Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Distribution Alignment With Dual-Subspace Mapping for Cross-Subject Driver Mental State Detection

For the detection of electroencephalogram-based driving mental states, it is important to utilize transfer learning to overcome individual and period differences. However, there are two challenges in existing unsupervised domain adaptation methods: 1) they ignore the geometric divergence of the source and target domains with single subspace mapping and 2) they usually employ a fixed weight distribution to align the marginal and conditional probability distributions. In this article, we propose a dynamic distribution alignment with dual-subspace mapping (DDADSM) method for cross-subject driver mental state detection. Initially, DDADSM explores two optimally aligned subspaces for the source and target domains, which can significantly reduce the geometric shifting. Subsequently, the dynamic probability distribution alignment method is introduced to acquire the adaptive weight between the marginal and conditional distributions, which adapts to domains with wide variations. Through our experiments based on the driving mental state detection task, DDADSM demonstrated superior performance compared with state-of-the-art models.
Controlling Protein Enrichment in Lipid Sponge Phase Droplets using SNAP‐Tag Bioconjugation

All cells use organized lipid compartments to facilitate specific biological functions. Membrane‐bound organelles create defined spatial environments that favor unique chemical reactions while isolating incompatible biological processes. Despite the fundamental role of cellular organelles, there is a scarcity of methods for preparing functional artificial lipid‐based compartments. Here, we demonstrate a robust bioconjugation system for sequestering proteins into zwitterionic lipid sponge phase droplets. Incorporation of benzylguanine (BG)‐modified phospholipids that form stable covalent linkages with an O6‐methylguanine DNA methyltransferase (SNAP‐tag) fusion protein enables programmable control of protein capture. We show that this methodology can be used to anchor hydrophilic proteins at the lipid‐aqueous interface, concentrating them within an accessible but protected chemical environment. SNAP‐tag technology enables the integration of proteins that regulate complex biological functions in lipid sponge phase droplets, and should facilitate the development of advanced lipid‐based artificial organelles.
A Two Dimension Signal Parameter Estimation Method Based on Super Resolution Technology

The 2D spectrum estimation based on uniform linear array is studied in this paper. MUSIC method is firstly introduced into array signal processing to realize the frequency and angle joint estimation. And the modified MUSIC method is then applied for two dim array signal processing to fulfill joint parameters estimation of coherent signal sources. Simulation results show the validity of the proposed method. Keywords: Super resolution;Array signal processing;Parameter estimation;MUSIC algorithm
The Glycosyltransferases sdgA and sdgB Expression in Staphylococcus Epidermidis Depends On The Conditions of Biofilm Formation.

The Staphylococcus aureus’ SdrG protein is glycosylated by SdgA and SdgB for their protection against its degradation by the neutrophil’s cathepsin G. So far, there is not information about the role of Staphylococcus epidermidis’ SdgA nor SdgB in the production of biofilm, therefore the main of this work was to determine the distribution and expression of sdrG, sdgA and sdgB genes in S. epidermidis in conditions of biofilm. The frequency of the genes sdrG, sdgA and sdgB were evaluated by PCR in a collection of 75 isolates. The isolates were grown in dynamic conditions (in agitation) or static conditions (biofilm productor: planktonic or sessile cells). The expression of sdrG, sdgA and sdgB were determined by RT-qPCR in cells grown under dynamic conditions (CGDC), as well as planktonic and sessile cells, and in cells adhered to a catheter (in vivo). The genes sdrG and sdgB were detected in 100% of isolates, meanwhile the gene sdgA was detected in 71% of the samples (p<0.001). The CGDC did not expressed the sdrG, sdgA and sdgB mRNAs. The planktonic and sessile cells expressed sdrG and sdgB, and the same was seen in cells adhered to the catheter. In particular, one isolate, able to induce biofilm under cathepsin G treatment, expressed sdrG and sdgB in planktonic, sessile and in cells adhered to the catheter. This suggests that the state of cells adherence is an important factor for the transcription of sdgA, sdgB and sdrG.
Measuring Service Gaps

The integration of transit needs into transit accessibility indexing is important for evaluating existing transportation systems and service gaps and for identifying priority areas for investments in transportation infrastructure. This study detailed an indexing model for accessibility of transit need and focused on the necessity of evaluating transit needs and transit accessibility simultaneously. A need index was developed to identify areas in high need of public transit services from economic and sociodemographic information, and a composite accessibility index was developed to identify levels of access to transit services and shortcomings in providing service. The need for transit service was then modeled as the lack of transit accessibility, and the model correlated different access indicators with their ability to predict transit service need. This model mapped areas with different levels of transit accessibility and transit needs by using a single score, which may be easily interpreted by planners who examine transit equity. The model was applied to the city of Meriden, Connecticut, and results were compared with a general approach for consistency and effectiveness. The usefulness of the model was also highlighted through a representative example of the model's application.
Who worked from home in Brazil? Inequalities highlighted by the pandemic

There is some consensus that the pandemic can widen pre-existing inequalities in the labor market and that an essential issue concerns the unequal possibilities of working remotely. This study analyzes inequalities in remote work in Brazil through descriptive analyzes and Probit regressions using PNAD COVID-19 microdata. We have found that workers with the least possibilities for remote work were the poorest, males, rural residents, non-whites, youngest, without college education, self-employed or wage workers from the private sector and agriculture workers. An important part of that stems from differences in selection into occupations;however, some variables maintained important independent effects, especially the college education and the labor income. The pandemic, regarding the possibility of remote work, had the effect of widening the existing inequalities, favoring the wealthier, more educated, and more formalized workers and imposing on the others the need to choose between employment and income versus risk of contagion. © 2022, Lundiana. All rights reserved.
Long-term culture expanded alveolar macrophages restore full epigenetic identity in vivo

Alveolar macrophages (AM) are tissue resident macrophages of the lung that can be expanded in culture, but it is unknown to what extent culture affects their in vivo identity. Here we show that long-term ex vivo expanded mouse AM (exAM) maintain core AM gene expression but show culture adaptations related to adhesion, metabolism and proliferation. Strikingly, even after several months in culture exAM reacquired full transcriptional and epigenetic identity upon transplantation into the lung and could self-maintain in the natural niche long-term. Changes in open chromatin regions (OCR) observed in culture were fully reversible in transplanted exAM (texAM) and resulted in a gene expression profile indistinguishable from resident AM. Our results demonstrate that long-term proliferation of AM in culture does not compromise cellular identity in vivo. The demonstrated robustness of exAM identity provides new opportunities for mechanistic analysis and highlights the therapeutic potential of ex vivo expanded macrophages.
The Development of the Cast Iron Frame in Textile Mills to 1850

AbstractThis contribution begins with a review of previous work on the use of structural cast iron in textile mills. The author's extensive site survey work is then utilised to provide additional information on structural detail. Finally, the diffusion of cast iron in textile mill construction is examined and some comments made on the rationalisation of design which accompanied the growing use of the material.
Proteomic Analysis of Exosomes Secreted from Human Alpha-1 Antitrypsin Overexpressing Mesenchymal Stromal Cells

Simple Summary The overexpression of human alpha-1 antitrypsin (hAAT) in mesenchymal stromal cells (MSCs) improved their intrinsic properties with enhanced protective effects in previous murine models of type 1 diabetes. This study compared the protein profiles of extracellular vesicles (EVs) from bone marrow-derived control or hAAT-MSCs. EVs from both cell types share common features in size and exosome marker expression. By comparing common proteins in EVs from three donor cell lines using Gene Ontology (GO) analysis, we found that common EV proteins from all donors are important to cell adhesion and extracellular matrix organization. Differentially expressed proteins from hAAT-MSCs and MSCs are involved in cytokine signaling of the immune system, stem cell differentiation, and carbohydrate metabolism. This study shows that hAAT-MSCs have different profiles of paracrine effector exosomal proteins compared to control MSCs. Abstract Extracellular vesicles (EVs) mediate many therapeutic effects of stem cells during cellular therapies. Bone marrow-derived mesenchymal stromal cells (BM-MSCs) were manufactured to overexpress the human antiprotease alpha-1 antitrypsin (hAAT) and studied to compare the EV production compared to lentivirus treated control MSCs. The goal of this study was to compare protein profiles in the EVs/exosomes of control and hAAT-MSCs using unbiased, high resolution liquid chromatography and mass spectrometry to explore differences. Nanoparticle tracking analysis (NTA) showed that the particle size of the EVs from control MSCs or hAAT-MSCs ranged from 30 to 200 nm. Both MSCs and hAAT-MSCs expressed exosome-associated proteins, including CD63, CD81, and CD9. hAAT-MSCs also expressed high levels of hAAT. We next performed proteomic analysis of EVs from three healthy donor cell lines. Exosomes collected from cell supernatant were classified by GO analysis which showed proteins important to cell adhesion and extracellular matrix organization. However, there were differences between exosomes from control MSCs and hAAT-MSCs in cytokine signaling of the immune system, stem cell differentiation, and carbohydrate metabolism (p < 0.05). These results show that hAAT-MSC exosomes contain a different profile of paracrine effectors with altered immune function, impacts on MSC stemness, differentiation, and prevention of cell apoptosis and survival that could contribute to improved therapeutic functions.
Preparation of multiple-reactive-site and flexible crosslinking agent with transaconitic acid and acrylic acid and its application for three-dimensional crosslinking of cellulose

A novel multiple-reactive-site crosslinking agent, P(TAA‒AA), was developed from transaconitic acid and acrylic acid in this study. Cotton fabrics with durable wrinkle-resistant properties were obtained by crosslinking with P(TAA‒AA), which benefited from the multifunctional carboxyl groups of crosslinking agents and the three-dimensional crosslinking inside cotton fibers. The wrinkle-resistant properties of P(TAA‒AA)-modified fabrics were evaluated and compared with those of other polycarboxylic acid-treated fabrics, and the P(TAA‒AA)-modified fabrics showed a wrinkle recovery angle of 262° as high as the 1,2,3,4-butanetetracarboxylic acid-modified fabrics while maintaining nearly two-fold higher tearing strength retention (62.9%), and they showed a much higher value of whiteness index than the citric acid-modified fabrics. This demonstrated that the obtained P(TAA‒AA) is an ideal polycarboxylic acid already known to date simultaneously to realize the high wrinkle recovery angle and high tearing strength retention for treated cotton fabrics. The Raman depth mapping images and the scanning electron microscope images of P(TAA‒AA)-modified samples indicated that P(TAA‒AA) molecules can diffuse into the amorphous regions of the cellulose fibers and form crosslinking bridges between cellulose chains. The multiple reactive carboxyl groups in P(TAA‒AA) may form three or more ester bonds between the P(TAA‒AA) molecule and different cellulose chains, which were regarded as the main contribution to the high crosslinking effectiveness of the P(TAA‒AA)-modified fabrics.
Fully three-dimensional vehicle dynamics over rough pavement

Simplified vehicle models are usually employed when studying the dynamic effects of road traffic: quarter-car, one-dimensional vertical and two-dimensional longitudinal models are the most common. Furthermore, when complete three-dimensional vehicles are modelled, the differences between the road roughness under the four wheels at each time instant that arise from the time lag between front and rear tyres and from the difference between the profiles under left and right tyres are frequently neglected. The influence of employing simplified models and neglecting those differences has been analysed by means of a three-dimensional truck model. If simple models are utilized or differences between the four wheels are not considered, accelerations in the vehicle body are overestimated, which may lead to an incorrect evaluation of the passengers' comfort. It has also been found that the vertical dynamic load applied by a tyre to the pavement depends not only on the profile under that wheel but also on the profile.
Deteksi Serangan Spoofing Wajah Menggunakan Convolutional Neural Network

Facial recognition-based biometric authentication is increasingly frequently employed. However, a facial recognition system should not only recognize an individual's face, but it should also be capable of detecting spoofing attempts using printed faces or digital photographs. There are now various methods for detecting spoofing, including blinking, lip movement, and head tilt detection. However, this approach has limitations when dealing with dynamic video spoofing assaults. On the other hand, these types of motion detection systems can diminish user comfort. As a result, this article presents a method for identifying facial spoofing attacks through Convolutional Neural Networks. The anti-spoofing technique is intended to be used in conjunction with deep learning models without using extra tools or equipment. Our CNN classification dataset can be derived from the NUAA photo imposter and CASIA v2. The collection contains numerous examples of facial spoofing, including those created with posters, masks, and smartphones. In the pre-processing stage, image augmentation is carried out with brightness adjustments and other filters so that the model to adapt to various environmental conditions. We evaluate the number of epochs, optimizer types, and the learning rate during the testing process. The test results show that the proposed model achieves an accuracy value of 91.23% and an F1 score of 92.01%.
ADAPTING WORD ORDER TRANSFORMATION FOR VIETNAMESE DEPENDENCY PARSING

: Dependency parsing, which is the task of automatically doing syntactic analysis and defining the binary dependencies between words in a sentence, has gained much attention from researchers in recent years. Besides that, to build effective and robust dependency parsers, we also need a large number of annotated treebanks to train the models. However, constructing such treebanks is complicated and requires considerable human effort. There are only a few languages (e.g., English, Chinese) that have succeeded in constructing treebanks and gain significant results in their dependency parsing and related tasks (e.g., machine translation). For Vietnamese, the treebanks resources are still very small, and it leads to the limit of the accuracy of the parsers. In this paper, we take advantage of available large-scale treebanks from English to tackle this problem in Vietnamese. Subsequently, we use English treebanks as additional resources to give more information supporting Vietnamese dependency parsing. However, the syntactic gap between two languages and the mismatch tagset between two datasets are obstacles in the efforts to enhance the efficiency and effectiveness of the parsers. In taking into account this problem, we narrow down these gaps by reordering the positions of the words in English sentences and modifying the dependency tree structure. We also enrich the Vietnamese dataset by automatically annotating the POS with CoNLL-U format and perform experiments by using this syntactically annotated corpora. Consequently, our parser gives a promising result, achieving high improvement
Development of Cad Software for Wheel Chair Design

Anthropometric data of Nigerian paraplegics was used to design wheel chair for the paraplegics. This was done by developing suitable software using Visual Basic, AutoCAD, Access and Corel- Draw programs. The software developed is capable of designing an ergonomically viable wheelchair for any category of paraplegic using their anthropometric data within 2 minutes. Keywords : CAD, Wheelchair, Paraplegics and Design Journal of Science & Technology (Ghana) Vol. 28 (3) 2008: pp. 82-93
Geotemporal analysis and topic modelling of Twitter data: study in nine big city areas of Indonesia

Nowadays, Twitter data is significant to many studies since there is a shift in the data collection paradigm. As one of the contemporary social media with many active users, Twitter provides geotagging facilities to create a geotagged Tweet. Various spatial based studies use geotagged Tweet data. This paper aims to review the geo-temporal characteristics of geotagged Twitter data in nine major cities in Indonesia, namely five cities in the Greater Area of Jakarta, Surabaya, Bandung, Medan, and Makassar. Twitter data was collected by the streaming method for two years (January 2019- December 2020). The temporal analysis was carried out by graphing the number of Tweets with 30-minute intervals. Weekly Twitter activities were also visualized to get a specific understanding of when the optimum time to post a Tweet was. Density analysis was employed to Twitter data to find out the spatial patterns in the study area. Kernel Density Estimation (KDE) was used to determine the Tweets Density in the day and night. This study also used a simple framework of text analysis of topic modelling using Latent Semantic Indexing (LSI) to use the Twitter data better. Overall, Central Jakarta and South Jakarta have a significant number of Tweets compared to other cities. The study results show that, in general, big cities in Indonesia have almost the same temporal curve and the peak time for making geotagged tweets occurs from 4 pm to 8 pm. Our finding also points out that a high number of the population in a city does not always produce a high number of Tweets. The results of topic modelling in the Greater Area of Jakarta show that the themes of traffic jams/congestion, entertainment, and culinary tourism are widely mentioned by Twitter users, thus opening opportunities for research on these subjects.
Development, Testing and Validation of a Waste Assay System for the Measurement and Characterisation of Active Spent Fuel Element Debris From UK Magnox Reactors - 12533

This paper describes the development, testing and validation of a waste measurement instrument for characterising active remote handled radioactive waste arising from the operation of Magnox reactors in the United Kingdom. Following operation in UK Magnox gas cooled reactors and a subsequent period of cooling, parts of the magnesiumaluminium alloy cladding were removed from spent fuel and the uranium fuel rods with the remaining cladding were removed to Sellafield for treatment. The resultant Magnox based spent fuel element debris (FED), which constitutes active intermediate level waste (ILW) has been stored in concrete vaults at the reactor sites. As part of the decommissioning of the FED vaults the FED must be removed, measured and characterised and placed in intermediate storage containers. The present system was developed for use at the Trawsfynydd nuclear power station (NPS), which is in the decommissionning phase, but the approach is potentially applicable to FED characterisation at all of the Magnox reactors. The measurement system consists of a heavily shielded and collimated high purity Germanium (HPGe) detector with electromechanical cooling and a high count-rate preamplifier and digital multichannel pulse height analyser. The HPGe based detector system is controlled by a software code, which stores the measurement result and allows a comprehensive analysis of the measured FED data. Fuel element debris is removed from the vault and placed on a tray to a uniform depth of typically 10 cm for measurement. The tray is positioned approximately 1.2 meters above the detector which views the FED through a tungsten collimator with an inverted pyramid shape. At other Magnox sites the positions may be reversed with the shielded and collimated HPGe detector located above the tray on which the FED is measured. A comprehensive Monte Carlo modelling and analysis of the measurement process has been performed in order to optimise the measurement geometry and eliminate interferences from radioactive sources and FED in the immediate vicinity of the measurement position. The detector system has been calibrated and high activity radioactive sources of Cs-137, Co-60 and Na-22 have been used to validate the measurement process. The data acquisition and analysis software code has been tested and validated in keeping with the software quality assurance requirements of both ISO:9001-2008 – TICK-IT in the UK and NQA-1. The measurement and analysis system has been comprehensively tested with high activity sources, is flexible and may be applicable to a wide range of remote handled radioactive waste measurement applications. It is due to be installed at Trawsfynydd NPS later this year.
Using Position‐Based Dynamics for Simulating Mitral Valve Closure and Repair Procedures

To achieve the best treatment of mitral valve disease in a patient, surgeons aim to optimally combine complementary surgical techniques. Image‐based in silico simulation as well as visualization of the mitral valve dynamics can support the visual analysis of the patient‐specific valvular dynamics and enable an exploration of different therapy options. The usage in a time‐constrained clinical environment requires a mitral valve model that is cost‐effective, easy to set up, parameterize and evaluate. Working towards this goal, we develop a simplified model of the mitral valve and analyse its applicability for the sketched use‐case. We propose a novel approach to simulate the mitral valve with position‐based dynamics. The resulting mitral valve model can be deformed to simulate the closing and opening, and incorporate changes caused by virtual interventions in the simulation. Ten mitral valves were reconstructed from transesophageal echocardiogram sequences of patients with normal and abnormal physiology for evaluation. Simulation results showed good agreements with expert annotations of the original image data and reproduced valve closure in all cases. In four of five pathological cases, abnormal closing behaviour was correctly reproduced. In future research, we aim to improve the parameterization of the model in terms of biomechanical correctness and perform a more extensive validation.