Miracle-dz/UniFAR-FTUs huggingface dataset:
Eating Behaviors of Children with Autism—Pilot Study, Part II

Autism spectrum disorder is characterized by social communication deficit and non-normative behavior. The people with autism often experience troubles with feeding. The purpose of this study was to conduct evaluation of the feeding and eating behaviors among children with autism. Patients and Methods: The study group included 41 high-functioning autistic children. The control group consisted of 34 children without the ASD. The questionnaire was used to assess the nutritional status. Results: The children with ASD fuss during mealtimes more frequently, they require entertaining and diverting their attention, they are fed by parents, and they consume their meals away from the table. The significant difference found in the use of utensils and food selectivity works to the disadvantage of the Study Group. Conclusions: The food selectivity occurs significantly more frequently among children with ASD. The feeding and eating problems should be considered on a wider scale. The cooperation of the multidisciplinary and the parents teams should be proposed in the ASD patients care.
Determinants of Farmers’ Intention of Straw Recycling: A Comparison Analysis Based on Different Pro-Environmental Publicity Modes

Promoting the intention of farmers to participate in straw recycling is an effective way to alleviate the contradiction between environmental pollution, scarcity of environmental resources, and sustainable development. In this study, social trust and value perception were integrated into the theory of planned behavior to build a theoretical framework of farmers’ intention to participate in straw recycling, considering the influences of three different pro-environmental publicity modes. A field investigation was used to collect research data in six sample villages. Finally, 761 valid questionnaires were collected, and partial least squares structural equation modeling was applied to test the research hypotheses. The results showed that the influence of attitudes, subjective norms, perceived behavior control, value perception, and social trust on farmers’ straw recycling intentions was different among different pro-environmental publicity modes. Among the three pro-environmental publicity modes, the concentrated pro-environmental publicity mode has the best effect of promoting straw recycling intentions among farmers. This study introduces some targeted suggestions on the aspects of pro-environmental publicity theory and management practice based on the above research results.
Can changes in platelet count, mean platelet volume, and platelet distribution width be used to determine the severity of COVID-19?

Objective: We aimed to investigate the relation of platelet count (PLT), mean platelet volume (MPV) and platelet distribution width (PDW) with other acute phase reactants in COVID-19 new corona virus. Material and Methods: Thirty one patients with COVID-19 were included in to study. There were three groups as outpatient (Group 1, OP)(n=6), hospital (Group 2, H)(n=16) and intensive care unit (Group 3, IC)(n=9) in this analytic study. Results: WBC (White Blood Cell), CRP (C-Reactive Protein) values were significantly different in all groups. PDW values were significantly lower in Group 3 than Group 1, 2. The result of ROC analysis was 10.9 as a cut-off value (Area under the curve, AUC)=0.407) Conclusions: This study indicates that lower PDW may frequently develop in COVID-19 cases and there is a relation between thrombocytosis and acute phase reactants, that is, the inflammatory response. So we can offer that PDW should be used as a marker of Covid-19 disease severity, but it needs more studies in the future.
Hybrid Particle Swarm and Ranked Firefly Metaheuristic Optimization-Based Software Test Case Minimization

Software testing is a valuable and time-consuming activity that aims to improve the software quality. Due to its significance, combinatorial testing focuses on fault identification by the interaction of small amount of input factors. But, deep testing is not sufficient due to time or resources availability. To select the optimal test cases with least computation time, Hybrid Multi Criteria Particle Swarm and Ranked Firefly Metaheuristic Optimization(HMCPW-RFMO) technique are introduced. Initially, the population of the test cases is randomly initialized. Then the fitness is calculated by the pairwise coverage, execution cost, fault detection capability and average execution frequency. RFM approach starts with ‘n’ fireflies. The light intensity of each firefly gets initialized.If the light intensity of one firefly is minor than the other one, it moves near the brighter one. Next, the rank is given to the firefly based on their light intensity. Lastly, the high ranked firefly is chosen as a global best solution.The result reveals that HMCPW-RFMO technique improves the software quality.
The moderating role of religion on tourist spending

ABSTRACT This study examines the relationships between tourist motivations and tourist spending across cultural, nature, and leisure experiences, and the role of religious affiliation in moderating the relationships. A survey conducted at Kuching International Airport, involving international tourists who travelled to Sarawak, Malaysia, found a significant positive relationship between tourists’ social motivation and their spending on seeking cultural, nature and leisure experiences. The study also found a significant negative relationship between nature and ego status motivations and tourist spending on similar experiences. The relationships are moderated by religious affiliation. This study taps into an unknown area of tourism research and provides evidence on how the factors could relate to different types of tourist spending.
Effects of fermented feed on growth performance, nutrient metabolism and cecal microflora of broilers

Objective To investigate the effects of enzyme-bacteria co-fermented feed on broilers, the basal diet (BF) was pretreated by microbial enzyme co-fermentation, and then different proportions of BF were replaced to study its effects on growth performance, nutrient metabolism and cecal microflora of broilers. Methods Four hundred and eighty 1-day-old broilers were randomly divided into 6 groups. The control group was fed with BF, and groups 1 to 4 were treated with dried fermented feed (DFF) instead of 10%, 15%, 20%, and 25% the BF, and group 5 was treated with wet fermented feed (WFF) instead of 10% the BF, named BF, 10% DFF, 15% DFF, 20% DFF, 25% DFF, and 10% WFF, respectively. The trial period was 42 days. Results The results showed that the average daily feed intake and average daily gain of 10% DFF, 15% DFF, and 10% WFF groups were significantly higher than those of the control group at 22 to 42 days and 1 to 42 days (p<0.05). Except for 10% DFF group, Firmicutes of all treatment were higher than that of control group. The Bacteroides of each treatment group were lower than that of the control group (p>0.05). At the same time, the nutrient apparent metabolic rate and cecal microbial abundance of each treatment group had an increasing trend (p>0.05). Conclusion In conclusion, the feed fermented by enzyme and bacteria had a potential promoting effect on the growth performance and nutrient digestibility of broilers.
Short Form of the Pediatric Symptom Checklist-Youth Self-Report (PSC-17-Y): Spanish Validation Study

Background The short form, 17-item version of the Pediatric Symptom Checklist-Youth Self-Report (PSC-17-Y) is a validated measure that assesses psychosocial problems overall (OVR) and in 3 major psychopathological domains (internalizing, externalizing, and attention-deficit/hyperactivity disorder), taking 5-10 min to complete. Prior research has established sound psychometric properties of the PSC-17-Y for English speakers. Objective This study extends psychometric evidence for the acceptability of the PSC-17-Y in a large sample of Spanish adolescents, providing proof of its reliability and structure, convergent and discriminant validity, and longitudinal and gender invariance. Methods Data were collected on 5430 adolescents, aged 12-18 years, who filled out the PSC-17-Y twice during 2018-2019 (7-month interval). We calculated the Cronbach alpha and the McDonald omega coefficients to test reliability, the Pearson correlation for convergent (distress) and criterion validity (well-being, quality of life, and socioemotional skills), confirmatory factor analysis (CFA) for structure validity, and multigroup and longitudinal measurement invariance analysis for longitudinal and gender stability. Results Within structural analysis for the PSC-17-Y, CFA supported a correlated 3-factor solution, which was also invariant longitudinally and across gender. All 3 subscales showed evidence of reliability, with coefficients near or above . 70. Moreover, scores of PSC-17-Y subscales were positively related with convergent measures and negatively related with criterion measures. Normative data for the PSC-17-Y are presented in the form of percentiles (75th and 90th). Conclusions This work provides the first evidence of the reliability and validity of the Spanish version of the PSC-17-Y administered over the internet to assess mental health problems among adolescents, maintaining the same domains as the long version.
A novel four‐tier software‐defined network architecture for scalable secure routing and load balancing

Software‐defined networking is an emerging paradigm for supporting flexible network management. In the traditional architecture for a software‐defined network (SDN), the controller commonly uses a general routing algorithm such as Open Shortest Path First (OSPF), which chooses the shortest path for communication. This may cause the largest amount of network traffic, especially in large‐scale environments. In this paper, we present the design for a novel SDN‐based four‐tier architecture for scalable secure routing and load balancing. In Tier 1, user authentication is conducted using elliptic curve cryptography (ECC); this avoids unnecessary loads from unauthorized users. In Tier 2, packet classification is performed based on the packet characteristics using the fuzzy analytical hierarchy process (fuzzy AHP), and packets are placed into three individual queues. In Tier 3, scalable secure routing is achieved by selecting the optimal path using the improved particle swarm optimization and ant colony optimization algorithms. With these optimization algorithms, we can adaptively change the number of users, the number of switches, and other parameters. In Tier 4, the recommended secure cluster (multicontroller) management is accomplished using an algorithm that employs modified k‐means clustering and a recurrent neural network. Deep reinforcement learning (DRL) is also proposed for updating the controller information. Experimental results are analyzed using the OMNeT++ network simulator, and the evaluated performance displayed improvement over a variety of existing methods in terms of response time (50% to 60%), load (55%), execution time (3.2%), throughput (9.8%), packet loss rate (1.02%), end‐to‐end delay (50%), and bandwidth consumption (45%).
Assessment of clinical significance of serum uric acid, serum bilirubin and serum creatinine in patients with breast lump

Background: Breast cancer is the most common cancer in females, approximately a quarter of all cancers. Several tumor markers are being studied now a days like α feto protein, carcinoembryonic antigen, and human chorionic gonadotropin but, the cost of these analytical methods is very high. This study is directed to assess prognostic value of serum uric acid, serum bilirubin and serum creatinine in breast lump cases. And to compare variation in benign and malignant breast lumps in relation to serum uric acid, serum bilirubin and serum creatinine values.Methods: Observational and prospective study conducted in Hamidia Hospital, Bhopal from November 2018-July 2020 included 100 patients. 50 patients were having benign breast lumps and other 50 patients malignant. Categorization of the patients done on the basis of histopathological examination. Autoanalyzer was used for estimation of serum uric acid, serum bilirubin and serum creatinine.Results: High serum uric acid level may anticipate poor prognosis in carcinoma breast, and it may perform a promising role in the management of the same. The level of serum bilirubin was slightly more or within normal range. The level of serum creatinine was within normal range in absence of any renal impairment by other etiology.Conclusions: The evaluation of serum uric acid and serum bilirubin may be useful for predicting prognosis in females with malignant breast lump and can provide help in making diagnosis during the initial assessment of the patient presenting with breast lump.
Alkali activated cement mixture at ambient curing: Strength, workability, and setting time

The success of ordinary Portland cement (OPC) comes at a risk to the environment because of the large carbon dioxide emissions associated with cement manufacturing. This has led the scientific community to look for alternative cementitious materials with lower environmental impact. Alkali activated cement (AAC) is an excellent alternative to this end. In this study, the effect of binder content, alkaline solid to binder ratio (AS/B), sodium silicate to sodium hydroxide solids ratio (SS/SH), and total water content to total solid binder ratio (TW/TB) on the strength, setting time and flowability of ambient cured AAC mixtures are studied using Taguchi method of experimental design. Binder content was varied from 550 to 750 kg/m3, AS/B ratio from 0.14 to 0.22, SS/SH ratio from 1.5 to 2.5, and TW/TB ratio from 0.29 to 0.39. The study results showed that within the investigated range, an increase in binder content has a minor effect on strength but resulted in a considerable increase in setting time and flowability. An increase in the AS/B ratio resulted in increased flowability and setting time and a decrease in strength. Moreover, the study also investigated the relationship between compressive strength and flexural strength.
Predicting and Interpreting Student Performance Using Ensemble Models and Shapley Additive Explanations

In several areas, including education, the use of machine learning, such as artificial neural networks, has resulted in significant improvements in predicting tasks. The opacity of these models is one of the problems with their use. Prediction models that may offer valuable insights while still being simple to comprehend are preferred by decision-makers in education. Hence, this study suggests an approach that improves the previous student performance prediction by enhancing performance and explaining why a student’s performance is attaining a certain score. A prediction model was proposed and tested using machine learning models. Our models outperform previous work models developed on the same dataset. Using a combined framework of data level and algorithm approaches, the proposed model achieves an accuracy of over 98%, inplying a 20.3% improvement compared with previous work models. As a balancing technique for upsampling data, we use the default strategy of synthetic minority oversampling technique (SMOTE) to oversample all classes to the number of examples in the majority class. We also use ensemble methods. For tuning the parameters, we use a simple grid search algorithm provided by scikit to estimate the optimal parameters of our model. This hyperparameter optimization along with a ten-fold cross-validation process demonstrates the dependability of the novel model. In addition, a novel visual and intuitive technique is used to help determine which factors most influence the score which helps to interpret and understand the entire model and visualizes feature attributions at the observation level for the machine learning model. Therefore, SHAP values are a powerful tool that should be incorporated within the student performance prediction framework by obtaining the prediction and explanation created through the experiment, educators can recognize students at risk early and provide suitable exhortation in an auspicious manner.
Intestinal Microbiota as a Contributor to Chronic Inflammation and Its Potential Modifications

The gut microbiota is a crucial factor in maintaining homeostasis. The presence of commensal microorganisms leads to the stimulation of the immune system and its maturation. In turn, dysbiosis with an impaired intestinal barrier leads to accelerated contact of microbiota with the host’s immune cells. Microbial structural parts, i.e., pathogen-associated molecular patterns (PAMPs), such as flagellin (FLG), peptidoglycan (PGN), lipoteichoic acid (LTA), and lipopolysaccharide (LPS), induce inflammation via activation of pattern recognition receptors. Microbial metabolites can also develop chronic low-grade inflammation, which is the cause of many metabolic diseases. This article aims to systematize information on the influence of microbiota on chronic inflammation and the benefits of microbiota modification through dietary changes, prebiotics, and probiotic intake. Scientific research indicates that the modification of the microbiota in various disease states can reduce inflammation and improve the metabolic profile. However, since there is no pattern for a healthy microbiota, there is no optimal way to modify it. The methods of influencing microbiota should be adapted to the type of dysbiosis. Although there are studies on the microbiota and its effects on inflammation, this subject is still relatively unknown, and more research is needed in this area.
Triplet Chemotherapy with Cisplatin, Ifosfamide and 5-Fluorouracil in Advanced Anal Cancer. A Population Based Retrospective Analysis from the Danish Anal Cancer Group

1Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, Denmark. 2The Danish Centre for Particle Therapy, Aarhus University Hospital, Denmark. 3Department of Oncology, Herlev and Gentofte Hospital, Denmark. 4Department of Oncology, Aarhus University Hospital, Denmark. 5Department of Experimental Clinical Oncology, Department of Oncology, Aarhus University Hospital, Denmark.
Zoonotic Cryptosporidium spp. in Wild Rodents and Shrews

There has been a significant increase in the number of reported human cryptosporidiosis cases in recent years. The aim of this study is to estimate the prevalence of Cryptosporidium spp. in wild rodents and shrews, and investigate the species and genotype distribution to assess zoonotic risk. Partial 18S rRNA gene nested-PCR reveals that 36.8, 53.9 and 41.9% of mice, voles and shrews are infected with Cryptosporidium species. The highest prevalence occurred in the Microtus agrestis (field vole) and Myodes glareolus (bank vole). Interestingly, bank voles caught in fields were significantly more often Cryptosporidium-positive compared to those caught in forests. The proportion of infected animals increases from over-wintered (spring and summer) to juveniles (autumn) suggesting acquired immunity in older animals. Based on Sanger sequencing and phylogenetic analyses, Apodemus flavicollis (yellow-necked mouse) is commonly infected with zoonotic C. ditrichi. Voles carry multiple different Cryptosporidium sp. and genotypes, some of which are novel. C. andersoni, another zoonotic species, is identified in the Craseomys rufocanus (grey-sided vole). Shrews carry novel shrew genotypes. In conclusion, this study indicates that Cryptosporidium protozoan are present in mouse, vole and shrew populations around Finland and the highest zoonotic risk is associated with C. ditrichi in Apodemus flavicollis and C. andersoni in Craseomys rufocanus. C. parvum, the most common zoonotic species in human infections, was not detected.
Surfing Performance in Para Surfers with Lower-Limb Amputations: A Cross-Sectional Study

ABSTRACT Introduction This study investigated surfing performance in surfers with transfemoral amputations (TFAs) and transtibial amputations (TTAs) who participated in international para surfing competitions. The purpose of this research was to compare surfers with lower-limb amputations with judged wave scores and surfing experience for para surfing classification efficacy. Materials and Methods Collected archived data (n = 20) from classification records included demographics, residual limb lengths, surfing experiences, and judged wave scores. Continuous variables age (years), residual leg length (cm), remaining leg length (%), prior surfing experience (years), and duration of competing experience (years) were analyzed using independent sample t-test. Ordinal variables surfing performance scores of 2019 and 2020 between the groups were compared using Mann-Whitney U test. Spearman ρ correlation coefficient was used to determine the association between the duration of prior surfing experience and duration of competition experience with the surfing score in both groups. Results Surfers with TFA with longer residual limb lengths (n = 3) and surfers with TTA (n = 14) surfed with a prosthetic leg standing. Surfers with TFA with shorter residual limb lengths (n = 3) surfed without a prosthesis kneeling. We found that para surfers who stood or kneeled with TFA performed significantly better than para surfers with TTA, reflected through judged wave scores in 2019 (P = 0.028) and 2020 (P = 0.019). No statistically significant relationship existed between para surfers with TFA who kneeled or stood. No statistically significant relationship existed between years of para surfing and judged wave scores. Conclusions Surfers with TFA who stood or kneeled received higher judged wave scores than surfers with TTA; however, no other significant significance was found for TFA intragroup comparisons or prior surf experience. The data size was too small for confirmatory analysis. Results appeal to a new need for inquiry on para surfers with TFA and TTA, specifically biomechanical performance surfing differences. Clinical Relevance Individuals with transfemoral and/or transtibial amputations can participate competitively in para surfing contests. Surfers with TFAs can successfully compete either standing with a prosthesis or kneeling without a prosthesis.
Spatial-temporal analysis of nanoparticles in live tumor spheroids impacted by cell origin and density

Nanoparticles hold great preclinical promise in cancer therapy but continue to suffer attrition through clinical trials. Advanced, three dimensional (3D) cellular models such as tumor spheroids can recapitulate elements of the tumor environment and are considered the superior model to evaluate nanoparticle designs. However, there is an important need to better understand nanoparticle penetration kinetics and determine how different cell characteristics may influence this nanoparticle uptake. A key challenge with current approaches for measuring nanoparticle accumulation in spheroids is that they are often static, losing spatial and temporal information which may be necessary for effective nanoparticle evaluation in 3D cell models. To overcome this challenge, we developed an analysis platform, termed the Determination of Nanoparticle Uptake in Tumor Spheroids (DONUTS), which retains spatial and temporal information during quantification, enabling evaluation of nanoparticle uptake in 3D tumor spheroids. Outperforming linear profiling methods, DONUTS was able to measure silica nanoparticle uptake to 10 µm accuracy in both isotropic and irregularly shaped cancer cell spheroids. This was then extended to determine penetration kinetics, first by a forward-in-time, center-in-space model, and then by mathematical modelling, which enabled the direct evaluation of nanoparticle penetration kinetics in different spheroid models. Nanoparticle uptake was shown to inversely relate to particle size and varied depending on the cell type, cell stiffness and density of the spheroid model. The automated analysis method we have developed can be applied to live spheroids in situ, for the advanced evaluation of nanoparticles as delivery agents in cancer therapy.