Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Behavioral Engagement of Students in the Wild Based on Contextual and Visual Data

To investigate the detection of students' behavioral engagement (On-Task vs. Off-Task), we propose a two-phase approach in this study. In Phase 1, contextual logs (URLs) are utilized to assess active usage of the content platform. If there is active use, the appearance information is utilized in Phase 2 to infer behavioral engagement. Incorporating the contextual information improved the overall F1-scores from 0.77 to 0.82. Our cross-classroom and cross-platform experiments showed the proposed generic and multi-modal behavioral engagement models' applicability to a different set of students or different subject areas.
Investigating epithelial-to-mesenchymal transition with integrated computational and experimental approaches

The transition between epithelial and mesenchymal (EMT) is a fundamental cellular process that plays critical roles in development, cancer metastasis, and tissue wound healing. EMT is not a binary process but involves multiple partial EMT states that give rise to a high degree of cell state plasticity. Here, we first reviewed several studies on theoretical predictions and experimental verification of these intermediate states, the role of partial EMT on kidney fibrosis development, and how quantitative signaling information controls cell commitment to partial or full EMT upon transient signals. Next, we summarized existing knowledge and open questions on the coupling between EMT and other biological processes, such as the cell cycle, epigenetic regulation, stemness, and apoptosis. Taken together, EMT is a model system that has attracted increasing interests for quantitative experimental and theoretical studies.
A Novel Hot Topic Detection Framework With Integration of Image and Short Text Information From Twitter

Twitter exhibits several characteristics, including a limited number of features and noisy text information. Extracting valuable information from Twitter has made hot topic detection a challenging task. In this paper, a novel four-stage framework is proposed to improve the performance of topic detection. Data preprocessing is the first stage. Deep learning is then exploited to enrich short text information via image understanding. Next, improved latent Dirichlet allocation is used to optimize the image effective word pairs, which improves the accuracy of the extracted topic words. Finally, both short text and images are integrated for topic detection, in which the corresponding topics are mined based on fuzzy matching of topic words. A large number of experiments show that the proposed framework significantly improves the performance of topic detection and outperforms the selected baseline methods.
Hierarchical Representations with Poincaré Variational Auto-Encoders

The Variational Auto-Encoder (VAE) model is a popular method to learn at once a generative model and embeddings for data living in a high-dimensional space. In the real world, many datasets may be assumed to be hierarchically structured. Traditionally, VAE uses a Euclidean latent space, but tree-like structures cannot be efficiently embedded in such spaces as opposed to hyperbolic spaces with negative curvature. We therefore endow VAE with a Poincar\'e ball model of hyperbolic geometry and derive the necessary methods to work with two main Gaussian generalisations on that space. We empirically show better generalisation to unseen data than the Euclidean counterpart, and can qualitatively and quantitatively better recover hierarchical structures.
Model-Free Active Input-Output Feedback Linearization of a Single-Link Flexible Joint Manipulator: An Improved ADRC Approach

Traditional Input-Output Feedback Linearization (IOFL) requires full knowledge of system dynamics and assumes no disturbance at the input channel and no system's uncertainties. In this paper, a model-free Active Input-Output Feedback Linearization (AIOFL) technique based on an Improved Active Disturbance Rejection Control (IADRC) paradigm is proposed to design feedback linearization control law for a generalized nonlinear system with known relative degree. The Linearization Control Law(LCL) is composed of a scaled generalized disturbance estimated by an Improved Nonlinear Extended State Observer (INLESO) with saturation-like behavior and the nominal control law produced by an Improved Nonlinear State Error Feedback (INLSEF). The proposed AIOFL cancels in real-time fashion the generalized disturbances which represent all the unwanted dynamics, exogenous disturbances, and system uncertainties and transforms the system into a chain of integrators up to the relative degree of the system, the only information required about the nonlinear system. Stability analysis has been conducted based on Lyapunov functions and revealed the convergence of the INLESO and the asymptotic stability of the closed-loop system. Verification of the outcomes has been achieved by applying the proposed AIOFL technique on the Flexible Joint Single Link Manipulator (SLFJM). The simulations results validated the effectiveness of the proposed AIOFL tool based on IADRC as compared to the conventional ADRC based AIOFL and the traditional IOFL techniques.
Cooperative Multi-Bitrate Video Caching and Transcoding in Multicarrier NOMA-Assisted Heterogeneous Virtualized MEC Networks

Cooperative video caching and transcoding in mobile edge computing (MEC) networks is a new paradigm for future wireless networks, e.g., 5G and beyond-5G, to reduce scarce and expensive backhaul resource usage by prefetching video files within radio access networks (RANs). Integration of this technique with other advent technologies, such as wireless network virtualization and multicarrier non-orthogonal multiple access (MC-NOMA), provides more flexible video delivery opportunities, which leads to enhancements both for the network’s revenue and for the end-users’ service experience. In this regard, we propose a two-phase RAF for a parallel cooperative joint multi-bitrate video caching and transcoding in heterogeneous virtualized MEC (HV-MEC) networks. In the cache placement phase, we propose novel proactive delivery-aware cache placement strategies (DACPSs) by jointly allocating physical and radio resources based on the network stochastic information to exploit flexible delivery opportunities. Then, for the delivery phase, we propose a delivery policy based on user requests and network channel conditions. The optimization problems corresponding to both phases aim to maximize the total revenue of network slices, i.e., virtual networks. Both problems are non-convex and suffer from high-computational complexities. For each phase, we show how the problem can be solved efficiently. We also propose a low-complexity RAF, in which the complexity of the delivery algorithm is significantly reduced. A delivery-aware cache refreshment strategy (DACRS) in the delivery phase is also proposed to tackle the dynamical changes of network stochastic information. The extensive numerical assessments demonstrate a performance improvement of up to 30% for our proposed DACPSs and DACRS over traditional approaches.
The Distinct Effects of Palmitic and Oleic Acid on Pancreatic Beta Cell Function: The Elucidation of Associated Mechanisms and Effector Molecules

In this study, we aimed to identify the mechanisms underlying the different effects of palmitic acid and oleic acid on human pancreatic beta cell function. To address this problem, the oxidative stress, endoplasmic reticulum stress, inflammation, apoptosis and their mediator molecules have been investigated in the insulin releasing beta cells exposed to palmitic and/or oleic acid. Herein, we have demonstrated that in cultured 1.1B4 beta cells oleic acid promotes neutral lipid accumulation and insulin secretion, whereas palmitic acid is poorly incorporated into triglyceride and it does not stimulate insulin secretion from human pancreatic islets at physiologically glucose concentrations. In addition, palmitic acid caused: (1) oxidative stress through a mechanism involving increases in ROS production and MMP-2 protein expression/gelatinolytic activity associated with down-regulation of SOD2 protein; (2) endoplasmic reticulum stress by up-regulation of chaperone BiP protein and unfolded protein response (UPR) transcription factors (eIF2α, ATF6, XBP1u proteins) and by PTP-1B down-regulation in both mRNA and protein levels; (3) inflammation through enhanced synthesis of proinflammatory cytokines (IL6, IL8 proteins); and (4) apoptosis by enforced proteic expression of CHOP multifunctional transcription factor. Oleic acid alone had opposite effects due to its different capacity of controlling these metabolic pathways, in particular by reduction of the ROS levels and MMP-2 activity, down-regulation of BiP, eIF2α, ATF6, XBP1u, CHOP, IL6, IL8 and by SOD2 and PTP-1B overexpression. The supplementation of saturated palmitic acid with the monounsaturated oleic acid reversed the negative effects of palmitic acid alone regulating insulin secretion from pancreatic beta cells through ROS, MMP-2, ATF6, XBP1u, IL8 reduction and SOD2, PTP-1B activation. Our findings have shown the protective action of oleic acid against palmitic acid on beta cell lipotoxicity through promotion of triglyceride accumulation and insulin secretion and regulation of some effector molecules involved in oxidative stress, endoplasmic reticulum stress, inflammation and apoptosis.
Evaluating Weaknesses of “Perceptual-Cognitive Training” and “Brain Training” Methods in Sport: An Ecological Dynamics Critique

The recent upsurge in “brain training and perceptual-cognitive training,” proposing to improve isolated processes, such as brain function, visual perception, and decision-making, has created significant interest in elite sports practitioners, seeking to create an “edge” for athletes. The claims of these related “performance-enhancing industries” can be considered together as part of a process training approach proposing enhanced cognitive and perceptual skills and brain capacity to support performance in everyday life activities, including sport. For example, the “process training industry” promotes the idea that playing games not only makes you a better player but also makes you smarter, more alert, and a faster learner. In this position paper, we critically evaluate the effectiveness of both types of process training programmes in generalizing transfer to sport performance. These issues are addressed in three stages. First, we evaluate empirical evidence in support of perceptual-cognitive process training and its application to enhancing sport performance. Second, we critically review putative modularized mechanisms underpinning this kind of training, addressing limitations and subsequent problems. Specifically, we consider merits of this highly specific form of training, which focuses on training of isolated processes such as cognitive processes (attention, memory, thinking) and visual perception processes, separately from performance behaviors and actions. We conclude that these approaches may, at best, provide some “general transfer” of underlying processes to specific sport environments, but lack “specificity of transfer” to contextualize actual performance behaviors. A major weakness of process training methods is their focus on enhancing the performance in body “modules” (e.g., eye, brain, memory, anticipatory sub-systems). What is lacking is evidence on how these isolated components are modified and subsequently interact with other process “modules,” which are considered to underlie sport performance. Finally, we propose how an ecological dynamics approach, aligned with an embodied framework of cognition undermines the rationale that modularized processes can enhance performance in competitive sport. An ecological dynamics perspective proposes that the body is a complex adaptive system, interacting with performance environments in a functionally integrated manner, emphasizing that the inter-relation between motor processes, cognitive and perceptual functions, and the constraints of a sport task is best understood at the performer-environment scale of analysis.
Robustness of Nutrient Signaling Is Maintained by Interconnectivity Between Signal Transduction Pathways

Systems biology approaches provide means to study the interplay between biological processes leading to the mechanistic understanding of the properties of complex biological systems. Here, we developed a vector format rule-based Boolean logic model of the yeast S. cerevisiae cAMP-PKA, Snf1, and the Snf3-Rgt2 pathway to better understand the role of crosstalk on network robustness and function. We identified that phosphatases are the common unknown components of the network and that crosstalk from the cAMP-PKA pathway to other pathways plays a critical role in nutrient sensing events. The model was simulated with known crosstalk combinations and subsequent analysis led to the identification of characteristics and impact of pathway interconnections. Our results revealed that the interconnections between the Snf1 and Snf3-Rgt2 pathway led to increased robustness in these signaling pathways. Overall, our approach contributes to the understanding of the function and importance of crosstalk in nutrient signaling.
Mycobacterium caprae Infection of Red Deer in Western Austria–Optimized Use of Pathology Data to Infer Infection Dynamics

Austria is officially bovine tuberculosis (TB) free, but during the last decade the west of the country experienced sporadic TB cases in cattle. Free-ranging red deer are known to be the maintenance host of Mycobacterium (M.) caprae in certain areas in Austria, where cattle can become infected on alpine pastures shared with deer. The epidemiology of TB in deer in alpine regions is still poorly understood. To inform decisions on efficient interventions against TB in deer, a method is needed to better capture the infection dynamics on population level. A total of 4,521 free-ranging red deer from Austria's most western Federal state Vorarlberg were TB-tested between 2009 and 2018. M. caprae was confirmed in samples from 257 animals. Based on descriptions of TB-like lesions, TB positive animals were categorized with a newly developed lesion score called “Patho Score. ” Analyses using this Patho Score allowed us to distinguish between endemic, epidemic and sporadic TB situations and revealed different roles of subgroups of infected deer in infection dynamics. Overall, deer in poor condition, deer of older age and stags were the subgroups that were significantly more often TB positive (p = 0.02 or smaller for all subgroups). Deer in poor condition (p < 0.001) and stags (p = 0.04) also showed more often advanced lesions, indicating their role in mycobacterial spread. TB was never detected in fawns, while hinds were the subgroup that showed the fewest advanced lesions. Analysis of outbreaks of TB and lesion development in yearlings provided some evidence for the role of winter feeding as a source for increased infection transmission. Sporadic cases in TB-free areas appear to precede outbreaks in these areas. These currently TB-free areas should receive particular attention in sampling schemes to be able to detect early spreading of the infection. The Patho Score is a quick, easy-to-apply and reproducible tool that provides new insights on the epidemiology of TB in deer at population level and is flexible enough to relate heterogeneous wildlife monitoring data collected following different sampling plans. This lesion score was used for systematic assessment of infection dynamics of mycobacterial infections.
Small Molecule Modulators of the Circadian Molecular Clock With Implications for Neuropsychiatric Diseases

Circadian rhythms regulate many biological processes and play fundamental roles in behavior, physiology, and metabolism. Such periodicity is critical for homeostasis because disruption or misalignment of the intrinsic rhythms is associated with the onset and progression of various human diseases and often directly leads to pathological states. Since the first identification of mammalian circadian clock genes, numerous genetic and biochemical studies have revealed the molecular basis of these cell-autonomous and self-sustainable rhythms. Specifically, these rhythms are generated by two interlocking transcription/translation feedback loops of clock proteins. As our understanding of these underlying mechanisms and their functional outputs has expanded, strategies have emerged to pharmacologically control the circadian molecular clock. Small molecules that target the molecular clock may present novel therapeutic strategies to treat chronic circadian rhythm-related diseases. These pharmaceutical approaches may include the development of new drugs to treat circadian clock-related disorders or combinational use with existing therapeutic strategies to improve efficacy via intrinsic clock-dependent mechanisms. Importantly, circadian rhythm disruptions correlate with, and often precede, many symptoms of various neuropsychiatric disorders such as sleep disorders, affective disorders, addiction-related disorders, and neurodegeneration. In this mini-review, we focus on recent discoveries of small molecules that pharmacologically modulate the core components of the circadian clock and their potential as preventive and/or therapeutic strategies for circadian clock-related neuropsychiatric diseases.
The Super-Donor Phenomenon in Fecal Microbiota Transplantation

Fecal microbiota transplantation (FMT) has become a highly effective bacteriotherapy for recurrent Clostridium difficile infection. Meanwhile the efficacy of FMT for treating chronic diseases associated with microbial dysbiosis has so far been modest with a much higher variability in patient response. Notably, a number of studies suggest that FMT success is dependent on the microbial diversity and composition of the stool donor, leading to the proposition of the existence of FMT super-donors. The identification and subsequent characterization of super-donor gut microbiomes will inevitably advance our understanding of the microbial component of chronic diseases and allow for more targeted bacteriotherapy approaches in the future. Here, we review the evidence for super-donors in FMT and explore the concept of keystone species as predictors of FMT success. Possible effects of host-genetics and diet on FMT engraftment and maintenance are also considered. Finally, we discuss the potential long-term applicability of FMT for chronic disease and highlight how super-donors could provide the basis for dysbiosis-matched FMTs.
Discurso visual de las enfermedades raras: encuadres latentes.

Prevalence of rare diseases is 5 cases to every 10,000 inhabitants. In Spain over 3 million people have been diagnosed one of these minority disorders, many of which have a genetic origin and are highly disabling. These disorders have become a growing public health concern, resulting in increasing social and media interest in them in the last years. This research is aimed at analysing visual representation of patients suffering from these minority disorders through the pictures published in the Spanish national press. The visual framing theory is considered suitable to reveal the
Impact of Ocean Acidification on the Energy Metabolism and Antioxidant Responses of the Yesso Scallop (Patinopecten yessoensis)

Ocean acidification (OA), which is caused by increasing levels of dissolved CO2 in the ocean, is a major threat to marine ecosystems. Multiple lines of scientific evidence show that marine bivalves, including scallops, are vulnerable to OA due to their poor capacities to regulate extracellular ions and acid-based status. However, the physiological mechanisms of scallops responding to OA are not well understood. In this study, we evaluated the effects of 45 days of exposure to OA (pH 7.5) on the energy metabolism and antioxidant capability of Yesso scallops. Some biochemical markers related to energy metabolism (e.g., content of glycogen and ATP, activity of ATPase, lactate dehydrogenase, glutamate oxaloacetate transaminase, and glutamate-pyruvate transaminase), antioxidant capacity (e.g., reactive oxygen species level, activity of superoxide dismutase, and catalase) and cellular damage (e.g., lipid peroxidation level) were measured. Our results demonstrate that the effects of the reduced pH (7.5) on scallops are varied in different tissues. The energy reserves are mainly accumulated in the adductor muscle and hepatopancreas. Yesso scallops exhibit energy modulation by increasing lactate dehydrogenase activities to stimulate anaerobic metabolism. The highly active Na+/K+-ATPase and massive ATP consumption in the mantle and gill indicate that a large amount of energy was allocated for the ion regulation process to maintain the acid-base balance in the reduced-pH environment. Moreover, the increase in the reactive oxygen species level and the superoxide dismutase and catalase activities in the gill and adductor muscle, indicate that oxidative stress was induced after long-term exposure to the reduced-pH environment. Our findings indicate that the effects of OA are tissue-specific, and physiological homeostasis could be modulated through different mechanisms for Yesso scallops.
Subcontractor selection with additive ratio assessment method

During the last decades, especially in large-scale construction projects, it is one of the widely applied strategies that the main contractors work with many subcontractors and overtake a large part of the works. This trend brings out the problem of selection of subcontractors. The classical approaches in the construction industry to select the subcontractor are the general practice reference, the lowest bid, and the familiarity. This creates major risks for contractors since the construction sector involves time-limited projects with a large variety of complex works. Putting the subcontractor selection on a scientific basis and minimizing the risks by choosing the most appropriate subcontractor among the bidders for a particular type of work, require for the construction industry to determine not only consistent and efficient but also uncomplicated and plain model. Instead of the widespread conventional application, this study represents a new alternative approach to the subcontractor selection with Additive Ratio Assessment Method, which is one of the multi-criteria decision-making techniques. Additive Ratio Assessment Method is quite practical and convenient to use among the other multi-criteria decision-making methods. This study aimed to demonstrate the use of Additive Ratio Assessment Method on sub-contractor selection problems by exemplifying a real case application.