Miracle-dz/UniFAR-FTUs huggingface dataset:
Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions

The exoskeleton technology has been rapidly advancing in the recent past due to its multitude of applications and diverse use cases in assisted living, military, healthcare, firefighting, and industry 4.0. The exoskeleton market is projected to increase by multiple times its current value within the next two years. Therefore, it is crucial to study the degree and trends of user interest, views, opinions, perspectives, attitudes, acceptance, feedback, engagement, buying behavior, and satisfaction, towards exoskeletons, for which the availability of Big Data of conversations about exoskeletons is necessary. The Internet of Everything style of today’s living, characterized by people spending more time on the internet than ever before, with a specific focus on social media platforms, holds the potential for the development of such a dataset by the mining of relevant social media conversations. Twitter, one such social media platform, is highly popular amongst all age groups, where the topics found in the conversation paradigms include emerging technologies such as exoskeletons. To address this research challenge, this work makes two scientific contributions to this field. First, it presents an open-access dataset of about 140,000 Tweets about exoskeletons that were posted in a 5-year period from 21 May 2017 to 21 May 2022. Second, based on a comprehensive review of the recent works in the fields of Big Data, Natural Language Processing, Information Retrieval, Data Mining, Pattern Recognition, and Artificial Intelligence that may be applied to relevant Twitter data for advancing research, innovation, and discovery in the field of exoskeleton research, a total of 100 Research Questions are presented for researchers to study, analyze, evaluate, ideate, and investigate based on this dataset.
Anti-aliased Pixel and Intensity Slope Detector

Each image dot can be associated with some image part, for example line, area where intensity changes or area with constant intensity. Image processing use these image parts. Image transferring into the digital domain in any words image digitizing, because of finite dot (pixel) size some pixels are partly closed with light and dark area. These pixels are called anti-aliased. Frequently these pixels are unwanted or impede to extract edge or blur magnified image or ripple edge in shrink image. When it is possible to detect that pixel, different algorithm can be applied for processing and image quality can be increased. A method to detect anti-aliased pixels and pixels which intensity change continuous (slope) is presented. Ill. 7, bibl. 5 (in English; summaries in English, Russian and Lithuanian).
The Influence of Economic Growth and Energy Consumption on Environmental Degradation in Pakistan

Globalization has substantial influence on the environmental issues and consequently on the economic activities of a country. Environmental problems are more prominent in developing countries. With the growing development, the issue of environmental degradation is also enhanced. The non-renewable energy consumption is the main cause of environmental degradation and this problem can’t be ignored. Therefore, the main objective of this research is to analyze the connection among energy consumption, growth of an economy, and emission of carbon dioxide gas in Pakistan. The data is collected from World development Indicators. Autoregressive Distributed-Lag Model (ARDL) is used for the analysis. The outcomes of ARDL technique stipulate that energy consumption and growth of an economy rise the emission of CO2 in Pakistan. On the basis of these results, it is suggested that policy makers in Pakistan must implement and encourage different sources of energy, which are renewable and will support to fulfill the huge demand of energy to boost the economy and to contribute in a sustainable environment of Pakistan.
Identification of key biomarkers and signaling pathways and analysis of their association with immune cells in immunoglobulin A nephropathy

Introduction Immunoglobulin A nephropathy (IgAN) is the most common glomerular disease worldwide, with a poor prognosis. The aim of our study was to identify key biomarkers and their associations with immune cells to aid in the study of IgAN pathology and immunotherapy. Material and methods The data of IgAN were downloaded from a public database. The metaMA package and limma package were used to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs), respectively. Biological functions of the DEmRNAs were analyzed. Machine learning was used to screen the mRNA biomarkers of IgAN. Pearson’s correlation coefficient was used to analyze the correlation between mRNA biomarkers, immune cells and signaling pathways. Moreover, we constructed a miRNAs-mRNAs targeted regulatory network. Finally, we performed in vitro validation of the identified miRNAs and mRNAs. Results 1205 DEmRNAs and 125 DEmiRNAs were identified. In gene set enrichment analysis (GSEA), tumor necrosis factor α (TNF-α) signaling via nuclear factor κB (NF-κB), apoptosis and MTORC-1 signaling were inhibited in IgAN. 8 mRNA biomarkers were screened by machine learning. In addition, the distribution of 8 immune cell types was found to be significantly different between normal controls and IgAN by difference analysis. Pearson correlation coefficient analysis demonstrated that AKAP8L was significantly negatively correlated with CD4+ memory T-cells. AKAP8L was also significantly negatively correlated with TNF-α signaling via NF-κB, apoptosis, and MTORC-1 signaling. Subsequently, 5 mRNA biomarkers predicted corresponding negative regulatory miRNAs. Conclusions The identification of 8 important biomarkers and their correlation with immune cells and biological signaling pathways provides new ideas for further study of IgAN.
Metabolic aspects of surgical subcutaneous fat removal: An umbrella review and implications for future research

Although obesity is a preventable disease, maintaining a normal body weight can be very challenging and difficult, which has led to a significant increase in the demand for surgical subcutaneous fat removal (SSFR) to improve physical appearance. The need for SSFR is further exacerbated because of the global rise in the number of bariatric surgeries, which is currently the single most durable intervention for mitigating obesity. Fat tissue is now recognized as a vital endocrine organ that produces several bioactive proteins. Thus, SSFR-mediated weight (fat) loss can potentially have significant metabolic effects; however, currently, there is no consensus on this issue. This review focuses on the metabolic sequelae after SSFR interventions for dealing with cosmetic body appearance. Data were extracted from existing systematic reviews and the diversity of possible metabolic changes after SSFR are reported along with gaps in the knowledge and future directions for research and practice. We conclude that there is a potential for metabolic sequelae after SSFR interventions and their clinical implications for the safety of the procedures as well as for our understanding of subcutaneous adipose tissue biology and insulin resistance are discussed.
Consumed by Boredom: Food Choice Motivation and Weight Changes during the COVID-19 Pandemic

Boredom is an established cause and correlate of eating behavior. Yet, existing work offers a scattered range of plausible motivations for why this is. We examined among 302 people representative of the adult UK population what motivations they had for selecting food during the COVID-19 pandemic and how this related to boredom. As predicted, bored people choose food less for health reasons and more for convenience. Boredom reduced ethical and ‘natural content’ motivations for selecting food and was not associated with choosing food to regulate one’s mood or to experience unfamiliarity. Boredom was also associated with greater absolute changes in weight over the course of the pandemic. Boredom did not predict weight gains or losses overall. These findings offer insights into the role that boredom plays in eating motivations in particular and health-relevant outcomes in general.
Metode SDLC Waterfall Pada Rancang Bangun Sistem Informasi Sekolah SMP Negeri 10 Kaur

Kegiatan belajar mengajar dengan tatap muka secara langsung dinilai tidak memungkinkan mengingat pentingnya mengutamakan kesehatan dan keselamatan siswa, pengajar, tenaga pendidikan, serta masyarakat lainnya. Permasalahan yang dihadapi oleh dunia pendidikan khususnya sekolah da-sar, sekolah menengah pertama dan sekolah menengah atas yaitu dengan mengubah sistem pembelajaran maka berdampak kepada sistem promosi sekolah. Berdasarkan tahapan penelitian yang telah dijalankan dan tujuan yang ingin dicapai pada penelitian ini yaitu pengembangan prototipe sistem informasi ini berhasil, dengan menggunakan pengembangan metode SDLC Waterfall, yang dibuktikan dengan hasil pengujian black box, yaitu keseluruhan dari sistem yang dikembangankan tidak memiliki bug/error pada sistem
The Antidepressant-like Activity, Effects on Recognition Memory Deficits, Bioavailability, and Safety after Chronic Administration of New Dual-Acting Small Compounds Targeting Neuropsychiatric Symptoms in Dementia

This study aimed to extend the body of preclinical research on prototype dual-acting compounds combining the pharmacophores relevant for inhibiting cyclic nucleotide phosphodiesterase 10 (PDE10A) and serotonin 5-HT1A/5-HT7 receptor (5-HT1AR/5-HT7R) activity into a single chemical entity (compounds PQA-AZ4 and PQA-AZ6). After i.v. administration of PQA-AZ4 and PQA-AZ6 to rats, the brain to plasma ratio was 0.9 and 8.60, respectively. After i.g. administration, the brain to plasma ratio was 5.7 and 5.3, respectively. An antidepressant-like effect was observed for PQA-AZ6 in the forced swim test, after chronic 21-day treatment via i.p. administration with 1 mg/kg/day. Both compounds revealed an increased level of brain-derived neurotrophic factor (Bdnf) mRNA in the hippocampus and prefrontal cortex. Moreover, PQA-AZ4 and PQA-AZ6 completely reversed (+)-MK801-induced memory disturbances comparable with the potent PDE10 inhibitor, compound PQ-10. In the safety profile that included measurements of plasma glucose, triglyceride, and total cholesterol concentration, liver enzyme activity, the total antioxidant activity of serum, together with weight gain, compounds exhibited no significant activity. However, the studied compounds had different effects on human normal fibroblast cells as revealed in in vitro assay. The pharmacokinetic and biochemical results support the notion that these novel dual-acting compounds might offer a promising therapeutic tool in CNS-related disorders.
Photoproduction of Lambda(1405) and Sigma0(1385) on the proton at E(gamma) = 1.5-2.4-GeV

Differential cross sections for {gamma}p{yields}K{sup +}{lambda}(1405) and {gamma}p{yields}K{sup +}{sigma}{sup 0}(1385) reactions have been measured in the photon energy range from 1.5 to 2.4 GeV and the angular range of 0.8<cos({theta})<1.0 for the K{sup +} scattering angle in the center-of-mass system. This data is the first measurement of the {lambda}(1405) photoproduction cross section. The line shapes of {lambda}(1405) measured in {sigma}{sup +}{pi}{sup -} and {sigma}{sup -}{pi}{sup +} decay modes were different with each other, indicating a strong interference of the isospin 0 and 1 terms of the {sigma}{pi} scattering amplitudes. The ratios of {lambda}(1405) production to {sigma}{sup 0}(1385) production were measured in two photon energy ranges: near the production threshold (1.5<E{sub {gamma}}<2.0 GeV) and far from it (2.0<E{sub {gamma}}<2.4 GeV). The observed ratio decreased in the higher photon energy region, which may suggest different production mechanisms and internal structures for these hyperon resonances.
Cross-Coupled Gated Tunneling Diodes With Unprecedented PVCRs Enabling Compact SRAM Design—Part II: SRAM Circuit

In Part I of this article, we present a novel device, i.e., a cross-coupled gated tunneling diode (XTD), which exhibits negative differential resistance (NDR) with peak-to-valley current ratios (PVCRs) exceeding 105. In this part of this article, based on the XTD, we introduce a compact static random access memory (SRAM) cell using a one-transistor and two-XTD (1T-2X) design. The layout of the SRAM cell as well as a detailed analysis of the cell behavior and SRAM array performance are presented. In particular, our simulation results show that the 1T-2X SRAM cell can achieve <inline-formula> <tex-math notation="LaTeX">$70\times $ </tex-math></inline-formula> improvement in standby power with ~<inline-formula> <tex-math notation="LaTeX">$8\times $ </tex-math></inline-formula> area reduction compared to standard CMOS SRAM.
Body Image and Body Mass Index Influence on Psychophysical Well-Being in Bariatric Patients: A Cross-Sectional Study

Background: Psychophysical factors may have an impact on the disease of obesity, and it is important to explore which aspects may play an important role on the well-being of obese patients undergoing bariatric surgery. The purpose of this study was to assess the associations of a high body mass index (BMI) and greater dissatisfaction with body image with higher levels of psychopathological aspects, feelings of hopelessness, and psychological and physical health in patients undergoing evaluation for bariatric surgery. Methods: Fifty-nine patients undergoing bariatric surgery filled out the Symptom Checklist-90-Revised, the Body Uneasiness Test, the 12-item Short Form Survey, the Beck Inventory Scale II, and the Beck Hopelessness Scale. Correlations and hierarchical regressions between measures were performed. Results: Dissatisfaction with the perception of one’s own body image was strongly correlated with a worse psychophysiological health. On the contrary, BMI showed no significant correlation with the previous variables. Furthermore, the perception of one’s own body image significantly predicted the state of psychological health. Conclusions: The findings showed a more relevant role of body image compared to the BMI in the association with psychological outcomes, suggesting the importance of considering body image in the assessment and treatment of obese patients requiring bariatric treatment.
NO CONFIRMED NEW ISOLATED NEUTRON STARS IN THE SDSS DATA RELEASE 4

We report on follow-up observations of candidate X-ray-bright, radio-quiet isolated neutron stars (INSs) identified from correlations of the ROSAT All-Sky Survey (RASS) and the Sloan Digital Sky Survey (SDSS) Data Release 4 in Agüeros et al. We obtained Chandra X-ray Observatory exposures for 13 candidates in order to pinpoint the source of X-ray emission in optically blank RASS error circles. These observations eliminated 12 targets as good INS candidates. We discuss subsequent observations of the remaining candidate with XMM-Newton, the Gemini North Observatory, and the Apache Point Observatory. We identify this object as a likely extragalactic source with an unusually high log (fX/fopt) ∼ 2.4. We also use an updated version of the population synthesis models of Popov et al. to estimate the number of RASS-detected INSs in the SDSS Data Release 7 footprint. We find that these models predict ∼3–4 INSs in the 11,000 deg2 imaged by SDSS, which is consistent with the number of known INSs that fall within the survey footprint. In addition, our analysis of the four new INS candidates identified in the SDSS footprint implies that they are unlikely to be confirmed as INSs; together, these results suggest that new INSs are not likely to be found from further correlations of the RASS and SDSS.
Cosmology with matter diffusion

We construct a viable cosmological model based on velocity diffusion of matter particles. In order to ensure the conservation of the total energy- momentum tensor in the presence of diffusion, we include a cosmological scalar field phi which we identify with the dark energy component of the universe. The model is characterized by only one new degree of freedom, the diffusion parameter sigma. The standard Lambda CDM model can be recovered by setting sigma = 0. If diffusion takes place (sigma > 0) the dynamics of the matter and of the dark energy fields are coupled. We argue that the existence of a diffusion mechanism in the universe may serve as a theoretical motivation for interacting models. We constrain the background dynamics of the diffusion model with Supernovae, H(z) and BAO data. We also perform a perturbative analysis of this model in order to understand structure formation in the universe. We calculate the impact of diffusion both on the CMB spectrum, with particular attention to the integrated Sachs-Wolfe signal, and on the matter power spectrum P(k). The latter analysis places strong constraints on the magnitude of the diffusion mechanism but does not rule out the model.
Using the Multidimensional AIMES to Estimate Connection-to-Nature in an Australian Population: A Latent Class Approach to Segmentation

Individuals can interact and develop multiple connections to nature (CN) which have different meanings and reflect different beliefs, emotions, and values. Human population are not homogenous groups and often generalised approaches are not effective in increasing connectedness to nature. Instead, target-group specific approaches focusing on different segments of the population can offer a promising approach for engaging the public in pro-environmental behaviours. This research employed latent class analysis to identify subgroups of individuals in a large, representative sample (n = 3090) of an Australian region. Three groups were identified using the AIMES measure of CN with its focus on five types of connection to nature. The high CN group comprised about one-third (35.4%) of participants while the group with the lowest profile of scores contained around a fifth (18.6%) of participants. The majority (46.0%) of participants registered CN levels between the high and low groups. These classes were then regressed on predictor variables to further understand differences between the groups. The largest, consistent predictors of class membership were biocentric and social-altruistic value orientations, stronger intentions to perform pro-environmental behaviours in public (e.g., travel on public transport), the amount of time spent in nature, and the age of participants.
Astrophysical Implications of the Superstring-Inspired E{sub 6} Unification and Shadow Theta-Particles

We have developed a concept of parallel existence of the ordinary (O) and mirror (M), or shadow (Sh) worlds. E6 unification, inspired by superstring theory, restores the broken mirror parity at the scale ∼1018 GeV. With the aim to explain the tiny cosmological constant, we consider the breakings: E6→SO(10)×U(1)Z—in the O‐world, and E′6→SU(6)′×SU(2)′θ—in the Sh‐world. We assume the existence of shadow θ‐particles and the low energy symmetry group SU(3)′C×SU(2)′L×SU(2)′θ×U(1)′Y in the shadow world, instead of the Standard Model. The additional non‐Abelian SU(2)′θ group with massless gauge fields, “thetons,” has a macroscopic confinement radius 1/Λ′θ. The assumption that Λ′θ≈2.3⋅10−3 eV explains the tiny cosmological constant given by recent astrophysical measurements. Searching for the Dark Matter (DM), it is possible to observe and study various signals of theta‐particles.
The mutual interaction between Population III stars and self-annihilating dark matter

We use cosmological simulations of high-redshift minihaloes to investigate the effect of dark matter annihilation (DMA) on the collapse of primordial gas. We numerically investigate the evolution of the gas as it assembles in a Population III stellar disc. We find that when DMA effects are neglected, the disc undergoes multiple fragmentation events beginning at approximately 500 yr after the appearance of the first protostar. On the other hand, DMA heating and ionization of the gas speeds the initial collapse of gas to protostellar densities and also affects the stability of the developing disc against fragmentation, depending on the DM distribution. We compare the evolution when we model the DM density with an analytical DM profile which remains centrally peaked, and when we simulate the DM profile using N-body particles (the 'live' DM halo). When utilizing the analytical DM profile, DMA suppresses disc fragmentation for approximately 3500 yr after the first protostar forms, in agreement with earlier work. However, when using a 'live' DM halo, the central DM density peak is gradually flattened due to the mutual interaction between the DM and the rotating gaseous disc, reducing the effects of DMA on the gas, and enabling secondary protostars of mass approximately 1 solar mass to be formed within approximately 900 yr. These simulations demonstrate that DMA is ineffective in suppressing gas collapse and subsequent fragmentation, rendering the formation of long-lived dark stars unlikely. However, DMA effects may still be significant in the early collapse and disc formation phase of primordial gas evolution.
Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs: the case of COVID-19 epidemiology in Wikidata

Urgent global research demands real-time dissemination of precise data. Wikidata, a collaborative and openly licensed knowledge graph available in RDF format, provides an ideal forum for exchanging structured data that can be verified and consolidated using validation schemas and bot edits. In this research article, we catalog an automatable task set necessary to assess and validate the portion of Wikidata relating to the COVID-19 epidemiology. These tasks assess statistical data and are implemented in SPARQL, a query language for semantic databases. We demonstrate the efficiency of our methods for evaluating structured non-relational information on COVID-19 in Wikidata, and its applicability in collaborative ontologies and knowledge graphs more broadly. We show the advantages and limitations of our proposed approach by comparing it to the features of other methods for the validation of linked web data as revealed by previous research.
The Role of Associations in Reducing the Emotional and Financial Impact on Parents Caring for Children with Duchenne Muscular Dystrophy: A Cross-Cultural Study

Caregivers’ emotions and finances are affected by the deterioration of functional capacity of patients with Duchenne muscular dystrophy (DMD), both in Mexico and Spain. Patient associations may reduce this impact on caregivers. This study aims to study the role of two models of associations, inspired by two different cultural models, in how the services they provide can help decrease the emotional and financial impact on the caregivers of children with DMD. The sample consisted of 34 caregivers from Mexico and 40 from Spain recruited from Spanish hospitals and rare disease organizations in Spain and Mexico. The instruments used consisted of a sociodemographic and socioeconomic questionnaire, the CarerQol-7D, the PHQ-15, the Zarit Caregiver’s Burden Scale and the SWLS. The results showed that caregivers in Mexico are in better physical and psychological health than caregivers in Spain. They also receive more subsidies than those in Spain. Caregivers in Mexico have a greater well-being and are less affected by the economic impact of the disease due to the associations’ day-to-day work and the fact that they generate a network of health services that they make available to the patient free of charge. These differences may also be attributable to cultural issues and to the fact that Mexico has a deeply established culture of support.