Miracle-dz/UniFAR-FTUs huggingface dataset:
Profiling Social Sentiment in Times of Health Emergencies with Information from Social Networks and Official Statistics

Social networks and official statistics have become vital sources of information in times of health emergencies. The ability to monitor and profile social sentiment is essential for understanding public perception and response in the context of public health crises, such as the one resulting from the COVID-19 pandemic. This study will explore how social sentiment monitoring and profiling can be conducted using information from social networks and official statistics, and how this combination of data can offer a more complete picture of social dynamics in times of emergency, providing a valuable tool for understanding public perception and guiding a public health response. To this end, a three-layer architecture based on Big Data and Artificial Intelligence is presented: the first layer focuses mainly on collecting, storing, and governing the necessary data such as social media and official statistics; in the second layer, the representation models and machine learning necessary for knowledge generation are built, and in the third layer the previously generated knowledge is adapted for better understanding by crisis managers through visualization techniques among others. Based on this architecture, a KDD (Knowledge Discovery in Databases) framework is implemented using methodological tools such as sentiment analysis, fuzzy 2-tuple linguistic models and time series prediction with the Prophet model. As a practical demonstration of the proposed model, we use tweets as data source (from the social network X, formerly known as Twitter) generated during the COVID-19 pandemic lockdown period in Spain, which are processed to identify the overall sentiment using sentiment analysis techniques and fuzzy linguistic variables, and combined with official statistical indicators for prediction, visualizing the results through dashboards.
Training for generalization in Theory of Mind: a study with older adults

Theory of Mind (ToM) refers to the ability to attribute independent mental states to self and others in order to explain and predict social behavior. Recent research in this area has shown a decline in ToM abilities associated with normal aging that is of a moderate magnitude or greater. Very few studies have investigated whether it is possible to improve older adults’ ToM abilities. The present study was designed to address this gap in the literature by evaluating the impact of a ToM training on practiced and transfer tasks. We provided older adults with a variety of activities designed to facilitate the generalization of benefits to other ToM-demanding tasks. Participants were 63 healthy older adults, native Italian speakers (Mage = 71.44, SD = 5.24, age range: 63–81 years). Participants were randomly assigned to one of two groups: the ToM training (age range: 63–81 years) and the physical-conversation training (age range: 64–81 years). Training effects were measured using the strange stories (practiced task) and the animation task (transfer task). Results revealed the efficacy of the training in producing improvements on practiced but also on transfer tasks.
An open medical imaging workstation architecture for platform-independent 3-D medical image processing and visualization

A need for an entirely new medical workstation design was identified to increase the deployment of 3D medical imaging and multimedia communication. Recent wide acceptance of the World Wide Web (WWW) as a general communication service within the global network has shown how big the impact of standards and open systems can be. Information is shared among heterogeneous systems and diverse applications on various hardware platforms only by agreeing on a common format for information distribution. For medical image communications, the Digital Imaging and Communication in Medicine (DICOM) standard is possibly anticipating such a role. Logically, the next step is open software: platform-independent tools, which can as easily be transferred and used on multiple platforms. Application of the platform-independent programming language Java enables the creation of plug-in tools, which can easily extend the basic system. Performance problems inherent to all interpreter systems can be circumvented by using a hybrid approach. Computationally intensive functions like image processing functions can be integrated into a natively implemented optimized image processing kernel. Plug-in tools implemented in Java can utilize the kernel functions via a Java-wrapper library. This approach is comparable to the implementation of computationally intensive operations in hardware.
Amyloid Beta Resistance in Nerve Cell Lines Is Mediated by the Warburg Effect

Amyloid beta (Aβ) peptide accumulation in the brains of patients with Alzheimer's disease (AD) is closely associated with increased nerve cell death. However, many cells survive and it is important to understand the mechanisms involved in this survival response. Recent studies have shown that an anti-apoptotic mechanism in cancer cells is mediated by aerobic glycolysis, also known as the Warburg effect. One of the major regulators of aerobic glycolysis is pyruvate dehydrogenase kinase (PDK), an enzyme which represses mitochondrial respiration and forces the cell to rely heavily on glycolysis, even in the presence of oxygen. Recent neuroimaging studies have shown that the spatial distribution of aerobic glycolysis in the brains of AD patients strongly correlates with Aβ deposition. Interestingly, clonal nerve cell lines selected for resistance to Aβ exhibit increased glycolysis as a result of activation of the transcription factor hypoxia inducible factor 1. Here we show that Aβ resistant nerve cell lines upregulate Warburg effect enzymes in a manner reminiscent of cancer cells. In particular, Aβ resistant nerve cell lines showed elevated PDK1 expression in addition to an increase in lactate dehydrogenase A (LDHA) activity and lactate production when compared to control cells. In addition, mitochondrial derived reactive oxygen species (ROS) were markedly diminished in resistant but not sensitive cells. Chemically or genetically inhibiting LDHA or PDK1 re-sensitized resistant cells to Aβ toxicity. These findings suggest that the Warburg effect may contribute to apoptotic-resistance mechanisms in the surviving neurons of the AD brain. Loss of the adaptive advantage afforded by aerobic glycolysis may exacerbate the pathophysiological processes associated with AD.
Disparity estimation in stereo videos using spatio-temporal disparity hyperplane models

We propose a method for disparity estimation in stereo video. We address the problems associated with spatially-temporally-correlated disparity variations (STCDV). STCDV problems are caused by complex motions, e.g., yaw-rotation, pan-tilt-zoom camera movements, etc. The key novelty of this study is to introduce a spatio-temporal disparity hyperplane (STDH) model. The proposed STDH model represents a hyperplane defined in four-dimensional space spanned by disparity, image plane, and time coordinates. Our STDH model is represented by surface normals varying with the spatially-temporally-correlated changes in disparity. Thus, our STDH model is effective in estimating disparity in a stereo video including STCDVs. We estimate video disparity by incorporating our STDH model into the PatchMatch brief propagation framework. Our experiments demonstrate that the proposed method outperforms other methods.
γδ Intraepithelial Lymphocyte Migration Limits Transepithelial Pathogen Invasion and Systemic Disease in Mice.

BACKGROUND & AIMS Intraepithelial lymphocytes that express the γδ T-cell receptor (γδ IELs) limit pathogen translocation across the intestinal epithelium by unknown mechanisms. We investigated whether γδ IEL migration and interaction with epithelial cells promote mucosal barrier maintenance during enteric infection. METHODS Salmonella typhimurium or Toxoplasma gondii were administered to knockout (KO) mice lacking either the T cell receptor δ chain (Tcrd) or CD103, or control TcrdEGFP C57BL/6 reporter mice. Intravital microscopy was used to visualize migration of green fluorescent protein (GFP)-tagged γδ T cells within the small intestinal mucosa of mice infected with DsRed-labeled S typhimurium. Mixed bone marrow chimeras were generated to assess the effects of γδ IEL migration on early pathogen invasion and chronic systemic infection. RESULTS Morphometric analyses of intravital video microscopy data showed that γδ IELs rapidly localized to and remained near epithelial cells in direct contact with bacteria. Within 1 hour, greater numbers of T gondii or S typhimurium were present within mucosae of mice with migration-defective occludin KO γδ T cells, compared with controls. Pathogen invasion in Tcrd KO mice was quantitatively similar to that in mice with occludin-deficient γδ T cells, whereas invasion in CD103 KO mice, which have increased migration of γδ T cells into the lateral intercellular space, was reduced by 63%. Consistent with a role of γδ T-cell migration in early host defense, systemic salmonellosis developed more rapidly and with greater severity in mice with occludin-deficient γδ IELs, relative to those with wild-type or CD103 KO γδ IELs. CONCLUSIONS In mice, intraepithelial migration to epithelial cells in contact with pathogens is essential to γδ IEL surveillance and immediate host defense. γδ IEL occludin is required for early surveillance that limits systemic disease.
A cellular genetic algorithm with self-adjusting acceptance threshold

We present a genetic algorithm (GA) whose population possesses a spatial structure. The GA is formulated as a probabilistic cellular automaton: The individuals are distributed over a connected graph and the genetic operators are applied locally in some neighborhood of each individual. By adding a self-organizing acceptance threshold schedule to the proportionate reproduction operator we can prove that the algorithm converges to the global optimum. First results for a multiple knapsack problem indicate a significant improvement in convergence behavior. The algorithm can be mapped easily onto parallel computers.
Research on Remote Sensing Image Compression Based on Lifting Wavelet Transform

The real-time compression of the remote sensing image is one of a problem in urgent need of satellite remote sensing technology, the development of the compression method suitable for real-time remote sensing image has an important theoretical and practical value. In response to this problem, a fast compression method which is fit for remote sensing image is designed based on the features of decomposed image and the statistical analysis of the sub-images. The method uses different processing methods for the every sub-image compression after lifting wavelet. The sub-image with low frequency is compressed lossless by DPCM method, and the improved EZW coding and RLC method was used to compress the sub-images with high frequency. Through extensive experiments, the results show that the new compression method is more effective than the others. In addition, the new compression method is simple, and the memory requirement in the operation process is lower, and it is fit for parallel optimizing progress.
Stress and its association with working efficiency of junior doctors during three postgraduate residency training programs

Background The residency training period in the medical profession is well known for physical and mental stress, which may affect cognitive function and practical life. The aims of this study were to assess prevalence of stress among the resident trainees of the three medical specialties of Saudi Commission for Health Specialties (SCHS) training programs, namely, Internal Medicine, Emergency Medicine, Family Medicine, and their association with training years, sex, and marital status. This study also aimed to correlate the stress levels with the working efficiency and self-perceived general health problems. Participants and methods Resident trainee physicians of SCHS were invited to complete a stress inventory Kessler 10, which is used for stress measurement. Pearson’s chi-square test (χ2) and odds ratios (ORs) were used to quantify the associations between categorical variables. A P-value of <0.05 was considered statistically significant. Results A total of 318 (out of 389, with the response rate of 82%) resident trainees participated in this study. The mean (± standard deviation) age of the study population was 27.9 (±1.6) years. The results showed 70.4% of resident trainees had stressful conditions, which consisted of severe stress: 22.6%, moderate stress: 20.4%, and mild stress: 27.4%. During the 1st year (R-1), moderate stress (OR =5.87; 95% confidence interval =2.93–17.79; P=0.001) and severe stress (OR =11.15; 95% confidence interval =4.35–28.51; P=0.0001) levels were quite high. The highest stress level was found in Emergency Medicine (80.5%), followed by Internal Medicine (73.6%), and Family Medicine (63.2%) (χ2=6.42; P=0.04). The stress level decreased with the increase of years of training in Emergency Medicine (χ2=23.76; P<0.0001) and Internal Medicine (χ2=60.12; P<0.0001), whereas increased in Family Medicine (χ2=11.80; P=0.008). High stress level was significantly associated with absence from duty days (χ2=28.48, P<0.0001), inefficient day activities (χ2=39.15; P<0.0001), and general health problems (χ2=45.27; P<0.0001) of resident trainees. Conclusion We found significantly high levels of stress among the resident trainees of SCHS. High levels of stress may have an effect on their working efficiency and general physical health. The high stress level decreased efficient day activity and made the trainees absent from the workplace.
Faster Eigenvector Computation via Shift-and-Invert Preconditioning

We give faster algorithms and improved sample complexities for estimating the top eigenvector of a matrix $\Sigma$ -- i.e. computing a unit vector $x$ such that $x^T \Sigma x \ge (1-\epsilon)\lambda_1(\Sigma)$: Offline Eigenvector Estimation: Given an explicit $A \in \mathbb{R}^{n \times d}$ with $\Sigma = A^TA$, we show how to compute an $\epsilon$ approximate top eigenvector in time $\tilde O([nnz(A) + \frac{d*sr(A)}{gap^2} ]* \log 1/\epsilon )$ and $\tilde O([\frac{nnz(A)^{3/4} (d*sr(A))^{1/4}}{\sqrt{gap}} ] * \log 1/\epsilon )$. Here $nnz(A)$ is the number of nonzeros in $A$, $sr(A)$ is the stable rank, $gap$ is the relative eigengap. By separating the $gap$ dependence from the $nnz(A)$ term, our first runtime improves upon the classical power and Lanczos methods. It also improves prior work using fast subspace embeddings [AC09, CW13] and stochastic optimization [Sha15c], giving significantly better dependencies on $sr(A)$ and $\epsilon$. Our second running time improves these further when $nnz(A) \le \frac{d*sr(A)}{gap^2}$. Online Eigenvector Estimation: Given a distribution $D$ with covariance matrix $\Sigma$ and a vector $x_0$ which is an $O(gap)$ approximate top eigenvector for $\Sigma$, we show how to refine to an $\epsilon$ approximation using $ O(\frac{var(D)}{gap*\epsilon})$ samples from $D$. Here $var(D)$ is a natural notion of variance. Combining our algorithm with previous work to initialize $x_0$, we obtain improved sample complexity and runtime results under a variety of assumptions on $D$. We achieve our results using a general framework that we believe is of independent interest. We give a robust analysis of the classic method of shift-and-invert preconditioning to reduce eigenvector computation to approximately solving a sequence of linear systems. We then apply fast stochastic variance reduced gradient (SVRG) based system solvers to achieve our claims.
Memory (and Time) Efficient Sequential Monte Carlo

Memory efficiency is an important issue in Sequential Monte Carlo (SMC) algorithms, arising for example in inference of high-dimensional latent variables via Rao-Blackwellized SMC algorithms, where the size of individual particles combined with the required number of particles can stress the main memory. Standard SMC methods have a memory requirement that scales linearly in the number of particles present at all stage of the algorithm. Our contribution is a simple scheme that makes the memory cost of SMC methods depends on the number of distinct particles that survive resampling. We show that this difference has a large empirical impact on the quality of the approximation in realistic scenarios, and also--since memory access is generally slow--on the running time. The method is based on a two pass generation of the particles, which are represented implicitly in the first pass. We parameterize the accuracy of our algorithm with a memory budget rather than with a fixed number of particles. Our algorithm adaptively selects an optimal number of particle to exploit this fixed memory budget. We show that this adaptation does not interfere with the usual consistency guarantees that come with SMC algorithms.
Early Ordovician CA-IDTIMS U–Pb zircon dating and conodont biostratigraphy, Canning Basin, Western Australia

ABSTRACT A continuously cored section of more than 300 m through the Nambeet Formation and the basal part of the conformably overlying Willara Formation in the Olympic 1 petroleum well, drilled in the Canning Basin of northern Western Australia, yields valuable information that increases by more than 40% the number of precise isotopic ages available to constrain the Ordovician Period. New CA-IDTIMS U–Pb zircon ages for seven bentonite layers in the Olympic 1 core are integrated into a new conodont biostratigraphic framework for the Early Ordovician comprising four biozones recognised in this well. The weighted mean U–Pb dates range from 479.37 ± 0.16 Ma within the late Tremadocian Paroistodus proteus conodont Biozone, to 470.18 ± 0.13 Ma near the boundary between the Floian and Dapingian stages within the Jumudontus gananda conodont Biozone. The intervening Prioniodus oepiki–Serratognathus bilobatus conodont Biozone (early Floian) and succeeding Oepikodus communis conodont Biozone (middle Floian) are similarly well constrained by isotopic dates centred on ca 477 Ma for the early Floian and by three ages of 473–471 Ma for the middle Floian. The seven new isotopic dates significantly increase the precision of dating for the Early Ordovician, where previously only two ages with limited or imprecise biostratigraphic control were known globally.
Visualisation by low‐angle shadowing of the leucocyte‐common antigen. A major cell surface glycoprotein of lymphocytes.

The leucocyte‐common antigen (L‐CA) from rat thymocytes is a cell surface glycoprotein of 180 000 apparent mol. wt. with an 80‐kd cytoplasmic domain. This paper reports the molecular dimensions of the molecule visualised by electron microscopy after low‐angle shadowing. The L‐CA monomer consists of a globular head region of approximately 12 nm diameter and a short tail approximately 18 nm long. In deoxycholate both monomers and multimers are seen with aggregation occurring at the head groups. When the detergent is removed, larger clusters are formed with tails extending from a central aggregate. A 100‐kd tryptic fragment of L‐CA that is known to include the extracellular parts of the molecule also exists in monomer and multimer forms and is seen to have a rod‐like structure of length 28 nm without evidence of the head group. Altogether the data indicate that the rod‐like structure is found outside the cell and that the extra sequence that forms the head is inside. The tryptic fragment is likely to be derived by cleavage after the transmembrane sequence.
Comparative evaluation of effectiveness of intra-pocket anesthetic gel and injected local anesthesia during scaling and root planing – A split-mouth clinical trial

Background and Aim: Pain control is an important outcome measure for successful periodontal therapy. Injected local anesthesia has been used to secure anesthesia for scaling and root planing (SRP) and continues to be the anesthetic of choice for pain control. Alternatively, intra-pocket anesthetic gel has been used as an anesthetic during SRP. Hence, this clinical trial was done to compare the effectiveness of intra-pocket anesthetic gel and injected local anesthesia during SRP and also to assess the influence of intra-pocket anesthetic gel on treatment outcomes in chronic periodontitis patients. Materials and Methods: Fifteen systemically healthy chronic periodontitis patients were recruited. The dental quadrants on right side received either intra-pocket 20% benzocaine gel (Gel group) or infiltration/block by 2% lidocaine with 1:80,000 adrenaline (injection group). Quadrants on the left side received the alternative. Pain perception and patients preference for the type of anesthesia was recorded. Clinical parameters: plaque index, modified gingival index, modified sulcular bleeding index, probing pocket depth, and clinical attachment level were recorded at baseline and 1 month after treatment. Results: No difference was observed in visual analog scale (P > 0.05) and verbal rating scale (P > 0.05) pain perception between gel group and injection group. A slightly increased preference to gel as anesthesia (53% vs. 47%) was observed. The treatment outcome after SRP did not show a significant difference between gel and injection group (P > 0.05). Conclusion: Intra-pocket administration of 20% benzocaine gel may be effective for pain control during SRP and may offer an alternative to conventional injection anesthesia.
An Interface for Email Summarization and Categorization

We describe the email summarization interface system we have developed that allows users to summarize and categorize email conversations from email clients such as Microsoft Outlook. The sytem which can be seamlessly integrated into a user’s email client employs a client-server architecture. With the client sending incoming emails to the server for preprocessing, a user can make various on-the-fly requests such as categorization of individual emails, categorization of email threads, summarization of individual emails and summarization of email threads. Summarization can be performed in two modes. For email threads without questionanswer exchanges, extractive summaries are generated. For others, extractive sentences are augmented with sentences from automatically detected question-answer pairs.