPEC CPU2017, GAP, and DaCapo, respectively, while at the same time incurring reduced hardware complexity. Compared to an OoO core, FSC reduces power consumption by 61.3% and chip area by 47%, providing a microarchitecture with high performance at low complexity.
Account of Deep Learning-Based Ultrasonic Image Feature in the Diagnosis of Severe Sepsis Complicated with Acute Kidney Injury

This study was aimed at analyzing the diagnostic value of convolutional neural network models on account of deep learning for severe sepsis complicated with acute kidney injury and providing an effective theoretical reference for the clinical use of ultrasonic image diagnoses. 50 patients with severe sepsis complicated with acute kidney injury and 50 healthy volunteers were selected in this study. They all underwent ultrasound scans. Different deep learning convolutional neural network models dense convolutional network (DenseNet121), Google inception net (GoogLeNet), and Microsoft's residual network (ResNet) were used for training and diagnoses. Then, the diagnostic results were compared with professional image physicians' artificial diagnoses. The results showed that accuracy and sensitivity of the three deep learning algorithms were significantly higher than professional image physicians' artificial diagnoses. Besides, the error rates of the three algorithm models for severe sepsis complicated with acute kidney injury were significantly lower than professional physicians' artificial diagnoses. The areas under curves (AUCs) of the three algorithms were significantly higher than AUCs of doctors' diagnosis results. The loss function parameters of DenseNet121 and GoogLeNet were significantly lower than that of ResNet, with the statistically significant difference (P < 0.05). There was no significant difference in training time of ResNet, GoogLeNet, and DenseNet121 algorithms under deep learning, as the convergence was reached after 700 times, 700 times, and 650 times, respectively (P > 0.05). In conclusion, the value of the three algorithms on account of deep learning in the diagnoses of severe sepsis complicated with acute kidney injury was higher than professional physicians' artificial judgments and had great clinical value for the diagnoses and treatments of the disease.
The Determinants of Housewives’ Sexual Health: A Qualitative Study: Qualitative Study

Background & Aims of the Study: Women’s health including, the sexual dimension is the basis of family’s and community’s health. Due to the lack of research on women’s sexual health, investigations seem necessary in this area. The present research aimed to study factors affecting women’s sexual health. Materials and Methods: This was qualitative research. The required data were collected using in-depth individual interviews. The statistical population consisted of married women under the age of 50 years residing in Qom City, Iran. Twenty married women were selected by the purposive sampling method and data were obtained until reaching saturation. Results: Our findings indicated that sexual disorders, anal intercourse, neglecting sexual foreplay, environmental conditions, body image, pudency, and feeling guilty during intercourse degraded sexual health according to the interviewed women. According to this qualitative research data, the most common dysfunction reported by the interviewed women was anorgasmia. Conclusion: In the present qualitative study, the factors affecting the sexual health of housewives were identified. Paying attention to these characteristics in designing appropriate interventions is suggested by health authorities in the country.
Pioneer Role of Extracellular Vesicles as Modulators of Cancer Initiation in Progression, Drug Therapy, and Vaccine Prospects

Cancer is one of the leading diseases, causing deaths worldwide. Nearly 10 million deaths were reported in 2020 due to cancer alone. Several factors are involved in cancer progressions, such as lifestyle and genetic characteristics. According to a recent report, extracellular vesicles (EVs) are involved in cancer initiation, progression, and therapy failure. EVs can play a major role in intracellular communication, the maintenance of tissue homeostasis, and pathogenesis in several types of diseases. In a healthy person, EVs carry different cargoes, such as miRNA, lncRNA etc., to help other body functions. On the other hand, the same EV in a tumor microenvironment carries cargoes such as miRNA, lncRNA, etc., to initiate or help cancer progression at various stages. These stages may include the proliferation of cells and escape from apoptosis, angiogenesis, cell invasion, and metastasis, reprogramming energy metabolism, evasion of the immune response, and transfer of mutations. Tumor-derived EVs manipulate by altering normal functions of the body and affect the epigenetics of normal cells by limiting the genetic makeup through transferring mutations, histone modifications, etc. Tumor-derived EVs also pose therapy resistance through transferring drug efflux pumps and posing multiple drug resistances. Such EVs can also help as biomarkers for different cancer types and stages, which ultimately help with cancer diagnosis at early stages. In this review, we will shed light on EVs’ role in performing normal functions of the body and their position in different hallmarks of cancer, in altering the genetics of a normal cell in a tumor microenvironment, and their role in therapy resistance, as well as the importance of EVs as diagnostic tools.
Сredit Agreement in Agriculture: Economic and Legal Analysis

The main purpose of the study is a comprehensive economic and legal analysis of the loan agreement in agriculture in the conditions of formation and development of elements of post-industrial economy in Ukraine. The research methodology is based on a systematic approach using the method of cognition from abstract to concrete and special methods of economic and statistical research (comparison, grouping, detailing of final indicators, generalization), which helped to ensure the reliability of research results and validity of conclusions. It was found that the loan agreement in agriculture is an economic and legal category that ensures the further development of agriculture in Ukraine in conditions of further integration of our economy to world market on competitive terms. It was determined that expanding the use of the loan agreement in agriculture is a necessary lever to increase production efficiency, formation and constant restoration of a competitive technological base in modern conditions and further development of the whole agro-industrial complex considering the formation of post-industrial economy. It is proved that the application of the mechanism of crediting of agriculture in Ukraine has a positive effect on the development of the agro-industrial sector in Ukraine. It is determined that the current level and availability of lending to the agro-industrial complex in Ukraine are insufficient for quality modernization and achieving a high level of efficiency of agricultural production. The main value of this study is that it analyzes the concept through the prism of two categories, namely: legal and economic.
A Deep Learning Technique for Emotion Recognition Using Face and Voice Features

Automatic emotion recognition is an emerging application in the field of artificial intelligence. Where the use of technology helps to curb various mental illnesses like anxiety, depression, schizophrenia etc. So, there is a need to create efficient artificial intelligent devices. In this experimental project, we developed a multimodal system using neural networks (CNN) for recognizing emotions from facial expressions and voice. We used an RGB images dataset for facial expression recognition. For voice emotion recognition, an audio recorded files dataset was used. We presented phases of automatic emotion recognition in the form of data acquisition, data analysis and data visualization. Comparative analysis among recent papers, features affecting the performance and proposed model in terms of accuracy have also been given in tabular form. The proposed model shows accuracy of 73% and 90.91% for face and voice features respectively. It's observed that variations in the factors of the feature-training phase of neural networks like epochs, batch sizes, training datasets, also affect the results.
Intravenous thrombolysis in ischemic stroke patients with a prior intracranial hemorrhage: a meta-analysis

Background: The history of intracranial hemorrhage (ICrH) is considered a contraindication for intravenous thrombolysis (IVT) among patients with acute ischemic stroke (AIS). Objective: This study aimed at comparing the safety of IVT among patients with and without a history of ICrH. Methods: We performed a systematic review of the literature. Data regarding all AIS patients with prior ICrH who received IVT were retrieved. Meta-analysis was performed to compare the rate of symptomatic hemorrhagic transformation (sHT), death within 90 days, and favorable and unfavorable 90-day functional outcomes based on modified Rankin Scale (mRS) among stroke patients with and without prior ICrH. Results: Out of 13,032 reviewed records, 7 studies were included in the systematic review and meta-analysis. Quantitative synthesis of data regarding the rate of sHT (5068 patients) revealed no significant difference between the two groups [odds ratio, OR: 1.55 (0.77, 3.12); p = 0.22]. However, a significantly higher risk of death within 90 days [OR: 3.91 (2.16, 7.08); p < 0.00001] and a significantly higher 90-day poor functional outcomes (mRS, 4–6) [OR: 1.57 (1.07, 2.30); p = 0.02] were observed among patients with prior ICrH. Likewise, the percentage of 90-day good functional outcomes (mRS, 0–1) was lower in the prior ICrH group [OR: 0.54 (0.35, 0.84); p = 0.06]. Subgroup analyses in patients with a history of ICrH (based on both patients’ medical history and imaging confirmation) revealed no significant between-group differences in rates of sHT. Also, sensitivity analysis consisting of only studies using standard-dose IVT showed no difference in sHT rates and 90-day outcomes between the two groups. There was no evidence of heterogeneity (I2 >50%) among included studies. Conclusion: The results of this study indicated that prior history of ICrH does not increase the risk of sHT post-IVT, but it is associated with a higher risk of death and poor functional outcomes in 90 days.
THE EFFECT OF EXPERIENTAL MARKETING TO CUSTOMER LOYALTY

The purpose of this study is to examine the effect of experiential marketing as measured by sense, feel, think, act and relate to customer loyalty. The sampling technique used purposive sampling with 97 people as samples, the research method used in this study is quantitative methods using SPSS. The result of analysis using multiple linear regression show that 1) sense has a positive effect on customer loyalty, 2) feel has a positive effect on customer loyalty, 3) think has a positive effect on customer loyalty, 4) act has a positive effect on customer loyalty, 5) relating has a positive effect on customer loyalty.
Geothermal: From Education to a New Solution for Renewable Energy

Fossil energy is still the main contributor in Indonesia. In fact, based on a study it is stated that fossil fuels will only last 50-70 years. For this reason, it is necessary to increase the role of geothermal energy as renewable energy. Geothermal energy is very good if it is developed into a new and renewable energy source because it has a good impact on the environment. Geothermal energy also does not damage the local conditions such as mining activities so that biodiversity is preserved. Then, the operation period of the Geothermal Power Generation (known as PLTP) can be more than 30 years and does not require fuel. Geothermal energy is environmentally friendly, and its potential impact on pollution is minimal. Thus, geothermal energy is the right solution to overcome dependence on fossil energy that is not renewable and is expected to run out in the near future.
In vitro and in vivo characterization of Entacapone-loaded nanostructured lipid carriers developed by quality-by-design approach

Abstract Entacapone, a reversible catechol-o-methyl transferase inhibitor, is used to enhance the action of dopamine agonists by reducing their metabolism and the ‘Wearing-off’ effects associated with long-term use in the treatment of Parkinson's disease. It is used as an adjunct to levodopa/Carbidopa therapy. Due to limited dissolution and first-pass clearance, it suffers low and variable bioavailability issues. To overcome this problem, the present study aims to explore the potential of nanostructured lipid carriers (NLCs) for the delivery of Entacapone. The Quality by Design (QbD) approach was used for the systematic development of NLCs. The 23 full factorial designs were investigated using Design-Expert®11 software. The three independent variables namely content of total lipid (X1), surfactant (X2), and sonication time (X3) were optimized against two responses namely particle size and entrapment efficiency. The optimized NLCs were characterized for their size, surface morphology, entrapment efficiency, drug release, thermal and crystallographic studies. In-vivo pharmacokinetic studies in Entacapone-loaded NLCs showed an increase in t 1/2, AUC0–∞, MRT compared to free drug. The reduction in elimination (Kel) depicts the prolonged action of Entacapone by loading in NLCs. The results displayed Entacapone-loaded NLCs have promising potential for oral delivery and enhanced therapeutic effect which otherwise was a major issue.
The Role of Crowd Support on Home Advantage during COVID-19 Restrictions on Italian Football Competitions. Comparison between 2018–19 and 2020–21 Seasons of the Italian Serie A and Serie B Championships

The home advantage (HA) affects football competitions, especially due to the presence of crowd support. Even though several studies demonstrated that HA (which is influenced by the crowd) decreased in recent years, the empty stadia caused by COVID-19 restrictions offered unique situations to explore and quantify HA. For this reason, we aimed to assess HA in two seasons of the major Italian Championships. We conducted an observational study with the data from the last three seasons of the Italian football championship A–B series, analyzing a total of 2.964 individual game scores. To quantify the HA, the number of points won at home was calculated as a percentage of the total number of points won, home and away. In every season and for every team classification, HA was found (scored points > 50% in home matches). We reported a difference in HA median score for Serie B. Additionally, a difference was found in Serie A for middle-ranking HA median scores in the two seasons compared (p-value = 0.017), which was similarly found in Serie B (p-value = 0.009). The number of penalties was lower in the season with a crowd compared to one without a crowd (p = 0.001). The HA did not disappear in empty stadiums, so there must be other contributing factors. Additionally, we found that the referees were biased by the presence of the crowd in favor of the home teams, and this result could be considered by the football association during referees’ training and formation.
Business cycle accounting para o Brasil

With the implementation of countercyclical economic policies, Brazil was less affected by the 2008 Crisis than the average for the rest of the world, with an average annual growth of 4.11% between 2008 and 2011, compared to 3.25% for this group for the same period. This meant that the country ended the 2000s with an average annual growth of 3.91% between 2002 and 2010, above the 2.69% seen in the average of its Latin American peers. Despite this, the worsening of Brazil’s debt led to a significant deterioration of the macroeconomic scenario as of 2014, which resulted in a reduction in private investment, an increase in unemployment and negative growth rates for several quarters. In this sense, this masters dissertation aims to analyze the macroeconomic fluctuations experienced by the Brazilian economy using the analytical framework developed by Business Cycle Accouting (BCA) for quarterly data from 2002 to 2019. Among the main results found, the efficiency wedge was the main responsible for reproducing the output movements observed in both crises, followed by labor wedge.
Normalized Brain Tissue–Level Evaluation of Volumetric Changes of Youth Athletes Participating in Collision Sports

Observations of short-term changes in the neural health of youth athletes participating in collision sports (e.g., football and soccer) have highlighted a need to explore potential structural alterations in brain tissue volumes for these persons. Studies have shown biochemical, vascular, functional connectivity, and white matter diffusivity changes in the brain physiology of these athletes that are strongly correlated with repetitive head acceleration exposure. Here, research is presented that highlights regional anatomical volumetric measures that change longitudinally with accrued subconcussive trauma. A novel pipeline is introduced that provides simplified data analysis on standard-space template to quantify group-level longitudinal volumetric changes within these populations. For both sports, results highlight incremental relative regional volumetric changes in the subcortical cerebrospinal fluid that are strongly correlated with head exposure events greater than a 50-G threshold at the short-term post-season assessment. Moreover, longitudinal regional gray matter volumes are observed to decrease with time, only returning to baseline/pre-participation levels after sufficient (5–6 months) rest from collision-based exposure. These temporal structural volumetric alterations are significantly different from normal aging observed in sex- and age-matched controls participating in non-collision sports. Future work involves modeling repetitive head exposure thresholds with multi-modal image analysis and understanding the underlying physiological reason. A possible pathophysiological pathway is presented, highlighting the probable metabolic regulatory mechanisms. Continual participation in collision-based activities may represent a risk wherein recovery cannot occur. Even when present, the degree of the eventual recovery remains to be explored, but has strong implications for the well-being of collision-sport participants.