Miracle-dz/UniFAR-FTUs huggingface dataset:
Metacognitive Awareness and Emotional Resilience in Children with Attention Deficit Hyperactivity Disorder

Abstract Background This study explored the metacognitive awareness and emotional resilience levels of children suffering from attention deficit hyperactivity disorder (ADHD) (n=60) with typically developing children (n=30). Methods Measures included Metacognitive Awareness Inventory and Resiliency Scales for Children and Adolescents filled out by participants, the List of Adverse Life Events, Turgay DSM-IV-Based Disruptive Behavior Disorders Scale, and Revised Child Anxiety and Depression Scale—Parent Form filled out by parents. Results Metacognitive awareness and emotional resilience were found to be low in the children with ADHD. Emotional resilience increases as metacognitive awareness increases. Metacognitive awareness decreased in the presence of heightened ADHD, anxiety, and/or depression symptoms expressed by the parents' questionnaires (p < 0.001, r = −0.438; p < 0.001, r = −0.403; and p < 0.001, r = −0.421). Conclusions Findings identified that metacognitive skills and emotional resilience are affected in ADHD.
Winston: Revisiting iterative compilation for WCET minimization

Static Worst-Case Execution Time (WCET) estimation techniques take as input the binary code of a program and output a conservative estimate of its execution time. While compilers, and iterative compilation, usually optimize for the average-case, previous work such as [7, 23] has shown that it is also possible to use existing optimization and iterative compilation techniques to lower the WCET estimates drastically. In this paper, we revisit the use of iterative compilation for WCET minimization and show that previous work can be improved both in terms of complexity and reduction of WCET estimates. In particular, we found that the use of long chains of compilation flags, from a few hundred to a few thousand, allows a significant reduction of WCET estimates, of 35% on average, and up to 70% on some benchmarks, compared to the best compilation level (-O0. -O3) applicable. These gains are significantly better than the reductions of WCET estimates obtained by [7], which, on the same benchmarks and experimental conditions, reduce the WCET estimates by 20% on average.
A Detailed Look at MIMO Performance in 60 GHz WLANs

One of the key enhancements in the upcoming 802.11ay standard for 60 GHz WLANs is the support for simultaneous transmissions of up to 8 data streams via SU- and MU-MIMO, which has the potential to enable data rates up to 100 Gbps. However, in spite of the key role MIMO is expected to play in 802.11ay, experimental evaluation of MIMO performance in 60 GHz WLANs has been limited to date, primarily due to lack of hardware supporting MIMO transmissions at millimeter wave frequencies. In this work, we fill this gap by conducting the first large-scale experimental evaluation of SU- and MU-MIMO performance in 60 GHz WLANs. Unlike previous studies, our study involves multiple environments with very different multipath characteristics. We analyze the performance in each environment, identify the factors that affect it, and compare it against the performance of SISO. Further, we seek to identify factors that can guide beam and user selection to limit the (often prohibitive in practice) overhead of exhaustive search. Finally, we propose two heuristics that perform both user and beam selection with low overhead, and show that they perform close to an Oracle solution and outperform previously proposed approaches in both static and mobile scenarios, regardless of the environment and number of users.
Visual Descriptor Extraction from Patent Figure Captions: A Case Study of Data Efficiency Between BiLSTM and Transformer

Technical drawings used for illustrating designs are ubiquitous in patent documents, especially design patents. Different from natural images, these drawings are usually made using black strokes with little color information, making it challenging for models trained on natural images to recognize objects. To facilitate indexing and searching, we propose an effective and efficient visual descriptor model that extracts object names and aspects from patent captions to annotate benchmark patent Figure datasets. We compared two state-of-the-art named entity recognition (NER) models and found that with a limited number of annotated samples, the BiLSTM-CRF model outperforms the Transformer model by a significant margin, achieving an overall F1 =96.60%. We further conducted a data efficiency study by varying the number of training samples and found that BiLSTM consistently beats the transformer model on our task. The proposed model is used to annotate a benchmark patent Figure dataset. CCS CONCEPTS • Computing methodologies Information extraction.
Pre-trained Transformer-Based Citation Context-Aware Citation Network Embeddings

Academic papers form citation networks wherein each paper is a node and citation relationships between papers are edges. The embeddings of each paper obtained by projecting the citation network into a vector space are called citation network embeddings. Thus far, only a limited number of studies have focused on incorporating information regarding the intent of one paper to cite another paper. We consider citation context, i.e., the text to cite a paper, as a source of information for citation intent, and propose a new method for generating citation context-aware citation network embeddings. We trained SciBERT with our proposed masked paper prediction task in which the model predicts the cited paper from the citing paper and the citation context. In addition, we propose a new loss function that considers not only the citation context but also the neighboring nodes in the citation network. We conducted experiments involving citation-recommendation and paper-classification tasks which we formulated on two existing datasets: FullTextPeer-Read and AASC. For both tasks, the proposed method outperformed hyperdoc2vec, an existing method for citation context-aware citation network embedding; further, it achieved a comparable performance to a state-of-the-art citation network embedding that do not utilize any citation context for paper classification.CCS CONCEPTS• Information systems → Document representation.
Convergence of a greedy algorithm for high-dimensional convex nonlinear problems

In this article, we present a greedy algorithm based on a tensor product decomposition, whose aim is to compute the global minimum of a strongly convex energy functional. We prove the convergence of our method provided that the gradient of the energy is Lipschitz on bounded sets. The main interest of this method is that it can be used for high-dimensional nonlinear convex problems. We illustrate this method on a prototypical example for uncertainty propagation on the obstacle problem.
Fantastic SSD internals and how to learn and use them

This work presents (a) Queenie, an application-level tool that can automatically learn 10 internal properties of block-level SSDs, (b) Kelpie, the learning and analysis results of running Queenie on 21 different SSD models from 7 major SSD vendors, and (c) Newt, a set of storage performance optimization examples that use the learned properties. By bringing numerous observations and unique findings, this work exposes substantial improvement spaces for both SSD users and vendors, enlightening possibilities of unleashing more SSD performance potential and highlighting the necessity of further exploring SSD internals.
Extension of Estermann's theorem to Euler products associated to a multivariate polynomial

Given a multivariate polynomial $h(X_1,.,X_n)$ with integral coefficients verifying an hypothesis of analytic regularity (and satisfying $h(\textbf{0})=1$), we determine the maximal domain of meromorphy of the Euler product $\prod_{p \ \textrm{prime}}h(p^{-s_1},.,p^{-s_n})$ and the natural boundary is precisely described when it exists. In this way we extend a well known result for one variable polynomials due to Estermann from 1928. As an application, we calculate the natural boundary of the multivariate Euler products associated to a family of toric varieties.
Tensor Completion with Nearly Linear Samples Given Weak Side Information

Tensor completion exhibits an interesting computational-statistical gap in terms of the number of samples needed to perform tensor estimation. While there are only Θ(tn) degrees of freedom in a t-order tensor with n^t entries, the best known polynomial time algorithm requires O(n^t/2 ) samples in order to guarantee consistent estimation. In this paper, we show that weak side information is sufficient to reduce the sample complexity to O(n). The side information consists of a weight vector for each of the modes which is not orthogonal to any of the latent factors along that mode; this is significantly weaker than assuming noisy knowledge of the subspaces. We provide an algorithm that utilizes this side information to produce a consistent estimator with O(n^1+κ ) samples for any small constant κ > 0. We also provide experiments on both synthetic and real-world datasets that validate our theoretical insights.
Preparation and In- vitro Evaluation of Baclofen as an Oral Microsponge Tablets

Iraq. Abstract Baclofen (BFN) is a skeletal muscle relaxant used for the treatment of spastic muscle disorder; BFN suffers from short plasma half-life and narrow absorption window. The aim of the present study was to formulate floating effervescent microsponge tablets of BFN for controlling drug release and thereby decrease the side effects of the drug. The microsponges of BFN were prepared by non-aqueous emulsion solvent diffusion method (oil in oil emulsion method). The effects of drug: polymer ratio, stirring time and type of Eudragit polymer on the physical characteristics of microsponges were investigated. The prepared microsponges were characterized for production yield (PY), loading efficiency (LD), particle size, surface morphology, and in vitro drug release. The selected microsponge formula was incorporated into the floating effervescent gastro-retentive tablets. The prepared floating microsponge tablets were evaluated for their hardness, friability, swelling in addition to in vitro drug release. The results showed that the microsponge formula with Eudragit RS100 had optimum physical properties with PY % equal to 97 %, and LD % equal to 81% and controlled drug release (75% of drug release in 8 hr.) when compared with other formulas and pure BFN. Therefore, the non-aqueous emulsion solvent diffusion method is a promising method to produce baclofen
Approximating WCET and Energy Consumption for Fast Multi-Objective Memory Allocation

Worst-Case Execution Time (WCET) is the most important design criterion in the domain of hard real-time systems. Most embedded systems also need to satisfy additional design criteria like, e.g., energy consumption. Performing WCET and energy analyses statically at compile-time can be time-consuming. Consequently, minimizing WCET and energy consumption of the code at the compiler level using multi-objective optimization can be a time-consuming process. In this paper, we propose an approximation model to quickly approximate the WCET and energy consumption of the code at compile-time. Instead of using traditional WCET and energy analyses, we exploit this approximation model to perform ScratchPad Memory (SPM) allocation-based multi-objective optimization. Furthermore, we solve the multi-objective optimization problem using metaheuristic algorithms and explore the trade-offs between WCET and energy consumption. Using the proposed approximation model, we achieved, on average, a 94.12% reduction in compilation time and maintained the quality of the Pareto optimal solutions while performing the multi-objective optimization. Furthermore, the approximation error while using the proposed approximation model was in an acceptable range of 2% - 4% on average.
Breeding of Penta Null Soybean [Glycine max (L.) Merr.] for Five Antinutritional and Allergenic Components of Lipoxygenase, KTI, Lectin, 7S α′ Subunit, and Stachyose

Soybean [Glycine max (L.) Merr. ] is an excellent source of protein, oil, carbohydrates and many other bioactive ingredients for humans. However, several antinutritional and allergenic components such as lipoxygenase, KTI, lectin, 7S α′ subunit, and stachyose exist in the raw mature seed. Genetic removal of these components would be the best method to improve soybean food quality. The objectives of this research were to breed a new soybean line with penta null recessive alleles (lox1/lox1/lox2/lox2/lox3/lox3-ti/ti-le/le-cgy1/cgy1-rs2/rs2) for these five components and to evaluate agronomic traits for a breeding line with penta null alleles. Seven germplasms were used to breed the penta null strain. Analysis of lipoxygenase, KTI, lectin, 7S α′ subunit, and stachyose components in mature seeds was conducted by SDS-PAGE, western blot, and HPLC. One breeding line with penta null recessive alleles was developed. The breeding line has purple flowers, tawny pubescence, a determinate growth habit, and light yellow pods at maturity. The seed of the breeding line has a yellow hilum and yellow seed coat color. The stem height of the breeding line was 53.0 cm. The stachyose content of the breeding line was 2.9 g/kg. The 100-seed weight of the breeding line was 31.1 g and yield (t/ha) was 2.80. This is the first soybean strain with the penta null (lox1lox2lox3/lox1lox2lox3-ti/ti-le/le-cgy1/cgy1-rs2/rs2) genotype (free of lipoxygenase, KTI, lectin, and 7S α′ subunit proteins, and with low stachyose content).
Oral Health, Antimicrobials and Care for Patients With Chronic Oral Diseases – A Review of Knowledge and Treatment Strategies

Periodontal and chronic oral mucosal diseases are significant life impacting conditions which may co-exist and synergistically act to cause more severe and widespread oral pathology with enhanced challenges in effective management. Clinicians regularly observe these effects and struggle to effectively manage both problems in many patients. There is limited understanding of many basic and applied scientific elements underpinning potentially shared aetiopathological features and management. Recent developments in translational science provide an opportunity to greater improve knowledge and subsequently care for patients with these problems.
Knowledge, Attitudes, and Practices Toward the Prevention of COVID-19 in Bangladesh: A Systematic Review and Meta-Analysis

Background Numerous studies on knowledge, attitude, and practice (KAP) about the prevention of COVID-19 infections are available in Bangladeshi contexts, with results that vary significantly. However, no earlier attempt has been made to analyze the available COVID-19 KAP studies in Bangladesh, which is incorporated in this meta-analysis for the first time. Methods Following the PRISMA guidelines, articles relevant to COVID-19 KAP that were conducted among the Bangladeshi population were found in databases such as PubMed, Scopus, CINAHL, Google Scholar, and ResearchGate. Random-effect meta-analysis was used to generate a pooled prevalence of knowledge, attitude, and practice level toward the prevention of COVID-19 infection. Results This review included 18 articles that were published between March 2020 and November 2021. Overall, 89.87% (95% CI: 67.71–97.40) understood about COVID-19 symptoms, 92.09% (95% CI: 84.32–96.18) knew about how it spreads, and 79.51% (95% CI: 59.38–91.15) knew about how to treat it. The public's perception of controlling COVID-19 is mixed, with only 44.16% (95% CI: 35.74–52.93) and 60.28% (95% CI: 49.22–70.38) believing the country would win the struggle against the pandemic and the infection will be successfully controlled, respectively. Although overall COVID-19 preventative practice was good, subgroup analysis found that men had a poor practice toward controlling the infection. The practice of avoiding crowded places (70.15%) and maintaining social distance (77.17%) was found to be satisfactory in institution-based studies. Conclusion The findings of this study revealed that the Bangladeshi population had a good awareness of COVID-19 symptoms, treatment, attitudes, and behaviors. The findings of this study are likely to aid Bangladeshi governments and policymakers in putting evidence into action by identifying gaps and emphasizing the importance of educating the less informed public about COVID-19 transmission.
Endoscopic Screening for Second Primary Tumors of the Esophagus Among Head and Neck Cancer Patients

Malignancies of the head and neck (HN) region and esophagus are among the most common cancers worldwide. Due to exposure to common carcinogens and the theory of field cancerization, HN cancer patients have a high risk of developing second primary tumors (SPTs). In our review of 28 studies with 51,454 HN cancer patients, the prevalence of SPTs was 12%. The HN area is the most common site of SPTs, followed by the lungs and esophagus, and 13% of HN cancer patients have been reported to have esophageal high-grade dysplasia or invasive carcinoma. The prognosis of HN cancer patients with concomitant esophageal SPTs is poor, and therefore identifying esophageal SPTs as early as possible is of paramount importance for risk stratification and to guide the treatment strategy. Image-enhanced endoscopy, especially using narrow-band imaging endoscopy and Lugol’s chromoendoscopy, has been shown to improve the diagnostic performance in detecting esophageal neoplasms at an early stage. Moreover, the early detection and minimally invasive endoscopic treatment of early esophageal neoplasm has been shown to improve the prognosis. Well-designed prospective studies are warranted to establish appropriate treatment and surveillance programs for HN cancer patients with esophageal SPTs.
Cardiometabolic Clinics: Is There a Need for a Multidisciplinary Clinic?

Approximately half a billion people live with diabetes mellitus (DM) worldwide. (1) Additionally, the prevalence of both DM and obesity, a major risk factor for type 2 DM, has doubled by 2015 compared to 1980 (2, 3). Given its high burden of morbidity and complications, DM has been ranked the ninth leading cause of death globally in 2019 (4). Furthermore, diabetes mellitus and obesity co-exist with a nexus of conditions, among others, hypertension, dyslipidemia, coronary artery disease (CAD), heart failure (HF), resulting in what is referred to as cardiometabolic syndrome (CMS) with a recent analysis revealing that half of type 2 DM patients suffers from at least three cardio-renal-metabolic conditions (5). On the other hand, patients with DM are overrepresented in cardiology outpatient clinics, coronary care units, and cardiovascular disease (CVD) remains the leading cause of death within this population. (6) Besides, abnormal glucose regulation is underdiagnosed in the CVD population; a large observational study in Europe has demonstrated that patients with CVD had abnormal glucose regulation in about two-thirds of the cases (7). This situation with multiple systemic conditions impacts the clinical course, quality of life, and long-term survival of patients with DM. Therefore, there is a substantial necessity for cardiometabolic multidisciplinary clinics (CMC) as a forum of collaboration for multiple specialities to achieve optimal CMS management.
The Orexin-A/OX1R System Induces Cell Death in Pancreatic Cancer Cells Resistant to Gemcitabine and Nab-Paclitaxel Treatment

Pancreatic ductal adenocarcinoma (PDAC) represents the fourth cause of cancer-associated death in the West. This type of cancer has a very poor prognosis notably due to the development of chemoresistance when treatments including gemcitabine and Abraxane (Nab-paclitaxel) were prescribed. The identification of new treatment circumventing this chemoresistance represents a key challenge. Previous studies demonstrated that the activation of orexin receptor type 1 (OX1R), which was ectopically expressed in PDAC, by its natural ligand named orexin-A (OxA), led to anti-tumoral effect resulting in the activation of mitochondrial pro-apoptotic mechanism. Here, we demonstrated that OxA inhibited the pancreatic cancer cell (AsPC-1) growth and inhibited the tumor volume in preclinical models as effectively as gemcitabine and Nab-paclitaxel. Moreover, the combination therapy including OxA plus gemcitabine or OxA plus Nab-paclitaxel was additive on the inhibition of cancer cell growth and tumor development. More importantly, the treatment by OxA of chemoresistant tumors to gemcitabine or Nab-paclitaxel obtained by successive xenografts in mice revealed that OxA was able to induce a strong inhibition of tumor development, whereas no OxA resistance was identified in tumors. The OX1R/OxA system might be an innovative and powerful alternative treatment of chemoresistant PDAC.
Interleukin-6 Receptor Blockade can Increase the Risk of Nonalcoholic Fatty Liver Disease: Indications From Mendelian Randomization

Background: Interleukin-6 receptor (IL-6R) blockade has been approved for inflammation-associated diseases and whether it is effective in treating non-alcoholic fatty liver disease (NAFLD) is still unknown. Methods: A target-based Mendelian randomization was performed to appraise whether inhibiting the IL-6 signaling pathway via IL-6R blockade can reduce the risk of NAFLD. The previously established genetic proxy SNP rs2228145 was mainly used to appraise the therapeutic effects and the genetic-predicted circulating IL-6 level was treated as the exposure with ∼30,000 samples. The genetic association between SNP rs2228145 (A > C) and NAFLD was obtained from non-FinnGen GWAS (1,483 cases and 17,781controls) and FinnGen GWAS (894 cases and 217,898 controls). The causal effects were estimated using a Wald ratio method and were combined using a fixed-effects meta-analysis. Furthermore, the SNP rs12048091 was employed as another proxy in the sensitivity analysis. Results: The positive control analysis suggested the SNP rs2228145 can mimic the effects of IL-6R blockade where inhibiting IL-6 signaling can reduce the risk of rheumatoid arthritis [OR = 0.68 (0.58, 0.80)] and coronary heart disease [OR = 0.75 (0.68, 0.84)]. This Mendelian randomization analysis suggested that IL-6R blockade can adversely increase the risk of NAFLD in the non-FinnGen GWAS [OR = 1.99 (1.27, 3.13)] while not significant in the FinnGen consortium. The fixed-effects meta-analysis indicated inhibiting the IL-6 signaling pathway can reduce the risk of NAFLD [OR = 1.80 (1.26, 2.57)]. When including SNP rs12048091 as the genetic instrument, the meta-analysis using two genetic variants also indicated a similar effect on NAFLD [OR = 1.83 (1.32, 2.53)]. There was no heterogeneity in the whole analysis. Conclusion: Our Mendelian randomization suggested inhibiting the IL-6 signaling pathway via IL-6R blockade might increase the risk of NAFLD, suggesting IL-6R should play a protective role in NAFLD.