Miracle-dz/UniFAR-FTUs huggingface dataset:
GRWD1-WDR5-MLL2 Epigenetic Complex Mediates H3K4me3 Mark and Is Essential for Kaposi’s Sarcoma-Associated Herpesvirus-Induced Cellular Transformation

By performing a genome-wide CRISPR-Cas9 screening, we have identified cellular epigenetic regulators that are essential for KSHV-induced cellular transformation. Among them, GRWD1 regulates epigenetic active mark H3K4me3 by interacting with WDR5 and MLL2 and recruiting them to chromatin loci of specific genes in KSHV-transformed cells. ABSTRACT Infection by Kaposi’s sarcoma-associated herpesvirus (KSHV) is causally associated with numerous cancers. The mechanism of KSHV-induced oncogenesis remains unclear. By performing a CRISPR-Cas9 screening in a model of KSHV-induced cellular transformation of primary cells, we identified epigenetic regulators that were essential for KSHV-induced cellular transformation. Examination of TCGA data sets of the top 9 genes, including glutamate-rich WD repeat containing 1 (GRWD1), a WD40 family protein upregulated by KSHV, that had positive effects on cell proliferation and survival of KSHV-transformed cells (KMM) but not the matched primary cells (MM), uncovered the predictive values of their expressions for patient survival in numerous types of cancer. We revealed global epigenetic remodeling including H3K4me3 epigenetic active mark in KMM cells compared to MM cells. Knockdown of GRWD1 inhibited cell proliferation, cellular transformation, and tumor formation and caused downregulation of global H3K4me3 mark in KMM cells. GRWD1 interacted with WD repeat domain 5 (WDR5), the core protein of H3K4 methyltransferase complex, and several H3K4me3 methyltransferases, including myeloid leukemia 2 (MLL2). Knockdown of WDR5 and MLL2 phenocopied GRWD1 knockdown, caused global reduction of H3K4me3 mark, and altered the expression of similar sets of genes. Transcriptome sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) analyses further identified common and distinct cellular genes and pathways that were regulated by GRWD1, WDR5, and MLL2. These results indicate that KSHV hijacks the GRWD1-WDR5-MLL2 epigenetic complex to regulate H3K4me3 methylation of specific genes, which is essential for KSHV-induced cellular transformation. Our work has identified an epigenetic complex as a novel therapeutic target for KSHV-induced cancers. IMPORTANCE By performing a genome-wide CRISPR-Cas9 screening, we have identified cellular epigenetic regulators that are essential for KSHV-induced cellular transformation. Among them, GRWD1 regulates epigenetic active mark H3K4me3 by interacting with WDR5 and MLL2 and recruiting them to chromatin loci of specific genes in KSHV-transformed cells. Hence, KSHV hijacks the GRWD1-WDR5-MLL2 complex to remodel cellular epigenome and induce cellular transformation. Since the dysregulation of GRWD1 is associated with poor prognosis in several types of cancer, GRWD1 might also be a critical driver in other viral or nonviral cancers.
Study on the Application of High Precision Strain Acquisition System Based on Twin-Constant-Current Source

Aiming at the shortcomings of the constant voltage source strain acquisition system, the paper put forward a new strain acquisition technology based on the double-side half-bridge measurement of the constant current source. It has demonstrated and analyzed the advantages of constant current source circuit using for strain collection, and has raised the design of multi-channel strain acquisition system. Lab test and running in a large fan blade deformation tests showed that the strain acquisition system had high measurement precision, stability, anti-interference and reliability.
Delving into gender gap perceptions of computing students: A replication study.

Gender gap in Computer Science has been studied from different dimensions although little research has been done in terms of subjective perception, which is essential to develop inclusive and diverse environments. The most relevant works in this context is the one by García-Holgado and collaborators [8, 9], who have developed the GENCE instrument to identify the perception of computing students about issues related to gender and diversity [10]. Such instrument has been used in a pilot study, which has been replicated in our university to improve external validity of the results. This paper describes the whole replication process, in which some previous results are confirmed, and some new findings are obtained.
Conceptual Design of a New Methodology Based on Intelligent Systems Applied to the Determination of the User Experience in Ambulances

The assessment of the satisfaction of patients in Healthcare environments is an increasingly active and influencing field when making decisions and improving the services offered by Health services. Since the beginning of the 21 st Century, and especially in the face of health alerts such as the current one that began in February 2020, the collection, weighting and assessment of the patients’ satisfaction is a key factor to guarantee the evolution and continuous improvement of the services being delivered to them. In this work, a novel methodology based in intelligent systems is defined and conceptualized, aiming to provide answers to the need for a metric of the patient’s satisfaction level with specific Health services –ambulance services in this case. To do that, it is proposed to combine expert systems that are in charge of assessing the measurable data from the ambulance trip, with natural language processors focused on the classification of the opinions written by the ambulance users themselves. The combination of those metrics will make possible to determine a quantifiable indicator of the patient’s satisfaction which, after being integrated into the information system and complemented with a decision-support system, will help the managers to adopt measures aimed to the optimization and improvement of the service under consideration.
Main geophysical techniques used for non-destructive evaluation in cultural built heritage: a review

Geophysical methodologies have been implemented, tested and validated as diagnostic and / or monitoring tools in artworks or historical monuments. They are non-destructive and can give an image of internal structure of investigated medium. This paper is a review about the main geophysical techniques applied to the study of cultural built heritage (excluding the archaeology field). A brief description of the used methodologies is presented, the main investigations done in this field are showed, the method or methods most appropriate to answer each problem (moisture detection, characterization of the materials, study of the structural continuity of the material, assessment of intervention’s effectiveness) are indicated and the main advances and gaps and future developments are also pointed out.
Service robotics in logistic automation: ROBOLIFT: vision based autonomous navigation of a conventional fork-lift for pallet handling

The paper describes an integrated mobile robot which has been designed and realised on top of a conventional fork lift carrier, to perform autonomous missions as well as to keep all the conventional drive actuators for the human driver. The most challenging goal of the project has been to provide the vehicle with the sensory capability and local intelligence, which is typical of the human driver, without altering the conventional driving control, such as the pedal control of the accelerator (forward and backward), the emergency brake, the direct steering wheel control. Computer vision is proved to be the main sensory system for both autonomous navigation and pallet recognition. ROBOLIFT is the result of a joint co-operation between Elsag Bailey Telerobot and Fiat OM Carrelli Elevatori SpA.
Intercultural competencies development for professional collaboration: a systematic literature mapping from 2016 to 2021: a systematic literature mapping from 2016 to 2021

∗Undoubtedly, we live in an increasingly interconnected world, where physical borders have ceased to impede interrelationships and collaborative work of people coming together to solve various global problems. This raises the question: how can we promote effective collaboration among professionals with different cultural references? This article aims to share the evidence analyses published from 2016 to July 2021 about forming intercultural competencies to promote professional collaboration. The method was a systematic mapping of the literature in the Scopus and Web of Science databases, with 325 articles identified from the search strings. The findings show that this collaborative work is relevant in academic studies, and English-speaking countries mainly produce research in this area. The most recurrent context for the research is higher education, and the primary competency present in the inquiries is intercultural communication. This systematic mapping provides a framework for identifying less significant challenges and contexts also, such as assessing learning and the influence these competencies exert on global and multicultural collaborations. The mapping also establishes a database of studies that can support future studies in this line of research.
Determining the Rumour Stance with Ensemble Method Based on BSAF Model

With the development of social platforms, the public can easily access lots of online information and express personal opinions. However, various unconfirmed rumors are flooding on social networks and leading public opinion which caused serious social problems. In view of this, scholars pay more and more attention to the research of rumors, such as the rumor stance classification. The rumor stance classification task aims to determine the stance of the target tweet about specific social media posts. The stance is divided into four categories: support, deny, query and comment. SemEval-2019 Task7 provided a dataset of dubious posts and ensuing conversations in social network which annotated the stance and accuracy of posts and subsequent conversations. We proposed a ensemble method based on BSAF model for the rumor stance classification. Pre-processed the original data and extracted the word-level features and tweet-level features of the target tweet are the first step. The pre-training model uses the fine-tuned BERT model to enrich semantic information and the key words are labeled via the self-attention mechanism. Finally the stance of target tweet is predicted with tweet vector, word-level features and tweet-level features. A number of BSAF models are obtained by adjusting the training parameters. According to the results of the validation set, the excellent BSAF model is added to the ensemble to predict the stance of target tweet of test set. In experiments, the ensemble method based on BSAF model has achieved the state-of-the-art results in F1-macro score and accuracy.
Digital resources online for physical activity and entertainment during the COVID-19 lockdown: a case of study in Spain

ACM Reference Format: González-González, Carina, Guerra-Balic, Myriam, Sansano-Nadal, Oriol, and López-Dóriga, Adriana. 2021. Digital resources online for physical activity and entertainment during the COVID-19 lockdown: a case of study in Spain. In Ninth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM’21), October 26–29, 2021, Barcelona, Spain. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3486011.3486446
Using Contextual Text Mining Algorithm to Analysis Yearly Trend for Population Ageing and Declining Fertility with Government Science and Technology Projects in Taiwan

∗ The growth of the world population has been steadily slowing down, primarily owing to an almost worldwide decline of fertility and ageing of population. In Taiwan, the fertility rate is experiencing long-term downtrends, and consequently, ageing of their populations. In view of this, the purpose of this paper is to analyze the yearly trend for population ageing and declining fertility. We proposed the yearly trend analysis based on contextual text mining methods from government science and technology projects to extract the Chinese pattern and word about the population ageing and declining fertility. The government science and technology projects, which archives research projects sponsored by government, are retrieved from Government Research Bulletin (GRB) from 1981 to April 2021. Then, the two issue of policy “Major trends and the importance of issues” and “Policies and action plans” combine the population ageing and declining fertility with yearly trend are explored and discussed. The obtained results can be analyzed the yearly trend about fertility rate, elderly population, and youth workforce with population ageing and declining fertility on the first policy issue “Major trends and the importance of issues”. And it can also be analyzed the yearly trend about formulates the policies and
A proposal for using active contour parametrical models in Cobb angle determination

∗Scoliosis is a spinal deformity that affects a large number of patients in its different modalities. One of the most-used characterizing metrics for scoliosis is known as the Cobb angle, which quantifies the degree of severity in the curvature of the patient’s spine. This angle has been traditionally calculated by hand, and while nowadays that calculation is computer-assisted, it is not free of the variability caused by the measurement procedures. Aiming to solve this issue and to provide an automated approach to the determination of the Cobb angle, in this paper the use of active contour parametric models is proposed for that determination, by combining these models with measurement algorithms. By implementing this combination into a programming environment, a model has been defined that, starting from an X-ray image, after its graphical processing it identifies the active contours associated to the spine and then determines the polynomial function associated to their mean profile, from which it is possible to calculate the Cobb angle by means of simple trigonometrical operations. With that, the usefulness and potential utility of the proposed model have been clearly established, inviting to carry out a deeper comparative case study that will allow to properly assess the use of this measurement methodology.
Empathy, creativity, and feelings using a modern board game: A learning experience valued by physiotherapy students

This study aimed at understanding how physiotherapy students perceive a modern board game experience as an opportunity to train socioemotional skills. Twenty physiotherapy students participated in a learning experience using the Telestration game and were assessed in terms of: game-based self-perceived experience; game’s serious dimension. The facilitator’s perceptionswere also accounted for. Students learned creative expression skills (85% students characterized a true/strong creative experience; 90% expressed a strong feeling of “freedom of experimentation”) and were considered immersed and emotionally involved (significant association between understanding game’s serious purposes and emotional relationship with experience, p-value=0.01). Telestration was classified as a relevant learning method for other serious purposes (>50% students revealed inttention to use Telestration for other serious purposes). Therefore, physiotherapy students self-rated this experience with the Telestration game as significant for learning relevant socioemotional skills. Additionally, facilitator’s perceptions confirmed that they were perfectly immersed and emotionally involved in this learning experience. Future studies in this topic are needed, including larger samples and students from different health courses. Future studies in this topic are needed, including larger samples and students from different health courses.
Quí-Bot-H2O Challenge: Integration of computational thinking with chemical experimentation in early ages including gender, inclusive and diversity patterns

This multidisciplinary and interdisciplinary project is developed with the main objective of increasing interest in science and technology among children and young people in an inclusive way, breaking stereotypes and invisible social and gender barriers. In order to reduce the gender gap in technical careers, the social aspect of robotics applied to chemistry is highlighted at early ages. Quí-Bot-H2O Project has been included in the gender equality lines of action of the two references territorial public administrations for UPC Manresa (Bages County Council in its III Gender Equality Plan and the Manresa City Council in the II Gender Equality Plan). Quí-Bot-H2O challenge is supported by the Spanish Ministry of Economy and Competitiveness under Grant FECYT2021-15626, Line of action 2. Education and scientific vocations (2nd place out of 120 awarded).
Dynamic control of the N queueing network with application to shipbuilding

The US shipbuilding industry faces challenges of building ships on time and within budgeted cost. We introduce an operational flexibility to shipbuilding to improve the system control. We model the flexible ship production system as an ‘N’ queueing network. However, the ‘N’ network model still lacks effective and computationally lightweight policies, especially with non-preemption. We use a Markov Decision Process (MDP) to gain structural insights into the optimal control policy. We develop a state dependent Optimal Threshold policy and benchmark it against other policies to show its excellent robustness and effectiveness. Our extensive test suite shows that (1) the Optimal Threshold policy performs the best in all the heuristics we tested; and (2) the cost of the system under control of this threshold policy is very close to the optimal cost calculated by the MDP. To calculate the exact optimal threshold level is difficult; therefore, we develop a birth-death process to determine a Analytical threshold level. Based on the optimal threshold values over a large test suite, we refine the analytical threshold level using a second-order regression model. We find the performance of the Regression Threshold policy to be within a few percent of optimal.
Laboratory and numerical experiments on the near wake of a sphere in a stably stratified ambient

Abstract The flow around and behind a sphere in a linear density gradient has served as a model problem for both body-generated wakes in atmospheres and oceans, and as a means of generating a patch of turbulence that then decays in a stratified ambient. Here, experiments and numerical simulations are conducted for 20 values of Reynolds number, $Re$, and internal Froude number, $Fr$, where each is varied independently. In all cases, the early wake is affected by the background density gradient, notably in the form of the body-generated lee waves. Mean and fluctuating quantities do not reach similar states, and their subsequent evolution would not be collapsible under any universal scaling. There are five distinguishable flow regimes, which mostly overlap with previous literature based on qualitative visualisations and, in this parameter space, they maintain their distinguishing features up to and including buoyancy times of 20. The possible relation of the low $\{Re, Fr\}$ flows to their higher $\{Re, Fr\}$ counterparts is discussed.
Optimal short-term scheduling for a large-scale cascaded hydro system

This paper describes a short term hydro generation optimization program that has been developed by the Hydro Electric Commission (HEC) to determine optimal generation schedules and to investigate export and import capabilities of the Tasmanian system under a proposed DC interconnection with mainland Australia. The optimal hydro scheduling problem is formulated as a large scale linear programming algorithm and is solved using a commercially-available linear programming package. The selected objective function requires minimization of the value of energy used by turbines and spilled during the study period. Alternative formulations of the objective function are also discussed. The system model incorporates the following elements: hydro station (turbine efficiency, turbine flow limits, penstock head losses, tailrace elevation and generator losses), hydro system (reservoirs and hydro network: active volume, spillway flow, flow between reservoirs and travel time), and other models including thermal plant and DC link. A valuable by-product of the linear programming solution is system and unit incremental costs which may be used for interchange scheduling and short-term generation dispatch. <<ETX>>
The Role of AI in Characterizing the DCM Phenotype

Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and dysfunction in the absence of coronary disease. Emerging evidence suggests many patients remain vulnerable to major adverse outcomes despite clear therapeutic success of modern evidence-based heart failure therapy. In this era of personalized medical care, the conventional assessment of left ventricular ejection fraction falls short in fully predicting evolution and risk of outcomes in this heterogenous group of heart muscle disease, as such, a more refined means of phenotyping this disease appears essential. Cardiac MRI (CMR) is well-placed in this respect, not only for its diagnostic utility, but the wealth of information captured in global and regional function assessment with the addition of unique tissue characterization across different disease states and patient cohorts. Advanced tools are needed to leverage these sensitive metrics and integrate with clinical, genetic and biochemical information for personalized, and more clinically useful characterization of the dilated cardiomyopathy phenotype. Recent advances in artificial intelligence offers the unique opportunity to impact clinical decision making through enhanced precision image-analysis tasks, multi-source extraction of relevant features and seamless integration to enhance understanding, improve diagnosis, and subsequently clinical outcomes. Focusing particularly on deep learning, a subfield of artificial intelligence, that has garnered significant interest in the imaging community, this paper reviews the main developments that could offer more robust disease characterization and risk stratification in the Dilated Cardiomyopathy phenotype. Given its promising utility in the non-invasive assessment of cardiac diseases, we firstly highlight the key applications in CMR, set to enable comprehensive quantitative measures of function beyond the standard of care assessment. Concurrently, we revisit the added value of tissue characterization techniques for risk stratification, showcasing the deep learning platforms that overcome limitations in current clinical workflows and discuss how they could be utilized to better differentiate at-risk subgroups of this phenotype. The final section of this paper is dedicated to the allied clinical applications to imaging, that incorporate artificial intelligence and have harnessed the comprehensive abundance of data from genetics and relevant clinical variables to facilitate better classification and enable enhanced risk prediction for relevant outcomes.
Dual-band bandpass filter using embedded spiral resonator and broadside-coupled meander slot-line

A dual-band bandpass filter with high selectivity is proposed. The filter is composed of two parts: 1. two embedded spiral resonators with a non 0°-feed coupled scheme, 2. a broadside-coupled meander slot-line. This structure can introduce seven transmission zeros to achieve strong passband selectivity and good stopband rejection. Based on the structure, a dual-band bandpass filter is fabricated to operate at the WLAN bands (i.e. 2.4/5.2 GHz).