Miracle-dz/UniFAR-FTUs huggingface dataset:
Prosodic prominence in a stressless language: An acoustic investigation of Indonesian

Although it has been proposed that all languages may have some lexical stress property, recent studies of (Standard) Indonesian have concluded, based primarily on perception, that lexical stress is not present in this language. While it is philosophically problematic to prove the non-existence of a phenomenon, we examine data from a large-scale production study for both direct and indirect evidence of stress, contributing to the growing body of literature in this field. In the first case, evidence is sought that indicates that a particular syllable in a word exhibits acoustic properties typically associated with prominence (i.e. fundamental frequency (f0), duration, intensity, vowel quality). In the second case, evidence of enhancement of these properties on a particular syllable under focus is sought, for a more abstract stress property that is not overtly manifested at the word level. Although we find no evidence of lexical prominence, we observe acoustic patterns consistent with a higher level prominence corresponding to focus, manifested by strong (Intonational Phrase) boundary properties. Overall, our findings reveal that there is strong support for a class of languages lacking lexical stress, and in the absence of a stressed syllable to enhance, focus may be manifested prosodically as boundary properties.
Unearthing Ecumenical Influences on Education Policy in England and Norway using Statement Archaeology

Abstract This paper focuses on the development of Religious Education in England and Norway examining changes that took place in the 1960s. Using Statement Archaeology, the influence of the Christian ecumenical movement on English RE is identified. This movement has mostly been overlooked in the historiographies of RE, yet it appears to play a key role in creating circumstances in which the legitimate study of non-Christian worldviews becomes possible. The paper presents existing research that demonstrates how these global ecumenical discourses affected educational policies in England, setting out a compelling case for further exploration of the developments in Norway.
Iodine and Peroxide Index Rapid Determination by Mid- and Near-infrared Spectroscopy in Ozonated Sunflower Oil and Ozonated Fats

ABSTRACT Ozone can react with fatty species such as vegetable oils to form oxidized compounds with interesting antibacterial activity. The iodine and peroxide indexes of these ozonated products are two crucial antibacterial characteristics. Currently, these two parameters are determined by chemical methods, which is disadvantageous because it requires long handling time, sample destruction and the use of toxic products. Spectroscopic analyses coupled with chemometric evaluations have already shown their usefulness for characterizing virgin oils via rapid, chemical-free methods. In addition, infrared spectroscopy is widely used to characterize ozonated compounds. The present study evaluates the possibility of coupling infrared spectroscopy with chemical analyses of ozonated compounds. We subjected 187 fat samples of varying compositions to different ozonation conditions to determine their chemical parameters. We analyzed the samples by infrared spectroscopy and modeled the results by combining chemical data with spectral analysis. The model results are quantified by the coefficient of determination R2, the root-mean-square error, and the residual predictive deviation (RPD). The model produces RPDs greater than 3.5 for the mid-infrared spectral range, which means that they may be used to estimate indexes. In addition, with RPDs between 2 and 3, partial least squares near-infrared models demonstrate a capacity for rough screening of ozonated fats.
Effect of Boron Supplementation on Bone Mineralization and Antioxidant Status in Broiler Chicken

Background: Functionality and requirement of Boron as a trace element in livestock feeding has not been well established. Limited research conducted worldwide suggests B is a trace element known to influence various physiological functions specifically the metabolism of minerals, hormones, immunity and antioxidant defense mechanism; thereby the performance of the birds. The whole grains widely used in poultry diets contain very little boron and currently, there is no definitive information regarding the boron requirement for any class of poultry and inclusion levels are far from standardized. Therefore, the present experiment has been conducted to study the influence of boron on bone mineralization and antioxidant status in broiler.Methods: A total of 240 day-old broiler chicks (Vencob) of mixed sex (avg. BW 47.50±0.26 g) were distributed in a completely randomized design into five treatments each with four replicates of 12 birds (6 of each sex). The dietary treatments involved supplementation of boron at 0 (B-0), 25 (B-25), 50 (B-50), 75 (B-75) and 100 (B-100) mg/kg diet. The birds were offered starter (d 1 to 21) and finisher (d 22 to 42) diet in mash form. At d 42, Whole blood (2 ml) sample was collected for the estimation of total antioxidant status and reduced glutathione by FRAP and DTNB method, respectively. Two birds per replication were selected randomly; sacrificed and right femur bone was collected to measure the bone ash and mineral content.Result: Boron supplementation enhanced the bone ash, calcium and phosphorus content but decreased the manganese and iron content in bone. Supplementation of Boron significantly enhanced (P less than 0.05) the total antioxidant capacity but lowered the plasma reduced glutathione level.
Hyperspectral Classification Based on Coupling Multiscale Super-Pixels and Spatial Spectral Features

Hyperspectral remotely sensed images contain not only the spatial information of ground objects, but also their rich spectral information. Effectively improve the classification accuracy of hyperspectral images (HSIs), the purpose is to accurately grasp the current land resource utilization information, which is of great significance to the formulation and implementation of future land and space planning. Existing research on the classification of hyperspectral remotely sensed images uses a single-scale superpixel method for image segmentation. The optimal number of superpixels cannot be determined, image details may get missed, and a single kernel matrix cannot represent the information from multiple features, which results in reduced classification accuracy. Therefore, this study intends to use the superpixel segmentation method to perform multiscale superpixel segmentation on the principal components of HSIs at multiple scales, and to couple the multiscale superpixel spatial spectral kernel (SSK) with the original spectral kernel to form a synthetic kernel using weights for HSI classification. The three HSIs of Pavia University, Pavia Center, and Washington DC Mall are used as the experimental data to test and analyze this method. The experimental results show that the effective classification accuracies for the three datasets obtained by this method are 5.28%, 5.90%, and 7.71% higher than the five comparison methods, at best. The results prove that this method can effectively solve the problem of imprecise image feature extraction and an unknown number of initial superpixels and can significantly improve the classification accuracy of HSIs.
Hydrological Changes in Restricted Basins: Insights From Strontium Isotopes on Late Miocene‐Pliocene Connectivity of the Eastern Paratethys (Dacian Basin, Romania)

The Dacian Basin was uniquely situated to record late Miocene hydrological changes that influenced depositional environments and faunal dispersal patterns in Central Eurasia's mega‐lake Paratethys. Differences between the high strontium isotope ratio (87Sr/86Sr) of the waters from Lake Pannon and local Carpathian rivers and low 87Sr/86Sr of the Eastern Paratethys (Black Sea ‒ Caspian Sea) allow a thorough investigation of connectivity and water fluxes in the transient Dacian Basin. We present a detailed 87Sr/86Sr record for the Dacian Basin, which provides an exceptional record of basin connectivity from the latest Tortonian (ca. 7.7 Ma) until the early Pleistocene (ca. 1.8 Ma). Data show that a late Tortonian transgression (7.6–7.4 Ma) started with an incursion of Eastern Paratethys waters into the Dacian Basin, after which local rivers became the dominant source for the mostly freshwater environments of the early Messinian. The regional Maeotian‐Pontian transitional interval (6.3–5.9 Ma) records a second incursion of Eastern Paratethys waters, but this time with an additional marine (Mediterranean) influx coinciding with a short‐lived salinity incursion. During the Messinian Salinity Crisis of the Mediterranean, the Dacian Basin progressively connected with the Eastern Paratethys (5.9–5.5 Ma), after which it became restricted during the peak Mediterranean lowstand (5.5 Ma) and filled with Lake Pannon and local river water (5.5–5.3 Ma). During the Plio‐Pleistocene, the Dacian Basin reconnected with the, at that time isolated, Black Sea, which shows similar 87Sr/86Sr as in the Last Glacial Maximum.
Opening Doors in the Democratic People’s Republic of Korea

This paper considers the opportunities for effective humanitarian collaboration in the Democratic People’s Republic of Korea (DPRK). It brings together perspectives from three individuals with extensive lived experience working in the DPRK. Collectively, these authors have worked in various sectors of international humanitarian aid and other areas of engagement such as emergency response and preparedness, education, social enterprise and tourism. The paper draws from these experiences to present lessons on overcoming obstacles and harnessing opportunities in the DPRK.
Deep Learning Method for Building Image Localization in Smart City

In recent years, with the construction and development of smart cities, the rapid popularization of the Internet of Things and the sharp increase of Internet users, a large amount of multimedia data with geo-location information shared by users has emerged.However, only a small part of the image data is used correctly.Therefore, building detection can not only realize geographic positioning, but also has guiding significance for GIS mapping and automatic updating.With the extensive application of convolutional neural network and cyclic neural network in image processing, this paper proposes that the BFPN-RCNN algorithm can be used to recognize the curved buildings in the image.By comparing with other image detection algorithms on different data sets, it is proved that the proposed algorithm can effectively locate curved images in natural scene images.
Asymmetric adjustment: Partisanship and correcting misinformation on Facebook

Across two studies, we test two of Facebook’s attempts to fight misinformation: labeling misinformation as disputed or false and including fact checks as related articles. We propose hypotheses based on a two-step model of motivated reasoning, which provides insight into how misinformation is corrected. For study 1 (n = 1,262) and study 2 (n = 1,586), we created a mock Facebook News Feed consisting of five different articles—four were actual news stories and the fifth was misinformation. Both studies tested (a) the effect of misinformation without correction, (b) Facebook’s changes to its platform, and (c) an alternative we theorized could be more effective. The findings, in line with the two-step model of motivated reasoning, provide evidence of symmetric party effects for the belief in misinformation. In both studies, we find partisan differences in responses to fact checking. We find modest evidence that our improvements to Facebook’s attempts at correcting misinformation reduce misperceptions across partisan divides.
Perbandingan Metode Deteksi Wajah Menggunakan OpenCV Haar Cascade, OpenCV Single Shot Multibox Detector (SSD) dan DLib CNN

Comparison of methods in face detection is needed to provide recommendation of best method. This study compared three methods in face detection, namely OpenCV haar cascade, OpenCV Single Shot Multibox Detector (SSD) and Dlib CNN. Face detection is focused on five challenging conditions, namely face detection in head position obstacles, wearing face masks, lighting, background images that have a lot of noise, differences in expression. Data testing is taken randomly on google with reference to one image consisting of more than one detected face with wild condition. The results of the comparative analysis in wild condition show that the OpenCV haar cascade has more weaknesses with a performance percentage of 20% compared OpenCV SSD and Dlib CNN method. Performance results of SSD and Dlib CNN have the same performance in the five conditions tested, which is about 80%.
Bending behavior of hybrid sandwich composite structures containing 3D printed PLA lattice cores and magnesium alloy face sheets

ABSTRACT In this study, the bending behavior of novel magnesium alloy facesheet and 3D-printed polylactic acid (PLA) lattice core sandwich panels with enhanced interface adhesion has been investigated by joint experiment and simulation method. A reliable numerical model for predicting three-point bending behavior of hybrid sandwich panels was developed and an explicit finite element analysis using ABAQUS/Explicit with a self-written VUMAT user subroutine was conducted. Meanwhile, hybrid sandwich panels were evaluated experimentally by three-point bending tests in order to validate the results obtained in the FEA. The comparison results have shown that the FEA predictions are consistent with the experimental tests. The bending resistance of the hybrid PLA core/Mg alloy composite sandwich panel is better than that of the integrated PLA sandwich panel. Among the four lattice geometries studied, namely body-centered cubic (BCC), BCC with gradient distribution of struts (BCCG), BCC with vertical struts connecting all nodes (BCCV), and face and body centered cubic unit cell with vertical struts (F2BCCZ), the sandwich structure with BCCV lattice cores has the better bending bearing capacity. The core configuration and core density have a coupling effect on the bending properties and failure modes of the hybrid sandwich panels.
Compatibility of Drought Magnitude Based Method With Spa for Assessing Reservoir Volumes: Analysis Using Canadian River Flows

The traditional sequent peak algorithm (SPA) was used to assess the reservoir volume (VR) for comparison with deficit volume, DT, (subscript T representing the return period) obtained from the drought magnitude (DM) based method with draft level set at the mean annual flow on 15 rivers across Canada. At an annual scale, the SPA based estimates were found to be larger with an average of nearly 70% compared to DM based estimates. To ramp up DM based estimates to be in parity with SPA based values, the analysis was carried out through the counting and the analytical procedures involving only the annual SHI (standardized hydrological index, i.e. standardized values of annual flows) sequences. It was found that MA2 or MA3 (moving average of 2 or 3 consecutive values) of SHI sequences were required to match the counted values of DT to VR. Further, the inclusion of mean, as well as the variance of the drought intensity in the analytical procedure, with aforesaid smoothing led DT comparable to VR. The distinctive point in the DM based method is that no assumption is necessary such as the reservoir being full at the beginning of the analysis - as is the case with SPA.
Optimal Soft Composites for Under‐Actuated Soft Robots

Material properties and composite structures play key roles in tailoring the performance of soft robots. Unfortunately, current design and fabrication approaches limit achievable complexity and functionality in these two categories and hinder soft robot performance. Here, an approach that allows design and direct fabrication of novel soft composite structures is presented. The process uses computational topology optimization to determine the required 3D composite structure of soft hyper‐elastic bodies. The direct fabrication of the soft composite structures using an all‐in‐one fabrication workflow with resilient silicone polymers enables precise tailoring of mechanical properties. By applying this approach to the design and fabrication of an underwater batoid‐inspired soft robot, significant swimming performance improvements is demonstrated. An optimized composite prototype displays 50% faster swimming speeds, 28% faster turning rates, and 55% smaller turning radii than un‐optimized benchmark prototypes.
Prevalence, Risk Factors, and Perception of Metabolic Syndrome Among Thai Buddhist Monks in a Rural Community, Central Thailand: A Mixed-Methods Study

Background Metabolic syndrome (MetS) is described as a cluster of cardiometabolic risk factors that can increase the possibility of developing atherosclerotic cardiovascular diseases. According to monastic rules, Thai Buddhist monks are not allowed to cook meals and do exercise. This unique lifestyle generally encompasses low physical activities and may cause several noncommunicable diseases. Thus, in this study, we aimed to examine the prevalence, risk factors, and perception of MetS among Thai Buddhist monks. Methods This was a cross-sectional study conducted among Thai Buddhist monks living in Tha Luang District, Lopburi Province, Central Thailand. Study participants completed a questionnaire inquiring about personal and health data, and they also underwent physical examination, including anthropometric measurements, before undergoing biochemical blood tests. MetS was defined based on the National Cholesterol Education Program ATP III (NCEP ATP3) criteria. A qualitative study using in-depth interview was conducted to determine the knowledge and perceptions regarding MetS among Thai Buddhist monks. Results In total, 96 Thai Buddhist monks were included in this study. The prevalence of MetS was 28.1%. Participants who had a body mass index of \(\ge\)25 kg/m2 were determined to have a higher risk of developing MetS (OR, 4.5; 95% CI, 1.6–13.3). The in-depth interview revealed that participants’ perceptions were directly associated with their beliefs, experience, and basic healthcare knowledge. A qualitative study identified two primary factors of MetS among Thai Buddhist monks, viz., unhealthy diet and low physical activity. Conclusions MetS prevalence in Thai Buddhist monks was moderate compared with that reported by other studies. Medical providers and Buddhist devotees should cooperate in providing health promotion by donating healthy food, conducting annual health checkups, and arranging alternative exercises in a private area that correspond with the monastic rules. Therefore, early screening, treatment, and patient education are the most important factors to manage MetS in Thai Buddhist monks.
A Deep Neural Network-based Nonlinear Dynamics Model for the Prediction of Lateral-longitudinal Vehicle Dynamics

The vehicle multibody model can be used for accurate coupling dynamics, but it has higher computational complexity. Numerical stability during integration is also very challenging, especially in complicated driving situations. This issue can be substantially alleviated by using a data-driven nonlinear dynamics model owing to its computational speed and robust generalization. In this work, we propose a deep neural network (DNN)-based modeling approach for predicting lateral-longitudinal vehicle dynamics. Dynamic simulations of vehicle systems are performed based on a semirecursive multibody formulation for data acquisition. The data are then used for training and testing the DNN model. The DNN inputs are the torque applied on wheels and the initial vehicle speed that imitates a double lane change maneuver with acceleration and deceleration. The DNN outputs are the longitudinal driving distance, lateral driving distance, final longitudinal velocities, final lateral velocities, and yaw angle. The dynamic responses obtained from the DNN model are compared with the multibody results. Furthermore, the accuracy of the DNN model is investigated in terms of error functions. The DNN model is finally verified via the results of a commercial software package. The results show that the DNN vehicle dynamics model predicts accurate dynamic responses in real time. The DNN model can be used for real-time simulation and preview control in autonomous vehicles.
Molecular Testing of Thyroid Fine-Needle Aspiration: Local Issues and Solutions. An Interventional Cytopathologist Perspective

Molecular testing has acquired a relevant role for diagnostic and prognostic stratification of indeterminate thyroid nodules. Besides the available commercial solutions marketed in the United States, various local testing strategies have been developed in the last decade. In this setting, the modern interventional cytopathologist, the physician who performs the both aspirate and the morphologic interpretation plays a key role in the correct handling of fine-needle aspiration (FNA) samples not only for microscopy but also for molecular techniques. This review summarizes experiences with local approaches to the molecular testing of thyroid FNA, highlighting the role of the modern interventional cytopathologist.
Pitfalls and Possibilities of Patinated Bronze: The Analysis of Pre-Roman Italian Armour Using pXRF

Despite the importance of weapons and armour as part of material culture in the Mediterranean during the first millennium BCE, such objects have generally not been studied beyond stylistic analyses. Bronze was extensively used in the construction of these materials; however, its characterisation is complicated due to patination and the different manufacturing techniques used. We used portable XRF (pXRF) to non-destructively characterise bronze material in a way that mitigates the distorting effects of patina. Analysis was conducted on 23 pieces of pre-Roman Italian bronze armour. Assays were taken using two different techniques; ‘single point’ assays and ‘cluster’ assays. There is variability visible across assays both on and between items, grouped both geographically and chronologically. We highlight significant trends visible in the results over time and different object types and discuss the utility of pXRF on ancient bronze with recommendations for best practice.