Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic assessment of voice similarity within and across speaker groups with different accents

As larger speaker databases materialise and speech technology becomes more efficient, an opportunity arises to automate assessments of perceived voice similarity (‘PVS’) among selections of voices for applications such as voice synthesis and forensic voice parades. Expanding on previous research [1], the present study addresses whether the correlation observed between listener ratings and automatic estimates of PVS can be found within different speaker groups with the same accent and across speaker groups with a different accent of English. Further, the impact on this correlation of variations in the automatic approach for PVS, based on a pre-trained automatic speaker recognition system, is explored; specifically, combinations of different feature extraction methods, speaker modelling approaches, and distance measures are considered. Results are positive and statistically highly significant within and across speaker groups particularly when relying on automatically extracted perceptually relevant phonetic features, demonstrating the generalisability of the method.
Path Tracking of Mining Vehicles Based on Nonlinear Model Predictive Control

Path tracking of mining vehicles plays a significant role in reducing the working time of operators in the underground environment. Because the existing path tracking control of mining vehicles, based on model predictive control, is not very effective when the longitudinal velocity of the vehicle is above 2 m/s, we have devised a new controller based on nonlinear model predictive control. Then, we compare this new controller with the existing model predictive controller. In the results of our simulation, the tracking accuracy of our controller at the longitudinal velocity of 4 m/s is close to that of the existing model predictive controller, at the longitudinal velocity of 2 m/s. When longitudinal velocity is 4 m/s, the existing model predictive controller cannot drive the mining vehicle to track the given path, but our nonlinear model predictive controller can, and the maximum displacement error and heading error are 0.1382 m and 0.0589 rad, respectively. According to these results, we believe that this nonlinear model predictive controller can be used to improve the performance of the path tracking of mining vehicles.
The embarrassed brain : towards a neurobiology of generalized socal anxiety disorder

There is circumstantial evidence for the involvement of serotonergic and dopaminergic systems in the pathophysiology of social anxiety disorder. In the present study, using SPECT imaging, we examined the 123 I-ß-(4-iodophenyl)-tropane binding potential for the serotonin and dopamine transporter in patients with a generalized social anxiety disorder and age-and sex-matched healthy controls. Methods: Twelve psychotropic medication-naïve patients with social anxiety disorder, generalized type (5 women and 7 men) and 12 sex-and age-matched healthy controls were studied. Volumes of interest were constructed on MRI-coregistered SPECT scans. Binding ratios were compared using the Mann-Whitney U test. Possible correlations between binding patterns and symptomatology were assessed using the Spearman rank correlation coefficient. Results: Significantly higher binding potentials were found for the serotonin transporter in the left and right thalamus of patients. Patients had also a significantly higher binding potential for the dopamine transporter in the striatum. Conclusion: The present study provided direct evidence for abnormalities in both the dopaminergic and the serotonergic systems in patients with generalized social anxiety disorder.
An ANFIS-based Framework for the Prediction of Bearing’s Remaining Useful Life

Bearings are critical components extensively used in rotary machines, often being the leading cause of unexpected machine shutdowns. To mitigate system failures, it is crucial to implement effective maintenance strategies. This paper introduces a novel methodology for bearing prognostics, employing Wavelet Packet Decomposition (WPD) for data pre-processing, Sequential Backward Selection (SBS) for feature selection, and Adaptive Neuro-Fuzzy Inference System (AN-FIS) networks for prognostic modeling. The proposed approach consists of two key steps. Firstly, the data undergoes preprocessing through Wavelet Packet Decomposition, enhancing the quality and extracting relevant features. Sub-sequently, the Remaining Useful Life (RUL) of the bearing is predicted using a degradation model. The accuracy of the proposed method is evaluated using a bearing life dataset obtained from a run-to-failure test (IMS dataset). The results demonstrate the remarkable capability of the ANFIS model to learn and accurately estimate the system’s RUL. By leveraging the combined power of WPD, SBS, and ANFIS, this methodology showcases its potential as an effective prognostic tool for bearing health assessment and proactive maintenance planning.
Human Mutation

MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom Division of Genetics, Department of Pediatrics, Nemours/Alfred I. duPont Hospital for Children, Wilmington, Delaware Department of Physiology, Faculty of Medicine, University of Kelaniya, Colombo, Sri Lanka Discipline of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, Australia Western Sydney Genetics Program, Sydney Children's Hospitals Network, Westmead, Australia Sarah M. and Charles E. Seay Center for Musculoskeletal Research, Texas Scottish, Rite Hospital for Children, Dallas, Texas McDermott Center for Human Growth and Development, University of Texas, Southwestern Medical Center, Dallas, Texas Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, Texas Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas
“ Holding on to What I Do ” : Experiences of Older Slovenians Moving into a Care

Publisher Rights Statement: Author accepted manuscript This is a pre-copyedited, author-produced PDF of an article accepted for publication in The Gerontologist following peer review. The version of record Tanja Krizaj, Alison Warren, and Anita Slade "Holding on to What I Do": Experiences of Older Slovenians Moving into a Care Home The Gerontologist 2016 : gnw150v1-gnw150. is available online at: http://gerontologist.oxfordjournals. org/content/early/2016/11/16/geront.gnw150
of β-casein A1 or A2 milk on body composition, milk intake, and growth in Holstein, Simmental, and crossbred dairy calves of both sexes

The aim of this study was to compare the effects of feeding homozygous β-casein A1 or A2 milk, on the body composition, milk intake, and growth of German Holstein (GH), German Simmental (GS), and crossbred dairy calves of both sexes during the first 2 weeks of life. A total of 104 calves (n = 54 female - f and n = 50 male - m) from the breed groups GH (n = 23), GS (n = 61), and crossbred GH x GS (CR; n = 20) were evaluated. Calves were weighed after birth and received colostrum ad libitum. On the second day, calves were alternately housed in pairs in double-igloo systems according to their random birth order and received either A1 milk (n = 52; 27 f / 25 m) or A2 milk (n = 52; 27 f / 25 m). They were offered 7.5 L/day, and the individual actual total milk intake (TMI) was recorded. Daily energy-corrected milk intake was also calculated based on the milk composition (fat and protein). Fecal scores were recorded daily. On d 15, visceral adipose tissue (VAT) volume was assessed by open magnetic resonance imaging (MRI) and dual-energy x-ray absorptiometry (DXA). In addition, fat and lean mass (g), as well as bone mineral content (g) and bone mineral density (g/cm 2 ), were determined by DXA. The body composition, milk intake, and growth were similar between the 2 types of milk in the first 2 weeks of life. Female calves had more VAT and fat mass, but less lean mass than male calves. GH and CR calves had more VAT and less lean mass than GS calves. Male calves were heavier than female calves after birth and on d 15. The average days with diarrhea and diarrhea occurrence were similar between calves fed A1 and A2 milk and between both sex groups. GS calves presented slightly more days with diarrhea and increased odds of having diarrhea compared with GH calves, not differing from CR.
Effects of bread waste and Calendula officinalis inclusion on egg production and egg quality

Grigorova, S. & Penkov, D. (2023). Effects of bread waste and Calendula officinalis inclusion on egg production and egg quality. Bulg. J. Agric. Sci., 29 (4), 759–764 Study of the effect of 20% substitution of maize with bread waste and 0.5% Calendula officinalis inclusion to the laying hen’s diets on their productivity, egg quality and chemical composition of egg yolk and egg albumen was made. A total of 90 layers (42 weeks old) from Lohman Klassik Brown breed were randomly allocated into 3 groups (n = 30 hens/group//each group = 3 replications(subgroups)*10 birds in replication) – control group (main energetic source in the diet – maize); I ex - perimental group – maize replacement with 20% extruded bread waste; II experimental group – maize replacement with 20% extruded bread waste+0.5% marigold ( Calendula officinalis ) flowers. The compound feeds for all the groups were isoenergetic and isoprotein balanced. The hens from II experimental group had the best feed conversion (159.80 g of feed for one egg), followed by the first experimental group – 164.17 g. It was found significant lower total yolk cholesterol content in hens from II-nd experimental group than other groups. Extruded bread waste can replace 20% of maize in laying hens diet, without nega - tively effect on their egg productivity and egg quality, but it’s way saved expensive maize grain, but also bread not consumed by humans is utilized.
Journal of Educational Leadership in Action

Higher education administrators and faculty often cite lifelong learning as a central focus. In fact, many institutions include lifelong learning in their student outcomes or mission statements. However, few may actually define what lifelong learning means as a construct. Research has suggested lifelong learning is a skill developed over time (Knapper & Cropley, 2000) which leads to self-directed development in the years following graduation (Candy, 1995). While researchers may agree lifelong learning is a skill, there appears to be a lack of literature explaining how higher education faculty may develop this skill in students. The following discussion will attempt to suggest methods of teaching this skill at colleges and universities through examination of theoretical foundations and current practices.
Radiocarbon Variations from Tasmanian Conifers: First Results from Late Pleistocene and Holocene Logs

Dendrochronological studies have begun on two conifer species in the Stanley River area of western Tasmania. The chronology extends to 273 BC for Huon pine (Lagarostrobos franklinii) and to AD 1450 for celery-top pine (Phyllocladus aspleniifolius). Apart from living or recently felled trees, sections have been taken from 58 logs preserved in floodplain sediments. Two of these logs have late Pleistocene ages, centered around 13.0 and 12.7 k 14C yr bp. Four logs are between 8 and 9 ka BP, and one is centered at 7.3 ka bp. The remaining logs have various ages between 6.2 ka BP and the present. 14C measurements have been performed on decadal samples from the two late Pleistocene logs, providing short (260-yr) records of atmospheric 14C variations when plotted against individual ring numbers. Decadal measurements on the 7300-yr-old log have been wiggle-matched with 14C calibration curves from German oak and bristlecone pine. Measurements for the period, AD 1600–1800, show good agreement with northern hemisphere results, and a nearly zero offset between the hemispheres.
Cow’s Milk: A Benefit for Human Health? Omics Tools and Precision Nutrition for Lactose Intolerance Management

Cow’s milk (CM) is a healthy food consumed worldwide by individuals of all ages. Unfortunately, “lactase-deficient” individuals cannot digest milk’s main carbohydrate, lactose, depriving themselves of highly beneficial milk proteins like casein, lactoalbumin, and lactoglobulin due to lactose intolerance (LI), while other individuals develop allergies specifically against these proteins (CMPA). The management of these conditions differs, and an inappropriate diagnosis or treatment may have significant implications for the patients, especially if they are infants or very young children, resulting in unnecessary dietary restrictions or avoidable adverse reactions. Omics technologies play a pivotal role in elucidating the intricate interactions between nutrients and the human body, spanning from genetic factors to the microbiota profile and metabolites. This comprehensive approach enables the precise delineation and identification of distinct cohorts of individuals with specific dietary requirements, so that tailored nutrition strategies can be developed. This is what is called personalized nutrition or precision nutrition (PN), the area of nutrition that focuses on the effects of nutrients on the genome, proteome, and metabolome, promoting well-being and health, preventing diseases, reducing chronic disease incidence, and increasing life expectancy. Here, we report the opinion of the scientific community proposing to replace the “one size fits all” approach with tailor-made nutrition programs, designed by integrating nutrigenomic data together with clinical parameters and microbiota profiles, taking into account the individual lactose tolerance threshold and needs in terms of specific nutrients intake. This customized approach could help LI patients to improve their quality of life, overcoming depression or anxiety often resulting from the individual perception of this condition as different from a normal state.
Pengaruh Pendidikan Dan Pelatihan Kepemimpinan Terhadap Kinerja Aparatur Di Lingkungan Pemerintah Kabupaten Rokan Hulu

Many factors can affect a person's performance, one of which is Education and training (Diklat). Training is a learning process in an organization that leads to changes in employee attitudes and behavior in order to meet expectations of work qualifications and demands for organizational development both internal and external. Among the types of education and training according to Government Regulation No. 14 of 1994 concerning Education and Training of Civil Servants, the author intends to examine leadership education and training that are classified in technical education and training. The main objective of this research is to find out and analyze the influence of leadership education and training on the performance of the apparatus in the government of Rokan Hulu Regency. This study examines the effect of Leadership Education and Training by using indicators of Training Implementation, Training Costs, Training Participants and Training Facilities on Apparatus Performance with indicators of Service Quality, Communication, Speed, Ability, and Initiatives. This type of research used in this study is this research using an associative explanatory approach (explanatory associate research) which seeks to explain the causal relationship between variables (associative) through hypothesis testing. The research method used is quantitative that aims to obtain evidence of a causal relationship or influence of the research variables. The total sample population in this study was 94 people with 2 people as key informants with census techniques for sampling, the type of data used was primary data collected by questionnaire and interview techniques while secondary data was collected by observation and documentation techniques. The data analysis technique used is the validity test, reliability test, normality test, simple linear regression test and partial test (T test). based on analysis techniques Based on the value that tcount is 10,587 at ttable with df = 92 and a significant level of 5% or 0.05 obtained 0.1707. Because tcount (10,587)> ttable (0.1707) then Ho is rejected and Ha is accepted, meaning that the variable Education and Training Leadership (X) has a significant influence on the Performance of the State Civil Apparatus (Y).
Correlation between hand grip strength and anthropometric measurement among undergraduate medical students

Background: Hand grip strength is a simple procedure of assessing the function of hand and forearm. It can be used as a tool to evaluate nutritional status of individual, neurological disorder and to assess the post-operative status of the patient. The grip strength is affected by different variables such as geographical variation, gender, height, weight, body mass index and handedness of the individual. Objective: This study aims to correlate hand grip strength with gender, height, weight, body mass index and handedness among Nepali population. Methods: The study was analytical cross-sectional study conducted in students of Kathmandu University School of Medical Sciences. Convenience sampling was used. The height of the participants was taken by using Stadiometer in centimeter and weight was taken by using weighing machine in kilogram and body mass index was calculated. Hand grip strength was obtained by using Dynamometer measured in kilogram. The data were entered in Microsoft Excel Sheet and analysis was done in SPSS version 16.0. Results: Hand grip strength showed moderate positive correlation with both height and weight both in both dominant and non-dominant hands. Hand grip strength was positively correlated in underweight, normal weight and obese category of body mass index whereas overweight category was negatively correlated. Conclusion: Hand grip strength shows correlation with the gender, height, weight and body mass index.
Enhancing Airline Operations by Flight Delay Prediction - A PySpark Framework Approach

Airline delay prediction plays a crucial role in the aviation industry, enabling airlines to optimize operations and improve passenger satisfaction. In this research, we propose a comprehensive framework for airline delay prediction using PySpark, a distributed data processing framework. Our study incorporates four widely used machine learning algorithms: Logistic Regression Classifier, Random Forest Classifier, Gradient Boosted Tree Classifier and Decision Tree Classifier. Our experimental results demonstrate the potential of the proposed framework. The identified classifiers when implemented achieve promising results in terms of predictive accuracy, highlighting their suitability for airline delay prediction. By comparing and contrasting these algorithms, we provide insights into their respective strengths and limitations. This research presents a robust framework for airline delay prediction, leveraging PySpark's distributed data processing capabilities. The experimental evaluation of multiple machine learning algorithms highlights their efficacy in accurately predicting flight delays. The deployed prediction system showcases the practical application of our framework, paving the way for improved operational efficiency and enhanced passenger experiences in the aviation industry. From the experiments, logistic regression classifier and random forest classifier had better results.
Novel Advances in Qualitative Diagnostic Imaging for Decision Making in Multidisciplinary Treatment for Advanced Esophageal Cancer

Background: Recently, neoadjuvant therapy and the succeeding surgery for advanced esophageal cancer have been evaluated. In particular, the response to the therapy has been found to affect surgical outcomes, and thus a precise evaluation of treatment effect is important for this strategy. In this study, articles on qualitative diagnostic modalities to evaluate tumor activities were reviewed, and the diagnostic indices were examined. Methods: For prediction of the effect, perfusion CT and diffusion MRI were estimated. For the histological response evaluation, perfusion CT, diffusion-MRI, and FDG-PET were estimated. For downstaging evaluation of T4, tissue-selective image reconstruction using enhanced CT was estimated and diagnostic indices were reviewed. Results: The prediction of the effect using perfusion CT with ‘pre CRT blood flow’ and diffusion MRI with ‘pre CRT ADC value’; the estimation of the histological response using perfusion CT with ‘post CRT blood flow reduction, using diffusion MRI with ‘post CRT ADC increasing’, and using FDG-PET with ‘post CRT SUV reduction’; and the downstaging evaluation of T4 using CT image reconstruction with ‘fibrous changed layer’ were performed well, respectively. Conclusions: Qualitative imaging modalities for prediction or response evaluation of neoadjuvant therapy for progressive esophageal cancer were useful for the decision making of the treatment strategy of the multidisciplinary treatment.
F-TBDA: A Frequency-Based Temporal Big Data Analytics Technique for Mining and Analyzing Quality-Of-Life Indicators of Cancer Patients

In this paper, we introduce and experimentally assess an innovative big data analytics technique for mining and analyzing Quality-of-Life Indicators (QoL) over time among patients with lung cancer and treated with immunotherapy. In more details, given datasets of QoL indicators collected over time, at regular intervals, the F-TBDA technique (Frequency-based Temporal Big Data Analytics) computes temporal relative frequency tables over fixed-time intervals where data of subsequent observations (i.e., intermediate therapy) are compared with the baseline observation (i.e., starting therapy). Then, on the basis of these relative frequency tables, both simple and complex frequency-based big data analytics tools are developed, in order to unveil hidden patterns over cancer patient therapies. Experimental results on top of a real-life dataset nicely complete the theoretical contributions we provide in our research.
Co-Design of Tapering and Dielectric Loading for Minimizing the Scattering Cross Section of a Near-Field Measurement Probe

This paper investigates the antenna capabilities of a near-field measurement probe, such as the return loss (S11), radiation pattern and peak gain. For this purpose, a rectangular open ended waveguide (OEWG) is used, while minimizing its scattering cross section (SCS), to increase the accuracy of near-field measurements. In this context, the relation between tapering and dielectric loading of the measurement probe is analyzed, since the taper is simultaneously utilized as an air to dielectric transition for the antenna. Furthermore, absorbers are used around the opening of the OEWG, to reduce the SCS even further. It is shown, that the tapering and dielectric loading of the measurement probe are highly correlated and significantly influence the antenna capabilities. Finally, the best constellations to reduce the SCS and increase the antenna capabilities of a rectangular OEWG are shown with improvements up to 15 dBsm.