Miracle-dz/UniFAR-FTUs huggingface dataset:
PCBP-1 Regulates the Transcription and Alternative Splicing of Inflammation and Ubiquitination-Related Genes in PC12 Cell

PCBP-1, a multifunctional RNA binding protein, is expressed in various human cell/tissue types and involved in post-transcriptional gene regulation. PCBP-1 has important roles in cellular Iron homeostasis, mitochondrial stability, and other cellular activities involved in the pathophysiological process of neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS) and Huntington’s disease (HD). However, it remains enigmatic whether PCPB-1 is associated with the pathogenesis of PD. In this study, we cloned and constitutively overexpressed PCBP-1 in rat PC12 cells (PC12 cell is the common cell line studying neurodegenerative disease include PD). RNA-seq was performed to analyze PCBP-1-regulated differentially expressed genes (DEGs) and alternative splicing events (ASEs) between control and PCBP1-overexpressed cells. GO and KEGG pathway analyses were performed to identify functional DEGs and alternatively spliced genes. Consequently, we validated PCBP-1-regulated genes using RT-qPCR. Finally, we downloaded CLIP-seq data from GEO (GSE84700) to analyze the mechanisms of PCBP-1’s regulation of gene expression and ASEs by revealing the binding profile of PCBP-1 on its target pre-mRNAs. Overexpression of PCBP-1 partially regulated the ASE and expression of genes enriched in neuroinflammation and protein ubiquitination, which were also associated with PD pathogenesis. Moreover, RT-qPCR assay verified the PCBP-1-modulated expression of neuroinflammatory genes, like LCN-2, and alternative splicing (AS) of ubiquitination-related gene WWP-2. Finally, CLIP-seq data analysis indicated that the first UC motif was the critical site for PCBP-1 binding to its targets. In this study, we provided evidence that PCBP-1 could regulate the expression of LCN-2 gene expression associated with neuroinflammation and AS of WWP-2 in relation to protein ubiquitination. These findings thus provided novel insights into the potential application of PCBP-1 as the disease pathophysiological or therapeutic target for neurodegenerative disease.
Motor Imagery Combined With Physical Training Improves Response Inhibition in the Stop Signal Task

Background Motor imagery training has a similar effect to that of physical training on motor performance. The objective of this study was to investigate the short-term effectiveness of motor imagery training on response inhibition using the stop signal task (SST). Methods Participants were divided into a physical training group (PT, n = 17), a motor imagery training group (MIT, n = 17), and a motor imagery combined with physical training group (MIPT, n = 17). All participants performed 10 SST training sessions over 5 days. Both stop signal reaction time (SSRT) and non-signal reaction time (NSRT) were measured before and after SST training. Results There were significant interaction (time × group) and time effects, although the group effect was not statistically significant. Bonferroni post hoc analysis showed that MIPT group revealed a significantly greater change in SSRT than PT and MIT groups, while there was no significant difference between PT and MIT groups. SSRT significantly decreased after training in all groups. In NSRT, there was a significant effect of time, but there was no significant interaction effect (time × group) or group effect. Conclusion Response inhibition could be enhanced via training, and it was most effective when motor imagery and physical training were combined. We demonstrate that motor imagery training significantly improves response inhibition and should be accompanied by physical training when performing SST.
Performance Evaluation of Anomaly-Based Detection Mechanisms

Common practice in anomaly-based intrusion detection is that one size fits all: a single anomaly detector should detect all anomalies. Compensation for any performance shortcomings is sometimes effected by resorting to correlation techniques, which could be seen as making use of detector diversity. Such diversity is intuitively based on the assumption that detector coverage is different – perhaps widely different – for different detectors, each covering some disparate portion of the anomaly space. Diversity, then, enhances detection coverage by combining the coverages of individual detectors across multiple sub-regions of the anomaly space, resulting in an overall detection coverage that is superior to the coverage of any one detector. No studies have been done, however, in which measured effects of diversity in anomaly detectors have been obtained. This paper explores the effects of using diverse anomalydetection algorithms (algorithmic diversity) in intrusion detection. Experimental results indicate that while performance/coverage improvements can in fact be effected by combining diverse detection algorithms, the gains are surprisingly not the result of combining large, non-overlapping regions of the anomaly space. Rather, the gains are seen at the edges of the space, and are heavily dependent on the parameter values of the detectors, as well as on the characteristics of the anomalies. As a consequence of this study, defenders can be provided with detailed knowledge of diverse detectors, how to combine and parameterize them, and under what conditions, to effect diverse detection performance that is superior to the performance of a single detector.
Simulation Based Measuring the Benefits of Converting to Lean Product Design and Development: A Case Study of Manufacturing Sector of Pakistan

Designers are facing the principal problems of effective decision making at the initial design stage of product development, which ultimately contribute to profit loss, low quality and increased time to launch the product onto the market. It requires a lot of knowledge and experience. Tools are required to analyze and ensure that crucial decisions have strong foundation before implementation. Discrete event simulation provides such a tool and has got potential to assist in decision making before final implementation. This research work aims measuring the benefits of transformation to lean product development (LPD) via simulation. Simulink-MATLAB tool was used for this purpose. The whole work is limited to design and cost estimation cells of a manufacturing company and consists of two phases. The first phase deals with the assessment of current working model of design and cost estimation cells. The areas for improvements were recognized at this phase. The proposed model for transformation to LPD was developed in the second phase. Four lean enablers namely product values, knowledge-based engineering, setbased concurrent engineering and poke-yoke were incorporated to further enhance the operation of the proposed model. This research work constitutes a useful case for practitioners.
Wind Turbine Fault Classification Using Support Vector Machines with Fuzzy Logic

Rapid and accurate identification of faults on wind turbine blades is important to ensure the continued operation of wind power generation systems. This paper explores the implementation of Support Vector Machines (SVM) combined with fuzzy logic for image recognition and fault classification of wind turbine blades. We discuss the concept, ideas, and implementation of SVM for image recognition, and the final result is to implement these features into a system for detecting the various cracks and damages on the blades of wind turbines using a scale model. The final system will be tested on a scale model of a wind turbine blade. We will focus on what SVM is, what the crossover between SVM and fuzzy may look like, and how it will effectively be able to detect cracks in the blades of wind turbines.
The Legitimacy of Private Schooling: Education Preferences in Nine European Contexts

ABSTRACT Motivated by empirical reality of differences in the scope and meaning of school choice and private schooling this article focuses on the public demand for increasing diversity of educational options In Europe and the division of public and private provision in it. We aim to test self-interest and ideology-driven logics of education policy preferences in different educational contexts. We operationalize this variety of contexts by the share of private education spending and between-school inequality. We show that, on average, more resourceful individuals are less pro-private-education and those that are ideologically right-leaning are more so. At the system level, private schooling feeds back positively, and this does not differ across educational or ideological divides. Educational inequality, at the same time, de-legitimizes the support for private schooling and its effect differs – higher educated and ideologically right-leaning turn to prefer more public schooling the higher the educational inequality. Thus, the more equal the educational provision, independent of public-private mix, the more entrenched pro-private school preferences will become.
Prevalence, Serotypes, and Antimicrobial Resistance Patterns of Non-Typhoid Salmonella in Food in Northern Taiwan

Salmonella is one of the most common bacteria causing food poisoning worldwide. We evaluated the prevalence, the serotypes, and the antimicrobial resistance (AMR) of Salmonella isolates from many kinds of food, particularly pork and chicken in retail, in Taiwan between January 2017 and December 2019. The E-test was used to assess antimicrobial susceptibility and a polymerase chain reaction was performed for serotyping. A total of 459 different foods were investigated, and 117 Salmonella strains were isolated. Retail pork and chicken were the most common Salmonella-contaminated foods (64.1% and 29.1%, respectively). Of the 117 isolates, 23 serotypes were identified. The serotypes Derby (16.2%), Anatum (13.7%), and Agona (8.5%) were the most prevalent. The resistance rates to ciprofloxacin, ceftriaxone, and carbapenem were 41.9%, 11.1%, and 1.7%, respectively. The Derby and Anatum serotypes were prevalent in chicken and pork; the Anatum serotype had significantly higher ciprofloxacin and ceftriaxone resistance rates and was highly prevalent in 2017 and 2018. Multi-locus sequence typing analysis revealed that the 58 randomly chosen Salmonella isolates belonged to 18 sequence types (STs). ST64 (Anatum, 16 out of 58, 27.6%) was the most common, followed by ST321 (Muenster, 6/58, 10.3%), ST831 (Give, 5/58, 8.6%), ST155 (London, 4/58, 6.9%) and ST314 (Kentucky, 4/58, 6.9%). Multidrug-resistant Salmonella strains were remarkably observed in the serotypes Anatum (ST64) and Goldcoast (ST358). This study revealed that retail pork was commonly contaminated with antimicrobial-resistant Salmonella. Thus, periodic investigations of Salmonella serotypes and AMR are needed.
Why do projects join the Apache Software Foundation?

While numerous open source projects operate on their own, others decide to join well-established foundations such as the Apache Software Foundation (ASF) and the Eclipse Foundation. Although many studies have investigated the motivations of individuals and companies contributing to open source, it remains unknown why projects decide to join software foundations. In this paper, we study the motivators behind the projects‘ decision to join the ASF, the geographical and organizational characteristics of these projects, and the differences between projects in terms of their motivations. To this aim, we analyzed 292 proposals submitted to ASF, and we found that there is an increasing number of company-based and Asia-based projects joining the ASF in recent years. Furthermore, we found that more than half of the projects are motivated by the desire to foster their community, strengthen the outcome of the project, increase interaction with other communities, and boost technical development. Our work shed some light on projects‘ expectations from the ASF. Having this understanding can help foundations to identify ways of supporting newly joined projects, while the prospective joiners can better decide on whether ASF is the right place for them by checking the alignment of their motivations and motivations of projects that have joined in the past. Open Source Software (OSS) is free to be used and modified by any-one in the world for any purpose. Nowadays, OSS is widely used in all kinds of products and hence plays an important role in our daily life. For example, as the most used OSS, the Linux kernel runs on 85% of all smartphones. To create a better environment for OSS de-velopers to collaborate and for OSS projects to grow, many software foundations have been established, such as the Apache Software Foundation (ASF). We have seen that many OSS projects joined the ASF over the years. To join the ASF, OSS projects have to donate all their assets to the foundation, adhering to the foundation's rules and culture. In this paper, we study why these projects decide to join the ASF to understand their expectations from such foundations so that the expected technical and non-technical support can be provided to them. We identified their motivations by analyzing 292 proposals that these projects submitted when applying for joining the ASF. We observed that more than half of the projects try to join the ASF with motivations related to fostering a community, strengthening the project's outcome, increasing interactions with other OSS projects in the ASF, and boosting technical development.
Radiomics Model for Frontotemporal Dementia Diagnosis Using T1-Weighted MRI

Radiomics has been proposed as a useful approach to extrapolate novel morphological and textural information from brain Magnetic resonance images (MRI). Radiomics analysis has shown unique potential in the diagnostic work-up and in the follow-up of patients suffering from neurodegenerative diseases. However, the potentiality of this technique in distinguishing frontotemporal dementia (FTD) subtypes has so far not been investigated. In this study, we explored the usefulness of radiomic features in differentiating FTD subtypes, namely, the behavioral variant of FTD (bvFTD), the non-fluent and/or agrammatic (PNFA) and semantic (svPPA) variants of a primary progressive aphasia (PPA). Classification analyses were performed on 3 Tesla T1-weighted images obtained from the Frontotemporal Lobar Degeneration Neuroimaging Initiative. We included 49 patients with bvFTD, 25 patients with PNFA, 34 patients with svPPA, and 60 healthy controls. Texture analyses were conducted to define the first-order statistic and textural features in cortical and subcortical brain regions. Recursive feature elimination was used to select the radiomics signature for each pairwise comparison followed by a classification framework based on a support vector machine. Finally, 10-fold cross-validation was used to assess classification performances. The radiomics-based approach successfully identified the brain regions typically involved in each FTD subtype, achieving a mean accuracy of more than 80% in distinguishing between patient groups. Note mentioning is that radiomics features extracted in the left temporal regions allowed achieving an accuracy of 91 and 94% in distinguishing patients with svPPA from those with PNFA and bvFTD, respectively. Radiomics features show excellent classification performances in distinguishing FTD subtypes, supporting the clinical usefulness of this approach in the diagnostic work-up of FTD.
Ender (2014) A constructive approach to examination timetabling based on adaptive decomposition and ordering. Annals of Operations Research, 218 (1). pp

In this study, we investigate a constructive local search approach for examination timetabling which employs an adaptive decomposition strategy as its key feature. This strategy automatically divides examinations into diﬃcult and easy sets. The examinations in the diﬃcult set are considered to be hard to place into a timetable slot and hence are listed before the ones in the easy set. Moreover, the examinations within each set are ordered using diﬀerent strategies based on graph colouring heuristics, separately. Initially, the examinations are placed into the easy set. During the construction process, the examinations that cannot be scheduled are identiﬁed as the ones causing infeasibility and are moved forward in the diﬃcult set to ensure earlier assignment than the others for subsequent attempts. On the other hand, the examinations that can be scheduled remain in the easy set. Within the easy set, a new subset called the boundary set is introduced to accommodate shuﬄing strategies to change the given ordering of examinations. The proposed approach, which incorporates diﬀerent ordering and shuﬄing strategies, is explored on the Carter benchmark problems. The empirical results show that its performance is promising and comparable to existing constructive and improvement approaches.
Physician Assisted Death for Psychiatric Suffering: Experiences in the Netherlands

Physician assisted death (PAD) for patients with a psychiatric disorder is a controversial topic of increasing relevance, since a growing number of countries are allowing it. General requirements for PAD include that patients possess decision-making capacity to decide on PAD and that their suffering is unbearable and irremediable. In the Netherlands PAD has been eligible for patients with psychiatric disorders since the 1990s, making it one of the few countries that can offer insights on the practice from real life experience. Much of the literature describing these experiences is only available in Dutch. This article aims to make this knowledge more widely available and provide a comprehensive overview of the experience with PAD for psychiatric suffering in the Netherlands. First, the history of PAD for patients suffering from a psychiatric disorder is described. Second, an overview of relevant rules and regulations governing the practice is given. Third, an overview is provided of the scarce epidemiological data. Finally, we will discuss two major clinical challenges; establishing irremediability and decision-making capacity.
Association Between Nutrition Social Behavior Change Communication and Improved Caregiver Health and Nutrition Knowledge and Practices in Rural Tanzania

Background Efforts to improve infant and young child feeding practices include the use of nutrition behavior change communication among caregivers of children under 5 years. We assessed the association between monthly participation in community-level nutrition group meetings on caregiver health and nutrition knowledge and practices (KPs). Methods Data from a community-based cross-sectional survey conducted in the Eastern and Southern Highland Zones of Tanzania were used. Indices were developed for caregivers' knowledge of nutrition, health and childcare, household (HDD) and young child dietary diversity (CDD), and vitamin A (VA) intakes. The comparison of means and proportions was assessed using Student's t-test and the Chi-square test, respectively, between the caregivers participating in nutrition group meetings and non-participants. The impact of the number of nutrition meeting attendance on caregiver KPs scores was examined using multiple regression. Results Of 547 caregivers surveyed, 49.7% attended nutrition group meetings and received information on nutrition social behavior change communication (SBCC). Overall, 28% of participating women had a moderate level of nutrition knowledge, 62% had a high level of VA knowledge, and 57% had a high level of health and childcare knowledge. Participation in nutrition group meetings was significantly associated with the health and childcare knowledge score (HKS), HDD and CDD scores, and household and young child VA intake; the magnitude of the associations was greater for caregivers who attended at least four meetings. Conclusion The findings emphasize the need for programs that seek to address the issues present in the use of nutrition SBCC at the community level to improve maternal or caregiver KPs and subsequently the nutrition status of infants and young children.
Navigating challenges during Covid-19 pandemic: experiences and coping strategies of Singapore students

ABSTRACT Objectives This study explores the experiences and coping strategies of secondary students as they engaged in learning activities during the pandemic. It investigated the sources of student stress during the pandemic, and the extent to which the pandemic influenced the stress that they usually experience. Method Semi-structured interviews were used to elicit details of the students’ lived experiences as they navigated learning via an online platform, their coping strategies in managing stress. Results With regards to academic experiences, many students found online learning challenging and ineffective and were concerned about their examinations. Under social experiences, many students shared that they missed social and recreational activities during the “circuit breaker”. However, some students demonstrated resilience and were able to see the benefits of going through the pandemic. More students reported academic-related than social-related stress. The students coped with stress in three ways: (1) disengagement, (2) taking active steps and (3) turning to others. Conclusion Academic concerns were a major source of distress among adolescents. Insights that were drawn from the results of the study can be utilized to support students in managing stress and mitigate its adverse effects on student learning and functioning.
Fabrication, Properties, and Biomedical Applications of Calcium-Containing Cellulose-Based Composites

Calcium-containing cellulose-based composites possess the advantages of high mechanical strength, excellent osteoconductivity, biocompatibility, biodegradation, and bioactivity, which represent a promising application system in the biomedical field. Calcium-containing cellulose-based composites have become the hotspot of study of various biomedical fields. In this mini-review article, the synthesis of calcium-containing cellulose-based composites is summarized via a variety of methods such as the biomimetic mineralization method, microwave method, co-precipitation method, hydrothermal method, freeze-drying method, mechanochemical reaction method, and ultrasound method. The development on the fabrication, properties, and applications of calcium-containing cellulose-based composites is highlighted. The as-existed problems and future developments of cellulose-based composites are provided. It is expected that calcium-containing cellulose-based composites are the ideal candidate for biomedical application.
Encoding-based Range Detection in Commodity RFID Systems

RFID technologies have been widely used for item-level object monitoring and tracking in industrial applications. In this paper, we study the problem of range detection in a commodity RFID system, which aims to quickly figure out whether there are any target tags that hold specific data between a lower and upper boundary. This is important to help users pinpoint tagged objects of interest (if any) and give an early warning for reducing the potential risk, e.g., temperature monitoring for fire safety. We propose a time-efficient protocol called encoding range query (EnRQ). The basic idea is to use a sparse vector to separate target tags from the others with a few select commands. The sparse vector is specifically designed by encoding the tag’s data based on notational systems. We implement EnRQ in commodity RFID systems with no need for any hardware modifications. Extensive experiments show that EnRQ can improve the time efficiency by more than 40% on average, compared with the state-of-the-art.