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The Internet of Medical Things (IoMT) combines medical devices and applications that use network technologies to connect healthcare information systems (HIS). IoMT is reforming the medical industry by adopting information and communication technologies (ICTs). Identity verification, secure collection, and exchange of medical data are essential in health applications. In this study, we implemented a hybrid security solution to secure the collection and management of personal health data using Spring Framework (SF), Services for Sensitive Data (TSD) as a service platform, and Hyper-Text-Transfer-Protocol (HTTP (H)) security methods. The adopted solution (SFTSDH = SF + TSD + H) instigated the following security features: identity brokering, OAuth2, multifactor authentication, and access control to protect the Microservices Architecture Application Programming Interfaces (APIs), following the General Data Protection Regulation (GDPR). Moreover, we extended the adopted security solution to develop a digital infrastructure to facilitate the research and innovation work in the electronic health (eHealth) section, focusing on solution validation with theoretical evaluation and experimental testing. We used a web engineering security methodology to achieve and explain the adopted security solution. As a case study, we designed and implemented electronic coaching (eCoaching) prototype system and deployed the same in the developed infrastructure to securely record and share personal health data. Furthermore, we compared the test results with related studies qualitatively for the efficient evaluation of the implemented security solution. The SFTSDH implementation and configuration in the prototype system have effectively secured the eCoach APIs from an attack in all the considered scenarios. The eCoach prototype with the SFTSDH solution effectively sustained a load of (≈) 1000 concurrent users in the developed digital health infrastructure. In addition, we performed a qualitative comparison among the following security solutions: SF security, third-party security, and SFTSDH, where SFTSDH showed a promising outcome.

In this paper, two planar Frequency Selective Surfaces (FSS) with dissimilar configurations along with monopole antenna exhibiting dual-band response at 3 GHz and 5.5 GHz is presented. One of the surfaces with two reflectors is reflective at 5.5 GHz and transmissive at 3 GHz, whereas the response is opposite for the FSS in another flat reflector. Accordingly the antenna exhibits directive radiation at both the frequencies, however in two opposite directions. Unit cell of the FSS at 3 GHz is on the order of $\lambda _{\mathrm {g}}$ /11, leading to low-profile design. With different orientations of the reflectors, beamwidths at 3 GHz and 5.5 GHz are different leading to different peak gains of 7.1 dBi and 12.2 dBi respectively. The composite antenna-FSS with a dimension on the order of $1.1\lambda \times 1.1\lambda \times 0.2\lambda $ exhibits diverse beam radiation. The radiation at 3 GHz can be used in applications involving wide coverage area, whereas at 5.5 GHz the antenna can be used in applications involving smaller beamwidths such as satellite communication, Ground Penetrating Radar etc.

BackgroundAutomatic e-coaching may motivate individuals to lead a healthy lifestyle with early health risk prediction, personalized recommendation generation, and goal evaluation. Multiple studies have reported on uninterrupted and automatic monitoring of behavioral aspects (such as sedentary time, amount, and type of physical activity); however, e-coaching and personalized feedback techniques are still in a nascent stage. Current intelligent coaching strategies are mostly based on the handcrafted string messages that rarely individualize to each user’s needs, context, and preferences. Therefore, more realistic, flexible, practical, sophisticated, and engaging strategies are needed to model personalized recommendations. ObjectiveThis study aims to design and develop an ontology to model personalized recommendation message intent, components (such as suggestion, feedback, argument, and follow-ups), and contents (such as spatial and temporal content and objects relevant to perform the recommended activities). A reasoning technique will help to discover implied knowledge from the proposed ontology. Furthermore, recommendation messages can be classified into different categories in the proposed ontology. MethodsThe ontology was created using Protégé (version 5.5.0) open-source software. We used the Java-based Jena Framework (version 3.16) to build a semantic web application as a proof of concept, which included Resource Description Framework application programming interface, World Wide Web Consortium Web Ontology Language application programming interface, native tuple database, and SPARQL Protocol and Resource Description Framework Query Language query engine. The HermiT (version 1.4.3.x) ontology reasoner available in Protégé 5.x implemented the logical and structural consistency of the proposed ontology. To verify the proposed ontology model, we simulated data for 8 test cases. The personalized recommendation messages were generated based on the processing of personal activity data in combination with contextual weather data and personal preference data. The developed ontology was processed using a query engine against a rule base to generate personalized recommendations. ResultsThe proposed ontology was implemented in automatic activity coaching to generate and deliver meaningful, personalized lifestyle recommendations. The ontology can be visualized using OWLViz and OntoGraf. In addition, we developed an ontology verification module that behaves similar to a rule-based decision support system to analyze the generation and delivery of personalized recommendation messages following a logical structure. ConclusionsThis study led to the creation of a meaningful ontology to generate and model personalized recommendation messages for physical activity coaching.

Abstract The gravitational dynamics of a collapsing matter configuration which is simultaneously radiating heat flux is studied in f(R) gravity. Three particular functional forms in f(R) gravity are considered to show that it is possible to envisage boundary conditions such that the end state of the collapse has a weak singularity and that the matter configuration radiates away all of its mass before collapsing to reach the central singularity.

Nod-Like Receptor (NLR) is the largest family of Pathogen Recognition Receptors (PRRs) that patrols the cytosolic environment. NLR engagement drives caspase-1 activation that cleaves pro-IL-1B which then gets secreted. Released IL-1B recruits immune cells to the site of infection/injury. Caspase-1 also cleaves Gasdermin-D (GSDM-D) that forms pores within the plasma membrane driving inflammatory cell death called pyroptosis. NLRP3 is the most extensively studied NLR. The NLRP3 gene is encoded by 9 exons, where exon 1 codes for pyrin domain, exon 3 codes for NACHT domain, and Leucine Rich Repeat (LRR) domain is coded by exon 4-9. Exon 2 codes for a highly disorganized loop that connects the rest of the protein to the pyrin domain and may be involved in NLRP3 regulation. The NLRP3 inflammasome is activated by many structurally divergent agonists of microbial, environmental, and host origin. Activated NLRP3 interacts with an adaptor protein, ASC, that bridges it to pro-Caspase-1 forming a multi-protein complex called inflammasome. Dysregulation of NLRP3 inflammasome activity is a hallmark of pathogenesis in several human diseases, indicating its highly significant clinical relevance. In this review, we summarize the existing knowledge about the mechanism of activation of NLRP3 and its regulation during activation by infectious and sterile triggers.

The impact of rise in ambient temperature is not confined to output; it has an impact on the work performance of human beings associated with occupational activities in informal sector, especially those carried out in the open field under the sky. The agricultural workers are constrained to work manually all through the day irrespective of disparity in working situation existing in the working environment. Hence, there is an urgent need to study the cardiac performance status in terms of indicators of physiological strain of the human resources. In this backdrop, the present study has been undertaken to assess the degree of physiological strain in male food crop cultivators’ (age range 24 - 36 years) engaged in manual threshing (separating the grains from the rice straw by manually - by hand i.e. beating method) during paddy cultivation time. Moreover the magnitude of physiological strain was significantly higher (P < 0.5) during “Boro” type of paddy cultivating time. The result of the study indicated that human resources are indeed subjected to strains, albeit to different degree, as adjudged by the indicators of physiological strain.

BackgroundDigital interventions have tremendous potential to improve well-being and health care conveyance by improving adequacy, proficiency, availability, and personalization. They have gained acknowledgment in interventions for the management of a healthy lifestyle. Therefore, we are reviewing existing conceptual frameworks, digital intervention approaches, and associated methods to identify the impact of digital intervention on adopting a healthier lifestyle. ObjectiveThis study aims to evaluate the impact of digital interventions on weight management in maintaining a healthy lifestyle (eg, regular physical activity, healthy habits, and proper dietary patterns). MethodsWe conducted a systematic literature review to search the scientific databases (Nature, SpringerLink, Elsevier, IEEE Xplore, and PubMed) that included digital interventions on healthy lifestyle, focusing on preventing obesity and being overweight as a prime objective. Peer-reviewed articles published between 2015 and 2020 were included. We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and a framework for an evidence-based systematic review. Furthermore, we improved the review process by adopting the Rayyan tool and the Scale for the Assessment of Narrative Review Articles. ResultsOur initial searches identified 780 potential studies through electronic and manual searches; however, 107 articles in the final stage were cited following the specified inclusion and exclusion criteria. The identified methods for a successful digital intervention to promote a healthy lifestyle are self-monitoring, self-motivation, goal setting, personalized feedback, participant engagement, psychological empowerment, persuasion, digital literacy, efficacy, and credibility. In this study, we identified existing conceptual frameworks for digital interventions, different approaches to provide digital interventions, associated methods, and execution challenges and their impact on the promotion of healthy lifestyle management. ConclusionsThis systematic literature review selected intervention principles (rules), theories, design features, ways to determine efficient interventions, and weaknesses in healthy lifestyle management from established digital intervention approaches. The results help us understand how digital interventions influence lifestyle management and overcome the existing shortcomings. It serves as a basis for further research with a focus on designing, developing, testing, and evaluating the generation of personalized lifestyle recommendations as a part of digital health interventions.

The theory of fractional calculus is attracting a lot of attention from mathematicians as well as physicists. The fractional generalisation of the well-known ordinary calculus is being used extensively in many fields, particularly in understanding stochastic process and fractal dynamics. In this paper, we apply the techniques of fractional calculus to study some specific modifications of the geometry of submanifolds. Our generalisation is applied to extend the Israel formalism which is used to glue together two spacetimes across a timelike, spacelike or a null hypersurface. In this context, we show that the fractional extrapolation leads to some striking new results. More precisely we demonstrate that, in contrast to the original Israel formalism, where many spacetimes can only be joined together through an intermediate thin hypersurface admitting effective matter fields violating standard energy conditions, the fractional generalisation allows these spacetimes to be smoothly sewed together without any such requirements on the stress tensor of the matter fields. We discuss the ramifications of these results for spacetime structure and the possible implications for gravitational physics.

Copyright of Journal of Sport & Health Research is the property of Journal of Sport & Health Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Sport & Health Research is the property of Journal of Sport & Health Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Heterogeneity is a problem in storing and exchanging data in a digital health information system (HIS) following semantic and structural integrity. The existing literature shows different methods to overcome this problem. Fast healthcare interoperable resources (FHIR) as a structural standard may explain other information models, (e.g., personal, physiological, and behavioral data from heterogeneous sources, such as activity sensors, questionnaires, and interviews) with semantic vocabularies, (e.g., Systematized Nomenclature of Medicine—Clinical Terms (SNOMED-CT)) to connect personal health data to an electronic health record (EHR). We design and develop an intuitive health coaching (eCoach) smartphone application to prove the concept. We combine HL7 FHIR and SNOMED-CT vocabularies to exchange personal health data in JavaScript object notion (JSON). This study explores and analyzes our attempt to design and implement a structurally and logically compatible tethered personal health record (PHR) that allows bidirectional communication with an EHR. Our eCoach prototype implements most PHR-S FM functions as an interoperability quality standard. Its end-to-end (E2E) data are protected with a TSD (Services for Sensitive Data) security mechanism. We achieve 0% data loss and 0% unreliable performances during data transfer between PHR and EHR. Furthermore, this experimental study shows the effectiveness of FHIR modular resources toward flexible management of data components in the PHR (eCoach) prototype.

Copyright of International Journal of Medicine & Science of Physical Activity & Sport / Revista Internacional de Medicina y Ciencias de la Actividad Física y del Deporte is the property of Revista Internacional de Medicina y Ciencias de la Actividad Fisica y del Deporte and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Skeleton extraction from 3D plant point cloud data is an essential prior for myriads of phenotyping studies. Although skeleton extraction from 3D shapes have been studied extensively in the computer vision and graphics literature, handling the case of plants is still an open problem. Drawbacks of the existing approaches include the zigzag structure of the skeleton, nonuniform density of skeleton points, lack of points in the areas having complex geometry structure, and most importantly the lack of biological relevance. With the aim to improve existing skeleton structures of state-of-the-art, we propose a stochastic framework which is supported by the biological structure of the original plant (we consider plants without any leaves). Initially we estimate the branching structure of the plant by the notion of β-splines to form a curve tree defined as a finite set of curves joined in a tree topology with certain level of smoothness. In the next phase, we force the discrete points in the curve tree to move toward the original point cloud by treating each point in the curve tree as a center of Gaussian, and points in the input cloud data as observations from the Gaussians. The task is to find the correct locations of the Gaussian centroids by maximizing a likelihood. The optimization technique is iterative and is based on the Expectation Maximization (EM) algorithm. The E-step estimates which Gaussian the observed point cloud was sampled from, and the M-step maximizes the negative log-likelihood that the observed points were sampled from the Gaussian Mixture Model (GMM) with respect to the model parameters. We experiment with several real world and synthetic datasets and demonstrate the robustness of the approach over the state-of-the-art.

In this study, we implemented an integrated security solution with Spring Security and Keycloak open-access platform (SSK) to secure data collection and exchange over microservice architecture application programming interfaces (APIs). The adopted solution implemented the following security features: open authorization, multi-factor authentication, identity brokering, and user management to safeguard microservice APIs. Then, we extended the security solution with a virtual private network (VPN), Blowfish and crypt (Bcrypt) hash, encryption method, API key, network firewall, and secure socket layer (SSL) to build up a digital infrastructure. To accomplish and describe the adopted SSK solution, we utilized a web engineering security method. As a case study, we designed and developed an electronic health coaching (eCoach) prototype system and hosted the system in the expanded digital secure infrastructure to collect and exchange personal health data over microservice APIs. We further described our adopted security solution’s procedural, technical, and practical considerations. We validated our SSK solution implementation by theoretical evaluation and experimental testing. We have compared the test outcomes with related studies qualitatively to determine the efficacy of the hybrid security solution in digital infrastructure. The SSK implementation and configuration in the eCoach prototype system has effectively secured its microservice APIs from an attack in all the considered scenarios with 100% accuracy. The developed digital infrastructure with SSK solution efficiently sustained a load of (≈)300 concurrent users. In addition, we have performed a qualitative comparison among the following security solutions: Spring-based security, Keycloak-based security, and their combination (our utilized hybrid security solution), where SSK showed a promising outcome.

Abstract Quasilocal formulations of black hole are of immense importance since they reveal the essential and minimal assumptions required for a consistent description of black hole horizon, without relying on the asymptotic boundary conditions on fields. Using the quasilocal formulation of Isolated Horizons, we construct the Hamiltonian charges corresponding to local Lorentz transformations on a spacetime admitting isolated horizon as an internal boundary. From this construction, it arises quite generally that the area of the horizon of an isolated black hole is the Hamiltonian charge for local Lorentz boost on the horizon. Using this argument further, it is shown that, observers at a fixed proper distance $$l_{0}$$ l0 , very close to the horizon, may define a notion of horizon energy given by $$E=A/8\pi G l_{0}$$ E=A/8πGl0 , the surface gravity is given by $$\kappa =1/l_{0}$$ κ=1/l0 , and consequently, the first law can be written in the quasilocal setting as $$\delta E=(\kappa /8\pi G)\delta A$$ δE=(κ/8πG)δA .

Urothelial cancer of the renal pelvis (CRP) is predominantly associated with cigarette smoking. However, the molecular pathogenesis of initiation and progression of cigarette smoke (CS)-induced CRP is unknown. Majority of CRP is high grade and high stage at presentation and has a high recurrence rate even after surgery. Earlier we reported that prolonged treatment (24 weeks) of a guinea pig model with p-benzoquinone (p-BQ), a product of CS in vivo, produced carcinoma in situ in the renal pelvis, a noninvasive cancer. Since CS is known to induce invasive cancer, we investigated the effect of CS exposure to the guinea pigs. We observed that CS exposure for a short period (18 weeks) produced invasive tumor (pT1). pT1 was confirmed by immunohistochemistry showing increased immunoexpression of nuclear p53 indicating p53 mutation, aberrant CK20, increased Ki-67 and uniformly negative labeling of CD44. As observed earlier with p-BQ treatment, the initial events of CS exposure were oxidative damage and apoptosis that was followed by persistent signaling through EGFR and MAP kinase pathway. CS exposure also caused hyperphosphorylation of pRb, activation of cyclin E and cell cycle deregulation leading to infiltration of epithelial cells in lamina propria of the renal pelvis resulting in pT1 tumor. Oral supplementation of vitamin C (30 mg/kg guinea pig/day) inhibited oxidative damage and apoptosis and holistically prevented the tumor formation. We consider that our preclinical findings on the intake of adequate vitamin C, along with intense advice for cessation of smoking, will be helpful for the prevention of CS-induced CRP in smokers. Keywords: Invasive cancer of the renal pelvis, Cigarette smoke, Vitamin C, Oxidative damage, Persistent EGFR signaling, Cell cycle deregulation

Copyright of Revista Kronos is the property of Revista Kronos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The beneficial effect of physical activity (PA) has been confirmed in several types of cancer (especially colon and breast tumours). However, the role of PA as a risk factor directly related to the incidence of gastric cancer is still open to doubt. This is in part due to the fact that most studies have not considered gastric sub-site or histology of oesophageal cancer, as well as the different approaches used in order to measure PA. Indeed, some studies have tried to link gastric cancer to PA intensity and timing, whereas others have focused on a specific PA type such as recreational, occupational or sporting activity. Furthermore, most of them do not use validated questionnaires, and others create a PA index and employ different unit measures (metabolic equivalents, hours/week, times per week, etc.), which makes it difficult to compare its findings. Under these circumstances, this brief critical review aims to explore and show all the methodological issues that need to be taken into account in order to objectify the link between PA and gastric cancer, as well as provide alternative solutions to these matters. [ABSTRACT FROM AUTHOR]

This study examined the effects of an eight-week progressive resistance training on different strength manifestations, muscle mass and functionality in multiple sclerosis patients. Thirteen volunteered patients (average age 43 years; range 35-51) with a confirmed diagnosis by a neurologist and mild to moderate disability participated twice a week in an eight-week progressive resistance training program after an eight-week control period without training. Intensity ranged from 40-70% of their maximal voluntary contraction. Outcome assessments included magnetic resonance image of the right and left thighs, strength manifestations (maximal voluntary contraction, muscular endurance and power), and functionality by the Up and Go test. All outcome assessments remained unaltered during the eight-week control period. After the eight-week strength training period, isometric strength (+16%, p<0.01), muscular endurance (+84%; p<0.001), maximal power (+51%. p <0.001), muscular hypertrophy from slice 6/27 to slice 11/27 of both thighs (p<0.05), and functionality (p<0.001) improved significantly. Moderate resistance training programs can improve muscle function without injuries and can be a promising therapy to delay the functional deterioration in multiple sclerosis patients. [ABSTRACT FROM AUTHOR]

According to WHO classification system, non-invasive urothelial carcinoma represents urothelial carcinoma in situ (CIS) and dysplasia. Dysplastic urothelium often progresses to CIS that further advances to urothelial carcinoma (UC). The strongest risk factor for UC is cigarette smoking. However, the pathogenesis of cigarette smoke (CS)-induced UC is poorly understood. Earlier we had shown that p-benzoquinone (p-BQ), a major toxic quinone derived from p-benzosemiquinone of CS in vivo, is a causative factor for various CS-induced diseases. Here, using a guinea pig model we showed that prolonged treatment with p-BQ led to non-invasive UC, specifically carcinoma in situ (CIS) of the renal pelvis and dysplasia in the ureter and bladder. The mechanisms of carcinogenesis were p-BQ-induced oxidative damage and apoptosis that were later suppressed and followed by activation of epidermal growth factor receptor, aberrant phosphorylation of intracellular tyrosine residues, activation of MAP kinase pathway and persistent growth signaling. This was accompanied by deregulation of cell cycle as shown by marked decrease in the expression of p21waf1/cip1 and cyclin D1 proteins as well as hyperphosphorylation of pRb. UC has been characterised by histopathology and immunohistochemistry showing aberrant CK20, increased Ki-67, and marked p53 nuclear immunopositivity with uniformly negative labelling of CD44. Oral supplementation of vitamin C (30Â mg/kg body weight/day) prevented CIS of the renal pelvis and dysplasia in the ureter and bladder. Since majority of non-invasive UC progresses to invasive cancer with increased risk of mortality, our preclinical study might help to devise effective strategies for early intervention of the disease. Abbreviations: Bax, Bcl-2, CS, DNPH, GAPDH, IARC, p-BQ, p-BSQ, PAHs, PBS, ROS, SDS PAGE, TUNEL, WHO, UC, CIS, EGFR, MAPK, Keywords: p-Benzoquinone, Carcinoma in situ, Dysplasia, Aberrant EGFR activation, Cell cycle deregulation, Vitamin C

Metastasis is the major cause of cancer-related morbidity and mortality. The ability of cancer cells to become invasive and migratory contribute significantly to metastatic growth, which necessitates the identification of novel anti-migratory and anti-invasive therapeutic approaches. Proteoglycan 4 (PRG4), a mucin-like glycoprotein, contributes to joint synovial homeostasis through its friction-reducing and anti-adhesive properties. Adhesion to surrounding extracellular matrix (ECM) components is critical for cancer cells to invade the ECM and eventually become metastatic, raising the question whether PRG4 has an anti-invasive effect on cancer cells. Here, we report that a full-length recombinant human PRG4 (rhPRG4) suppresses the ability of the secreted protein transforming growth factor beta (TGFβ) to induce phenotypic disruption of three-dimensional human breast cancer cell-derived organoids by reducing ligand-induced cell invasion. In mechanistic studies, we find that rhPRG4 suppresses TGFβ-induced invasiveness of cancer cells by inhibiting the downstream hyaluronan (HA)-cell surface cluster of differentiation 44 (CD44) signalling axis. Furthermore, we find that rhPRG4 represses TGFβ-dependent increase in the protein abundance of CD44 and of the enzyme HAS2, which is involved in HA biosynthesis. It is widely accepted that TGFβ has both tumor suppressing and tumor promoting roles in cancer. The novel finding that rhPRG4 opposes HAS2 and CD44 induction by TGFβ has implications for downregulating the tumor promoting roles, while maintaining the tumor suppressive aspects of TGFβ actions. Finally, these findings point to rhPRG4's potential clinical utility as a therapeutic treatment for invasive and metastatic breast cancer.

“Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)”, the novel coronavirus, is responsible for the ongoing worldwide pandemic. “World Health Organization (WHO)” assigned an “International Classification of Diseases (ICD)” code—“COVID-19”-as the name of the new disease. Coronaviruses are generally transferred by people and many diverse species of animals, including birds and mammals such as cattle, camels, cats, and bats. Infrequently, the coronavirus can be transferred from animals to humans, and then propagate among people, such as with “Middle East Respiratory Syndrome (MERS-CoV)”, “Severe Acute Respiratory Syndrome (SARS-CoV)”, and now with this new virus, namely “SARS-CoV-2”, or human coronavirus. Its rapid spreading has sent billions of people into lockdown as health services struggle to cope up. The COVID-19 outbreak comes along with an exponential growth of new infections, as well as a growing death count. A major goal to limit the further exponential spreading is to slow down the transmission rate, which is denoted by a “spread factor (f)”, and we proposed an algorithm in this study for analyzing the same. This paper addresses the potential of data science to assess the risk factors correlated with COVID-19, after analyzing existing datasets available in “ourworldindata.org (Oxford University database)”, and newly simulated datasets, following the analysis of different univariate “Long Short Term Memory (LSTM)” models for forecasting new cases and resulting deaths. The result shows that vanilla, stacked, and bidirectional LSTM models outperformed multilayer LSTM models. Besides, we discuss the findings related to the statistical analysis on simulated datasets. For correlation analysis, we included features, such as external temperature, rainfall, sunshine, population, infected cases, death, country, population, area, and population density of the past three months—January, February, and March in 2020. For univariate timeseries forecasting using LSTM, we used datasets from 1 January 2020, to 22 April 2020.

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and “obesity/overweight” is one of the consequences. “Obesity and overweight” are one of the major lifestyle diseases that leads to other health conditions, such as cardiovascular diseases (CVDs), chronic obstructive pulmonary disease (COPD), cancer, diabetes type II, hypertension, and depression. It is not restricted within the age and socio-economic background of human beings. The “World Health Organization” (WHO) has anticipated that 30% of global death will be caused by lifestyle diseases by 2030 and it can be prevented with the appropriate identification of associated risk factors and behavioral intervention plans. Health behavior change should be given priority to avoid life-threatening damages. The primary purpose of this study is not to present a risk prediction model but to provide a review of various machine learning (ML) methods and their execution using available sample health data in a public repository related to lifestyle diseases, such as obesity, CVDs, and diabetes type II. In this study, we targeted people, both male and female, in the age group of >20 and

Metastasis is the ultimate cause of breast cancer related mortality. Epithelial-mesenchymal transition (EMT) is thought to play a crucial role in the metastatic potential of breast cancer. Growing evidence has implicated the SUMO E3 ligase PIAS1 in the regulation of EMT in mammary epithelial cells and breast cancer metastasis. However, the relevance of PIAS1 in human cancer and mechanisms by which PIAS1 might regulate breast cancer metastasis remain to be elucidated. Using tissue-microarray analysis (TMA), we report that the protein abundance and subcellular localization of PIAS1 correlate with disease specific overall survival of a cohort of breast cancer patients. In mechanistic studies, we find that PIAS1 acts via sumoylation of the transcriptional regulator SnoN to suppress invasive growth of MDA-MB-231 human breast cancer cell-derived organoids. Our studies thus identify the SUMO E3 ligase PIAS1 as a prognostic biomarker in breast cancer, and suggest a potential role for the PIAS1-SnoN sumoylation pathway in controlling breast cancer metastasis.

This paper proposes a simple yet effective method for improving the efficiency of sparse coding dictionary learning (DL) with an implication of enhancing the ultimate usefulness of compressive sensing (CS) technology for practical applications, such as in hyperspectral imaging (HSI) scene reconstruction. CS is the technique which allows sparse signals to be decomposed into a sparse representation “a” of a dictionary D u . The goodness of the learnt dictionary has direct impacts on the quality of the end results, e.g., in the HSI scene reconstructions. This paper proposes the construction of a concise and comprehensive dictionary by using the cluster centres of the input dataset, and then a greedy approach is adopted to learn all elements within this dictionary. The proposed method consists of an unsupervised clustering algorithm (K-Means), and it is then coupled with an advanced sparse coding dictionary (SCD) method such as the basis pursuit algorithm (orthogonal matching pursuit, OMP) for the dictionary learning. The effectiveness of the proposed K-Means Sparse Coding Dictionary (KMSCD) is illustrated through the reconstructions of several publicly available HSI scenes. The results have shown that the proposed KMSCD achieves ~40% greater accuracy, 5 times faster convergence and is twice as robust as that of the classic Spare Coding Dictionary (C-SCD) method that adopts random sampling of data for the dictionary learning. Over the five data sets that have been employed in this study, it is seen that the proposed KMSCD is capable of reconstructing these scenes with mean accuracies of approximately 20−500% better than all competing algorithms adopted in this work. Furthermore, the reconstruction efficiency of trace materials in the scene has been assessed: it is shown that the KMSCD is capable of recovering ~12% better than that of the C-SCD. These results suggest that the proposed DL using a simple clustering method for the construction of the dictionary has been shown to enhance the scene reconstruction substantially. When the proposed KMSCD is incorporated with the Fast non-negative orthogonal matching pursuit (FNNOMP) to constrain the maximum number of materials to coexist in a pixel to four, experiments have shown that it achieves approximately ten times better than that constrained by using the widely employed TMM algorithm. This may suggest that the proposed DL method using KMSCD and together with the FNNOMP will be more suitable to be the material allocation module of HSI scene simulators like the CameoSim package.

Research on snapshot multispectral imaging has been popular in the remote sensing community due to the high demands of video-rate remote sensing system for various applications. Existing snapshot multispectral imaging techniques are mainly of a fixed wavelength type, which limits their practical usefulness. This paper describes a tunable multispectral snapshot system by using a dual prism assembly as the dispersion element of the coded aperture snapshot spectral imagers (CASSI). Spectral tuning is achieved by adjusting the air gap displacement of the dual prism assembly. Typical spectral shifts of about 1 nm at 400 nm and 12 nm at 700 nm wavelength have been achieved in the present design when the air-gap of the dual prism is changed from 4.24 mm to 5.04 mm. The paper outlines the optical designs, the performance, and the pros and cons of the dual-prism CASSI (DP-CASSI) system. The performance of the system is illustrated by TraceProTM ray tracing, to allow researchers in the field to repeat or to validate the results presented in this paper.

The objective of this cross-sectional study was to explore sleep patterns and the potential relationship between sleep and tryptophan intake among Spanish university students. A total of 11,485 students self-reported their sleep and dietary patterns and habits. Tryptophan intake was calculated using a food intake matrix and results were presented as quartiles of total intake. Short sleep duration prevalence was 51.0%, with males exhibiting a significantly higher frequency. A total of 55.0% of participants presented inadequate sleep efficiency, with males again presenting a higher rate. Median tryptophan intake was 692.16 ± 246.61 mg/day, 731.84 ± 246.86 mg/day in males and 677.24 ± 244.87 mg/day in females ( p = 0.001). Dietary tryptophan intake below the first quartile (<526.43 mg/day) was associated with a higher risk of short sleep duration in males (1.26; 95%CI: 1.02-1.55) and females (1.19; 95%CI: 1.05-1.34) and with the Athens Insomnia Scale insomnia in males (2.56; 95%CI: 1.36-4.82) and females (1.47; 95%CI: 1.10-2.05). Regarding academic specializations, females in the humanities field showed a higher risk of Athens Insomnia Scale insomnia due to low tryptophan intake (Q1: 3.15; 95% CI: 1.04-9.55 and Q2: 3.41; 95%CI: 1.01-11.5). In summary, lower tryptophan consumption appears to be associated with poorer sleep quality in Spanish university students; however, other social factors affecting students may also influence sleep quality. These findings have important implications for nutritional recommendations aimed at enhancing tryptophan intake to improve sleep quality.

Introduction: Spinal cord injuries (SCI) have physiological, emotional, and economic consequences in the lives of affected people. Resistance training (RT) is efficient in improving several physiological factors, quality of life, and body composition. Due to the scarce literature on the analysis of isolated RT, the objective of this systematic review is to evaluate the effects of RT without the association of other techniques, in aspects related to the quality of life and body composition of people with SCI., Evidence Acquisition: The research was carried out in databases such as Pubmed, Cochrane, and Web of Science using the terms ("Spinal cord injury") AND (("Resistance Training") OR ("Strength training")). Given the lack of evidence on the subject, no deadline was set for the study to be eligible for analysis., Evidence Synthesis: The search for the articles was carried out in November of 2023 and returned 470 results, of which 315 remained after the elimination of duplicates, with 281 being excluded after title analysis. A total of 34 abstracts were analyzed and 29 studies were excluded, leaving 5 complete articles for thorough analysis., Conclusions: After analyzing the main results, we concluded that RT promotes significant improvements in body composition, pain, stress and depression symptoms, increased functionality, physical awareness, and quality of life., Competing Interests: Declaration of competing interest None, (Copyright © 2024 Elsevier Ltd. All rights reserved.)