Miracle-dz/UniFAR-FTUs huggingface dataset:
Fear of Negative Evaluation Factors from Ought-to L2 Self among Indonesian High School EFL Learners

The present study aims to investigate Indonesian high school English as Foreign Language (EFL) learners’ views on factors originating from Ought to L2 Self (OL2S), a second language (L2) motivation construct, affecting their Fear of Negative Evaluation (FNE), L2 anxiety construct. Six learner participants were involved in the study. It employed online semi-structured interviews to obtain the data. Through Thematic Analysis, the present study found three main findings. First, the desire to study abroad lessened the learners' FNE. Secondly, a realization of possible future negative impacts of not learning English and the obligation to avoid these impacts made the learners have less FNE. Third, their perceived obligation to have 'correct' English pronunciation instills higher FNE. Pedagogical implications include promoting study abroad aspiration among learners, introducing Global Englishes prioritizing intelligibility over attaining native speakers' ability and designing more activities mirroring future practical uses of English. Suggestive directions for future studies are also stated concerning the limitations and findings of the present study.
Salvage Radiotherapy Plus Androgen Deprivation Therapy for High-Risk Prostate Cancer with Biochemical Failure after High-Intensity Focused Ultrasound as Primary Treatment

We conduct a retrospective analysis of salvage radiotherapy plus androgen deprivation therapy (SRT+ADT) for high-risk prostate cancer patients with biochemical failure after high-intensity focused ultrasound (HIFU) as the primary treatment. A total of 38 patients, who met the criteria of biochemical failure and were consecutively treated with SRT+ADT, were enrolled. All patients received intensity modulated radiotherapy with a median dose of 70 Gy to the clinical target volume. ADT was given before, during or after the course of SRT with the duration of ≦6 months (n = 14), 6–12 months (n = 12) or >12 months (n = 12). The median follow-up was 45.9 months. A total of 10 (26.3%) patients had biochemical failure after SRT+ADT. The cumulative 5-year biochemical progression free survival (b-PFS) and overall survival (OS) rate was 73.0% and 80.3%, respectively. A nadir prostate-specific antigen (nPSA) value 0.02 ng/mL was observed to predict the b-PFS in multivariate analysis. The 5-year b-PFS was 81.6% for those with nPSA < 0.02 compared with 25.0% with nPSA ≧ 0.02. The adverse effects related to SRT+ADT were mild in most cases and only three (8%) patients experienced grade 3 urinary toxicities. For high-risk prostate cancer after HIFU as primary treatment with biochemical failure, our study confirms the feasibility of SRT+ADT with high b-PFS, OS and low toxicity.
Mechanisms of Caspases 3/7/8/9 in the Degeneration of External Gills of Chinese Giant Salamanders (Andrias davidianus)

Metamorphosis is a critical stage in the adaptive development of amphibians from aquatic to terrestrial animals. Metamorphosis of the Chinese giant salamander is mainly manifested by the loss of external gills with consequent changes in the respiratory pattern. The loss of the external gill is regulated by the pathway of apoptosis in which caspase genes are the key factors. This study cloned and expressed the caspase 3/7/8/9 genes of the Chinese giant salamander. The main results were as follows: the complete open reading frames (ORFs) were 885 bp, 960 bp, 1461 bp and 1279 bp, respectively; caspase 3/7/8/9 genes all contained the CASc domain, and most of the motifs were located in CASc domain; and caspase 8 possessed two DED structural domains and caspase 9 possessed a CARD structural domain. Furthermore, results from the tissue distribution analysis indicated that caspase 3/7/8/9 genes were all significantly expressed in the external gill, and at 9 and 10 months of age (MOA), which is the peak time for the loss, the EXPRESSION level of caspase 3/7/8/9 genes was obviously high, which was consistent with the histological result. Moreover, the loss of external gills of the Chinese giant salamander may result from activation of both the apoptosis-related death receptor pathway and the mitochondrial pathway. Finally, it was discovered that thyroid hormone (TH) treatment could both advance the time point at which the external gills of the Chinese giant salamander began to degenerate and shorten this process. Interestingly, at the peak of its metamorphosis (9 MOA), the Chinese giant salamander further accelerated the metamorphosis rate of TH treatment, which suggested a promotive effect on the loss of external gills via the superimposition of the exogenous TH and caspase genes. The study of caspase genes in this experiment was conducive to understanding the mechanism of external gill loss in the Chinese giant salamander, as well as improving our understanding of the metamorphosis development of some Caudata species.
The Impact of Oulema melanopus—Associated Bacteria on the Wheat Defense Response to the Feeding of Their Insect Hosts

Wheat production is threatened by the destructive effects of numerous pests, including Oulema melanopus (cereal leaf beetle, CLB). Both adults and larvae of CLB damage grain crops, but the target of insecticide treatments are the larvae. Insect-associated bacteria are important for many of the insects’ life processes and may also modulate plant defense responses to feeding of their insect host. The aim of our study was to elucidate the early wheat plants’ reaction to this herbivore feeding and to disclose the CLB-associated bacteria modulation of the wheat-insect interactions. Transcriptome analyses were performed for the leaves wounded mechanically and by feeding of the CLB larvae as well as for the distal leaves to study both, the plant’s local and systemic response. Comparative transcriptome analysis indicated that 24 h after the plant treatment, a much larger number of up-regulated DEGs in damaged leaves was noted, especially those on which larvae were fed. It may suggest that at the analysed time point, the local response was stronger than the systemic one. In the leaves on which larvae with natural bacterial flora were fed (local response), the number of up- and down-regulated differentially expressed genes (DEGs) was 7136 and 7411, respectively, in comparison to the dataset obtained for the leaves wounded by larvae with a reduced number of bacteria. In the distal leaves, 3015 up- and 2372 down-regulated DEGs were noted. CLB-associated bacteria were found to affect many aspects of the physiology of wheat plants, especially in wounded leaves, including the expression of genes related to primary metabolism, phytohormone signaling and photosynthesis. We also observed that CLB-associated bacteria mitigated numerous anti-herbivore processes and pathways associated with the synthesis of metabolites and proteins, potentially harmful to the insects. The bacteria also reversed the expression of some genes involved, inter alia, in the phosphorylation of proteins, oxidative stress, cell wall organization, and biogenesis. Understanding the role of CLB-associated bacteria in the plant’s defense response will be important to the fields of pest control and herbivore and its host ecology and evolution.
Identification of the Antigens Recognised by Colorectal Cancer Patients Using Sera from Patients Who Exhibit a Crohn’s-like Lymphoid Reaction

A Crohn’s-like lymphoid reaction (CLR) is observed in about 15% of colorectal cancer (CRC) patients and is associated with favourable outcomes. To identify the immune targets recognised by CRC CLR patient sera, we immunoscreened a testes cDNA library with sera from three patients. Immunoscreening of the 18 antigens identified by SEREX with sera from normal donors showed that only the heavy chain of IgG3 (IGHG3) and a novel antigen we named UOB-COL-7, were solely recognised by sera from CRC CLR patients. ELISA showed an elevation in IgG3 levels in patients with CRC (p = 0.01). To extend our studies we analysed the expression of our SEREX-identified antigens using the RNA-sequencing dataset (GSE5206). We found that the transcript levels of multiple IGHG probesets were highly significant (p < 0.001) in their association with clinical features of CRC while above median levels of DAPK1 (p = 0.005) and below median levels of GTF2H5 (p = 0.004) and SH3RF2 (p = 0.02) were associated with improved overall survival. Our findings demonstrate the potential of SEREX-identified CRC CLR antigens to act as biomarkers for CRC and provide a rationale for their further characterization and validation.
The reliability and validity of the Turkish version of the brief pain inventory-short form in patients with cancer pain

Objectives The aim of this study was to evaluate the reliability and validity of the Turkish version of the Brief Pain Inventory (BPI-TR) in patients with cancer pain. Patients and methods The study included 130 patients (70 females, 60 males; mean age: 56.1±13.3 years; range, 18 to 87 years) diagnosed with any type and stage of cancer between April 2017 and March 2018. Brief Pain Inventory, Pain Disability Index, EORTC QLQ C30 and Pain Management Index were used to collect data. The reliability of the scale was tested with `internal consistency` and its validity with `construct validity`. Cronbach`s alpha values of >0.70 were accepted as the threshold for internal consistency. Construct validity was tested in the context of structural validity with factor analysis and also tested in terms of convergent construct validity by investigating its correlation with the Pain Disability Index (PDI) and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). Results The internal consistency of pain severity and pain-related interference was found as 0.91 and 0.95, respectively. The alpha coefficient was found to be between 0.795 and 0.873 for the pain severity index and between 0.729 and 0.861 for the pain-related interference index. There was a clear link between the BPI-TR pain severity index and the ninth question in the EORTC QLQ-C30 (rho=0.66, p<0.05). The association between the BPI-TR interference index and the 19th question in the EORTC QLQ-C30 was also strong (rho=0.77, p<0.05). The correlation between the BPI-TR interference index and the PDI was found to be moderate (rho=0.50, p<0.05). Conclusion The BPI-TR was found to be a reliable and legitimate tool to evaluate cancer pain in the Turkish population.
A Hybrid Evolutionary Algorithm for the Sequencing m-Vector Bin Packing Problem

—In this paper, the product sequencing decisions in multiple-piece-flow assembly lines problem is approximately solved with a hybrid evolutionary algorithm. The product sequencing decisions in multiple-piece-flow assembly lines, known as the sequencing m -vector bin packing problem, occurs in manufacturing organization and because of its NP-hardness it is however computationally challenging. The designed method combines a population approach and both first fit bin packing procedure coupled with a repairing operator: the population approach tries to maintain the diversity of a series of populations reached throughout an iterative procedure while the added operators try to highlight the quality of the solutions throughout the search process. The performance of the proposed method is evaluated on a set of benchmark instances taken from the literature. The results provided by the method are compared to those reached by recent published methods and to those reached by the state-of-the-art Cplex solver. The preliminary experimental part showed that the designed method outperforms the other ones by discovering new bounds for most of considered instances.
The Promising Nanovectors for Gene Delivery in Plant Genome Engineering

Highly efficient gene delivery systems are essential for genetic engineering in plants. Traditional delivery methods have been widely used, such as Agrobacterium-mediated transformation, polyethylene glycol (PEG)-mediated delivery, biolistic particle bombardment, and viral transfection. However, genotype dependence and other drawbacks of these techniques limit the application of genetic engineering, particularly genome editing in many crop plants. There is a great need to develop newer gene delivery vectors or methods. Recently, nanomaterials such as mesoporous silica particles (MSNs), AuNPs, carbon nanotubes (CNTs), and layer double hydroxides (LDHs), have emerged as promising vectors for the delivery of genome engineering tools (DNA, RNA, proteins, and RNPs) to plants in a species-independent manner with high efficiency. Some exciting results have been reported, such as the successful delivery of cargo genes into plants and the generation of genome stable transgenic cotton and maize plants, which have provided some new routines for genome engineering in plants. Thus, in this review, we summarized recent progress in the utilization of nanomaterials for plant genetic transformation and discussed the advantages and limitations of different methods. Furthermore, we emphasized the advantages and potential broad applications of nanomaterials in plant genome editing, which provides guidance for future applications of nanomaterials in plant genetic engineering and crop breeding.
Ancillary ligand effects on α-olefin polymerization catalyzed by zirconium metallocene: a computational study

The polymerization of α-olefins catalyzed by zirconium metallocene catalyst was systematically studied through experiments and density functional theory (DFT) calculations. Having achieved an agreement between theory and experiment, it was found that the effect of the catalyst ligand on the C <svg xmlns="http://www.w3. org/2000/svg" version="1.0" width="13.200000pt" height="16.000000pt" viewBox="0 0 13.200000 16.000000" preserveAspectRatio="xMidYMid meet"><metadata> Created by potrace 1.16, written by Peter Selinger 2001-2019 </metadata><g transform="translate(1.000000,15.000000) scale(0.017500,-0.017500)" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg> C insertion reaction was significantly greater than that on the β-H elimination reaction. Therefore, the molecular weight of polymers can be increased by improving the activity of the CC insertion. In addition, in comparison with propylene, the chain length of α-olefins can directly affect the stereotacticity of polymerization products, owing to steric hindrance between the polymer chain and monomer.
Assessment of Bacteriocin-Antibiotic Synergy for the Inhibition and Disruption of Biofilms of Listeria monocytogenes and Vancomycin-Resistant Enterococcus

In this study, we have evaluated the effects of previously characterized bacteriocins produced by E. faecium strains ST651ea, ST7119ea, and ST7319ea, against biofilm formation and biofilms formed by L. monocytogenes ATCC15313 and vancomycin-resistant E. faecium VRE19. The effects of bacteriocins on the biofilms formed by L. monocytogenes ATCC151313 were evaluated by crystal violet assay and further confirmed by quantifying viable cells and cell metabolic activities through flow cytometry and TTC assay, respectively, indicating that bacteriocin activities required to completely eradicate biofilms are at least 1600 AU mL−1, 3200 AU mL−1, and 6400 AU mL−1, respectively for each bacteriocin evaluated. Furthermore, bacteriocins ST651ea and ST7119ea require at least 6400 AU mL−1 to completely eradicate the viability of cells within the biofilms formed by E. faecium VRE19, while bacteriocin ST7319ea requires at least 12800 AU mL−1 to obtain the same observations. Assessment of synergistic activities between selected conventional antibiotics (ciprofloxacin and vancomycin) with these bacteriocins was carried out to evaluate their effects on biofilm formation and pre-formed biofilms of both test microorganisms. Results showed that higher concentrations are needed to completely eradicate metabolic activities of cells within pre-formed biofilms in contrast with the biofilm formation abilities of the strains. Furthermore, synergistic activities of bacteriocins with both ciprofloxacin and vancomycin are more evident against vancomycin-resistant E. faecium VRE19 rather than L. monocytogenes ATCC15313. These observations can be further explored for possible applications of these combinations of antibiotics as a possible treatment of clinically relevant pathogens.
Rotation, Translation and Scale Invariant Sign Word Recognition Using Deep Learning

Communication between people with disabilities and people who do not understand sign language is a growing social need and can be a tedious task. One of the main functions of sign language is to communicate with each other through hand gestures. Recognition of hand gestures has become an important challenge for the recognition of sign language. There are many existing models that can produce a good accuracy, but if the model test with rotated or translated images, they may face some difficulties to make good performance accuracy. To resolve these challenges of hand gesture recognition, we proposed a Rotation, Translation and Scale-invariant sign word recognition system using a convolutional neural network (CNN). We have followed three steps in our work: rotated, translated and scaled (RTS) version dataset generation, gesture segmentation, and sign word classification. Firstly, we have enlarged a benchmark dataset of 20 sign words by making different amounts of Rotation, Translation and Scale of the original images to create the RTS version dataset. Then we have applied the gesture segmentation technique. The segmentation consists of three levels, i) Otsu Thresholding with YCbCr, ii) Morphological analysis: dilation through opening morphology and iii) Watershed algorithm. Finally, our designed CNN model has been trained to classify the hand gesture as well as the sign word. Our model has been evaluated using the twenty sign word dataset, five sign word dataset and the RTS version of these datasets. We achieved 99.30% accuracy from the twenty sign word dataset evaluation, 99.10% accuracy from the RTS version of the twenty sign word evolution, 100% accuracy from the five sign word dataset evaluation, and 98.00% accuracy from the RTS version five sign word dataset evolution. Furthermore, the influence of our model exists in competitive results with state-of-the-art methods in sign word recognition.
Public Sentiment Analysis and Topic Modeling Regarding COVID-19's Three Waves of Total Lockdown: A Case Study on Movement Control Order in Malaysia

The COVID-19 pandemic has affected many aspects of human life. The pandemic not only caused millions of fatalities and problems but also changed public sentiment and behavior. Owing to the magnitude of this pandemic, governments worldwide adopted full lockdown measures that attracted much discussion on social media platforms. To investigate the effects of these lockdown measures, this study performed sentiment analysis and latent Dirichlet allocation topic modeling on textual data from Twitter published during the three lockdown waves in Malaysia between 2020 and 2021. Three lockdown measures were identified, the related data for the first two weeks of each lockdown were collected and analysed to understand the public sentiment. The changes between these lockdowns were identified, and the latent topics were highlighted. Most of the public sentiment focused on the first lockdown as reflected in the large number of latent topics generated during this period. The overall sentiment for each lockdown was mostly positive, followed by neutral and then negative. Topic modelling results identified staying at home, quarantine and lockdown as the main aspects of discussion for the first lockdown, whilst importance of health measures and government efforts were the main aspects for the second and third lockdowns. Governments may utilise these findings to understand public sentiment and to formulate precautionary measures that can assure the safety of their citizens and tend to their most pressing problems. These results also highlight the importance of positive messaging during difficult times, establishing digital interventions and formulating new policies to improve the reaction of the public to emergency situations.
Allocation strategy for time‐sensitive tasks in mobile edge computing: An observable perspective

With the development of computing technology and the popularization of application in 5G network, mobile‐edge computing (MEC), which can effectively reduce time delay and save energy consumption, has attracted extensive attention from the academic community. How to make a suitable allocation decision for tasks becomes one of the critical issues in MEC systems. In order to yield the most benefit to a newly arriving task, by placing a decision making module (DMM) in a mobile device, a MEC system architecture is presented. Based on the net benefit of a newly arriving task, the DMM makes a decision of dropping the task, allocating the task to the local execution system, or offloading the task to the MEC server via the transmission system. From the observable perspective of task individuals, a pure threshold strategy is proposed to show that a Nash equilibrium is always allowed. By constructing a two‐dimensional continuous‐time Markov chain, a social optimal threshold strategy is proposed. Numerical results show that threshold under the pure threshold strategy is always greater than that under the social optimal threshold strategy. For this, a charging policy is presented to coincide the pure threshold strategy with the social optimal threshold strategy.
Safety, Security and Privacy in Machine Learning Based Internet of Things

Recent developments in communication and information technologies, especially in the internet of things (IoT), have greatly changed and improved the human lifestyle. Due to the easy access to, and increasing demand for, smart devices, the IoT system faces new cyber-physical security and privacy attacks, such as denial of service, spoofing, phishing, obfuscations, jamming, eavesdropping, intrusions, and other unforeseen cyber threats to IoT systems. The traditional tools and techniques are not very efficient to prevent and protect against the new cyber-physical security challenges. Robust, dynamic, and up-to-date security measures are required to secure IoT systems. The machine learning (ML) technique is considered the most advanced and promising method, and opened up many research directions to address new security challenges in the cyber-physical systems (CPS). This research survey presents the architecture of IoT systems, investigates different attacks on IoT systems, and reviews the latest research directions to solve the safety and security of IoT systems based on machine learning techniques. Moreover, it discusses the potential future research challenges when employing security methods in IoT systems.