Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying the Strength Level of Objects’ Tactile Attributes Using a Multi-Scale Convolutional Neural Network

In order to solve the problem in which most currently existing research focuses on the binary tactile attributes of objects and ignores identifying the strength level of tactile attributes, this paper establishes a tactile data set of the strength level of objects’ elasticity and hardness attributes to make up for the lack of relevant data, and proposes a multi-scale convolutional neural network to identify the strength level of object attributes. The network recognizes the different attributes and identifies differences in the strength level of the same object attributes by fusing the original features, i.e., the single-channel features and multi-channel features of the data. A variety of evaluation methods were used for comparison with multiple models in terms of strength levels of elasticity and hardness. The results show that our network has a more significant effect in accuracy. In the prediction results of the positive examples in the predicted value, the true value has a higher proportion of positive examples, that is, the precision is better. The prediction effect for the positive examples in the true value is better, that is, the recall is better. Finally, the recognition rate for all classes is higher in terms of f1_score. For the overall sample, the prediction of the multi-scale convolutional neural network has a higher recognition rate and the network’s ability to recognize each strength level is more stable.
The Influence of Students’ Physical Activity on the Use of Information Technology

Physical activity is very important for human health in carrying out daily activities. Activity lack of movement caused by too often playing online and offline games, internet, watching television too much will lead to the risk of obesity. A person's obesity is considered a risk factor for various diseases, such as diabetes, heart, hypertension and many others. One of the efforts that are considered to reduce the risk of obesity is to increase physical activity. Physical activity is not only limited to sports-specific activities, but also other activities that require physical labor, such as sweeping, mopping, washing, walking, dancing, painting, hoeing, walking and so on. This research aims to find out if there is an influence and how much information technology users have on the physical activity of students in SMK Negeri 5 Kota Bengkulu. This study is a non-experimental study. The subjects in this study were students of class X SMK Negeri 5 Kota Bengkulu by using a random sampling cluster consisting of 16 classes with a total of 558 students who were categorized as 72 male students and 486 female students. And from the results of the random sampling cluster obtained 5 classes with a total sample of 150 students. From the results of the calculation of statistics can conclude that there is no significant influence between the use of information technology on the physical activity of students. Because the data tests performed showed that the calculated r was smaller than the r tabelrhitung (-.717) > rtabel (0.197).
Effect of Trehalose and Ceftriaxone on the Stability of Aggregating-Prone Tau Peptide Containing PHF6* Sequence: An SRCD Study

The tau protein, a soluble protein associated with microtubules, which is involved in the assembly and stabilization of cytoskeletal elements, was found to form neurofibrillary tangles in different neurodegenerative diseases. Insoluble tau aggregates were observed to be organized in paired helical filaments (PHFs) and straight filaments (SFs). Recently, two small sequences (306–311 and 275–280) in the microtubule-binding region (MTBR), named PHF6 and PHF6*, respectively, were found to be essential for tau aggregation. Since a possible therapeutic approach consists of impairing amyloid formation either by stabilizing the native proteins or reducing the level of amyloid precursors, here we use synchrotron radiation circular dichroism (SRCD) at Diamond B23 beamline to evaluate the inhibitory effects of two small molecules, trehalose and ceftriaxone, against the aggregation of a small peptide containing the PHF6* sequence. Our results indicate that both these molecules, ceftriaxone and trehalose, increased the stability of the peptide toward aggregation, in particular that induced by heparin. With trehalose being present in many fruits, vegetables, algae and processed foods, these results support the need to investigate whether a diet richer in trehalose might exert a protective effect toward pathologies linked to protein misfolding.
Integrated Taxonomy Revealed Genetic Differences in Morphologically Similar and Non-Sympatric Scoliodon macrorhynchos and S. laticaudus

Simple Summary In this study, the species identities of similar-looking coastal spadenose sharks from different areas were clarified by adding new molecular markers and more individual body measurements, including animals from the Malaysian Peninsula that had not been examined previously. Collective evidence showed that there are two genetically distinct species that do not overlap in their spatial occurrence. The Malacca Strait acts as a boundary delineating the distribution range of the Pacific spadenose shark Scoliodon macrorhynchos to the east and, of the Northern Indian Ocean, S. laticaudus to the west. In addition, the need to determine the species status of Scoliodon animals from Indonesian waters was identified. The present study reinforced the need to rely on comprehensive genetic information in addition to external characteristics to assess the species identities and distribution range for small sharks and rays that have apparent contiguous coastal distribution with limited dispersal abilities. Abstract Previous examination of the mitochondrial NADH2 gene and morphological characteristics led to the resurrection of Scoliodon macrorhynchos as a second valid species in the genus, in addition to S. laticaudus. This study applied an integrated taxonomic approach to revisit the classification of the genus Scoliodon based on new materials from the Malaysian Peninsula, Malaysian Borneo and Eastern Bay of Bengal. Mitochondrial DNA data suggested the possibility of three species of Scoliodon in the Indo-West Pacific, while the nuclear DNA data showed partially concordant results with a monophyletic clade of S. macrorhynchos and paraphyletic clades of S. laticaudus and S. cf. laticaudus from the Malacca Strait. Morphological, meristic and dental characteristics overlapped between the three putative species. Collective molecular and morphological evidence suggested that the differences that exist among the non-sympatric species of Scoliodon are consistent with isolation by distance, and Scoliodon macrorhynchos remains as a valid species, while S. cf. laticaudus is assigned as S. laticaudus. The Malacca Strait acts as a spatial delineator in separating the Pacific S. macrorhynchos (including South China Sea) from the Northern Indian Ocean S. laticaudus. Future taxonomic work should focus on clarifying the taxonomic status of Scoliodon from the Indonesian waters.
Plasma-controlled surface wettability: recent advances and future applications

Materials with the desirable surface wettability are of key importance in diverse applications. However, most of the existing chemical processes used for surface wettability control are often energy-inefficient, pollute the environment, and rely on harsh processing conditions. Therefore, highly-selective, green, and low-cost alternative fabrication techniques are in urgent demand. Low-temperature plasma processing is one such promising approach that satisfies the above requirements. In this review, we present recent advances in plasma processing to control surface wettability for diverse emerging applications in the environment, energy, and biomedicine fields. The underlying mechanisms of the plasma surface engineering, key features of the fabrication processes, and water-surface interactions are discussed. This review aims to guide further development of the plasma processing to effectively control the surface wettability of various surfaces. This effort is poised to contribute to the development of advanced functional materials targeting a broad range of applications.
Association between Heavy Metal Exposure and Dyslipidemia among Korean Adults: From the Korean National Environmental Health Survey, 2015–2017

Cardiovascular disease (CVD) is a leading cause of death in Korea. Dyslipidemia, characterized by the presence of abnormal lipid levels, has been suggested as an early diagnostic and preventable factor for CVD. Recent studies have shown that exposure to lead (Pb), cadmium (Cd), and mercury (Hg) affects lipid metabolism. This study aimed to verify the association between heavy metal concentrations and serum lipid profiles in the general population. A representative sample of 2591 Korean adults from the Korean National Environmental Health Survey (2015–2017) was analyzed. The associations between heavy metals [Blood Pb (BPb), blood Hg (BHg), urinary Hg (UHg), urinary Cd (UCd)] and serum lipid profiles [total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), non-low level of high-density lipoprotein cholesterol (Non-HDL-C)] were assessed using regression analysis. After adjusting for demographic and socioeconomic factors, the proportional changes in serum lipid levels were significantly associated with increases in BPb, BHg, and UHg levels (p for trend < 0.05). Overall, BPb, BHg, and Uhg levels positively correlated with dyslipidemia, whereas UCd levels did not show a significant association. Our results suggest that heavy metal exposure, at low levels, may contribute to an increased prevalence of dyslipidemia in Korean adults.
Efficient color image retrieval method using deep stacked sparse autoencoder

Abstract. The recent advancement in deep learning-based approaches vastly outperforms the traditional image descriptors. Deep learning models, such as residual networks (ResNet), are well known for finding salient features. Although effective, high-level description often has a high dimensionality that increases computational overhead. The autoencoders find the useful approximation of the input data without losing critical information. Considering this, we propose a content-based image retrieval system for natural color images using a deep stacked sparse autoencoder (DSSA). The DSSA model learns latent features in an unsupervised way from the high-level description obtained using ResNet. The DSSA model achieves a nearly 50% reduction in size compared with the full-length features for the simple distance-based retrieval approach while increasing accuracy. The image retrieval efficacy of the learned latent features is also evaluated for two classifier-based methods using a Softmax classifier. Further, this study investigates the impact of unsupervised feature learning on retrieval using three benchmark natural color image databases of varying complexities, viz., Corel-1K, Corel-10K, and Canadian Institute for Advanced Research (CIFAR)-10. The latent features learned by the DSSA model with the fuzzy class membership-based retrieval method achieve promising improvements and yield a highly competitive retrieval performance with the large-size CIFAR-10 database.
Supporting College Learners’ Study Time Calibration: Relations to Course Achievement and Self-Regulated Learning Skills

ABSTRACT Planning for and evaluating study behaviors are key regulatory skills that present considerable challenge for college learners. This study examined the utility of a targeted intervention tool intended to promote college learners’ study time calibration. Through implementation of a weekly, reflective activity, we examined improvement in learners’ study time calibration over time as well as the contributions of students’ initial study time calibration to their end-of-course study time calibration, course performance, and self-regulated learning skills. Students’ study time calibration scores improved across the college success strategies course. Students’ mid-course study time calibration predicted their end-of-course study time calibration and course performance. Students’ end-of-course study time calibration also predicted their reported goal-setting skills after controlling for their prior regulatory skills. Recommendations for future research and practice are described.
Multi-Label Speech Emotion Recognition via Inter-Class Difference Loss Under Response Residual Network

Speech emotion recognition has always been a challenging task due to the difference in emotion expression and perception. Currently, in the supervised speech emotion recognition systems, the soft label overcomes the disadvantage of the hard label losing annotations variability and emotion perception subjectivity, but it only considers the emotion perceptions of a few annotators and thus still brings high statistical error. For this issue, this paper redefines the target and designs a novel loss function (denoted as inter-class difference loss), which enables the network to adaptively learn an emotion distribution in all utterances. This not only restricts the negative class probability less than the positive class probability, but also limits the negative class probability close to zero. To make the speech emotion recognition system more efficient, this paper proposes an end-to-end network, called response residual network (R-ResNet), which incorporates the ResNet for features extraction, together with the emotion response module for data augmentation and variable-length data processing. Finally, the experimental results not only demonstrate the advanced performance of our work, but also confirm that the ambiguous utterances contain emotional characteristics. In addition, another interesting finding is that, on the unbalanced dataset, the batch normalization (BN) after addition performs better than BN before addition.
A Novel Untethered Hand Wearable with Fine-Grained Cutaneous Haptic Feedback

During open surgery, a surgeon relies not only on the detailed view of the organ being operated upon and on being able to feel the fine details of this organ but also heavily relies on the combination of these two senses. In laparoscopic surgery, haptic feedback provides surgeons information on interaction forces between instrument and tissue. There have been many studies to mimic the haptic feedback in laparoscopic-related telerobotics studies to date. However, cutaneous feedback is mostly restricted or limited in haptic feedback-based minimally invasive studies. We argue that fine-grained information is needed in laparoscopic surgeries to study the details of the instrument’s end and can convey via cutaneous feedback. We propose an exoskeleton haptic hand wearable which consists of five 4 × 4 miniaturized fingertip actuators, 80 in total, to convey cutaneous feedback. The wearable is described as modular, lightweight, Bluetooth, and WiFi-enabled, and has a maximum power consumption of 830 mW. Software is developed to demonstrate rapid tactile actuation of edges; this allows the user to feel the contours in cutaneous feedback. Moreover, to demonstrate the idea as an object displayed on a flat monitor, initial tests were carried out in 2D. In the second phase, the wearable exoskeleton glove is then further developed to feel 3D virtual objects by using a virtual reality (VR) headset demonstrated by a VR environment. Two-dimensional and 3D objects were tested by our novel untethered haptic hand wearable. Our results show that untethered humans understand actuation in cutaneous feedback just in a single tapping with 92.22% accuracy. Our wearable has an average latency of 46.5 ms, which is much less than the 600 ms tolerable delay acceptable by a surgeon in teleoperation. Therefore, we suggest our untethered hand wearable to enhance multimodal perception in minimally invasive surgeries to naturally feel the immediate environments of the instruments.
HYPNO-BREASTFEEDING REDUCES ANXIETY OF BREASTFEEDING MOTHERS DURING THE COVID-19 PANDEMIC

Background: COVID-19 pandemic is a time when a lot of people are vulnerable for virus transmission which can cause anxiety and psychological disorders, including for postpartum and breastfeeding mothers. The harmful effects of postpartum anxiety, if not managed properly, can affect the physical and psychological health of both mother and baby. The purpose of this study was to determine the effect of hypno-breastfeeding on reducing postnatal maternal anxiety.Methods: The design of this study was quasi-experimental design with one pretest-posttest group, without control group. This study was conducted at the South Denpasar Health Center III with samples of 32 respondents who met the inclusion criteria. The sampling technique used in this research was purposive sampling. The independent variable in this study was hypno-breastfeeding and the dependent variable was decreased anxiety. Data were collected using the Zung Self-rating Anxiety Scale (ZSAS) questionnaire and data analysis was carried out using univariate and bivariate test (t test). Result: The results showed that most of the breastfeeding mother before being given hypno-breastfeeding (65%) experienced moderate anxiety and after being given hypno-breastfeeding, most mother (47%) experienced mild anxiety. The bivariate results show the t-count value of 6.851 with p-value (0.000) which showed that there is a significant effect of hypno-breastfeeding on reducing anxiety of breastfeeding mothers.Conclusion: Hypno-breastfeeding can be applied to breastfeeding mothers to reduce anxiety and make exclusive breastfeeding successful.
Smo-Shh Agonist Purmorphamine Prevents Neurobehavioral and Neurochemical Defects in 8-OH-DPAT-Induced Experimental Model of Obsessive-Compulsive Disorder

Obsessive-compulsive disorder is a mental disorder characterized by repetitive, unwanted thoughts and behavior due to abnormal neuronal corticostriatal-thalamocortical pathway and other neurochemical changes. Purmorphamine is a smoothened-sonic-hedgehog agonist that has a protective effect against many neurological diseases due to its role in maintaining functional connectivity during CNS development and its anti-inflammatory and antioxidant properties. As part of our current research, we investigated the neuroprotective effects of PUR against behavioral and neurochemical changes in 8-hydroxy-2-(di-n-propylamino)-tetralin-induced obsessive-compulsive disorder in rats. Additionally, the effect of PUR was compared with the standard drug for OCD, i.e., fluvoxamine. The intra-dorsal raphe-nucleus injection of 8-OH-DPAT in rats for seven days significantly showed OCD-like repetitive and compulsive behavior along with increased oxidative stress, inflammation, apoptosis, as well as neurotransmitter imbalance. These alterations were dose-dependently attenuated by long-term purmorphamine treatment at 5 mg/kg and 10 mg/kg i.p. In this study, we assessed the level of various neurochemical parameters in different biological samples, including brain homogenate, blood plasma, and CSF, to check the drug’s effect centrally and peripherally. These effects were comparable to the standard oral treatment withfluvoxamine at 10 mg/kg. However, when fluvoxamine was given in combination with purmorphamine, there was a more significant restoration of these alterations than the individualtreatmentswithfluvoxamine and purmorphamine. All the above findings demonstrate that the neuroprotective effect of purmorphamine in OCD can be strong evidence for developing a new therapeutic target for treating and managing OCD.
Field-of-View Constrained Three-Dimensional Impact Angle Control Guidance for Speed-Varying Missiles

This article develops a three-dimensional (3-D) impact angle control guidance law with the field-of-view (FOV) constraint. The impact error is defined as the difference between the predicted impact angle by proportional navigation guidance and the desired impact angle. The derived guidance command enables the impact angle error trajectory to follow a desired impact angle error dynamic. It can guarantee that the impact error converges to zero before the time of interception. Meanwhile, zero terminal guidance command is achieved, and the FOV constraint is always met during the guidance process. Furthermore, the trajectory of a guided missile is not affected by the variation of missile speed even under the FOV constraint, which reveals that the impact angle control performance is independent of time-varying missile speed. Numerical simulations are conducted to demonstrate the effectiveness of the proposed guidance law.
Prediction Ability of Charlson, Elixhauser, and Rx-Risk Comorbidity Indices for Mortality in Patients with Hip Fracture. A Danish Population-Based Cohort Study from 2014 – 2018

Objective Comorbidity has an important role in risk prediction and risk adjustment modelling in observational studies. However, it is unknown which comorbidity index is most accurate to predict mortality in hip fracture patients. We aimed to evaluate the prediction ability, including discrimination and calibration of Charlson comorbidity index (CCI), Elixhauser comorbidity index (ECI) and Rx-risk index for 30 day- and 1 year mortality in a population-based cohort of hip fracture surgery patients. Methods Using the Danish Multidisciplinary Hip Fracture Registry in the period 2014–2018, 31,443 patients were included. CCI and ECI were based on discharge diagnoses, while Rx-Risk index was based on pharmacy dispensings. We used logistic regression to assess discrimination of the different indices, individually and in combinations, by calculating c-statistics and the contrast in c-statistic to a base model including only age and gender with 95% confidence intervals (CI). Results The study cohort were primarily female (69%) and older than 85 years (42%). The 30-day mortality was 10.1% and the 1-year mortality was 26.6%. Age and gender alone had a good discrimination ability for 30-day and 1-year mortality (c-statistic=0.70, CI: 0.69–0.71 and c-statistic=0.68, CI: 0.67 −0.69, respectively). By adding indices individually to the base model, Rx-risk index had the best 30-day and 1-year mortality discrimination ability (c-statistic=0.73, CI: 0.72–0.74 and 0.71 CI: 0.71–0.72, respectively). By adding combination of indices to the base model, a combination of CCI and the Rx-risk index had a 30-day and 1-year mortality discrimination ability of c-statistic=0.74, CI: 0.73–0.75 and c-statistic=0.73, CI: 0.73–0.74, respectively. Calibration of indices was similar. Conclusion The highest discrimination ability was achieved by combining CCI and Rx-risk index in addition to age and gender. However, age and gender alone had a fair mortality discrimination ability.
A Promising Cobalt Catalyst for Hydrogen Production

In this work, a metal cobalt catalyst was synthesized, and its activity in the hydrogen production process was tested. The substrates were water and ethanol. Activity tests were conducted at a temperature range of 350–600 °C, water to ethanol molar ratio of 3 to 5, and a feed flow of 0.4 to 1.2 mol/h. The catalyst had a specific surface area of 1.75 m2/g. The catalyst was most active at temperatures in the range of 500–600 °C. Under the most favorable conditions, the ethanol conversion was 97%, the hydrogen production efficiency was 4.9 mol (H2)/mol(ethanol), and coke production was very low (16 mg/h). Apart from hydrogen and coke, CO2, CH4, CO, and traces of C2H2 and C2H4 were formed.