Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dataset for Emotion Recognition Using Virtual Reality and EEG (DER-VREEG): Emotional State Classification Using Low-Cost Wearable VR-EEG Headsets

Emotions are viewed as an important aspect of human interactions and conversations, and allow effective and logical decision making. Emotion recognition uses low-cost wearable electroencephalography (EEG) headsets to collect brainwave signals and interpret these signals to provide information on the mental state of a person, with the implementation of a virtual reality environment in different applications; the gap between human and computer interaction, as well as the understanding process, would shorten, providing an immediate response to an individual’s mental health. This study aims to use a virtual reality (VR) headset to induce four classes of emotions (happy, scared, calm, and bored), to collect brainwave samples using a low-cost wearable EEG headset, and to run popular classifiers to compare the most feasible ones that can be used for this particular setup. Firstly, we attempt to build an immersive VR database that is accessible to the public and that can potentially assist with emotion recognition studies using virtual reality stimuli. Secondly, we use a low-cost wearable EEG headset that is both compact and small, and can be attached to the scalp without any hindrance, allowing freedom of movement for participants to view their surroundings inside the immersive VR stimulus. Finally, we evaluate the emotion recognition system by using popular machine learning algorithms and compare them for both intra-subject and inter-subject classification. The results obtained here show that the prediction model for the four-class emotion classification performed well, including the more challenging inter-subject classification, with the support vector machine (SVM Class Weight kernel) obtaining 85.01% classification accuracy. This shows that using less electrode channels but with proper parameter tuning and selection features affects the performance of the classifications.
Molecular Aspects of Resistance to Immunotherapies—Advances in Understanding and Management of Diffuse Large B-Cell Lymphoma

Despite the unquestionable success achieved by rituximab-based regimens in the management of diffuse large B-cell lymphoma (DLBCL), the high incidence of relapsed/refractory disease still remains a challenge. The widespread clinical use of chemo-immunotherapy demonstrated that it invariably leads to the induction of resistance; however, the molecular mechanisms underlying this phenomenon remain unclear. Rituximab-mediated therapeutic effect primarily relies on complement-dependent cytotoxicity and antibody-dependent cell cytotoxicity, and their outcome is often compromised following the development of resistance. Factors involved include inherent genetic characteristics and rituximab-induced changes in effectors cells, the role of ligand/receptor interactions between target and effector cells, and the tumor microenvironment. This review focuses on summarizing the emerging advances in the understanding of the molecular basis responsible for the resistance induced by various forms of immunotherapy used in DLBCL. We outline available models of resistance and delineate solutions that may improve the efficacy of standard therapeutic protocols, which might be essential for the rational design of novel therapeutic regimens.
The Collaborative Approach to Sustainability: A Model of Commissioning System Intervention in Supporting Multi-Stakeholder Partnerships from National to Global Levels

The paper addresses the role of intermediaries in optimizing collaborative practices for sustainability and provides new perspectives on how the commissioning system intervenes in supporting multi-stakeholder partnerships that operate on different geographical scales. We present in this study a unitary model for the development of the commissioning system with geographically hierarchical structures, from local and national to regional and global levels, capable of creating a network of interdependent connections with international potential between a wide range of parties engaged in collaboration for sustainable territorial development. The paper highlights the potential of the commissioning system to provide better support for sustainability partnerships and identifies the roles that commissioning structures can play for the benefit of the parties interested in mobilizing and accessing capabilities and resources for development. Through its intervention, the collaborative actions between the parties are streamlined and the management of demands and offers of development resources is optimized. Our findings show that such an intervention adds value to partnerships for sustainability at regional and global levels by dynamizing the collaboration, exchange and transfer of resources between the states, using functional collaboration networks created among multiple interacting stakeholders to support the sustainable development goals implementation.
A numerical and experimental study on the drag of a cavitating underwater vehicle in cavitation tunnel

Abstract For Super-Cavitating Underwater Vehicles (SCUV), the numerical analyses and experiments in a large cavitation tunnel are carried out at relatively large Reynolds numbers. The numerical results agree well with experiments and the drag coefficient of SCUV is rarely changed by the Reynolds number. As the cavitation number is decreased, the cavity occurs and grows, the cavitator drag decreases and the body drag is affected by the degree of covering the body with the cavity. The tunnel effects, i.e. the blockage and the friction pressure drop of the tunnel, on the drag and the cavitation of SCUV are examined from the numerical results in between the tunnel and unbounded flows. In the tunnel, a minimum cavitation number exists and the drag of SCUV appears larger than that in unbounded flow. When the super-cavity covers the entire body, the friction drag almost disappears and the total drag of SCUV can be regarded as the pressure drag of cavitator.
Matching design for augmenting the control arm of a randomized controlled trial using real-world data

ABSTRACT Randomized clinical trials (RCTs) have often been considered as the gold standard in drug development, but they may not be fully powered due to limited patient population and can even lead to ethical concerns in rare disease studies. In situations like this, real-world data (RWD)/historical data can be utilized to augment or possibly serve as the control arm for the current trial. If a subset of subjects from the RWD/historical trial could be matched to the concurrent control arm subjects and they are deemed comparable following certain criteria, then pooling the matched subjects from the historical control arm and the concurrent control arm can boost the power. In this paper, we propose two matching methods of borrowing historical control data that not only balance key observed baseline covariates but also ensure the comparability of responses between the historical and concurrent controls. Close similarity in response variables among controls reduces Type I error inflation and provides further protection against unmeasured confounding bias, which is a major challenge in using RWD. Simulation studies are conducted to evaluate the empirical performance of the two matching methods in terms of Type I error rate and power, and an illustrative description of a planned study is presented.
Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia

With many countries experiencing a resurgence in COVID-19 cases, it is important to forecast disease trends to enable effective planning and implementation of control measures. This study aims to develop Seasonal Autoregressive Integrated Moving Average (SARIMA) models using 593 data points and smoothened case and covariate time-series data to generate a 28-day forecast of COVID-19 case trends during the third wave in Malaysia. SARIMA models were developed using COVID-19 case data sourced from the Ministry of Health Malaysia’s official website. Model training and validation was conducted from 22 January 2020 to 5 September 2021 using daily COVID-19 case data. The SARIMA model with the lowest root mean square error (RMSE), mean absolute percentage error (MAE) and Bayesian information criterion (BIC) was selected to generate forecasts from 6 September to 3 October 2021. The best SARIMA model with a RMSE = 73.374, MAE = 39.716 and BIC = 8.656 showed a downward trend of COVID-19 cases during the forecast period, wherein the observed daily cases were within the forecast range. The majority (89%) of the difference between the forecasted and observed values was well within a deviation range of 25%. Based on this work, we conclude that SARIMA models developed in this paper using 593 data points and smoothened data and sensitive covariates can generate accurate forecast of COVID-19 case trends.
Associations between Heart Rate Variability and Brain Activity during a Working Memory Task: A Preliminary Electroencephalogram Study on Depression and Anxiety Disorder

Heart rate variability (HRV) has been suggested to reflect executive function and related neural activity. Executive dysfunction has been suggested to play an important role in the pathophysiology of emotional disorders. The purpose of this study was to investigate whether HRV showed a significant correlation with electroencephalogram (EEG) during a working memory performance in patients with depressive or anxiety disorder. A retrospective analysis was conducted with data from 61 patients with depressive disorder (43 women and 18 men) and 59 patients with anxiety disorder (35 women and 24 men). HRV was measured in the resting state, and EEG was recorded in the resting state and during the execution of a working memory task. It was performed in patients with depressive and anxiety disorder, and the paired sample t-test between resting state and task performance, as well as the partial correlation analysis between HRV and EEG, was conducted. Both depressed and anxious patients showed weaker beta relative power during the working memory task compared to the rest period. The resting-state EEG did not correlate with HRV parameters in both groups. In depressed patients, HRV showed a positive correlation with delta power during the task and a negative correlation with beta relative power during the task. In patients with anxiety disorder, HRV showed a significant positive correlation with theta power of the right frontal region during the task. Our results suggest that HRV would be related to executive-function-related neural activity in patients with depressive or anxiety disorder. Future studies with more subjects, including healthy controls, are needed to verify the correlation between HRV and EEG and to come up with a more comprehensive picture of neurobiological changes in emotional disorders.
Determination of failure zone of vane shear test using artificial transparent soil

The vane shear test method is used extensively in a variety of geotechnical exploration to determine the undrained shear strength fine grained clays and silts. A small scale physical model was developed to study the failure mechanism during the vane shear test. The soil was simulated using a mixture of amorphous silica and mineral oil, which becomes transparent when the refractive indices the oil and the silica are well matched. A special fabricated row cell equipped with vane shear device was developed to determine the strength of the transparent soil. One dimensional consolidation test was carried out to obtain the consolidation properties of the transparent soil. The laboratory vane shear test used is similar to the field vane shear test but is on smaller scale. The vane was mounted vertically at the centre of the rowe cell based which the vertical section aligned with the vane centerline was illuminated with laser light and sequence of digital image was recorded using a digital camera. Particle image velocimetry (PIV) was used to analyze the failure mechanism during vane shear test. The result obtained and the observation made in this study suggested that the failure zone was close to the conventional assumption of a uniform shear stress distribution at the vertical sides of the failure surface.
Self-heating and isothermal characterization of heterojunction bipolar transistors

Self-heating, the process by which power dissipation causes a rise in the operating temperature of the device, causes significant changes in the operation of bipolar transistors and can compromise the accuracy of device models if the operating environment of the device is not identical to the one in which it was characterized. As conventional methods utilized to construct device models are based in part upon measurements of device performance in which the static power dissipation results in an elevated device temperature, the extracted model contains information pertaining to the thermal environment in which it was characterized. This hidden temperature dependence is often ignored, and results in erroneous parameter extraction. Extending a technique developed by workers at Hewlett-Packard, a pulsed bias measurement system has been developed which addresses the need for temperature-independent device characterization. This system can be used to measure the isothermal collector characteristics at constant base-emitter voltage, and the isothermal Gummel plot of collector current. The resulting data can be used to extend the region of model validity by de-embedding the thermal effects from the inherent isothermal electrical response of the device. The system can also be used to determine the values of the thermal resistance and capacitance, macroscopic
Transplantation of Olfactory Ensheathing Cells: Properties and Therapeutic Effects after Transplantation into the Lesioned Nervous System

The primary olfactory system (POS) is in permanent renewal, especially the primary olfactory neurons (PON) are renewed with a turnover of around four weeks, even in adulthood. The re-growth of these axons is helped by a specific population of glial cells: the olfactory ensheathing cells (OECs). In the POS, OECs constitute an “open-channel” in which the axons of PON cause regrowth from peripheral nervous system (PNS) to central nervous system (CNS). The remarkable role played by OECs into the POS has led scientists to investigate their properties and potential beneficial effects after transplantation in different lesion models of the CNS and PNS. In this review, we will resume and discuss more than thirty years of research regarding OEC studies. Indeed, after discussing the embryonic origins of OECs, we will describe the in vitro and in vivo properties exert at physiological state by these cells. Thereafter, we will present and talk over the effects of the transplantation of OECs after spinal cord injury, peripheral injury and other CNS injury models such as demyelinating diseases or traumatic brain injury. Finally, the mechanisms exerted by OECs in these different CNS and PNS lesion paradigms will be stated and we will conclude by presenting the innovations and future directions which can be considered to improve OECs properties and allow us to envisage their use in the near future in clinical applications.
Metrological Characterization of a High-Temperature Hybrid Sensor Using Thermal Radiation and Calibrated Sapphire Fiber Bragg Grating for Process Monitoring in Harsh Environments

Fiber Bragg gratings inscribed in single crystalline multimode sapphire fibers (S-FBG) are suitable for monitoring applications in harsh environments up to 1900 °C. Despite many approaches to optimize the S-FBG sensor, a metrological investigation of the achievable temperature uncertainties is still missing. In this paper, we developed a hybrid optical temperature sensor using S-FBG and thermal radiation signals. In addition, the sensor also includes a thermocouple for reference and process control during a field test. We analyzed the influence of the thermal gradient and hotspot position along the sensor for all three detection methods using an industrial draw tower and fixed point cells. Moreover, the signal processing of the reflected S-FBG spectrum was investigated and enhanced to determine the reachable measurement repeatability and uncertainty. For that purpose, we developed an analytical expression for the long-wavelength edge of the peak. Our findings show a higher stability against mechanical-caused mode variations for this method to measure the wavelength shift compared to established methods. Additionally, our approach offers a high robustness against aging effects caused by high-temperature processes (above 1700 °C) or harsh environments. Using temperature-fixed points, directly traceable to the International System of Units, we calibrated the S-FBG and thermocouple of the hybrid sensor, including the corresponding uncertainty budgets. Within the scope of an over 3-weeks-long field trial, 25 production cycles of an industrial silicon manufacturing process with temperatures up to 1600 °C were monitored with over 100,000 single measurements. The absolute calibrated thermocouple (Uk=2≈1K…4K) and S-FBG (Uk=2≈10K…14K) measurements agreed within their combined uncertainty. We also discuss possible strategies to significantly reduce the uncertainty of the S-FBG calibration. A follow-up measurement of the sensor after the long-term operation at high temperatures and the transport of the measuring system together with the sensor resulted in a change of less than 0.5 K. Thus, both the presented hybrid sensor and the measuring principle are very robust for applications in harsh environments.
Intralesional Infiltrations of Arteriosclerotic Tissue Cells-Free Filtrate Reproduce Vascular Pathology in Healthy Recipient Rats

Lower-extremity arterial disease is a major health problem with increasing prevalence, often leading to non-traumatic amputation, disability and mortality. The molecular mechanisms underpinning abnormal vascular wall remodeling are not fully understood. We hypothesized on the existence of a vascular tissue memory that may be transmitted through soluble signaling messengers, transferred from humans to healthy recipient animals, and consequently drive the recapitulation of arterial wall thickening and other vascular pathologies. We examined the effects of the intralesional infiltration for 6 days of arteriosclerotic popliteal artery-derived homogenates (100 µg of protein) into rats’ full-thickness wounds granulation tissue. Animals infiltrated with normal saline solution or healthy brachial arterial tissue homogenate obtained from traumatic amputation served as controls. The significant thickening of arteriolar walls was the constant outcome in two independent experiments for animals receiving arteriosclerotic tissue homogenates. This material induced other vascular morphological changes including an endothelial cell phenotypic reprogramming that mirrored the donor’s vascular histopathology. The immunohistochemical expression pattern of relevant vascular markers appeared to match between the human tissue and the corresponding recipient rats. These changes occurred within days of administration, and with no cross-species limitation. The identification of these “vascular disease drivers” may pave novel research avenues for atherosclerosis pathobiology.
Pseudomonas protegens FJKB0103 Isolated from Rhizosphere Exhibits Anti-Methicillin-Resistant Staphylococcus aureus Activity

Staphylococcus aureus is amongst the most virulent pathogens, causing chronic and life-threatening human infections. Methicillin-resistant S. aureus (MRSA) are multidrug-resistant strains, and the ability of forming a biofilm reduces their sensitivity to antibiotics. Thus, the alternative compounds inhibiting both resistant strains and biofilm formation are in high demand. In our study, the strain FJKB0103 was isolated from the rhizosphere of Garcinia mangostana, showing strong anti-MRSA activity. We performed molecular phylogenic analysis, analyzed average nucleotide identity (ANI), in silico DNA-DNA hybridization (isDDH), and biochemical characteristics to identify strain FJKB0103 as Pseudomonas protegens. Herein, the genome of strain FJKB0103 was sequenced and subjected to antiSMASH platform, mutational, and functional analyses. The FJKB0103 draft genome was 6,776,967 bp with a 63.4% G + C content, and 16 potential secondary compound biosynthetic clusters in P. protegens FJKB0103 were predicted. The deletion mutant and complementary analysis suggested that DAPG was the anti-MRSA compound. Further tests showed that MRSA strains were sensitive to DAPG, and the lysis of bacterial cells was observed at a high concentration of DAPG. Additionally, DAPG inhibited the biofilm formation of MRSA at subinhibitory concentration. These results suggested that DAPG might be a good alternative treatment to control infections caused by MRSA.
Aligning Learning Incentives (ALI)

Mexican students score low in international learning assessments, particularly in math. To help remedy this situation, the Inter-American Development Bank is supporting a pilot study to identify to what extent performance based incentives for students, teachers and principals in upper-secondary schools can improve students? mathematical skills, as measured by their scores in curriculum-based mathematics tests.
Topology Inference and Link Parameter Estimation Based on End-to-End Measurements

This paper focuses on the design, implementation, experimental validation, and evaluation of a network tomography approach for performing inferential monitoring based on indirect measurements. In particular, we address the problems of inferring the routing tree topology (both logical and physical) and estimating the links’ loss rate and jitter based on multicast end-to-end measurements from a source node to a set of destination nodes using an agglomerative clustering algorithm. The experimentally-driven evaluation of the proposed algorithm, particularly the impact of the employed reduction update scheme, takes place in real topologies constructed in an open large-scale testbed. Finally, we implement and present a motivating practical application of the proposed algorithm that combines monitoring with change point analysis to realize performance anomaly detection.
Molecular Characterization of Bovine Leukemia Virus with the Evidence of a New Genotype Circulating in Cattle from Kazakhstan

Bovine leukemia virus (BLV) is a retrovirus that causes enzootic bovine leukosis (EBL) and has worldwide distribution. Infections with BLV have been reported in cattle from Kazakhstan but the virus has not yet been thoroughly characterized. In this study, we detect and estimate the level of BLV proviral DNA by qPCR in DNA samples from 119 cattle naturally infected with BLV, from 18 farms located in four different geographical regions of Kazakhstan. Furthermore, we conducted the phylogenetic and molecular analysis of 41 BLV env-gp51 gene sequences from BLV infected cattle. Phylogenetic analysis showed the affiliation of sequences to two already known genotypes G4 and G7 and also to a new genotype, classified as genotype G12. In addition, a multivariate method was employed for analysis of the association between proviral load and different variables such as the geographical location of the herd, cattle breeds, age of animals, and the presence of particular BLV genotypes. In summary, the results of this study provide the first evidence on molecular characterization of BLV circulating in cattle from Kazakhstan.