Miracle-dz/UniFAR-FTUs huggingface dataset:
Force-Bioreactor for Assessing Pharmacological Therapies for Mechanobiological Targets

Tissue fibrosis is a major health issue that impacts millions of people and is costly to treat. However, few effective anti-fibrotic treatments are available. Due to their central role in fibrotic tissue deposition, fibroblasts and myofibroblasts are the target of many therapeutic strategies centered primarily on either inducing apoptosis or blocking mechanical or biochemical stimulation that leads to excessive collagen production. Part of the development of these drugs for clinical use involves in vitro prescreening. 2D screens, however, are not ideal for discovering mechanobiologically significant compounds that impact functions like force generation and other cell activities related to tissue remodeling that are highly dependent on the conditions of the microenvironment. Thus, higher fidelity models are needed to better simulate in vivo conditions and relate drug activity to quantifiable functional outcomes. To provide guidance on effective drug dosing strategies for mechanoresponsive drugs, we describe a custom force-bioreactor that uses a fibroblast-seeded fibrin gels as a relatively simple mimic of the provisional matrix of a healing wound. As cells generate traction forces, the volume of the gel reduces, and a calibrated and embedded Nitinol wire deflects in proportion to the generated forces over the course of 6 days while overhead images of the gel are acquired hourly. This system is a useful in vitro tool for quantifying myofibroblast dose-dependent responses to candidate biomolecules, such as blebbistatin. Administration of 50 μM blebbistatin reliably reduced fibroblast force generation approximately 40% and lasted at least 40 h, which in turn resulted in qualitatively less collagen production as determined via fluorescent labeling of collagen.
A Simple Conceptual Model for the Self‐Sustained Multidecadal AMOC Variability

Multidecadal variability of Atlantic Meridional Overturning Circulation (AMOC) has been reconstructed by various proxies, simulated in climate models, and linked to multidecadal Arctic salinity variability. Here we construct a simple conceptual model to understand the two‐way interactions of the Arctic with multidecadal AMOC variability through a delayed oscillator mechanism. We revise Stommel's Two‐Box Model by including an advective time delay for the Arctic density/salinity anomalies to reach the subpolar North Atlantic and a coupled negative feedback between the AMOC and the freshwater flux entering the Arctic through atmosphere and/or sea ice responses. Self‐sustained multidecadal AMOC oscillations exist in the revised Stommel's Two‐Box model if the oceanic advective time delay is longer than the oscillation threshold, and the periods of the AMOC delayed oscillator depend crucially on this advective time delay. The coupled freshwater feedback provides additional delayed negative feedback and reduces the advective time delay threshold required for the oscillations.
Communications Signal Processing Using RISC-V Vector Extension

Flexible and scalable solutions will be needed for future communications processing systems. RISC-V processors enhanced with vector processing capabilities as specified by the soon-to-be ratified RISC-V vector extension (RVV) pose an interesting base for such systems. Vector processors provide an efficient means of exploiting data-level parallelism, which is heavily present in communications kernels. Furthermore, RVV code is by its design agnostic from the underlying hardware platform which enables scalability. On the exemplary basis of a generalized frequency division multiplexing (GFDM) implementation on a RVV processor, we investigate its baseband processing capabilities and guide through RVV's key features and peculiarities. Our vectorization achieves a speedup of up to 60 times compared to the scalar base case and a throughput of 784 symbols per second. The utilization of 77 % is slightly below more specialized solutions. Nevertheless, this work serves as a baseline for further investigations on flexible and scalable RISC-V vector communications processors.
Determination of multidrug-resistant populations and molecular characterization of complex Klebsiella spp. in wild animals by multilocus sequence typing

Background and Aim: One of the most significant public health concerns is multidrug-resistant (MDR) microorganisms. Klebsiella spp. have been at the forefront of causing different types of infections such as bacteremia, urinary tract infections, pneumonia, enteritis, and sepsis in humans as well as animals. This study aimed to determine the genomic similarity between Klebsiella spp. isolated from wild animal samples and those described in the Institut Pasteur genomic database to verify the spread of resistant clones regionally in the state of Mato Grosso, and to compare the epidemiological data in different regions of Brazil and the world. Materials and Methods: Isolates from various sites of injury in wild animals were identified by sequencing the 16S rRNA gene. Antimicrobial susceptibility testing was performed using the disk diffusion method to verify the resistance profile, and then, multilocus sequence typing was performed to verify the population structure and compare the isolates from other regions of Brazil and the world. Results: Twenty-three sequence types (STs) were observed; of these, 11 were new STs, as new alleles were detected. There was no predominant ST among the isolates. All isolates were MDR, with high rates of resistance to sulfonamides, ampicillin, amoxicillin, and nitrofurantoin and low resistance to meropenem, imipenem, and amikacin. Conclusion: Improving our understanding of the population structure of Klebsiella spp. in wild animals may help determine the source of infection during outbreaks in humans or animals, as the One Health concept emphasizes the interlinks between humans, animals, and environmental health.
Prevalence and antimicrobial susceptibility of Salmonella isolates from apparently healthy slaughtered goats at Dire Dawa municipal abattoir, Eastern Ethiopia

A cross-sectional study was conducted from January to April 2014 on 249 apparently healthy slaughtered goats at the municipal abattoir of Dire Dawa to estimate the prevalence Salmonella spp. and determine the antimicrobial susceptibility pattern of the isolates. A total of 249 goat carcass swab samples were collected using a systematic random sampling technique and examined for the presence of Salmonella spp. Out of the total of 249 carcass swab samples, 44 (17.7%) were positive for Salmonella. Of all the isolates, 41 (93.2%) were multiply antimicrobial resistant and the highest level of resistance was observed for tetracycline (100%), nitrofurans (100%), streptomycin (81.8%) and kanamycin (79.5%). However, all isolates were susceptible to ciprofloxacin. The present study shows high prevalence of Salmonella spp. contamination of goat meat and resistance of the pathogen to most antimicrobials except ciprofloxacin. Authors recommended the use of standardized procedures and applications in handling of goat meat in the abattoir and rational use of antimicrobials particularly ciprofloxacin. Furthermore studies should be conducted to identify the potential source of contamination and identification of genes responsible for antimicrobial resistance. Key words: Abattoir, antimicrobial sensitivity, goat meat, prevalence, Salmonella.
Morphological and Physiological Indicators for Screening Cell Lines with High Potential for Somatic Embryo Maturation at an Early Stage of Somatic Embryogenesis in Pinus Koraiensis

Many cell lines in the embryogenic callus cannot produce somatic embryos (SEs) even if they meet the optimal SE maturation culture conditions during conifer somatic embryogenesis. This phenomenon hinders the progress of the industrial-scale reproduction of conifers. Therefore, there is an urgent need to obtain morphological and physiological markers to screen embryogenic calli in response to SE maturation conditions. To detect cell lines with high somatic embryogenesis potential during the proliferation process, we counted the number of pro-embryos and early SEs (ESEs) in different cell lines and storage substances, endogenous hormones, and polyamine contents. The results showed that the yield of P. koraiensis SEs was heavily dependent on genotype (p = 0.001). There were high levels of PE III (pro-embryo III) number, ESE number, and soluble protein content, in the response cell lines (R cell lines), which were 1.6-, 3-, and 1.1-fold those of the obstructive cell lines (B cell lines), respectively. The B cell line had high levels of starch, auxin (IAA), Put, Spd, and putrescine: spermine (Put: Spm) compared to the R cell line. In addition, the numbers of PE III, ESEs, and soluble protein content were significantly positively correlated with SE yield. In contrast, the contents of starch, abscisic acid (ABA), Put, Spm, and Spd were significantly negatively correlated with SE yield. To ensure the accuracy of the results, we used nine cell lines to test the results. The PE III and ESE numbers and the Spm and Spd contents were positively correlated with SE yield, while the levels of starch, ABA, IAA, Put: Spd, and Put: Spm were negatively correlated with SE yield. Thus, we recommend using high PE III and ESEs as morphological indicators and low levels of starch, IAA, ABA, and Put: Spm as physiological markers to screen cell lines with a high somatic embryogenesis potential. In addition, we also found that the relationship between Spd, Spm, and SE yield was opposite in the two experimental results. Therefore, we speculate that the differences in Spd and Spm content are mainly affected by genotype. In conclusion, this study obtained the morphological and physiological markers of some high-somatic embryogenic cell lines by comparing the differences between nine somatic embryogenic cell lines. Our results can guide the improvement of conifer somatic embryogenesis technology and can provide a theoretical basis for accelerating the application of biotechnology in large-scale artificial breeding.
Measuring the control of landscape modifications on surface temperature in India

Abstract This study highlights the land use/land cover change, and its implications on the long-term changes in various hydrometeorological parameters in India during 2001–2018. The study exhibited a decrease in grassland (15.1%), barren land (10.2%), and shrubland (9.5%) in contrast to an increase in deciduous broadleaf forest cover (27.4%) and croplands (25.2%) in India. The study exhibited 31.7% of the geographical area observed a low warming (<0.8 °C), in contrast to 52.1% of the area observed a low cooling (> −0.8 °C) in India over the observation period. The transformation of (a) barren land to shrubland and cropland (Western India) and (b) cropland, and grassland to forest cover (Central India) led to the cooling effects. While Indo-Gangetic Plain and North-Eastern parts observed warming effects due to greenness and wetness change. The findings highlight the relevance of bio-geophysical and land-climate feedback, which may help in developing integrated and effective climate mitigation and adaptation strategies.
Study On ECG Data Dependency For Atrial Fibrillation Detection Based On Residual Networks

Atrial fibrillation (AF) is an arrhythmia that can cause blood clot and may lead to stroke and heart failure. To detect AF, deep learning-based detection algorithms have recently been developed. However, deep learning models were often trained with limited datasets and were evaluated within the same datasets, which makes their performance generally drops on the external datasets, known as data dependency. For this study, three different databases from PhysioNet were used to investigate the data dependency of deep learning-based AF detection algorithm using the residual neural network (Resnet). Resnet 18, 34, 50 and 152 model were trained with raw electrocardiogram (ECG) signal extracted from independent database. The highest accuracy was about 98–99% which is evaluation results of test dataset from the own database. On the other hand, the lowest accuracy was about 53–92% which was evaluation results of the external dataset extracted from different source. There are data dependency according to the train dataset and the test dataset. However, the data dependency decreased as a large amount of train data.
Incidence of Leader–Member Exchange Quality, Communication Satisfaction, and Employee Work Engagement on Self-Evaluated Work Performance

Within the scope of the Theory of Demands and Labor Resources, the Healthy & Resilient Organizations (HERO) Model, and the Leader–Member Exchange (LMX) Theory, this research contrasts a mediation model in which evidence on the factors that affect work performance is integrated, thus establishing the direct and indirect relationships between LMX quality, communication satisfaction, employee work engagement, and self-rated work performance. A total of 488 workers participated in this research. Adequate goodness of fit was found in the model (χ2 = 3876.996, df = 3715, p = 0.031; χ2/df = 1.044; CFI = 0.999; TLI = 0.999; SRMR = 0.056; RMSEA = 0.010): the LMX–work performance relationship is mediated by communication satisfaction and work engagement, whereas the LMX–work engagement relationship is mediated by communication satisfaction. This has led to the conclusion that, as employees consider the relationship with their superiors to be of higher quality, the satisfaction they experience in terms of organizational communication increases, and as organizational communication satisfaction increases, the extent to which employees feel more vigorous, involved and concentrated, and absorbed by work also increases, which, in turn, leads them to perceive their work performance to be higher.
A Combined Model for Multivariate Time Series Forecasting Based on MLP-Feedforward Attention-LSTM

Multivariate time series forecasting has very great practical significance for a long time, and it has been attracting the attention of researchers from a diverse range of fields. However, it is difficult to analyze the relationship and transformation law among multivariate data. Further, it is hard to obtain a relatively accurate prediction. In recent years, long short-term memory (LSTM) has shown high capability in dealing with nonlinearity and long memory of time series data. Although LSTM can also process multivariate data, it is insufficient to pay various degrees of attention to multivariate data. To address this issue, a multivariate time series prediction model based on multilayer perceptron (MLP), feed-forward attention mechanism, and LSTM is proposed in this paper. Firstly, the simulation process utilizes the MLP module to map the multivariate initial sequences into another latent dimensional space, thereby obtaining easily captured mapping features. Then, these features are adaptively assigned attention weights through the feed-forward attention mechanism. Finally, the LSTM module uses these feature sequences with attention weights to make final predictions. The experimental results show that the method that combines the MLP layer with the feed-forward attention layer is effective in extracting multivariate features. Also, the empirical results indicate that our proposed framework (a combined model of MLP-Feedforward attention-LSTM) can achieve better performance than baselines.
An Authentication Mechanism for Remote Keyless Entry Systems in Cars to Prevent Replay and RollJam Attacks

Modern cars come with Keyless Entry Systems that can be either Remote Keyless Entry (RKE) systems or Passive Keyless Entry and Start (PKES) systems. In the initial versions of RKE implementation, fixed code was used by the key fob to unlock the car door. However, this method is vulnerable to replay attacks as an adversary may capture and replay the same code later to unlock the car. A rolling code system was introduced to protect RKE systems from such replay attacks. Studies have shown that even the rolling code system is vulnerable to certain attacks. In this work, we investigate the attacks possible on RKE systems and propose an efficient and effective authentication mechanism to defend RKE systems against such attacks with minimal changes to the existing RKE system. The proposed mechanism makes use of hashing and asymmetric cryptographic techniques for the secure transmission of signals from the key fob to the car that cannot be replayed. The security of the proposed mechanism is shown using informal security proof and simulation of the proposed solution is also provided.
Rational Design of Synergistic Structure Between Single-Atoms and Nanoparticles for CO2 Hydrogenation to Formate Under Ambient Conditions

Single-atom catalysts (SACs) as the new frontier in heterogeneous catalysis have attracted increasing attention. However, the rational design of SACs with high catalytic activities for specified reactions still remains challenging. Herein, we report the rational design of a Pd1-PdNPs synergistic structure on 2,6-pyridinedicarbonitrile-derived covalent triazine framework (CTF) as an efficient active site for CO2 hydrogenation to formate under ambient conditions. Compared with the catalysts mainly comprising Pd1 and PdNPs, this hybrid catalyst presented significantly improved catalytic activity. By regulating the ratio of Pd1 to PdNPs, we obtained the optimal catalytic activity with a formate formation rate of 3.66 molHCOOM·molPd −1·h−1 under ambient conditions (30°C, 0.1 MPa). Moreover, as a heterogeneous catalyst, this hybrid catalyst is easily recovered and exhibits about a 20% decrease in the catalytic activity after five cycles. These findings are significant in elucidating new rational design principles for CO2 hydrogenation catalysts with superior activity and may open up the possibilities of converting CO2 under ambient conditions.
Visual Aggregation of Spatial Recognition Scientific Computations in the Financial Service Sector Based on the Random Forest Graph Model

In view of the current problems in the visual aggregation of the financial service industry, the random forest graph model is applied to the spatial recognition of the financial service industry’s scientific calculation visual aggregation in this paper. Based on the detailed analysis of the characteristics of the financial service industry in the past, combined with the characteristics of finance, this method is used to construct a random forest graph model, which mainly optimizes parameters from different aspects such as model structure, data characteristics, and dynamic changes of the model to obtain optimal parameter values of the random forest graph model. Finally, through the analysis of the experimental results, it can be seen that, according to the spatial state of the financial service industry, the method proposed in this paper can be used for visual aggregation analysis. This method can effectively improve the timeliness of the scientific calculation of spatial recognition in the financial service industry.
Stabilization of Tuberculosis Reporter Enzyme Fluorescence (REFtb) Diagnostic Reagents for Use at the Point of Care

Tuberculosis is one of the most frequent causes of death in humans worldwide. One of the primary reasons tuberculosis remains a public health threat is that diagnosis can take weeks to months, is often not very sensitive and cannot be accomplished in many remote environments. A rapid, sensitive and inexpensive point-of-care (POC) diagnostic would have a major impact on tuberculosis eradication efforts. The tuberculosis diagnostic system REFtb is based on specific detection of the constitutively expressed β-lactamase (BlaC) in Mycobacterium tuberculosis using a custom fluorogenic substrate designated as CDG-3. REFtb has potential as a diagnostic for tuberculosis that could be very inexpensive (<USD 2.00/test), used at the POC and could provide definitive diagnosis within 10 min. However, the reagents for REFtb are currently in liquid form, making them more susceptible to degradation and difficult to transport. We evaluated the improvement in the stability of REFtb reagents by lyophilization under a variety of conditions through their effects on the performance of REFtb. We found that lyophilization of REFtb components produces an easily reconstituted powder that displays similar performance to the liquid system and that lactose represents one of the most promising excipients for use in a final POC REFtb diagnostic system. These studies provide the foundation for the production of a stable POC REFtb system that could be easily distributed worldwide with minimal or no requirement for refrigeration.
Academic Silver Linings in a Philippine State University Amid the Early Stages of Pandemic Cases

The primary role of the academe is knowledge building, however, due to the prevailing digital divide, some institutions of higher learning were not able to offer even Emergency Online Teaching (EOT) for continuous formal education during the early stages of the pandemic. This article highlights diversified ways that a state university from a developing country (Philippines) responded to the crisis to offer assistance towards the social development of the stakeholders amid the COVID-19 pandemic.
On the Performance of SIC-Free NOMA-VLC Based on Multiuser Superposition Transmission

As the linearly superposed category of multiuser superposition transmission (MUST), power-domain non-orthogonal multiple access (PD-NOMA) has been widely studied for visible light communication (VLC) systems. However, the utilization of successive interference cancellation (SIC) entails high complexity and latency. Error propagation (EP) caused by imperfect SIC would also degrade the system performance. To address this problem, a MUST-based SIC-free NOMA VLC system is studied in this work. At the transmitter, coded bits from users with diverse channel conditions are jointly mapped to a composite constellation by linear or non-linear superposition coding. At the receivers, independent demapping is employed directly to extract the soft information of related coded bits. Constellation constrained capacity regions for different MUST categories with SIC-free reception are derived and analyzed comprehensively. Considering user fairness, we restrict the comparison to the working points that satisfy the direct ratio policy (DRP). It is observed that the non-linear categories of MUST are superior to the linear one due to their Gray labeled composite constellation and show considerable throughput gain over orthogonal multiple access (OMA) although SIC is not utilized. Additionally, the throughput loss to conventional PD-NOMA is also very small.
More energy, more searches, but the phenomenological MSSM lives on

We further examine the capability of the 7 and 8 TeV LHC to explore the parameter space of the p(henomenological)MSSM with neutralino LSPs. Here we present an updated study employing all of the relevant ATLAS SUSY analyses, as well as all relevant LHC non-MET searches, whose data were publically available as of mid-September 2012. We find that roughly 1/3 of our pMSSM model points are excluded at present with an important role being played by both the heavy flavor and multi-lepton searches, as well as those for heavy stable charged particles. Nonetheless, we find that light gluinos, 1st/2nd generation squarks, and stop/sbottoms (\lsim 400-700 GeV), as well as models with 1% fine-tuning or better, are still viable in the pMSSM. In addition, we see that increased luminosity at 8 TeV is unlikely to significantly improve the reach of the "vanilla" searches. The impact of these null searches on the SUSY sparticle spectrum is discussed in detail and the implications of these results for models with low fine-tuning, a future lepton collider and dark matter searches are examined.