Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional Speed Reserve as a Proxy for the Anaerobic Speed Reserve Using the Critical Speed Concept

Background. Although maximal sprint speed (MSS) and the anaerobic speed reserve (ASR) provides valuable information about an athletes' speed profile, these parameters fall short of providing important information about submaximal metabolic thresholds. The only field test that can offer an estimate of a sub-maximal metabolic threshold is the 3-minute all-out test for running (3MT), which delivers three parameters of interest: the critical speed (CS), fatigability constant (D'), and 3MT-specific maximal running speed (MS 3MT ). Objectives. We offer an alternative to the ASR, termed the 'functional' speed reserve (FSR). Therefore, this study's purpose was two-fold: firstly, to compare MSS to MS 3MT and FSR to ASR, and secondly, to determine the correlations between ASR, FSR, and D'. Methods. Thirty-two participants volunteered for the study (age: 22.50 ± 4.32 years; height: 1.67 ± 0.78 m; body mass: 66.58 ± 11.30 kg) and completed a graded exercise test (GXT), 3MT, and 40-m sprint test following familiarization bouts for each test. Results. MSS and MS 3MT were strongly correlated (r = 0.93, p < 0.001). The ASR and FSR were also strongly correlated (r = 0.77, p < 0.05), with the FSR also showing a strong correlation with D’ (r = 0.77, P < 0.05). Conclusion. The 3MT provides a viable, arguably more ecological alternative to the ASR (i.e., FSR) and provides additional parameters such as CS, D', and MS3MT. Field testing based on the 3MT can offer coaches and athletes unique performance insights and tools to program and effectively prescribe training interventions.
Machine Learning-Based Identification of Potentially Novel Non-Alcoholic Fatty Liver Disease Biomarkers

Non-alcoholic fatty liver disease (NAFLD) is a chronic liver disease that presents a great challenge for treatment and prevention. This study aims to implement a machine learning approach that employs such datasets to identify potential biomarker targets. We developed a pipeline to identify potential biomarkers for NAFLD that includes five major processes, namely, a pre-processing step, a feature selection and a generation of a random forest model and, finally, a downstream feature analysis and a provision of a potential biological interpretation. The pre-processing step includes data normalising and variable extraction accompanied by appropriate annotations. A feature selection based on a differential gene expression analysis is then conducted to identify significant features and then employ them to generate a random forest model whose performance is assessed based on a receiver operating characteristic curve. Next, the features are subjected to a downstream analysis, such as univariate analysis, a pathway enrichment analysis, a network analysis and a generation of correlation plots, boxplots and heatmaps. Once the results are obtained, the biological interpretation and the literature validation is conducted over the identified features and results. We applied this pipeline to transcriptomics and lipidomic datasets and concluded that the C4BPA gene could play a role in the development of NAFLD. The activation of the complement pathway, due to the downregulation of the C4BPA gene, leads to an increase in triglyceride content, which might further render the lipid metabolism. This approach identified the C4BPA gene, an inhibitor of the complement pathway, as a potential biomarker for the development of NAFLD.
Feasibility and Acceptability of Tele-Colposcopy on the Caribbean Coast of Nicaragua: A Descriptive Mixed-Methods Study

Background: Cervical cancer, a preventable cancer of disparities, is the primary cause of cancer death for women in Nicaragua. Clinics and personnel in rural and remote Nicaragua may not be accessible to perform recommended screening or follow-up services. Objective: To assess acceptability and feasibility of integrating innovations for high-quality screening and treatment follow-up (tele-colposcopy) into existing pathways on Nicaragua's Caribbean Coast within the context of the National Cervical Cancer Control Program. Methods: Provider focus groups, key informant interviews, and environmental scans were conducted for 13 clinics on the Caribbean Coast of Nicaragua. Topics discussed included a smartphone-based mobile colposcope (MobileODT hardware and mobile platform), mobile connectivity capacity, clinic resources, provider acceptability, and current diagnostic and clinical protocols. We tested device connectivity through image upload availability and real-time video connection and simulated clinical encounters utilizing MobileODT and a low-cost cervical simulator. We developed a database of colposcopic images to establish feasibility of integrating this database and clinical characteristics into the cervical cancer registry. Results: Provider acceptability of integrating tele-colposcopy into existing cancer control efforts was high. Image upload connectivity varied by location (mean = 1 h 9 min). Most clinics had running water (84.6%) and consistent electricity (92.3%), but some did not have access to landline telephones (53.8%). Conclusions: As faster connectivity becomes available in remote settings, Mobile Health tools such as tele-colposcopy will be increasingly feasible to provide access to high-quality cervical cancer follow-up. World Health Organization guidance on integrating technology into existing programs will remain important to ensure programmatic efficacy, local relevance, and sustainability.
Propagation Measurement of a Pedestrian Tunnel at 24 GHz for 5G Communications

In this paper, we report the results of a field measurement campaign carried out inside a pedestrian tunnel at 24 GHz in two conditions, namely, empty tunnel scenario and busy tunnel scenario with pedestrian movement. The experiment measures the fading effects of various groups of pedestrian crowds using directional antennas at the transmitter and receiver for millimeter-wave radio communications. Having presented and analyzed the measurement data in several diverse scenarios, we have further investigated human scattering effects in the crowded pedestrian tunnel and performed ray-tracing simulation for an empty pedestrian tunnel condition. Because tunnel is an enveloped scenario that is not bound by any geographic areas, the results of this study can be applied to a wider scenario like other pedestrian tunnels across the globe. Above all, these findings contribute towards ensuring wireless connectivity for everyone even in a remote scenario like underground passages.
Oceanic nutrient rise and the late Miocene inception of Pacific oxygen-deficient zones

Significance Oxygen is critical to marine ecosystems. The ocean contains oxygen-deficient zones (ODZs) that have been expanding over the past several decades. Predicting future changes in ocean deoxygenation is important for marine ecosystems and human societies that rely on fisheries. Understanding the history of the ocean's oxygen content can provide important insights into how ODZs will behave in the future with climate change and increasing anthropogenic nutrient inputs. In this study, we found that the largest ODZs on our planet were much smaller eight million years ago than they are today. Furthermore, our observations revealed that the expansion of the ODZs was mainly driven by increasing oceanic nutrient content and primary productivity. This finding provides valuable context for ocean deoxygenation processes in the modern and future ocean.
56.4: Invited Paper: New‐Technology Light Sources for Projection Displays

Virtually all projectors sold for professional or consumer applications use HID lamps as a light source. The most common lamps are ultra‐high pressure mercury lamps for most applications and xenon lamps for high‐end applications. New light sources including lasers, LEDs and microwave‐powered electrodeless lamps are challenging the dominance of HID lamps. This paper highlights the advantages and limitations of projection light sources, including example applications.
Lifetime predictions of miniature fuses and semiconductor protection fuses

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
An empirical research on the relationship between human capital and innovative capability: A study on Taiwan's commercial banks

This study reveals the relationships between human capital and innovative capability. It also suggests that the larger the commercial banks’ human capital, the stronger the innovative capability. The implication is that enterprises should cultivate high human capital rather than simply treating employees as costs. For different levels of employees, the required capabilities clearly differ. Therefore, the leaders’ characteristics, and the open-mindedness, vision and execution of core employees are more significant than for low-level employees. This research is focused on the banking industry rather than the high technology or manufacturing industry, and it is believed the findings will be beneficial to developing countries, such as Latin American countries or Asian Pacific countries.
Electricity Spot Prices Forecasting Based on Ensemble Learning

Efficient modeling and forecasting of electricity prices are essential in today’s competitive electricity markets. However, price forecasting is not easy due to the specific features of the electricity price series. This study examines the performance of an ensemble-based technique for forecasting short-term electricity spot prices in the Italian electricity market (IPEX). To this end, the price time series is divided into deterministic and stochastic components. The deterministic component that includes long-term trends, annual and weekly seasonality, and bank holidays, is estimated using semi-parametric techniques. On the other hand, the stochastic component considers the short-term dynamics of the price series and is estimated by time series and various machine learning algorithms. Based on three standard accuracy measures, the results indicate that the ensemble-based model outperforms the others, while the random forest and ARMA are highly competitive.
The Determinants of Design Applications in Europe

In this article we estimate the level of “Design Application” in 37 European Countries in the period 2010-2019. We use data from the European Innovation Scoreboard-EIS of the European Commission. We perform four econometric models i.e., Pooled OLS, Panel Data with Random Effects, Panel Data with Fixed Effects, Dynamic Panel. We found that the level of Design Applications is negatively associated to “Enterprise Births”, “Finance and Support”, “Firm Investments” and positively associated with “Venture Capital”, “Turnover share large enterprises”, “R&D expenditure public sector”, “Intellectual Assets”. In adjunct we perform a cluster analysis with the application of the k-Means algorithm optimized with the Silhouette Coefficient and we found three different clusters. Finally, we confront eight different machine learning algorithms to predict the level of “Design Application” and we found that the Tree Ensemble is the best predictor with a value for the 30% of the dataset analyzed that is expected to decrease in mean of -12,86%.
An NB-ANN based Fusion Approach for Disease Genes Prediction and LFKH-ANFIS Classifier for Eye Diseases Identification

A key step to apprehend the mechanisms of cells related to a particular disease is the disease gene identification. Computational forecast of disease genes are inexpensive and also easier compared to biological experiments. Here, an effectual deep learning-centered fusion algorithm called Naive BayesArtificial Neural Networks (NB-ANN) is proposed aimed at disease gene identification. Additionally, this paper proposes an effectual classifier, namely Levy Flight Krill herd (LFKH) based Adaptive Neuros-Fuzzy Inferences System (ANFIS), for the prediction of eye disease that are brought about by the human disease genes. Utilizing this technique, completely '10' disparate sorts of eye diseases are identified. The NB-ANN includes these ‘4’ steps: a) construction of ‘4’ Feature Vectors (FV), b) selection of negative data, c) training of FV utilizing NB, and d) ANN aimed at prediction. The LFKH-ANFIS undergoes Feature Extraction (FE), Feature Reduction (FR), along with classification for eye disease prediction. The experimental outcomes exhibit that method’s efficiency with regard to precision and recall. Keywords—Disease gene identification; eye disease identification; deep learning; adaptive neuro-fuzzy inferences system (ANFIS); levy flight based krill herd (LFKH); principle component analysis (PCA)
Measuring and Evaluating ICT Use: Developing an Instrument for Measuring Student ICT Use

Teaching and learning in the 21st Century requires teachers and students to capitalise upon the relative advantage of integrating Information and Communication Technologies (ICT) to enhance current curriculum, pedagogy and assessment approaches, as well as transform teaching and learning. While most educational systems agree that ICT has the potential to transform teaching and learning, attention has been given recently to the challenge of how to measure and evaluate the impact ICT is having on teaching and learning. This Chapter argues that the most important focus in measuring ICT use needs to be on student use of ICT, as policies and teacher professional development initiatives by themselves are insufficient to ensure that student learning is either enhanced or transformed through ICT use. Insights are provided into the development of a contemporary instrument, for use by Education Queensland, Australia, which aims to measure teacher perceptions of the quantity and quality of student use (as opposed to teacher use) of ICT in the curriculum. The instrument enables teachers and schools to identify their current and preferred levels of student ICT use, and from this, to generate discussion about the integration and transformational potential of ICT and to develop strategic plans to achieve their preferred level of student use. This Chapter also provides summaries of the implementation of the instrument in two large Queensland education systems, and argues that ICT research, such as this approach, which enables large scale, evidence-based research to measure student outcomes as a result of using ICT in the curriculum should be a matter of priority to effectively monitor and manage learning with ICT.
F3D: Accelerating 3D Convolutional Neural Networks in Frequency Space Using ReRAM

3D convolutional neural networks (CNNs) are widely deployed in video analysis. Fast algorithms such as fast Fourier transforms (FFTs) are gaining popularity in reducing computation complexity for their superior capability of replacing convolutions with simpler element-wise multiplications. Conventional frequency-domain dedicated accelerators employ memory hierarchy organization for high throughput but at the expensive costs of a significant amount of data movements and energy consumptions. This paper presents F3D, a processingin-memory frequency-domain accelerator using resistive random access memory (ReRAM). F3D supports frequency-domain complex number multiplications directly in ReRAM-based crossbar architecture. We alleviate the overheads of redundant data movements in ReRAM-based complex number multiplications by data reuse and the inherent symmetry of inputs in the frequency space. Evaluation results demonstrate that F3D outperforms state-of-the-art accelerators with significant improvements in performance and energy efficiency.
Anti-Obesity Effect of α-Cubebenol Isolated from Schisandra chinensis in 3T3-L1 Adipocytes

The efficacy of α-cubebenol isolated from Schisandra chinensis has been studied in several diseases, including cecal ligation, puncture challenge-induced sepsis, and degranulation of neutrophils. To identify the novel functions of α-cubebenol on lipid metabolism, alterations on the regulation of lipogenesis, lipolysis, and inflammatory response were observed in 3T3-L1 adipocytes treated with α-cubebenol. Most lipogenic targets, including lipid accumulation, level of lipogenic transcription factors, and expression of lipogenic regulators, were suppressed in MDI (3-isobutyl-1-methylxanthine, dexamethasone, and insulin)-stimulated 3T3-L1 adipocytes treated with α-cubebenol without significant cytotoxicity. In addition, similar inhibition effects were observed in the iNOS-induced COX-2 mediated pathway and NLRP3 inflammasome pathway of MDI-stimulated 3T3-L1 cells treated with α-cubebenol. Lipolytic targets, such as cAMP concentration, expression of adenylyl cyclase and PDE4, and their downstream signaling pathway, in MDI-stimulated 3T3-L1 cells were stimulated by the α-cubebenol treatment. The levels of transcription factors and related proteins for β-oxidation were significantly higher in the MDI + α-cubebenol treated group than in the MDI + Vehicle treated group. These results show that α-cubebenol has a novel role as a lipogenesis inhibitor, lipolysis and β-oxidation stimulator, and inflammasome suppressor in MDI-stimulated 3T3-L1 adipocytes.
Calcium Phosphate-Coated Lipid Nanoparticles as a Potential Tool in Bone Diseases Therapy

The treatment of bone diseases (including osteoporosis, osteoarthritis, and bone cancer) often results in reduced efficiency and/or adverse reactions due to the fact that it is not specifically targeted to the site of action. The employment of a suitable carrier should increase drug location to the site of bone disease. The purpose of this study is to prepare and characterize lipid nanoparticles (NPs) coated with calcium phosphate (CaP-NPs). A coating method, to date used only to obtain liposomes covered with CaP, is herein partially-modified to prepare CaP-coated lipid NPs. An extensive physico-chemical characterization was achieved by employing several techniques (DLS, SEM and TEM, and both combined with EDS, XRD, and FTIR) that confirmed the feasibility of the developed coating method. Preliminary uptake studies on human osteosarcoma cells (U-2OS) were performed by entrapping, as a lipid probe, Sudan Red III in NPs. The obtained data provided evidence that CaP-NPs showed higher cell accumulation than uncoated NPs. This result may have important implications for the development of drug loaded CaP-NPs to be tested in vitro with a view of planning future treatment of bone diseases, and indicate that CaP-NPs are potential vehicles for selective drug delivery to bone tissue.
Energy and Expenditure Aware Data Replication Strategy

Energy saving is a major challenge for Information Technology (IT) companies that aim to reduce their carbon footprint while providing large scale cloud services. These companies often rely on data replication technique in order to satisfy tenant's objectives, e.g., performance, especially with the increasing volume of data distributed throughout the world. In this paper, we propose a static and multi objective data replication strategy (E2ARS) that aims to reduce both energy consumption and expenditure of the provider. E2ARS leverages on cloud heterogeneity and energy efficient technologies. We first compare different policies of our strategy, from only taking energy consumption into account to only taking expenditure into account. Unsurprisingly, the more you want to reduce the energy consumption, the less you replicate. Then, we compare E2ARS with strategies from the literature. E2ARS reduces both energy consumption and expenditure where those strategies satisfy only one of the two objectives.
Practical Applications of Set-Based Concurrent Engineering in Industry

Set-Based Concurrent Engineering is sometimes seen as a means to dramatic improvements in product design processes. In spite of its popularity in literature, the number of reported applications has so far been limited. This paper adds new information by describing implementations of Set-Based Concurrent Engineering in four product developing companies. The research took a case study approach, with the objective to investigate if the principles of Set-Based Concurrent Engineering can improve the efficiency and the effectiveness of the development process. The study shows that set-based projects can be driven within an existing organization, if given proper support. The participants claim that a set-based approach has a positive effects on development performance, especially on the level of innovation, product cost and performance. The improvements were achieved at the expense of slightly higher development costs and longer lead time. However, the positive effects are dominating and the companies involved intend to use Set-Based Concurrent Engineering in future projects when appropriate.
Power Generation, Operation, and Control

Topics considered include characteristics of power generation units, transmission losses, generation with limited energy supply, control of generation, and power system security. This book is a graduate-level text in electric power engineering as regards to planning, operating, and controlling large scale power generation and transmission systems. Material used was generated in the post-1966 period. Many (if not most) of the chapter problems require a digital computer. A background in steady-state power circuit analysis is required.
An Examination of Interactive Whiteboard Perceptions using the Concerns-Based Adoption Model Stages of Concern and the Apple Classrooms of Tomorrow Model of Instructional Evolution.

Practical Application Two high school mathematics teachers who use Interactive Whiteboards (IWBs) in the classroom were interviewed annually over the course of three years regarding their perceptions of the technology. During the third year, the two teachers were asked to complete the Concerns-based Adoption Model Stages of Concern Questionnaire. The data obtained from the questionnaire and their responses to the annual interviews were then compared, contrasted and evaluated with results from the Apple Classrooms of Tomorrow (ACOT) study, the ACOT Stages of Instructional Evolution and the Apple Classrooms of Tomorrow – Today (ACOT2) principles. This study’s findings indicate that IWBs provide some of the same benefits as the multitude of computers and other technologies available in ACOT classrooms: increased student motivation, more dynamic instruction and greater teacher collaboration. Unlike the ACOT technologies, however, IWBs did not lead to the implementation of more project-based instruction.
InFoBERT: Zero-Shot Approach to Natural Language Understanding Using Contextualized Word Embedding

Natural language understanding is an important task in modern dialogue systems. It becomes more important with the rapid extension of the dialogue systems’ functionality. In this work, we present an approach to zero-shot transfer learning for the tasks of intent classification and slot-filling based on pre-trained language models. We use deep contextualized models feeding them with utterances and natural language descriptions of user intents to get text embeddings. These embeddings then used by a small neural network to produce predictions for intent and slot probabilities. This architecture achieves new state-of-the-art results in two zero-shot scenarios. One is a single language new skill adaptation and another one is a cross-lingual adaptation.