Miracle-dz/UniFAR-FTUs huggingface dataset:
DEMO: Deep MR Parametric Mapping with Unsupervised Multi-Tasking Framework

resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1 ρ mapping.
Mesenchymal Stem Cells in the Treatment of Human Spinal Cord Injury: The Effect on Individual Values of pNF-H, GFAP, S100 Proteins and Selected Growth Factors, Cytokines and Chemokines

At present, there is no effective way to treat the consequences of spinal cord injury (SCI). SCI leads to the death of neural and glial cells and widespread neuroinflammation with persisting for several weeks after the injury. Mesenchymal stem cells (MSCs) therapy is one of the most promising approaches in the treatment of this injury. The aim of this study was to characterize the expression profile of multiple cytokines, chemokines, growth factors, and so-called neuromarkers in the serum of an SCI patient treated with autologous bone marrow-derived MSCs (BM-MSCs). SCI resulted in a significant increase in the levels of neuromarkers and proteins involved in the inflammatory process. BM-MSCs administration resulted in significant changes in the levels of neuromarkers (S100, GFAP, and pNF-H) as well as changes in the expression of proteins and growth factors involved in the inflammatory response following SCI in the serum of a patient with traumatic SCI. Our preliminary results encouraged that BM-MSCs with their neuroprotective and immunomodulatory effects could affect the repair process after injury.
An integrated software process assessment for Malaysia's SME organizations

There are currently a number of specific international standards relevant to software process. Controls requirement on software development are defined in standards such as Capability Maturity Model Integration (CMMI), ISO/IEC 15504, ISO/IEC 90003 and ISO/IEC 27001 (formerly known as ISO 17799). ISO/IEC 12207 looks at the software life cycle and its components. Currently, there are no initiative to integrate and harmonise these best practices, standards and models. Integrated software process assessment knowledge base and methodology (iSPA) is an initiative to harmonise and integrate various existing software process assessment /improvement standards, models and benchmarks. This will enable software development companies to achieve flexibility and choices in the self-assessment of their software development processes. This paper presents and proposes a new methodology for implementation of software process improvement in Malaysia as well as the application tool in assisting the implementation.
Mechanism of pharmacological effect of Angelica essential oil on anxiety based on network pharmacology and molecular docking

Purpose: To investigate the pharmacological effect of Angelica essential oil (AEO) on anxiety disorder and the mechanism of action involved, using network pharmacology and molecular docking. Method: Chemical compositions of AEO were determined using gas chromatography-mass spectrometry (GC-MS). The potential targets involved in the effect of AEO on anxiety were predicted by searching Bioinformatics databases. Cytoscape software was applied for networks construction. Analysis of Gene Ontology (GO) and pathway was done via R Programming Language, while molecular docking analysis was conducted by Autodock vina software. Results: Network analysis showed that there were 10 bioactive components and 34 potential targets. The potential targets were distributed in cerebellar cortex, basic ganglia, hippocampal formation, amygdala, pons and medulla and liver. AEO was involved in multiple biological processes (BP), cell components (CC) and molecular functions (MF) associated with anxiety disorder. Molecular docking revealed good binding affinity between the major bioactive components and targets. Conclusion: This study has revealed the pharmacological mechanism involved in the effect of AEO on anxiety, through network pharmacology and molecular docking. The pharmacological mechanism provides a firm theoretical basis for further studies in this area of research.
Yearly change in severely salt-damaged areas in paddy fields in Ban Phai in Northeast Thailand

: Future expansion of salt-damaged areas is anticipated in Northeast Thailand. We conducted a field investigation of paddy fields from 2016 to 2019 in Ban Phai district, Khon Kaen province in Northeast Thailand to evaluate yearly changes in the effect of salinity damage on rice production. The investigation area was classified into severely salt-affected areas (2 nd of 5 classes) based on the definition used in Thailand. Since salinity severely damages rice produc‐ tion, rice cultivation was abandoned in some fields, although some were still planted. The soil electrical con‐ ductivity (EC) in the rice-planted paddy fields changed yearly in association with the amount of precipitation. The effect of the difference in EC on rice yield was moderate, suggesting that rice yield was mediated by surface water. Some areas in the abandoned fields did not have any vege‐ tation, and quite high soil EC values were observed. The non-vegetated areas evaluated based on yearly unmanned aerial vehicle (UAV) images changed partly due to the amount of precipitation. However, some non-vegetated areas decreased in contrast to the decrease in precipitation, probably because of the effect of groundwater. Although the continuous expansion of severely salt-damaged areas was not observed, the monitoring of salinity levels is rec‐ ommended for the future.
Systematic Review on Speaking Skill Teaching Approaches in the ESL / EFL Classroom: Before and During Covid 19

Despite its significance, speaking skill is often neglected in ESL/EFL classroom as most educators and learners find it challenging. It becomes more challenging with the strike of global crisis Covid 19 due to the forced remote teaching and learning. This study reviews the teaching approaches that are effective to enhance speaking skill among ESL/EFL speakers. It aims to systematically review the developments of teaching approaches that can be used to enhance learners’ speaking skill and highlight the trends that began in the strike of pandemic covid 19. This systematic review is conducted based on the five steps proposed by Khan et al (2003). Articles were explored based on the application of selected keywords on various data base. A total of 15 related articles were identified, where 5 of them are conducted during the pandemic. Data were analyzed and tabulated in findings. Result shows that task-based approach and present, practice and produce approach are effective to enhance speaking skill. Meanwhile role play and information gap are most popular intervention used in task-based approach. Result also indicates that speaking skill teaching approaches used before the pandemic is transferable to be applied in remote teaching during the pandemic.
Structure and Properties of Copper Pyrophosphate by First-Principle Calculations

Investigated the structural, electronic, and magnetic properties of copper pyrophosphate dihydrate (CuPPD) by the first-principle calculations based on the density functional theory (DFT). Simulations were performed with the generalized gradient approximation (GGA) of the exchange-correlation functional (Exc) supplemented by an on-site Coulomb self-interaction (U–Hubbard term). It was confirmed that the GGA method did not provide a satisfactory result in predicting the electronic energy band gap width (Eg) of the CuPPD crystals. Simultaneously, we measured the Eg of CuPPD nanocrystal placed inside mesoporous silica using the ultraviolet–visible spectroscopy (UV–VIS) technique. The proposed Hubbard correction for Cu-3d and O-2p states at U = 4.64 eV reproduces the experimental value of Eg = 2.34 eV. The electronic properties presented in this study and the results of UV–VIS investigations likely identify the semiconductor character of CuPPD crystal, which raises the prospect of using it as a component determining functional properties of nanomaterials, including quantum dots.
Design and signal processing of finger photo plethysmograph ring sensors for reduced motion artifact and circulation interference

This work centers on creating a new design for a photo plethysmograph ring sensors to address the problems of previous ring sensors. Two major issues are addressed: to improve the signal-to-noise ratio and lack of motion detection. A new design for photo plethysmographic devices is presented to increase the amplification of arterial volumetric pulsations. The unit provides a mechanism capable of pressurizing the finger base at localized point, thus circulation is not obstructed. An experiment study compares the new design with a cuff system. Results show that the new design does not obstruct the blood, while the cuff does. In addition, the new design will decrease corruption of the signal due to saturation effects from ambient light and small motion perturbation. Motion detection was also presented in this work. Based on size and power constraints, an autocorrelation method in addition to a 2nd photodetector (motion detector) were decided upon. The motion detector is more susceptible to motion, thus providing a noise reference. An algorithm using the autocorrelation method determines if motion is present based on the noise reference. Thesis Supervisor: H. Harry Asada, Ph.D. Ford Professor of Mechanical Engineering, Director, d'Arbeloff Laboratory for Information Systems and Technology
Bivalve body-size distribution through the Late Triassic mass extinction event

Abstract. The synergic relationship between physiology, ecology, and evolutionary process makes the body-size distribution (BSD) an essential component of the community ecology. Body size is highly susceptible to environmental change, and extreme upheavals, such as during a mass extinction event, could exert drastic changes on a taxon's BSD. It has been hypothesized that the Late Triassic mass extinction event (LTE) was triggered by intense global warming, linked to massive volcanic activity associated with the Central Atlantic Magmatic Province. We test the effects of the LTE on the BSD of fossil bivalve assemblages from three study sites spanning the Triassic/Jurassic boundary in the United Kingdom. Our results show that the effects of the LTE were rapid and synchronous across sites, and the BSDs of the bivalves record drastic changes associated with species turnover. No phylogenetic signal of size selectivity was recorded, although semi-infaunal species were apparently most susceptible to change. Each size class had the same likelihood of extinction during the LTE, which resulted in a platykurtic BSD with negative skew. The immediate postextinction assemblage exhibits a leptokurtic BSD, although with negative skew, wherein surviving species and newly appearing small-sized colonizers exhibit body sizes near the modal size. Recovery was relatively rapid (∼100 kyr), and larger bivalves began to appear during the pre-Planorbis Zone, despite recurrent dysoxic/anoxic conditions. This study demonstrates how a mass extinction acts across the size spectrum in bivalves and shows how BSDs emerge from evolutionary and ecological processes.
Predicting Anticancer Drug Resistance Mediated by Mutations

Cancer drug resistance presents a challenge for precision medicine. Drug-resistant mutations are always emerging. In this study, we explored the relationship between drug-resistant mutations and drug resistance from the perspective of protein structure. By combining data from previously identified drug-resistant mutations and information of protein structure and function, we used machine learning-based methods to build models to predict cancer drug resistance mutations. The performance of our combined model achieved an accuracy of 86%, a Matthews correlation coefficient score of 0.57, and an F1 score of 0.66. We have constructed a fast, reliable method that predicts and investigates cancer drug resistance in a protein structure. Nonetheless, more information is needed concerning drug resistance and, in particular, clarification is needed about the relationships between the drug and the drug resistance mutations in proteins. Highly accurate predictions regarding drug resistance mutations can be helpful for developing new strategies with personalized cancer treatments. Our novel concept, which combines protein structure information, has the potential to elucidate physiological mechanisms of cancer drug resistance.
Preliminary Study of Chemistry Knowledge Through Ethnochemistry Approaches to Communities

This research was a descriptive qualitative study using ethnographic methods. It aimed to determine the understanding and application of chemistry knowledge in the daily lives of Wiapore society, Marawola Barat district, through an ethnochemistry approach. Data obtained was in the form of an initial data inventory. These inventory data were then grouped into several data categories, namely categories related to food, beverage, and agriculture categories. The percentage value of each data was as follows, related to food 55.55%, related to drinks were 22.22%, and connected to agriculture were 22.22%. The results of this study are significant for local governments in taking policies relating to education for children and the Wiapore community
MX2 Viral Substrate Breadth and Inhibitory Activity Are Regulated by Protein Phosphorylation

Productive infection by human immunodeficiency virus type-1 (HIV-1) requires the import of viral replication complexes into the nuclei of infected cells. Myxovirus resistance 2 (MX2/MxB) blocks this step, halting nuclear accumulation of viral DNA and virus replication. ABSTRACT Human immunodeficiency virus type-1 (HIV-1) infection is potently inhibited by human myxovirus resistance 2 (MX2/MxB), which binds to the viral capsid and blocks the nuclear import of viral DNA. We have recently shown that phosphorylation is a key regulator of MX2 antiviral activity, with phosphorylation of serine residues at positions 14, 17, and 18 repressing MX2 function. Here, we extend the study of MX2 posttranslational modifications and identify serine and threonine phosphorylation in all domains of MX2. By substituting these residues with aspartic acid or alanine, hence mimicking the presence or absence of a phosphate group, respectively, we identified key positions that control MX2 antiviral activity. Aspartic acid substitutions of residues Ser306 or Thr334 and alanine substitutions of Thr343 yielded proteins with substantially reduced antiviral activity, whereas the presence of aspartic acid at positions Ser28, Thr151, or Thr343 resulted in enhanced activity: referred to as hypermorphic mutants. In some cases, these hypermorphic mutations, particularly when paired with other MX2 mutations (e.g., S28D/T151D or T151D/T343A) acquired the capacity to inhibit HIV-1 capsid mutants known to be insensitive to wild-type MX2, such as P90A or T210K, as well as MX2-resistant retroviruses such as equine infectious anemia virus (EIAV) and murine leukemia virus (MLV). This work highlights the complexity and importance of MX2 phosphorylation in the regulation of antiviral activity and in the selection of susceptible viral substrates. IMPORTANCE Productive infection by human immunodeficiency virus type-1 (HIV-1) requires the import of viral replication complexes into the nuclei of infected cells. Myxovirus resistance 2 (MX2/MxB) blocks this step, halting nuclear accumulation of viral DNA and virus replication. We recently demonstrated how phosphorylation of a stretch of three serines in the amino-terminal domain of MX2 inhibits the antiviral activity. Here, we identify additional positions in MX2 whose phosphorylation status reduces or enhances antiviral function (hypomorphic and hypermorphic variants, respectively). Importantly, hypermorphic mutant proteins not only increased inhibitory activity against wild-type HIV-1 but can also exhibit antiviral capabilities against HIV-1 capsid mutant viruses that are resistant to wild-type MX2. Furthermore, some of these proteins were also able to inhibit retroviruses that are insensitive to MX2. Therefore, we propose that phosphorylation comprises a major element of MX2 regulation and substrate determination.
A Narrative Review of the Design of Ultrasound Indices for Detecting Enthesitis

With the increased utilization of musculoskeletal ultrasound in clinical practice, there has been rapid proliferation of publications on sonographic evaluation of enthesitis. This has led to the development of multiple new approaches to scoring sonographic findings in the detection of enthesitis, with variations including entheseal sites and sonographic features that limit cross-study comparisons. Furthermore, despite efforts to standardize the definition of enthesitis, there is still heterogeneity in the sonographic features included in existing ultrasound scores, and additional adjustments are required to distinguish active inflammatory changes from non-inflammatory conditions and to adjust for demographic features associated with increased prevalence of abnormal sonographic findings. This review provides an update on the current landscape of ultrasound scoring systems for enthesitis and emphasizes the importance of future data-based ultrasound scoring systems to improve the distinction between inflammatory and non-inflammatory or degenerative changes of the enthesis.
Defects in DNA double‐strand break repair resensitize antibiotic‐resistant Escherichia coli to multiple bactericidal antibiotics

Antibiotic resistance is becoming increasingly prevalent amongst bacterial pathogens and there is an urgent need to develop new types of antibiotics with novel modes of action. One promising strategy is to develop resistance-breaker compounds, which inhibit resistance mechanisms and thus re-sensitise bacteria to existing antibiotics. In the current study, we identify bacterial DNA double-strand break repair as a promising target for the development of resistance-breaking co-therapies. We examined genetic variants of Escherichia coli that combined antibiotic-resistance determinants with DNA repair defects. We observed that defects in the double-strand break repair pathway led to significant re-sensitisation towards five bactericidal antibiotics representing different functional classes. Effects ranged from partial to full re-sensitisation. For ciprofloxacin and nitrofurantoin, sensitisation manifested as a reduction in the minimum inhibitory concentration. For kanamycin and trimethoprim, sensitivity manifested through increased rates of killing at high antibiotic concentrations. For ampicillin, repair defects dramatically reduced antibiotic tolerance. Ciprofloxacin, nitrofurantoin, and trimethoprim induce the pro-mutagenic SOS response. Disruption of double-strand break repair strongly dampened the induction of SOS by these antibiotics. Our findings suggest that if break-repair inhibitors can be developed they could re-sensitise antibiotic-resistant bacteria to multiple classes of existing antibiotics and may supress the development of de novo antibiotic-resistance mutations.
Validated extractive analytical methods for the estimation of pregabalin in bulk and pharmaceutical dosage form

Two simple, rapid, sensitive and accurate spectrophotometric methods are described for the determination of Pregabalin (PRG) in bulk and pharmaceutical formulations. The methods are based on the reactions of the drug with bromocresol purple (BCP) and bromocresol green (BCG) in buffered hydrochloric acid solutions at pH 1.2 to give coloured ion-pair complexes extractable with chloroform. The coloured products are quantitated spectrophotometrically at 431 nm with BCP and 444.80 nm with BCG. Beer's law is obeyed in the concentration range 10-50 µg/ml with both reagents. Recovery studies gave satisfactory results indicating that none of common additives and excipients interfere the assay method. The proposed methods are found to be simple, accurate and reproducible that was successfully applied for the analysis of capsule formulations. The developed methods are easy to use, accurate and highly cost-effective for routine studies relative to HPLC and other techniques.
A Dual Attention Convolutional Neural Network for Crop Classification Using Time-Series Sentinel-2 Imagery

Accurate and timely mapping of crop types and having reliable information about the cultivation pattern/area play a key role in various applications, including food security and sustainable agriculture management. Remote sensing (RS) has extensively been employed for crop type classification. However, accurate mapping of crop types and extents is still a challenge, especially using traditional machine learning methods. Therefore, in this study, a novel framework based on a deep convolutional neural network (CNN) and a dual attention module (DAM) and using Sentinel-2 time-series datasets was proposed to classify crops. A new DAM was implemented to extract informative deep features by taking advantage of both spectral and spatial characteristics of Sentinel-2 datasets. The spectral and spatial attention modules (AMs) were respectively applied to investigate the behavior of crops during the growing season and their neighborhood properties (e.g., textural characteristics and spatial relation to surrounding crops). The proposed network contained two streams: (1) convolution blocks for deep feature extraction and (2) several DAMs, which were employed after each convolution block. The first stream included three multi-scale residual convolution blocks, where the spectral attention blocks were mainly applied to extract deep spectral features. The second stream was built using four multi-scale convolution blocks with a spatial AM. In this study, over 200,000 samples from six different crop types (i.e., alfalfa, broad bean, wheat, barley, canola, and garden) and three non-crop classes (i.e., built-up, barren, and water) were collected to train and validate the proposed framework. The results demonstrated that the proposed method achieved high overall accuracy and a Kappa coefficient of 98.54% and 0.981, respectively. It also outperformed other state-of-the-art classification methods, including RF, XGBOOST, R-CNN, 2D-CNN, 3D-CNN, and CBAM, indicating its high potential to discriminate different crop types.