Recent simulation studies have revealed a wealth of distinct crystal polymorphs encountered in the self-organization of polymer systems driven by entropy or free energy. The present analysis, based on the concept of self-avoiding random walks on crystal lattices, is useful to calculate upper bounds for the entropy difference of the crystals that are formed during polymer crystallization and thus provide predictions on polymorph thermodynamic stability. Here, we compare two pairs of crystals sharing the same coordination number, ncoord: hexagonal close packed (HCP) and face centered cubic (FCC), both having ncoord = 12 and the same packing density, and the less dense hexagonal (HEX) and body centered cubic (BCC) lattices, with ncoord = 8. In both cases, once a critical step length is reached, one of the crystals shows a higher number of SAWs compatible with the crystal. We explain the observed trends in terms of the bending and torsion angles corresponding to the different chain geometry as imposed by the geometric constraints of the crystal lattice.

Inflammatory diseases are common pathological processes caused by various acute and chronic factors and some of them are autoimmune diseases. Exosomes are fundamental extracellular vesicles secreted by almost all cells, which contain a series of constituents, i.e. cytoskeletal and cytosolic proteins (actin, tubulin, histones), nucleic acids (mRNA, miRNA, DNA), lipids (diacylglycerophosphates, cholesterol, sphingomyelin, ceramide), and other bioactive components (cytokines, signal transduction proteins, enzymes, antigen presentation and membrane transport/fusion molecules, adhesion molecules). This review would be a synopsis of the actual knowledge on the contribution of exosomes from different cell sources as possible therapeutic agents against inflammation, focusing on several inflammatory diseases, neurological diseases, rheumatoid arthritis and osteoarthritis, intestinal bowel disease, asthma, liver and kidney injuries. Current knowledge indicates that the role of exosomes in therapy of inflammation and in inflammatory diseases could be distinctive. Main limitations to their clinical translation are still production, isolation, and storage. Additionally, there is an urgent need to personalize the treatments in terms of selection of exosomes, their dosages and routes of administration, and a deeper knowledge about their biodistribution, type and incidence of adverse events and long-term effects of exosomes. In conclusion, exosomes can very promising next generation therapeutic option, superior to synthetic nanocarriers and cell therapy, and can represent a new strategy of effective, safe, versatile and selective delivery systems in the future.

Environmentally friendly lead-free K1-xNaxNbO3 (KNN) ceramics possess electromechanical properties comparable to lead-based ferroelectric materials, but cannot meet the needs of device miniaturization, and the corresponding thin films lack of theoretical and experimental studies. To this end, we developed the nonlinear phenomenological theory for ferroelectric materials to study the effects of non-equiaxed misfit strain on the phase structure, electromechanical properties and electrical response of K0.5Na0.5NbO3 epitaxial films and constructed the in-plane misfit strain (u1-u2) phase diagrams. The results show that K0.5Na0.5NbO3 epitaxial film under non-equiaxed in-plane strain can exhibit abundant phase structures, including orthorhombic a1c, a2c and a1a2 phases, tetragonal a1, a2 and c phases, and monoclinic r12 phases. Moreover, in the vicinity of a2c-r12, a1c-c and a1a2-a2 phase boundaries, K0.5Na0.5NbO3 epitaxial films exhibit excellent dielectric constant ε11, while at a2c -r12 and a1c-c phase boundaries large piezoelectric coefficient d15 is observed. It was also found that high permittivity ε33 and piezoelectric coefficients d33 exist near the a2c - a2, r12- a1a2 and a1c-a1 phase boundaries due to the existence of polymorphic phase boundaries (PPB) in the KNN system, which makes it easy to polarize near the phase boundaries, and the polarizability changes suddenly, leading to electromechanical enhancement. In addition, the results show that the K0.5Na0.5NbO3 thin films possess a large electrocaloric response at the phase boundary at the r12-a1a2 and a1c-a1 phase boundaries. And the maximum adiabatic temperature change ∆T is about 3.62 K when the electric field change is 30 MV/m at room temperature, which is significantly enhanced compared with equiaxed strain. This study provides theoretical guidance for obtaining K1-xNaxNbO3 epitaxial thin films with excellent properties.

Dyslipidemia (Dys) is a disease characterised by abnormally high levels of lipids in the blood. It causes the deposits of lipids on the arterial wall leading to the insurgence of atherosclerosis, i.e. the increased thickness of arterial walls, which finally increases the risk of cardiovascular diseases. Dyslipidemia is a comorbidity of Type 2 Diabetes Mellitus (T2DM). A set of genes has been associated with dyslipidemia, but examining the regulation of such genes in age and sex is still an open research field. In this study, we select from publicly available databases the genes associated with dyslipidemia and analyse changes in the basal level of such genes by age and sex. Moreover, we also distinct differential rewiring of the related gene association network in males and females. Our results show that there exist a set of genes whose expression changes with age in artery tibial, artery aorta and blood. Moreover, there exist significant differences between sex.

High prevalence of allergic disorders in Indian pediatric patients demands early diagnosis of allergens so that appropriate allergen avoidance methods, pharmacotherapy or immunotherapy can be provided in time to avoid the worsening of symptoms due to triggers. In this context, identification of the most prevalent aeroallergens in a given area is critical for diagnosis and treatment of various allergic reactions especially in case of rhino-conjunctivitis and asthma. The specific diagnosis of IgE mediated allergy is usually based on the correlation between the clinical history and signs and symptoms endorsed by the diagnostic tests. Skin prick tests are the gold standard however has some limitation. In view of this, the aim of this study was to assess the significance of ImmunoCAP assay for assessing serum specific IgE levels, available in India, against skin prick test by standardized allergens, for the diagnosis of allergic sensitization. A single-center observational study was conducted at tertiary care corporate hospitals in North India from 2017-2020. Patients with self-reported allergic symptoms or whose symptoms were suspected for allergies were tested for the type of sensitization using skin prick test (SPT) after their consents followed by ImmunoCAP based quantification of serum specific IgE levels. A total of 256 (95.9%) pediatric patients were analyzed in the study and were analysed. The patients were most commonly (30% patients) sensitized to D. farinae (173 [67.6%]), D. pteronyssinus (174 [68.0%]), Acarus siro (93 [36.3%]), Lepidoglyphus destructor (96 [37.5%]), Plantago lanceolata (Engl.). The ROC curve of Bermuda grass shows that the AUC of serum-specific IgE is larger than that of SPT (1.000 / 0.881). The receiver operating characteristic (ROC) analysis of serum-specific IgE reference method resulted in the largest AUC of all the allergens taken into consideration (0.711 / 1.000) compared to those of SPT (0.589 / 1.000). These results revealed that serum-specific IgE is more reliable method over prick test for accessing the sensitivity of patient for various allergens. This study may be helpful in performing early diagnosis of allergies as well as in taking appropriate preventive measures for managing life threatening allergic reactions

The development of biosensors for target detection plays a crucial role in advancing various fields of bioscience. This work presents the development of a genosensor that exploits the colorimetric phenol-sulfuric acid sugar reaction for the detection of DNA, and RNA as specific targets, and DNA intercalator molecules. The biosensor combines simplicity and reliability to create a novel bio-assay for accurate and rapid analysis. A 96-well microplate based on polystyrene polymer was used as the platform for an unmodified capture DNA immobilization via a silanization process and with (3-Aminopropyl) triethoxysilane (APTES). After that, a hybridization step was carried out to catch the target molecule, followed by adding phenol and sulfuric acid to quantify the amount of DNA or RNA sugar backbone. This reaction generates a yellow-orange color on the wells measured at 490 nm that was proportional to the target concentration. Under the optimum conditions, a calibration curve was obtained for each target. The developed biosensor demonstrated high sensitivity, good selectivity, and linear response over a wide concentration range for DNA and RNA targets. Additionally, the biosensor was successfully employed for the detection of DNA intercalator agents that inhibit the hybridization of DNA complementary to the immobilized capture DNA. The developed biosensor offers a potential tool for sensitive and selective detection in various applications, including virus diagnosis, genetic analysis, pathogenic bacteria monitoring, and drug discovery.

Humans learn from a lot of information sources to make decisions. Once this information is learned in the brain, spatio-temporal associations are made, connecting all these sources (variables) in space and time represented as brain connectivity. In reality, to make a decision, we usually have only part of the infor-mation, either as a limited number of variables, or limited time to make the decision, or both. The brain functions as spatio-temporal associative memory. Inspired by the ability of the human brain, a brain-inspired spatio-temporal associative memory was proposed earlier, that utilizes the NeuCube brain-inspired spiking neural network framework. Here we apply the STAM framework to develop STAM for neuroimaging data, on the cases of EEG and fMRI, resulting in STAM-EEG and STAM-fMRI. The paper shows that once a NeuCube STAM classification model is trained on a complete spatio-temporal EEG or fMRI data, it can be recalled using only part of the time series, or/and only part of the used variables. We evaluate accordingly the temporal association accuracy and spatial association accuracy. This is a pilot study that opens the field for the development of multimodal classification systems on other multimodal neuroimaging data, such as the also shown longitudinal MRI data, trained on complete data, but recalled on partial data collected across different settings, in different labs and clinics, that may vary in terms of variables, time of data collection, and other parameters. The proposed methods will allow also for brain diagnostic/prognostic marker discovery using spatio-temporal neuroimaging data.

Comparisons of power flows and efficiencies in two structurally quite similar cylindrical series-parallel planetary gear systems (PGSs) were performed in three separate parts of this paper. Each of these single degree of freedom (DoF) systems consists of three different 2KH subsystems connected in series-parallel. The main goal was to prove that apart from complex, structurally and dynamically coupled PGSs, there are also complex and only structurally coupled PGSs, in which the phenomenon of power flow circulation inside closed loops does not occur. Such a half-coupled type of PGS is herein called pseudo-coupled. Therefore, Part I discusses in detail the geometry, kinematics and statics of coupled PGSs in order to determine power flow paths. A comparison of the directions of power flow in both types of PGSs can be made in Part II after determining the power flow paths in the second planetary gear in a similar way. The directions of power flow in both types of PGSs were determined in a relatively simple way, thanks to the distinction between active and passive torques and thus active and passive shafts of individual subsystems. The efficiency comparison made in Part III will show whether power circulation has an influence on the efficiency value, at least in these two types of PGSs.

The Covid-19 pandemic has forced the transfer of local government public ser-vices to the virtual world. Remote handling of matters in government offices has be-come the norm rather than the exception. The 2016 EU directive on public sector web-sites and mobile applications and the 2019 European Digital Accessibility Act made it mandatory that these services be provided electronically and accessible to people with disabilities. The purpose of the study conducted by the authors was to determine whether the Covid-19 pandemic resulted in the implementation of European solutions in the Polish legal order and whether this implementation resulted in the actual adap-tation of digital activities of local government units (LGUs) to the needs of people with disabilities. The research was conducted in Q4 2022 in two trial formats: 1. In the form of a survey (about 250 LGUs), which covered compliance with for-mal requirements, the level of readiness of the officials to create digitally accessible documents and content, and organizational readiness of the offices. 2. In the form of an analysis of the source code of the websites of 66 Polish cities with county rights - due to the availability of results of the same sample from 2015. The completed research showed that the LGUs in Poland: 1. met the formal and organizational requirements for digital accessibility, 2. did not make the necessary efforts to prepare employees to create digitally ac-cessible documents and content, 3. the surveyed websites had inferior source code in terms of meeting the WCAG standard in 2022 than in 2015. It seems reasonable to conclude that the Covid-19 pandemic had a formal, rather than real, impact on the digital accessibility of services provided by Polish LGUs.

Cu-Sn shape-memory microwires were fabricated by a glass-coated melt spinning method. Effects of Sn content on the microstructure and mechanical property of microwires were investigated. The phase transforms from martensite to austenite with Sn content increasing from 14.0 atomic percent (at.%) to 16.5 at.%, and highly ordered intermetallic phase, δ, formed with higher Sn content. The fracture stress, σf, and the critical stress for martensitic transformation, σMs, increases with Sn content increasing. The mechanical property as well as superelasticity were improved greatly by high cooling rate of the glass-coated melt spinning method.

The erythropoietin-producing hepatocellular carcinoma (Eph) receptors are the largest receptor tyrosine kinases family. EphB4 is essential for cell adhesion and motility during embryogenesis. Pathologically, EphB4 is overexpressed and contributes to poor prognosis in various tumors. Therefore, sensitive monoclonal antibodies (mAbs) should be developed to predict the prognosis for multiple tumors with high EphB4 expression, including breast and gastric cancers. This study aimed to develop highly sensitive and specific anti-EphB4 mAbs for several applications using the Cell-Based Immunization and Screening (CBIS) method. EphB4-overexpressed Chinese hamster ovary (CHO)-K1 (CHO/EphB4) cells were immunized into mice, and we established an anti-EphB4 mAb (clone B4Mab-7), which is applicable for flow cytometry, western blotting, and immunohistochemistry. B4Mab-7 reacted with endogenous EphB4-positive breast cancer cell lines, MCF-7 and MDA-MB-468, but did not react with EphB4-knockout MCF-7 (BINDS-52) in flow cytometry. Dissociation constant (KD) values were determined to be 2.9 × 10‑9 M, 1.3 × 10‑9 M, and 3.3 × 10‑9 M by flow cytometric analysis for CHO/EphB4, MCF-7, and MDA-MB-468 cells, respectively. B4Mab-7 detected the EphB4 protein bands from breast cancer cells in western blotting, and stained breast cancer tissues immunohistochemistry. Altogether, B4Mab-7 demonstrated high sensitivity and specificity against EphB4 in various applications.

Polymer electrolyte membrane water electrolyser suffers mainly from slow kinetics regarding oxygen evolution reaction (OER). Noble metal oxides, like IrO2, RuO2, are generally more active for OER than metal electrodes, exhibiting low anodic overpotentials and high catalytic activity. However, issues like electrocatalyst stability under continuous operation and cost minimization through reduction of the catalyst loading are of great importance for the research community. In the present study, unsupported IrO2 of various particle sizes (different calcination temperatures) were evaluated for the OER and as anode electrodes for PEM water electrolyzers [1]. The elec-trocatalysts were synthesized by the modified Adams method [2][3] and the effect of calcination temperature on the properties of IrO2 electrocatalysts is investigated. Physicochemical charac-terization was conducted using X-ray Diffraction, BET, High-Resolution TEM and XPS analyses. For the electrochemical performance of synthesized electrocatalysts in the OER, cyclic voltammetry and linear sweep voltammetry were conducted in a typical 3-cell electrode configuration, using glassy carbon as working electrode, where the synthesized electrocatalysts were casted on, in 0.5 M H2SO4 solution. The materials, as anode PEM water electrolysis electrodes, were further evaluated in a typical electrolytic cell using Nafion®115 membrane as electrolyte and Pt/C as cathode elec-trocatalyst. The IrO2 electrocatalyst calcined at 400°C shows high crystallinity with 1.24 nm particle size, high specific surface area (185 m2 g-1) and a high OER activity of 177 mA cm-2 at 1.8 V as anode electrocatalyst for PEM water electrolyzer.

The spread of SARS-CoV-2 variants of concern (VOCs), is of great importance to the whole community, since their genetic changes may increase transmissibility, disease severity and reduce effectiveness of vaccines. Moreover, these changes may lead to failure of diagnostic measures, thus variant-specific diagnostic methods are essential. To date, genetic sequencing is the gold standard method to discriminate between variants, however it is time consuming (several days) and expensive. Therefore, the development of rapid diagnostic methods for SARS-CoV-2 in accordance with its genetic modification is of great importance. In this study, we introduce a Mass-Spectrometry (MS)-based methodology for the diagnosis of SARS-CoV-2 in clinical specimens, a methodology which enables universal identification, alongside with variant-specific discrimination. The universal identification of SARS-CoV-2 is based on conserved markers shared by all variants, while the identification of the specific variant relies on variant-specific markers. Determining a specific set of peptides for a given variant consists of a multistep procedure, starting with in-silico search for variant-specific tryptic peptides, followed by tryptic digest of a cell-cultured SARS-CoV-2 variant and identification of these markers by HR-LC-MS/MS analysis. As a proof of concept, this approach was demonstrated for four representative VOCs, in comparison with the wild-type Wuhan reference strain. For each variant, at least two unique markers, derived mainly from the spike (S) and nucleocapsid (N) viral proteins, were identified. This methodology is specific, rapid, easy to perform and inexpensive, therefore can be applied as a general diagnostic tool of pathogenic variants.

Mitochondrial dysfunction plays a pivotal role in numerous complex diseases. Understanding the molecular mechanisms by which the “powerhouse of the cell” turns into the “factory of death” is an exciting yet challenging task that can unveil new therapeutic targets. The mitochondrial matrix protein CyPD is a peptidylprolyl cis-trans isomerase involved in the regulation of the permeability transition pore (mPTP). The mPTP is a multi-conductance channel in the inner mitochondrial membrane whose dysregulated opening can ultimately lead to cell death and whose involvement in pathology has been extensively documented over the past few decades. Moreover, several mPTP-independent CyPD interactions have been identified, indicating that CyPD could be involved in the fine regulation of several biochemical pathways. To further enrich the picture, CyPD undergoes several post-translational modifications that regulate both its activity and interaction to its clients. Here, we will dissect what is currently known about CyPD and critically review the most recent literature about its involvement in neurodegenerative disorders, focusing on Alzheimer’s Disease and Parkinson’s Disease, supporting the notion that CyPD could serve as a promising therapeutic target for the treatment of such conditions. Notably, significant efforts have been made to develop CyPD-specific inhibitors, which hold promise for the treatment of such complex disorders.

Our search of existing cancer databases aimed to assess the current landscape and identify key needs. We analyzed 71 databases, focusing on genomics, proteomics, lipidomics, and glycomics. We found a lack of cancer-related lipidomic and glycomic databases, indicating a need for further development in these areas. Proteomic databases dedicated to cancer research were also limited. To assess overall progress, we included human non-cancer databases in proteomics, lip-idomics, and glycomics for comparison. This provided insights into advancements in these fields over the past eight years. We also analyzed other types of cancer databases, such as clinical trial databases and web servers. Evaluating user-friendliness, we used the FAIRness principle to assess findability, accessibility, interoperability, and reusability. This ensured databases were easily accessible and usable. Our search summary highlights significant growth in cancer databases while identifying gaps and needs. These insights are valuable for researchers, clinicians, and database developers, guiding efforts to enhance accessibility, integration, and usability. Addressing these needs will support advancements in cancer research and benefit the wider cancer community.

Material selection for product design is a complex task. Thus, one of the objectives of this work is to analyze, understand and promote the importance of selection of materials to conceive quality products with help of designers' that promote green self-identity in the early stage of the conception of new products. A questionnaire was sent to professional designers and engineers. 38 responses were validated, this being the sample of our study. The aspects that influence the complex selection of materials and the final quality of the products through the design and production process is presented. As a result of the answers carried out with product designers who work in the market, with students who are graduating and with some engineers, a new approach for the selection of materials was developed. Based on a collection of main ideas from traditional and non-traditional methods of material selection, seeking to group the maximum requirements of both methods, inspired by the "Canvas" model on the basic modular methodology, a new model for a project of new product is presented. Our study focuses on the selection of materials, since this aspect is one of the most relevant steps in early stage of the prototyping phase of new products, with a view to reducing CO² from the air in the atmosphere that we all breathe. The classification of materials is complex, due to the diversity of available options. The novelty of this model is that all properties of the newly designed product, such as technical, aesthetic, productive, environmental and other properties, are all grouped in a model, which serves as an innovative support. Thus, the designer has at his disposal a tool that can help him in the selection of the best material for the products he designs. This study intends to make a contribution in the field of material selection, quality and design of new products, promoting a green self-identity for designers in the initial phase of product design. Consequently, all consumers in search of a sustainable planet will profit from it.

Although instructional feedback plays an essential role in regulating learning and improving performance, few studies have systematically investigated the needs of teachers and students for instructional feedback system or developed designs and experiments, especially at the high school level. To address this research need, the present study investigated the needs of selected students and teachers in a high school in Hubei Province, China, and designed and developed a diagnostic visual feedback system for an experimental study with 125 students from a 10th-grade biology class in the same high school. The results showed that this diagnostic visual feedback report improved student performance (ES=0.37) and that functions such as misconception location, knowledge diagnosis, and knowledge alert were well received by students. These findings have multiple implications for facilitating the design and development of diagnostic visual feedback system.

Nucleic acid therapeutics are witnessing an impressive acceleration in recent years. They work through multiple mechanisms of action, including downregulation of gene expression and modulation of RNA splicing. While several drugs based on the former mechanism have been approved, few target the latter, despite the promise of RNA splicing modulation. To improve our ability to discover novel RNA splicing-modulating therapies, we developed HCS-Splice, a robust cell-based High-Content Screening (HCS) assay. By implementing the use of a two-colour (GFP/RFP) fluorescent splicing reporter plasmid, we developed a versatile, effective, rapid, and robust high-throughput strategy for the identification of potent splicing-modulating molecules. The HCS-Splice strategy can also be used to functionally confirm splicing mutations in human genetic disorders or to screen drug candidates. As a proof-of-concept, we introduced a dementia-related splice-switching mutation in Microtubule-Associated Protein Tau (MAPT) exon 10 splicing reporter. We applied HCS-Splice to the wild-type and mutant reporters and measured the functional change in exon 10 inclusion. To demonstrate the applicability of the method to cell-based drug discovery, HCS-Splice was used to evaluate the efficacy of an exon 10-targeting siRNA, which was able to restore the correct alternative splicing balance.

KV channel-interacting proteins (KChIPs) belong to a family of Ca2+-binding EF-hand proteins that are able to bind to the N-terminus of the KV4 channel α-subunits. As the auxiliary subunit, KChIPs are critically involved in regulating the amplitude and gating properties of KV4 channels by modulating their cell surface trafficking, voltage-dependent activation, inactivation kinetics, and recovery rate from inactivation. IKs, ICa,L, and INa can also be regulated by KChIPs. KChIPs are predominantly expressed in the brain and heart, where they contribute to the maintenance of the excitability of neurons and cardiomyocytes by modulating the KV4 currents. Interestingly, all KChIPs can act as transcription factors to control the expression of genes involved in pain, memory, and circadian regulation. Altered expression of KChIPs has been implicated in the pathogenesis of many diseases, such as arrhythmia, heart failure, Alzheimer's disease, etc. In this review, we summarize the research progress of KChIPs in their structural properties, physiological functions, and pathological roles in disease progression, and provide an overview of the therapeutic potential of KChIPs as pharmacological targets for associated disorders.

Scutellaria multicaulis, a member of the Lamiaceae, is a medicinal plant indigenous to Iran, Afghanistan, and Pakistan. It has been widely used as a prominent herb in traditional medicine for thousands of years. This plant is reported with baicalein, wogonin, and chrysin flavonoids as a significant group of chemical ingredients, which can cure different diseases such as breast cancer. S. multicaulis leave extract was used for the bioreduction of silver nanoparticles (SmL-Ag-NPs), and their phytochemical contents and antioxidant, antibacterial, anti-proliferative, and apoptotic activity were evaluated. Optimal physicochemical properties of SmL-Ag-NPs were obtained by mixing 5% of leave extract and 2 mM of aqueous AgNO3 solution and confirmed by characterization studies including UV–visible spectrophotometry, FE-SEM, EDX, DLS, zeta potential, TGA, SERS, XRD and FTIR Spectroscopy. SmL-Ag-NPs exhibited higher content of TPC (Total Phenolic Content) and TFC (Total Flavonoid Content) and potential antioxidant activity. SmL-Ag-NPs also demonstrated dose-dependent cytotoxicity against MDA-MB231 cells multiplication with an IC50 value of 37.62 μg/mL at 48h through inducing cell apoptosis. This is the first report on the biosynthesis of silver nanoparticles using S. multicaulis leave extract, which can provide treatment for cancer diseases and reduce some negative effects of chemotherapy.

Tree growth is under the combined influence of abiotic and biotic factors. Trees with different sizes may respond differently to these factors, implying that tree heterogeneity in tree size may also modulate the overall growth trend. To test this hypothesis, we focused on the radial growth trends of natural subalpine forests on the Tibetan Plateau. We first extended the iterative growth model (IGM) to the tree-ring scale (IGMR) to test the applicability of the generalized metabolic growth theory to tree growth. As predicted by the IGMR, the radial growth of trees at the aggregate scale is constrained by a unimodal pattern. Using the IGMR, we reconstructed the historical best growth trajectory (HBGT) of trees within the same community based on the tree with the largest radius and/or longest age in the community. From the average difference between the HBGT and the current radial growth rate of trees with different sizes, we constructed an indicator that can measure the overall variation in tree radial growth. Based on this indicator, we found a negative effect of tree size heterogeneity on the overall variability of tree growth across elevations. Further analysis also revealed that the radial growth rate of trees on the Tibetan Plateau has increased significantly compared to the past, where growing season average temperature and annual minimum temperature were negatively and positively correlated with tree growth below and above the treeline, respectively. Our study not only confirmed that the overall variability of tree growth depends on tree size heterogeneity but also proposed an indicator that reveals net changes in tree radial growth rate relative to the past. These theoretical advances facilitate the understanding of changes in the extent of subalpine forests.

A medical entity (hospital, nursing home, rest home, revalidation center, etc.) usually includes a multitude of information systems that allow for quick decision-making close to the medical sensors. The Internet of Medical Things (IoMT) is an area of IoT that generates a lot of data of different natures (radio, CT scan, medical reports, medical sensor data). However, these systems need to share and exchange medical information in a seamless, timely, and efficient manner with systems that are either located within the same entity or located in other healthcare entities. The lack of inter and intra entity interoperability causes major problems in the analysis of patient records and leads to additional financial costs (e.g., redone examinations). In order to develop a medical data interoperability architecture model that will allow providers and different actors in the medical community to exchange patient summary information with other caregivers and partners in order to improve the quality of care, the level of data security, and the efficiency of care, we take stock of the state of knowledge.

To solve the problem of low efficiency of source seeking in implicit information field, this paper presents an autonomous souring method based on balanced searching strategy is enlighten by biological homing behaviors. At the beginning of the research, the source seeking task come down to a multi-objective convergence issue. By taking the feasibility search behaviors as the individual sample of the evolutionary population drawing on the thought of evolutionary algorithms, then combine motion searching with population evolution, so the carrier can be guide to complete source seeking task by solving the multi-objective problem. Furthermore, the distribution entropy is also considerated d to measure the searching bias in the process of source seeking. Combined with the demand of the source seeking process, a new source seeking method of balanced searching strategy is designed. Ultimately, through theoretical analysis and simulation verification confirm the effectiveness and rationality of the proposed method.

Oxidative stress (OS) is a condition in which there is an excess of reactive oxygen species (ROS) in the body, which can lead to cell and tissue damage. This occurs when there is an overproduction of ROS or when the body's antioxidant defense systems are overwhelmed. Quercetin is part of a group of compounds called flavonoids. It is found in high concentrations of vegetables, fruits, and other foods. Over the past decade, a growing number of studies have highlighted the therapeutic potential of flavonoids to modulate neuronal function and prevent age-related neurodegeneration. Therefore, quercetin has been shown to have antioxidant, anticancer, and anti-inflammatory properties, both in vitro and in vivo. Due to its antioxidant character, quercetin alleviates oxidative stress, thus improving cognitive function, reducing the risk of neurodegenerative diseases. On the other hand, quercetin can also help support the body's natural antioxidant defense systems, thus being a potentially practical supplement for managing oxidative stress. This review focuses on experimental studies supporting the neuroprotective effects of quercetin in Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington's disease (HD) and epilepsy.

Spodoptera frugiperda is a relatively new invasive polyphagous insect pest in Indonesia. So far, S. frugiperda infestation has only been reported in corn, however in other countries S. frugiperda has been known to attack many commercial crops. To date, information on biological parameters of S. frugiperda is limited in Indonesian ecologies. Since host plants are a critical factor for insect life-history and has the potential to be used for pest control strategies, it is important to study the biology and survival of S. frugiperda on different host plants. This research was aimed to study the survival, life cycle, and fecundity of S. frugiperda on different host plants and how it affects pest management. The study was conducted by rearing S. frugiperda on 14 common cultivated host plant species in Indonesia. Survival rate, development time, fecundity, and potential attack rate of S. frugiperda on various tested host plants were analyzed in this study. The findings re-vealed that corn was the main host for S. frugiperda. The ability of S. frugiperda to survive on pa-paya, water spinach, banana, spinach, cucumber, and coco grass indicates that these plants are potential alternate host for S. frugiperda. Long beans, bok choy, choy sum, and beans might be in-dicated as a shelter for S. frugiperda. Meanwhile, inappropriate hosts for S. frugiperda include cabbage, broccoli, and cauliflower due to their low survival rate on these plants. This research implies that these plants have the potential to be used as a hedge, trap, or bunker plant in S. frugi-perda management strategies. However, to prevent a detrimental damage, control methods are needed in integrated manner, including monitoring pest populations, environmental engineering, and conservation of natural enemies.

CD44 is known as a cancer stem cell marker of head and neck squamous cell carcinoma (HNSCC) and plays a critical role in cancer malignant progression. Splicing variant isoforms of CD44 (CD44v) are overexpressed in cancers and considered a promising target for cancer therapy. Several monoclonal antibodies (mAbs) against CD44 have been developed by immunizing mice with CD44v3–10-overexpressed cancer cells. In this study, we characterized a novel clone, C₄₄Mab-18 (IgM, kappa). C₄₄Mab-18 reacted with CHO/CD44v3–10, but not with CHO/CD44s by flow cytometry. Enzyme-linked immunosorbent assay revealed that the epitope of C₄₄Mab-18 is determined to be the border sequence between variant 10 and the constant exon 16-encoded sequence. Flow cytometry showed that C₄₄Mab-18 recognizes HSC-3, an oral squamous cell carcinoma(OSCC) cell line. The apparent dissociation constant (K_D) of C₄₄Mab-18 for CHO/CD44v3–10 and HSC-3 was determined to be 1.6 × 10⁻⁷ M and 1.7 × 10⁻⁷ M, respectively. C₄₄Mab-18 detected CD44v3–10, but not CHO/CD44s in western blotting. Furthermore, C₄₄Mab-18 detected endogenous CD44v10 in immunohistochemistry using OSCC tissues. Taken together, C₄₄Mab-18 is useful for detecting CD44v10 in flow cytometry and immunohistochemistry.

Over the years, chitosan has been the subject of numerous studies and has gained significant popularity as a biomaterial due to its various characteristics, including biocompatibility, biodegradability, and bioactivity. In this work, chitosan fibres surface was modified with ursolic acid to improve their antibacterial properties by wet impregnation method. Five specimens of chitosan fibres were immersed in ursolic acid (UA) solution for varying immersion times of 1, 2, 4, 6, and 8 hours. Characterization was carried out by means of FTIR, SEM, UV-Vis spectroscopy; the results indicated an ongoing chemical reaction between chitosan and ursolic acid resulting in changes to the chemical structure. After 2 hours, the absorbance ratio remained constant; suggesting that the reaction had reached completion and the chemical structure of the sample remained stable. Antibacterial tests were performed on the resulting chitosan fibres against two bacterial strains. The fibres without ursolic acid did not exhibit any noteworthy antibacterial activity against either strain. However, the chitosan fibres modified with ursolic acid showed significant and almost strong antibacterial activity against the Gram-positive strain, S. aureus. These results suggest that chitosan fibres modified with ursolic acid could have potential applications as antibacterial materials, particularly against Gram-positive bacteria.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are inevitable, and they can escalate into blowouts and other catastrophic events that result in casualties and substantial economic losses. Therefore, maintaining drilling safety requires accurate monitoring of gas invasion and overflow. The majority of overflow monitoring methods currently utilized at drilling sites are threshold-based. However, monitoring parameters acquired during actual drilling operations frequently contain noise signals, making it difficult for threshold-based methods to strike a balance between improving accuracy and minimizing false positives. In this paper, Pattern Recognition-based Kick Detection (PRKD) is proposed as a novel method for diagnosing overflow in offshore drilling. This method utilizes the overflow evolution process by integrating multi-phase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. The PRKD effectively detects and monitors gas intrusion and overflow based on single parameters by analyzing the shape and wave characteristics of the curves. The case analysis demonstrates that the proposed method for monitoring drilling overflow achieves high precision while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, the PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations.

Margarines are W/O emulsions with minimal fat and are heat treated when used for baking. Lipid oxi-dation has been identified as the major deterioration process of margarines and addition of antioxidants is necessary. Consumers are increasingly demanding that chemical antioxidants in foods be replaced by natural preservatives. A multivariate statistical study gave us oxidative stability depending on the com-position of 20 different commercial margarines and an analysis of the principal components allowed us to classify and select eight of them. This study analyzes the antioxidant capacity of six different natural ground herbs (Curcuma longa, Illicium verum, Rosmarinus officinalis, Taraxacum officinale, Thymus piperella and Thymus vulgaris) on the oxidative stability of eight selected margarines. In order to evalu-ate the oxidative stability, we determine the induction period (IP) with Rancimat assays at 120 ºC with 1.5 hours of suppression. As results, Rosmarinus officinalis increases the IP value by 73.17% with respect to its basal values, Curcuma longa, Thymus vulgaris and Thymus piperella increases it between 17% and 26% and Taraxacum officinale together with Illicium verum reduces it between 19% and 34% respec-tively. A multiple linear regression model approach shows that IP has a positive correlation with SFA, PUFA,  acids, MUFA/PUFA ratio and antioxidant activity.

Chi-squared automatic interaction detector (CHAID) algorithm is considered to be one of the mostly used supervised learning methods as it is adaptable to solving any kind of problem at hand. We have been starkly aware of CHAID maps non-linear relationships quite well, and it can empower predictive models with stability. But we don’t know how high its accuracy is precisely. To find out the perfect scope CHAID algorithm fits into, this paper presents the analysis of the accuracy of the CHAID algorithm. We introduce the causes, applicable conditions and application scope of CHAID algorithm at first, and then highlight the difference of branching principal between the CHAID algorithm and several other common decision tree algorithms, which is our first step towards basic analysis on CHAID algorithm. We next employee an actual branching case to help us understand CHAID algorithm better. Specifically, we use vehicle customer satisfaction data to compare multiple decision tree algorithms, and cite some factors that affecting the accuracy and some corresponding countermeasures which are more conducive to us to obtain accurate results. The results show that CHAID can analyze the data very well, and detect the significantly correlated factors surely. In this paper, we learn the clear information required to understand CHAID algorithm, thereby make better choices when we need to use decision tree algorithms.

In Thailand, parking time violation is a major problem, especially for mini-marts. At present the task of detecting parking time violation is mainly conducted manually using Closed-Circuit Television (CCTV). This method requires additional human labour to track incoming and outgoing vehicles. Therefore, low cost time violation tracking is needed. To the best of our knowledge, there has not been any research for parking violation detection and tracking conducted for parking time limits. This paper introduces a novel parking time violation detection algorithm using the Yolov8 and DeepSORT tracking algorithms to track vehicles in consecutive frames. The presented parking violation tracking algorithm can provide a guideline for research in parking time violation detection.

In the presence of aquatic plants in streams, a variety of flow structures have been reported. Re-sults of earlier investigations indicated that the hydrodynamic features of flows in rivers, and streams are influenced by a wide range of submerged and non-submerged vegetation. In the pre-sent study, eight experiment runs were conducted in two artificial pools built in a laboratory flume to assess the flow structures across vegetation cover. The slopes for entrance and exit sec-tions of these two pools are of 5 and 10 degrees, respectively. A patch of artificial grass covered the entire pool area over the gravel bed. The effect of stream flow velocity was investigated by considering two aspect ratios of 2 and 2.7. Also, distributions of flow velocity, Reynolds normal and shear stresses, turbulence intensities, turbulent kinetic energy (TKE), and higher-order mo-ments of velocity fluctuations have been investigated. By means of quadrant analysis, it is found that the skewness coefficients of velocity profiles are significant parameters to evaluate. Based on skewness values for the bursting processes, along the pool entrance section with a smaller slope, the contribution of sweep motion occurs in a more restricted zone above the canopy, and this im-plies that the ejection motion occurs in a pool entrance section with a higher slope. Immediately above the vegetation canopy, the dominant process is the sweep motion of bursting events. Whereas, at the upstream boundary of the vegetation patch, an outward motion with slightly pos-itive value occurs; and around the downstream boundary of the vegetation patch, the isotropic turbulence appears at the boundary of the vegetation and gravel bed. Over the vegetation canopy in the pool, less mixing eddies result in lower Reynolds shear stress values, and thus the turbulent flow becomes weak with lower turbulent kinetic energy (TKE). Because of the shallow flow in an artificial channel with an aspect ratio less than five and the availability of vertical non-zero ve-locity components, secondary currents become stronger in the channel. Consequently, there is a divergence from a linear dispersion of Reynolds shear stress.

More than fifty million people over the age of fifty have osteoporosis issues due to low bone mass, disease contribution, and not exercising continuously. Certain most important risk factors and causes of osteoporosis contain age, gender, hormones, visits to inexperienced doctors, and certain medical conditions. In this manuscript, we diagnosed certain frank operational laws under the availability of complex intuitionistic fuzzy (CIF) information. Furthermore, using the evaluated operational laws, we pioneered the theory of CIF frank weighted averaging (CIFFWA), CIF frank ordered weighted averaging (CIFFOWA), CIF frank hybrid averaging (CIFFHA), CIF frank weighted geometric (CIFFWG), CIF frank ordered weighted geometric (CIFFOWG), CIF frank hybrid geometric (CIFFHG) operators, and described their beneficial and valuable results with certain useful properties. Moreover, we aim to evaluate the most dangerous type of osteoporosis based on their symptoms, causes, and risk factors using diagnosed approaches. Finally, to enhance the worth of the evaluated operators, we compare the diagnosed result with certain prevailing results and illustrated their geometrical representation with the help of MATLAB.

This study was conducted to identify soil cadmium (Cd) removal pathways and their contribution rates during phytoremediation by Pennisetum hybridum, as well as to comprehensively assess its phytoremediation potential. Multilayered soil column tests and farmland simulating lysimeter tests were conducted to investigate the Cd phytoextraction and migration patterns in topsoil and subsoil simultaneously. The aboveground annual yield of P. hybridum grown in the lysimeter was 206 ton·ha–1. The total amount of Cd extracted in P. hybridum shoots was 234 g·ha–1, which was similar to that of other typical phytoremediation plants. After the test, the topsoil Cd removal rate was 21.50%–35.81%, whereas the extraction efficiency in P. hybridum shoots was only 4.17%–8.53%. These findings indicate that extraction by plant shoots was not the most important contributor to the decrease of Cd in the topsoil. The proportions of Cd retained by root cell wall was approximately 50% of the total Cd in root. Based on column test results, P. hybridum treatment led to a significant decrease in soil pH and considerably enhanced Cd migration to subsoil and groundwater. P. hybridum decreases Cd in the topsoil through multiple pathways and provides a relatively ideal material for phytoremediation of Cd-contaminated soils.

Solute carrier (SLC) proteins transport a wide range of substrates across biological membranes and more than 400 proteins are considered as SLCs based on its sequence. Despite it has important potential applications in drug development, the SLC superfamily is still understudied. Drosophila blot, an orphan SLC protein, regulates F-actin organization in the syncytial blastoderm and the Malpighian tubules. However, the molecular mechanism was unknown. In this study, we found Blot was localized at the furrow canal, the front of the invaginating membrane during cellularization process. Blot is required for maintaining proper morphology of furrow canal and cellularization process. By affinity purification and mass spectrometry we identified RhoGEF ELMO/DOCK complex was required for Blot-mediated F-actin organization and cellularization. Further analysis revealed that ELMO localization depends on Blot. Taken together, we propose Blot plays a role in F-actin organization as an upstream factor of ELMO by recruiting ELMO to the target membrane compartments.

Environmental legislation on waste management coupled with the potential for nutrients recovery are key factors encouraging the use of advanced treatment technologies to manage biosolids waste. In this context, phosphorus recovery from a sewage sludge treated by a wet oxidation process was carried out. High organic matter (up to 85% in COD) and Total Solids content (up to 75%) removal values were achieved at elevated temperature (up to 300 ºC) and pressure (up to 200 bar) conditions. The liquid and solid fractions found in oxidation process effluent contain amounts of phosphorus that can be recovered. This research aims to maximize its valorization in both liquid and solid fractions. In the liquid effluent, phosphorus was recovered (up to 90 mg P L-1) by chemical precipitation as struvite (MgNH4PO4∙6 H2O), a slow-release fertilizer. In this case, P recoveries greater than 95% were achieved. Also, the solid fraction, analyzed after filtration and drying (68 mg P gsolid-1), was treated by acid leaching, to achieve up to 60% phosphorus recovery. All phosphorus extracted was in orthophosphate form.

Radiotherapy commonly utilizes CBCT for patient positioning and treatment monitoring. CBCT is deemed to be secure for patients, making it suitable for the delivery of fractional doses. However, limitations such as a narrow field of view, beam hardening, scattered radiation artifacts, and variability in pixel intensity hinder the direct use of raw CBCT for dose recalculation during treatment. To address this issue, reliable correction techniques are necessary to remove artifacts and remap pixel intensity into HU values. This study proposes a deep-learning framework for calibrating CBCT images acquired with narrow FOV systems and demonstrates its potential use in proton treatment planning updates. Cycle-consistent GAN processes raw CBCT to reduce scatter and remap HU. Monte Carlo simulation is used to generate CBCT scans, enabling the possibility to focus solely on the algorithm’s ability to reduce artifacts and cupping effects without considering intra-patient longitudinal variability and producing a fair comparison between planning CT and calibrated CBCT dosimetry. To showcase the viability of the approach using real-world data, experiments were also conducted using real CBCT. Tests were performed on a publicly available dataset of 40 patients who received ablative radiation therapy for pancreatic cancer. The simulated CBCT calibration led to a difference in proton dosimetry of less than 2%, compared to the planning CT. The potential toxicity effect on the organs at risk decreased from about 50% (uncalibrated) up the 2% (calibrated). The gamma pass rate at 3%/2mm produced an improvement of about 37% in replicating the prescribed dose before and after calibration (53.78% vs 90.26%). Real data also confirmed this with slightly inferior performances for the same criteria (65.36% vs 87.20%). These results may confirm that generative artificial intelligence brings the use of narrow FOV CBCT scans incrementally closer to clinical translation in proton therapy planning updates.

Altered metabolism is a common feature of many cancers and in some cases is a consequence of mutation in metabolic genes, such as the ones involved in Krebs cycle. Isocitrate dehydrogenase (IDH) gene is mutated in many gliomas and other cancers. Physiologically IDH converts isocitrate to αketoglutarate (αKG), but when mutated, IDH reduces αKG to D2-hydroxyglutarate (D2-HG). D2-HG accumulates at high levels in IDH mutant cancers, and in the last decade, a massive effort has been done to develop small inhibitors targeting mutant IDH. In this review, we summarize current knowledge about the cellular and molecular consequences of IDH mutations, and the therapeutic approached developed to target IDH mutant tumours, with a focus on gliomas.

Biowaste management is in the center of attention in recent years, due to the increased focus on Circular Economy practices. Recent management solutions promote exploration for small and medium scale processing and monitoring practices. In this context, two pathways of biowaste valorization are analyzed: composting and anaerobic digestion. This study focuses on energy production with the hydrothermal carbonization (HTC) of anaerobic residues from biogas production. Lesvos has numerous processing facilities and olive mills, and therefore Olive Mill Wastewater (OMWW) are the main biowaste streams in the island, along with olive tree pruning, the organic fraction of municipal solid waste and sludge from wastewater treatment facilities. Most studies present applications on specific types of biowaste, while this study aims to co-treat several biowaste streams. A holistic experimental set-up that combines aerobic and anaerobic treatment strategies was developed taking into consideration the hydrothermal treatment of AD digestate along with locally available biowaste, like OMWW, sludge etc. A main target objective is to investigate if solid fraction could have a high heating potential In addition, HTC was able significantly to reduce the COD of OMWW while resulting in hydrochars with increased heating values.

Salmon aquaculture generates 80% of the total revenue of finfish aquaculture across Canada. Salmon farming is carried out in a multilevel process, and at least 60% of the total production is considered as by-products, including skin, head, viscera, trimming, frames, bones, and roes. These by-products are an excellent source of protein, which can be converted to protein hydrolysates through enzymatic hydrolysis and non-enzymatic processes such as chemical hydrolysis (acid and alkaline) and salt extraction. Several studies have reported that peptides from salmon protein hydrolysates possess bioactivities, including antihypertensive, antioxidant, anticancer, antimicrobial, antidiabetic, anti-allergic, and cholesterol-lowering effects. Incorporating in-silico computational methods is gaining more attention to identify potential peptides from source protein. The in-silico methods can be used to predict the properties of the peptides and thereby predetermine the processing, isolation, and purification steps that can be used for the peptides of interest. Therefore, it is essential to implement robust, standardized, and cost-effective processing techniques that can easily be transferrable and scale up for industrial applications. This contribution summarizes the latest research information on Atlantic salmon, production statistics, growth lifecycle, processing, protein production techniques, nutritional and functional properties, peptide production and purification processes, as well as potential health benefits as a nutraceutical product.

A FIB/STEM interfacial study was performed on a TBC/Ti₂AlC MAX phase system, oxidized in an aggressive burner rig test (Mach 0.3 at 1300°C for 500 h). The 7YSZ TBC, a-Al₂O₃ TGO, and MAXthal 211 Ti₂AlC base were variously characterized by TEM/STEM, EDS, SADP, and HRTEM. The YSZ was a mix of ‘clean’ featureless and ‘faulted’ high contrast grains. The latter exhibited ferro-elastic domains of high Y content tetragonal t'' variants. No martensite was observed. The TGO was essentially a duplex a-Al₂O₃ structure of inner columnar plus outer equiaxed grains. It maintained a perfectly intact, clean interface with the Ti₂AlC substrate. The Ti₂AlC substrate exhibited no interfacial Al-depletion zone, but rather numerous faults along the basal plane of the hexagonal structure. These are believed to offer a means of depleting Al by forming crystallographic, low-Al planar defects, proposed as Ti_2.5AlC_1.5. These characterizations support and augment prior optical, SEM, and XRD findings that demonstrated remarkable durability for the YSZ/Ti₂AlC MAX phase system in aggressive burner tests.

As a fundamental, overall, and strategic issue facing human society, human migration is a key factor affecting the development of countries and cities given constantly changing population numbers. The fuzziness of the spatiotemporal attributes of human migration limits the pool of open-source data for human migration prediction, leading to a relative lag in human migration prediction algorithm research. This study expands the definition of human migration research, reviews the progress of research into human migration prediction, and classifies and compares human migration algorithms based on open-source data. It also explores the critical uncertainty factors restricting the development of human migration prediction. Given the effect of human migration prediction, in combination with artificial intelligence and big data technology, the paper concludes with specific suggestions and countermeasures aimed at enhancing human migration prediction research results to serve economic and social development and national strategy.

The ability of 2D hybrid structures formed by boron, nitrogen and carbon atoms (h-BNCs) as potential substrates for surface enhanced Raman spectroscopy (SERS) detection of dioxin-like pollutants is theoretically analyzed. The strong confinement and high tunability of the electromagnetic response of the carbon nanostructures embedded within the h-BNC sheets point out that these hybrid structures could be promising for applications in optical spectroscopies, such as SERS. In this work, two model dioxin-like pollutants, TCDD and TCDF, and a model h-BNC surface composed by a carbon nanodisk of ninety-six atoms surrounded by a string of borazine rings, BNC96, are employed for the simulation of the adsorption complexes and the static and pre-resonance Raman spectra of the adsorbed molecules. A large affinity of BNC96 by these pollutants is reflected on the large interaction energies obtained for the most stable stacking complexes, with dispersion being the most important contribution to their stability. The large vibrational coupling of some active modes of TCDF and, specially, of TCDD makes the Raman static spectra display a ‘pure’ chemical enhancement of one order of magnitude. On the other hand, due to the strong electromagnetic response of BNC96, confined within the carbon nanodisk, pre-resonance Raman spectra obtained for TCDD and TCDF display large enhancement factors of 108 and 107, respectively. Promisingly, laser excitation wavelengths frequently used in SERS experiments also provoke significant Raman enhancements, around 104, for the TCDD and TCDF signals. Both the strong confinement of the electromagnetic response within the carbon domains and the high modulation of the resonance wavelengths within the visible and/or UV ranges in h-BNCs should lead to a higher sensitivity than graphene and white graphene parent structures, solving one of the main disadvantages of using 2D substrates for SERS applications.

Geological structures such as joints and faults in rock mass have significant influence on open pit mining. Hence, it is critical to develop a understanding of dynamic joint behaviour under blasting loading. This in turn can provide both theoretical and practical guidance to improve blasting rock fragmentation and associated bucket excavating efficiency. In this paper, delayed blasting on the highwall bench at Baiyunebo open-pit mine was used as an example, a nonlinear joint blasting model was also constructed. By simplifying the blasting wave propagation velocity, the P-wave normal incidence to the joint was obtained. The peak vibration velocity was 0.33m/s at 3.0s. The S-wave reflected by the joint interface was first reflected backward and then forward, which the peak vibration velocity was 0.027 m/s. By combining the relevant stress and displacement theories of type I and II cracks, the equipotential diagrams of the stress and displacement field with the vibration velocity of the particle were obtained. σx was positive in the direction of 0~330° and subjected to tensile stress, whereas σy was positive in the direction of 0~180° and under tensile stress. The longitudinal σy along joint was low in compressive stress distribution area and did not affect surrounding rock at the time. The stress concentration appeared in the lower right corner. Based on the continuous behavior of stress wave in joints, the asymmetry and continuous changes reflected in the whole process could not be analysed by the contour diagram. Hence, ANSYS used to analyse distribution of the stress field. The intensity of the shock wave after detonation was greater than that of the rock strength. Subsequently, the sub-layer shock wave supplemented the shock wave energy that was not enough to break the rock and induced further cracking. This was able to be visualized by the degree of color change post-processing. It was concluded that with the attenuation of the detonation wave energy, the stress exhibited a decreasing trend in this process. According to distribution of the peak effective stress, it was found that the peak value first increased to 10-12 MPa and then showed a downward trend. Overall, the results were validated against the finite element simulation and mathematical analysis.

Digitalisation is one of the European Union's priorities. The European Parliament is shaping and helping to shape new legislation in this area. Digitisation should also help in the transition to a greener economy and in achieving climate neutrality. E-government is one area of digitisation that has been under way for several years in European countries. In this paper, we have focused on identifying different indices that are aimed at measuring digitalization or e-Government. The results of the analysis showed that there are several indices that focus on this area within the EU, such as EGDI, EPI, LOSI, DGI, e-Government benchmark, Eurostat - internet use, GII, DSGI, Going Digital toolkit and DESI. Subsequently, the index areas to be used in the DEA method to measure the effectiveness of e-Government related inputs and outputs within the EU were identified. As can be seen from the analysis, the DEA method has various uses. In order to be able to use the method properly it was necessary to select the most appropriate parameter and to verify their suitability by means of correlation analysis. Among the input and output indices were chosen Internet usage, DSGI, GII, e-Government benchmark, Interaction with public administration online. From the analysis 3 inputs and 3 outputs were used. After implementing the correlation, it can be said that the values between the selected sub-variables are suitable for DEA analysis. Two models were chosen for the calculation, namely CCR and BCC model. CCR model evaluated 10 states as efficient and BCC model evaluated 13 states as efficient. In addition, in the close analysis, we have taken a closer look at the CCR model's inference. Countries such as Denmark, Finland, Estonia, Malta, Portugal, etc. were efficient outliers. When comparing the regions within the EU, we can conclude that the countries of Northern Europe are the most efficient in the field of digitalization (e-Government). As many as 4 countries out of 7 are efficient. In a future study it would be useful to use the SBM model and try to measure the impact of digitalization on selected areas such as economy, society, environment, etc.

Symbolic pole/zero analysis is an important step when designing an analog operational amplifier. Generally, a simplified symbolic analysis of analog circuits suffers from NP-hardness, i.e., an exponential growth of the number of symbolic terms of the transfer function with the circuit size. In this study, we present a mathematical model combined with a heuristic-metaheuristic solution method for the symbolic pole/zero simplification in operational transconductance amplifiers (OTA). At first, the circuit is symbolically solved and an improved root splitting method is applied to extract symbolic poles/zeroes from the exact expanded transfer function. Then, a hybrid algorithm based on heuristic information and a metaheuristic technique using simulated annealing is performed for the simplification of the derived symbolic pole/zero expressions. The developed method has been tested on three analog OTAs. The obtained results show the effectiveness of the proposed method to achieve accurate simplified symbolic pole/zero expressions with the least complexity.

BACKGROUND. The aims of this study was to compare differences in daytime sleepiness between genders and qualification levels in a cohort university Chinese soccer player under 0 Covid policy restrictions in the urban area of Shanghai. METHODS. 491 questionnaires of Epworth Sleepiness Scales (ESS) were compiled online by males and females Soccer Students (SS), Semi-professional players (SP) and professional players (PP) during the ongoing measures of Shanghai lockdown. ANOVA was performed for players levels and gender. RESULTS. Significant differences were found between the 3 levels and between males and females. PP showed a very low score in the ESS (5,97) well below the threshold of 8, while SS and SP showed an ESS score above the threshold. Female showed higher scores than males. CONCLUSIONS. This study present the first data on sleepiness in Chinese soccer players of different level of qualification in a lockdown condition. Professional players has been less affected by lockdown measures than SS and SP. We can hypothesize the reasons resides in the more ordered lifestyle of PP in comparison to SS and SP, which mitigated the effects of the lockdown. Measures to improve sleep in females’ soccer player should be adopted.

Coronavirus disease 2019 (COVID-19), the emissary behind the worst global pandemic of the 21st century, is primarily a respiratory disease-causing virus called SARS-CoV-2 which is responsible for millions of new cases (incidence) and deaths (mortalities), worldwide. Many factors have played a role in the differential morbidity and mortality experienced by nations and ethnicities against SARS-CoV-2, such as the quality of primary medical health facilities or enabling economies. Nevertheless, the most important variable, i.e., the subsequent ability of individuals to be immunologically sensitive or resistant to the infection, was not properly discussed before. Therefore, an astounding issue arose when some developed countries experienced higher morbidity and mortality, compared with their relatively underdeveloped counterparts, despite having excellent medical health facilities. Hence this investigative review attempts to analyze the issue from an angle of previously undiscussed genetic, epigenetic, and molecular immune resistance mechanisms in correlation with the pathophysiology of SARS-CoV-2 and varied ethnicity-based immunological responses against it. The biological factors discussed here include the overall landscape of human microbiota, endogenous retroviral genes spliced into the human genome, copy number variation, and how they could modulate the innate and adaptive immune systems, which put a particular ethnic genetic architecture at a higher risk of SARS-CoV-2 infection than others. Considering an array of these factors in their entirety may help explain the geographic disparity of disease incidence, severity, and subsequent mortality associated with the disease while at the same time encouraging scientists to design new experimental approaches to investigation.

People with sickle cell disease (SCD) are at greater risk of severe illness and death from respiratory infections, including COVID-19 than people without SCD (Centers for Disease Control and Prevention, USA). Vaso-occlusive crises (VOC) in SCD and severe SARS-CoV-2 infection are both characterized by thrombo-inflammation mediated by endothelial injury, complement activation, inflammatory lipid storm, platelet activation, platelet-leukocyte adhesion, and activation of the coagulation cascade. Notably, lipid mediators, including thromboxane A2, significantly increase in severe COVID-19 and SCD. In addition, the release of thromboxane A2 from endothelial cells and macrophages stimulates platelets to release microvesicles which are harbingers of multicellular adhesion and thrombo-inflammation. Currently, there are limited therapeutic strategies targeting platelet-neutrophil activation and thrombo-inflammation in either SCD or COVID-19 during acute crisis. However, due to many similarities between the pathobiology of thrombo-inflammation in SCD and COVID-19, therapies targeting one disease may likely be effective in the other. Therefore, the preclinical and clinical research spurred by the COVID-19 pandemic, including clinical trials of anti-thrombotic agents, are potentially applicable to VOC. Here, we first outline the parallels between SCD and COVID-19; second, review the role of lipid mediators in the pathogenesis of these diseases and lastly, examine the therapeutic targets and potential treatments for the two diseases.

Artic root is a well-known plant adaptogen with multipotential pharmacological properties. Thin-layer chromatography (TLC) – screening followed by diode-array high-performance liquid chromatography and nuclear magnetic resonance spectroscopy proved to be a reliable and convenient method for simultaneous determination of quality of various herbal raw materials and supplements. This combination allowed for comparing and differentiating arctic root samples as well as defining their authenticity. The study provided information on the chemical and biological properties of the seven chosen samples as well as qualitative and quantitative evaluation of the quality markers: rosavin, salidroside, and p-tyrosol. The absence of rosavin, salidroside, and p-tyrosol in three samples was detected using TLC-screening and confirmed by HPLC-DAD and NMR. The paper highlighted the importance of quality control and strict regulation for herbal medicine supplements and preparations.

The rapid development of three-dimensional (3D) acquisition technology based on 3D sensors provides a large volume of data, which is often represented in the form of point clouds. Point cloud representation can preserve the original geometric information along with associated attributes in a 3D space. Therefore, it has been widely adopted in many scene-understanding-related applications such as virtual reality (VR) and autonomous driving. However, the massive amount of point cloud data aggregated from distributed 3D sensors also poses challenges for secure data collection, management, storage, and sharing. Thanks to the characteristics of decentralization and security nature, Blockchain has a great potential to improve point cloud services and enhance security and privacy preservation. Inspired by the rationales behind Software Defined Network (SDN) technology, this paper envisions SAUSA, a blockchain-based authentication network that is capable of recording, tracking, and auditing the access, usage, and storage of 3D point cloud data sets in their life-cycle in a decentralized manner. SAUSA adopts an SDN-enabled point cloud service architecture which allows for efficient data processing and delivery to satisfy diverse Quality-of-Service (QoS) requirements. A blockchain-based authentication framework is proposed to ensure security and privacy preservation in point cloud data acquisition, storage, and analytics. Leveraging smart contracts for digitizing access control policies and point cloud data on the blockchain, data owners have full control of their 3D sensors and point clouds. In addition, anyone can verify the authenticity and integrity of point clouds in use without relying on a third party. Moreover, SAUSA integrates a decentralized storage platform to store encrypted point clouds while recording references of raw data on the distributed ledger. Such a hybrid on-chain and off-chain storage strategy not only improves robustness and availability but also ensures privacy preservation for sensitive information in point cloud applications. A proof-of-concept prototype is implemented and tested on a physical network. The experimental evaluation validates the feasibility and effectiveness of the proposed SAUSA solution.

Read-Across Structure-Activity Relationship (RASAR) is an emerging cheminformatic approach that combines the usefulness of a QSAR model and similarity-based Read-Across predictions. In this work, we have generated a simple, interpretable, and transferable quantitative-RASAR (q-RASAR) model which can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials. The data set involves 29 TiO2-based nanomaterials which contain specific amounts of noble metal precursors in the form of Ag, Au, Pd, and Pt. The data set was rationally divided into training and test sets and the Read-Across-based predictions for the test set were generated using the tool Read-Across-v4.1 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. The hyperparameters were optimized based on the training set data and using this optimized setting, the Read-Across-based predictions for the test set were obtained. The optimized hyperparameters and the similarity approach, which yields the best predictions, were used to calculate the similarity and error-based RASAR descriptors using the tool RASAR-Desc-Calc-v2.0 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. These RASAR descriptors were then clubbed with the physicochemical descriptors and were subjected to features selection using the tool Best Subset Selection v2.1 available from https://dtclab.webs.com/software-tools. The final set of selected descriptors was used to develop multiple linear regression based q-RASAR models, which were validated using stringent criteria as per the OECD guidelines. Finally, a random forest model was also developed with the selected descriptors. The final machine learning model can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials superseding previously reported models in the prediction quality.

The therapeutic effects of volatile anesthetics on mental diseases, particularly schizophrenia, have gained considerable interest. Although isoflurane is a commonly used volatile anesthetic, there’s no more evidence that it could work on treating schizophrenia. Here, we discovered that inhaling isoflurane at low concentrations might reverse the behavioral phenotypes of schizophrenia caused by MK801, such as hyperlocomotion, pre-pulse inhibition impairment, and working memory loss. Isoflurane also helped recovering adult neurogenesis and synaptic plasticity impairments in the dentate gyrus (DG) induced by MK801. To better understand the mechanism, we discovered that isoflurane could reverse the reduction of parvalbumin (PV)-positive GABAergic interneuron (PVI) number and the aberration of NRG1-ErbB4 signaling in the DG; however, isoflurane could not reverse the schizophrenia-related phenotypes caused by PVI ablation, indicating that PVI are necessary for the therapeutic effect of isoflurane. Interestingly, isoflurane could reverse phenotypes caused by blocking PVIs GABA release in the DG, indicating the therapeutic impact is independent of PVI GABA release. Our research revealed that isoflurane might be used to treat schizophrenia, possibly through PVI in the DG.

We present results on the spontaneous crystallization of freely-jointed polymers of hard spheres obtained in an unprecedentedly long Monte Carlo (MC) simulation on a system of 54 chains of 1000 monomers. Starting from a purely amorphous configuration and after a transitory dominance of the hexagonal closed packed (HCP) polymorph, the system crystallizes in a final, stable, face centered cubic (FCC) crystal of very high perfection. Through refined metrics we gauge the degree of ordering and identify the regions of the phase transition and the corresponding morphologies. An analysis of chain conformational characteristics, of the spatial distribution of monomers and of the volume accessible to them shows that the phase transition is caused by an increase in translational entropy that is larger than the loss of conformational entropy of the chains in the crystal compared to the amorphous state. Polymer chains in the crystal adopt ideal random walk statistics as their great length renders local conformational details, imposed by the geometry of the FCC crystal, irrelevant.

Background: Malnutrition has negative consequences in hospitals, like poor disease recovery, increased mortality, length of hospitalization, readmission, and health care costs.Aims: This review was designed to determine malnutrition prevalence in hospitals located in eastern Mediterranean region (EMR).Study design: To conduct this systematic review, papers, including original articles, related references and conference proceedings on the prevalence of malnutrition in adult hospitalized patients published in international journals and scientific databases from 1 Jan 2017 to 31 Jan 2022 will be included. The following keywords and their alternatives will be used in the literature search: malnutrition, patient, and EMR. The protocol has been registered at PROSPERO (code: CRD42022339426).Methods: After initial screening based on inclusion and exclusion criteria, the full text articles will be read carefully and eligible documents will be selected according to the defined objectives. Afterward, the selected papers will be reviewed for methodological quality and the required information will be extracted. Finally, in case of sufficient data, a meta-analysis will be performed. Screening, selection, quality assessment, and data extraction will be done by at least two independent reviewers.Results: This review is ongoing and will be completed until the end of year 2023.Conclusion: This review aims to provide comprehensive evidence about the prevalence of malnutrition among adult inpatients in EMR hospitals. This can provide regional authorities, health managers and policy makers good information regarding current status to make appropriate decisions for promoting the health status in hospitals.

Phase synchronization of weakly coupled limit cycle oscillators are related to the stability of the zero solution of the reduced-order dynamics of phase differences, represented by a systems of differential equations on a hypertorus. Using Rantzer's density function, a dual form of Lyapunov function, we propose a method to certify almost global stability of an equilibrium on a hypertorus. We show that the proposed method can certify robustness of phase synchronization of all-to-all and weakly coupled limit cycle oscillators with respect to disturbances in phases. The method leverages sum of squares polynomial optimization to construct the certification function.

Forests are increasingly becoming fragmented and declining due to natural causes and human-induced activities. The latter creates an imbalance which put the survival of vulnerable species such as those of avifauna at risk. Honeyeaters are group of birds common in Fiji, with certain species strictly confined to specific habitats. This study is an attempt to compare the abundance and foraging behaviours of three sympatric honeyeaters namely Kikau wattled honeyeater, Orange-breasted myzomela and Giant honeyeater at two contradicted sites (USP campus and Colo-i-Suva Forest Reserve). The survey was carried out using point count method along three different transect routes of approximately 2 Km on each study sites . A higher species diversity and abundance was observed in Colo-i-Suva Forest Reserve than in USP campus. Kikau wattled honeyeater are more populated at USP campus due to adequate nectar-producing plants. Whereas both Orange-breasted myzomela (highly adaptable bird species) and Giant honeyeater (forest specifics) are frequent in Colo-i-Suva Forest Reserve. All exhibited a wider range of foraging techniques across forest vertical strata and plant species, except for Giant honeyeater (not observed). The statistical analysis showed that there is a significant difference (p < 0.05) in abundance as well as between the number of honeyeater species in both sites across the forest vertical strata. However, there is no significant difference in the foraging behaviour and the number of honeyeaters found foraging on diverse plant species (p > 0.05).

The specialisation and intensification in agriculture have increased the productivity but have also led to the spread of monocultural systems, simplifying production and reducing genetic diversity. The purpose of this study was to propose crop diversification as a tool to increase biodiversity and achieve sustainable and resilient intensive agriculture, particularly in areas with water scarcity. In this paper, a combined Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) was applied to evaluate the environmental and economic sustainability of a differentiated system of cultivation (pomegranate, almond and olive), according to modern intensive and superintensive cropping systems. Based upon the results obtained, it is deduced that pomegranate cultivation generated the highest environmental load, followed by almond and olive. From the financial analysis, it emerged that almond is the most profitable, followed by pomegranate and olive.

Lemonomycin (1) was first isolated from the fermentation broth of Streptomyces candidus in 1964. The complete chemical structure was not elucidated until 2000 with extensive spectroscopic analysis. Lemonomycin is currently known as the only glycosylated tetrahydroisoquinoline antibiotic. Its potent antibacterial activity against Staphylococcus aureus and Bacillus subtilis and complex architecture make it an ideal target for total synthesis. In this short review, we summarize the research status of lemonomycin for biological activity, biosynthesis and chemical synthesis. The unique deoxy aminosugar-lemonose was proposed to play a crucial role in biological activity, as shown in other antibiotics, such as arimetamycin A, nocathiacin I, glycothiohexide α, and thiazamycins. Given the self-resistance of the original bacterial host, the integration of biosynthesis and chemical synthesis to pursue efficient synthesis and further derivatization is in high demand for the development of novel antibiotics to combat antibiotic-resistant infections.

The ageing transformation of digital health services faces issues of how to distinguish influencing factors, redesign services, and effectively promote measures and policies. In this study, in-depth interviews are conducted and grounded theory applied to open coding, main axis coding, and selective coding to form concepts and categories. Trajectory equifinality modeling clarified the evolution logic of digital transformation. Based on the theory of service ecology, a digital health service ageing model is constructed from the "macro-medium-micro" stages and includes governance, service, and technology transformation paths. The macro stage relies on organizational elements to promote the institutionalization of management and guide the transformation of governance for value realization, including the construction of three categories: mechanism, indemnification, and decision-making. The meso stage relies on service elements to promote service design and realize service transformation suitable for aging design, including the construction of three categories: organization, resources, and processes. The micro stage relies on technical elements to practice experiencing humanization, including the construction of three categories: target, methods, and evaluation. These results deepen the understanding of the main behaviors and roles of macro-organizational, meso-service, and micro-technical elements in digital transformation practice and have positive significance for health administrative agencies to implement action strategies.

Zinc protection of galvanized steel is initially dissolved in alkaline solutions. However, passive layer is formed over time which protects the steel from corrosion. The behavior of galvanized steel exposed to strong alkaline solutions (pH values of 12.7) with a fixed concentration of sulfate ion of 0.04M is studied. Electrochemical measurement techniques such as corrosion potential, linear polarization resistance and electrochemical impedance spectroscopy are used. Synergistic effect of sulfate ion is also studied together with other anions such as chloride Cl- or bicarbonate ion HCO3- and with other cations such as calcium Ca2+, ammonium NH4+ and magnesium Mg2+. Presence of sulfate ions can depassivate the steel, leading to corrosion density of 0.3 µA/cm2 at the end of the test. The presence of other ions in the solution increases this effect. The increase in corrosion density caused by cations and anions responds to the following order (greater to lesser influence): NH4+&gt;Ca2+&gt;Mg2+ and HCO3- &gt;Cl- &gt;SO42-.

Machine learning has become widely adopted as a strategy for dealing with a variety of cybersecurity issues, ranging from insider threat detection to intrusion and malware detection. However, by their very nature, machine learning systems can introduce vulnerabilities to a security defence whereby a learnt model is unaware of so-called adversarial examples that may intentionally result in mis-classification and therefore bypass a system. Adversarial machine learning has been a research topic for over a decade and is now an accepted but open problem. Much of the early research on adversarial examples has addressed issues related to computer vision, yet as machine learning continues to be adopted in other domains, then likewise it is important to assess the potential vulnerabilities that may occur. A key part of transferring to new domains relates to functionality-preservation, such that any crafted attack can still execute the original intended functionality when inspected by a human and/or a machine. In this literature survey, our main objective is to address the domain of adversarial machine learning attacks and examine the robustness of machine learning models in the cybersecurity and intrusion detection domains. We identify the key trends in current work observed in the literature, and explore how these relate to the research challenges that remain open for future works. Inclusion criteria were: articles related to functionality-preservation in adversarial machine learning for cybersecurity or intrusion detection with insight into robust classification. Generally, we excluded works that are not yet peer-reviewed; however, the authors include some significant papers that make a clear contribution to the domain. There is a risk of subjective bias in the selection of non-peer reviewed articles; however, this is mitigated by co-author review. We selected the following databases with a sizeable computer science element to search and retrieve literature: IEEE Xplore, ACM Digital Library, ScienceDirect, Scopus, SpringerLink,Google Scholar. The literature search was conducted upto January 2022. We have striven to ensure a comprehensive coverage of the domain to the best of our knowledge. We have performed systematic searches of the literature, noting our search terms and results, and following up on all materials that appear relevant and fit within the topic domains of this review. This research was funded by the Partnership PhD scheme at the University of the West of England in collaboration with Techmodal Ltd.

Walker Glacier near the northern coast of Ellesmere Island in the High Canadian Arctic (terrestrial margin of the ‘Last Ice Area’) is undergoing rapid ice attrition in response to climate change. We applied culture and molecular methods to investigate fungal diversity in sediments at the terminus of this glacier. Analysis of the mycoflora composition showed that the Walker Glacier isolates separated into two clusters: the surface of the glacier ice and the glacier foreland. The recently exposed soils of the foreland had a lower fungal diversity and different species from those on the ice, with the exception of five species that occurred in both habitats. This loss of glacial ice in the Arctic is therefore resulting in the loss of habitats for cold-dwelling fungal species. Fungal diversity is a potentially rich biological resource of glacial ecosystems, with unique taxa. The rapid loss of these glacial habitats underscores the urgency for more detailed surveys of fungal diversity in the High Arctic, and the need for further isolation of strains as well as cryopreservation of environmental microbiome samples for future research and conservation.

Research Highlights: This study identified the cell cycle genes in birch that likely play important roles during plant growth and development. This analysis provides a basis for understanding the regulatory mechanism of various cell cycles in Betula pendula. Background and Objectives: The cell cycle factors not only influence cell cycle progression together, but also regulate accretion, division and differentiation of cells, and then regulate growth and development of plant. In this study, we identified the putative cell cycle genes in B. pendula genome, based on the annotated cell cycle genes in A. thaliana. It could serve as a foundation for further functional studies. Materials and Methods: The transcript abundance was determined for all the cell cycle genes in xylem, root, leaf and flower tissues using RNA-seq technology. Results: We identified 59 cell cycle gene models in the genome of B. pendula, 17 highly expression genes among them. These genes were BpCDKA.1, BpCDKB1.1, BpCDKB2.1, BpCKS1.2, BpCYCB1.1, BpCYCB1.2, BpCYCB2.1, BpCYCD3.1, BpCYCD3.5, BpDEL1, BpDpa2, BpE2Fa, BpE2Fb, BpKRP1, BpKRP2, BpRb1 and BpWEE1. Conclusions: We identified 17 core cell cycle genes in the genome of birch by combining phylogenetic analysis and tissue specific expression data.

Rapid industrialization, urbanization, and population explosion in sub-Saharan Africa escalate environmental Lead levels with subsequent elevation of blood Lead levels in children. Nutrition status, age, and genetics govern one’s susceptibility to Lead toxicity. This study expounded this susceptibility by relating blood Lead levels, d-aminolevulinic acid dehydratase enzyme activity (ALAD), and genetic variations of proteins that code for ALAD enzyme in urban children of Uganda. Spectrophotometric analysis for blood Lead (BL), hemoglobin levels, and determination d-levels aminolevulinic acid dehydratase enzyme activity of the blood samples from 198 children were performed prior to a polymerase chain reaction and restriction fragment length digestion for ALAD polymorphism was done. Up to 99.5% of samples coded for the ALAD1 allele whereas 0.05% coded for ALAD2. Genotypes ALAD2-2 members had elevated BLL (mean 14.1 µg/dL) and reduced ALAD enzyme activity compared to others. This, therefore, implies that the majority of children hoard BL which may affect them later in life.

The shortage of quantum computers, and their current state of development, constraints research in many fields that could benefit from quantum computing. Although the work of a quantum computer can be simulated with classical computing, personal computers take so long to run quantum experiments that they are not very useful for the progress of research. This manuscript presents an open quantum computing simulation platform that enables quantum computing researchers to have access to high performance simulations. This platform, called QUTE, relies on a supercomputer powerful enough to simulate general purpose quantum circuits of up to 38 qubits, and even more under particular simulations. This manuscript describes in-depth the characteristics of the QUTE platform and the results achieved in certain classical experiments in this field, which would give readers an accurate idea of the system capabilities.

The provenance of the aminoacyl-tRNA synthetases (aaRS) poses challenging questions because of their role in the emergence and evolution of genetic coding. We investigate evidence about their ancestry from curated structure-based multiple sequence alignments of a structurally invariant “scaffold” shared by all 10 canonical Class I aaRS. Three uncorrelated phylogenetic metrics—residue-by-residue conservation, its variance, and row-by-row cladistic congruence—imply that the Class I scaffold is a mosaic assembled from distinct, successive genetic sources. These data are especially significant in light of: (i) experimental fragmentations of the Class I scaffold into three partitions that retain catalytic activities in proportion to their length; and (ii) evidence that two of these partitions arose from an ancestral Class I aaRS gene encoding a Class II ancestor in frame on the opposite strand. Phylogenetic metrics of different modules vary in accordance with their presumed functionality. A 46-residue Class I “protozyme” roots the Class I molecular tree prior to the adaptive radiation of the Rossmann dinucleotide binding fold that refined substrate discrimination. Such rooting is consistent with near simultaneous emergence of genetic coding and the origin of the proteome, resolving a conundrum posed by previous inferences that Class I aaRS evolved long after the genetic code had been implemented in an RNA world. Further, pinpointing discontinuous enhancements of aaRS fidelity establishes a timeline for the growth of coding from a binary amino acid alphabet.

Background: Vascular inflammation plays a crucial role in peripheral arterial disease (PAD), although the role of the mediators involved has not yet been properly defined. The aim of this work is to investigate gene expression and plasma biomarkers in chronic limb-threating ischemia (CLTI). Methods: Using patients from the GHAS trial, both blood and ischemic muscle samples were obtained to analyze plasma markers and mRNA expression, respectively. Statistical analy-sis was performed by using univariate (Spearman, t-Student, X2) and multivariate (multiple lo-gistic regression) tests. Results: 35 patients were available at baseline (29 for mRNA expression). Baseline characteristics (mean): Age:71.4±12.4 (79.4% male); TNF-α:10.7±4.9; hs-CRP:1.6±2.2; Neutrophil-to-lymphocyte ratio (NLR):3.5±2.8. Plasma TNF-α was found elevated (≥8.1) in 68.6% of patients, while high hs-CRP (≥0.5) in 60.5%. Diabetic patients with high level of inflammation showed significantly higher levels of NOX4 expression at baseline (p=0.0346). Plasma TNF-α had a negative correlation with eNOS expression (-0.5, p=0.015) and hs-CRP with VEGF-A (-0.63, p=0.005). The expression of NOX4 was parallel to that of plasma TNF-α (0.305, p=0.037), especial-ly in DM. Cumulative mortality at 12-month was related to NLR ≥3 (p=0.019) and TNF-α ≥8.1 (p=0.048). The best cut-off point for NLR to predict mortality was 3.4. Conclusions: NOX4 and TNF-α are crucial for the development and complications of lower limb ischemia, especially in DM. hs-CRP could have a negative influence on angiogenesis too. NLR and TNF-α represent suita-ble markers of mortality in CLTI. These results are novel because they connect muscle gene expres-sion and plasma information in patients with advanced PAD, deepening the search of new and ac-curate targets for this condition.

In this experimental work, pure nickel oxide and Al-doped NiO thin films have successfully been elaborated onto glass substrates by solar spray pyrolysis technique. The substrates were heated at around 450°C using a solar heater (furnace). The structural, optical and electrical properties of the elaborated Al-doped films have been studied at different atomic percentage ratios (0, 0.5, 1, 1.5 and 2 at. %). The results of Al-doped NiO films XRD patterns were, the formation of (NiO) phase under a cubic crystalline structure (polycrystalline) with a strong favored orientation along (111) plane were noticed at all sprayed films. When Al doping ratio reaches 1 at.%, an growth in crystallite size over 31.9 nm was obtained denoting the nano-structure of the product, which confirmed by SEM images. In addition, aluminum oxide Al₂O₃ was clearly observed at 1.5 at.% Al ratio. Otherwise, all thin films have a good optical transmission in the visible region of about 65%, the optical band gap energy decreased from 3.69 to 3.64 eV with increasing Al doping ratio. It is shown that the layer deposited with 0.5 at.% has less disorder with few defects. The investigation on electrical properties of elaborated thin films confirmed that the conductivity of NiO films was improved, after doping them with Al which affirms their p-type character of semiconductor. However, an addition of an excessive quantity of Al content causes the formation of Al₂O₃ which leads to a decrease in the conductivity. It is worth mentioning that the Al content of 0.5 at.% is the optimum ratio in terms of electrical conductivity and formation defect. Al-doped NiO can be used in various optoelectronic devices due to its good transparency and high electrical conductivity.

Background: Students in the United States gain weight significantly during their first year of university, however limited data are available for Australian students. Methods: This 12-month observational study was conducted to monitor monthly body weight and composition, as well as quarterly eating behaviours, dietary intake, physical activity, sedentary behaviours, and basal metabolic rate changes amongst first-year Australian university students. Participants were first-year university students over 18 years. Results: Twenty-two first-year university students (5 males and 17 females) completed the study. Female students gained weight significantly at two, three, and four-months (+0.9 kg; +1.5 kg; +1.1 kg, p <0.05). Female waist circumference (2.5 cm increase at three-months, p = 0.012), and body fat also increased (+0.9%, p = 0.026 at three-months). Intakes of sugar, saturated fat (both >10% of total energy), and sodium exceeded recommended levels (>2000 mg) at 12-months. Greater sedentary behaviours were observed amongst male students throughout the study (p <0.05). Conclusions: Female students are at risk of unfavourable changes in body composition during the first year of university, while males are at risk of increased sedentary behaviours. High intakes of saturated fat, sugars, and sodium warrant future interventions in such a vulnerable group.

A reliable Electronic Voting Machine (EVM) is proposed and implemented in this study, which is integrated with a biometric fingerprint scanner to ensure a secure election process. This biometric EVM includes features such as an interactive user interface, hack-free design and master lock. The EVM system has the capability of registering user data and storing them in a database through proper authentication. Moreover, the system proposed lowers the requirement for human resources. This paper provides a detailed description of the systematic development of the hardware and software used. The software part includes algorithm development and implementation. A thorough and in-depth understanding of the data and the communication protocols along with the pathways used for storage of data in the devices is provided. Additionally, the cost of the system is 62.82% less than the officially existing EVM machines of India. Furthermore, this study seeks to demonstrate the benefits of such an approach from a technological and a social standpoint.

Socio-ecologic, socio-economic, and socio-technical transitions are opportunities that require fundamental changes in the system. These will encounter matters associated with security, service adoption by end-users, infrastructure and availability. The purpose of this study is to examine and overcome the risks to take advantage of opportunities through the novel Risky-Opportunity Analysis Method (ROAM). A novel quantitative method is designed to determine when, after making some changes, the risks become acceptable so that the opportunity does not deviate from the objectives. The approach provided a quantitative evaluation of the possible changes in parallel with digitization, towards providing a green Service Supply Chain (SSC). The result of ROAM shows that the most cost-effective change to increase the resilience of the system is a solution (SMS) which is different from that identified by a TOPSIS multi-criteria method. Real-word decisions in change management should tackle the complexity of systems and uncertainty of events during and after transition through a careful analysis of the alternatives. A case-study was carried out to evaluate the alternatives of an ancillary service in the Payment Service Providers (PSP). The comparison of the ROAM results with the traditional TOPSIS of the case-study unveils the priority of the ROAM in practice when the alternatives are Risky-Opportunities. The existing risk assessment tools do not take advantage of risky opportunities. To this aim, the current article introduces the term Risky-Opportunity, and two indexes Stress and Strain of the alternatives that are designed to be employed in the new quantitative ROAM approach.

The present study aimed to investigate the effect of a motor skills training program in children with DCD considering their gender. The Movement Assessment Battery for Children (MABC-2) classified the children and assessed skill changes over time. The study was implemented at four kindergartens in the Khorezm region of Uzbekistan. In the study, all children had DCD (5.17 ± 0.70 years; 10 girls), and all indicators on MABC-2 were less than 16 percent. Participants were divided into an experimental group (n=17) receiving ten weeks of motor skills training program for 45 min twice per week, the control group (n=7) proceeded with exercises of everyday living. All children in the experimental group had a significant increase in total percentile rank of MABC-2 and concerning each domain (manual dexterity; throwing and catching; balance). In the control group, a significant decrease in the total percentile rank of MABC-2 and each domain of MABC-2 was observed. The effectiveness of the intervention program was similar across both genders. The study supports that a period of 10 weeks of a motor skills training program can increase the quality of children's motor coordination and represent a valuable procedure for physical education specialists to enhance motor skills for children with DCD.

A developed six-port reflectometry (SPR) system was integrated to measure the relative permittivity of tumor and normal breast tissue for medical diagnostic purpose. In order to obtain an accurate and precise measurement, the calibration process was done to the SPR using the well-known three-standard technique. Next, the studied dielectric probe was connected to the calibrated measurement-port of the SPR. The open end of the probe aperture was dibbed into the normal and tumor synthetic breast tissue samples to measure the synthetic breast tissues dielectric constant, ɛrʹ, and loss factor, ɛrʺ in the frequency range of 1.5 GHz to 3.3 GHz. Finally, the comparative studies were conducted between commercial VNA with Keysight 85070E dielectric probe and the studied SPR-probe system based on the measured magnitude of the reflection coefficient, phase shift, dielectric constant, and loss factor of the synthetic breast samples. The maximum absolute errors of the measured reflection coefficient magnitude, phase shift, dielectric constant, and loss factor were found to be 0.01, 1.07°, 1.12, and 0.75, respectively. It was ascertained that the predicted dielectric constant, ɛrʹ, is able to differentiate between normal, (ɛrʹ &lt; 50) and tumor, (ɛrʹ &gt; 50) breast tissues.

Four-wire low voltage microgrids supply one-phase consumers with continuously changing electricity demand. For addressing climate change concerns, governments implemented incentive schemes for residential consumers, encouraging the installation of home PV panels for covering self-consumption needs. In the absence of sufficient storage capacities, the surplus is sold back by these entities, called prosumers, to the grid operator or in local markets, to other consumers. While these initiatives encourage the proliferation of green energy resources, and ample research is dedicated to local market designs for prosumer-consumer trading, the main concern of distribution network operators is the influence of power flows generated by prosumer surplus injection on the operating states of microgrids. The change in power flow amount and direction can greatly influence the economic and technical operating conditions of radial grids. This paper proposes a metaheuristic algorithm for prosumer surplus management that optimizes the power surplus injections using the automated control of three-phase inverters, with the aim of improving the active power losses and balancing the phase voltage profiles. A case study is performed on two real distribution networks with distinct layouts and load profiles and the algorithm shows its efficiency in both scenarios.

We investigate the power of time series analysis based on a variety of information-theoretic approaches from statistics (AIC, BIC) and machine learning (Minimum Message Length) - and we then compare their efficacy with traditional time series model and with hybrids involving deep learning. More specifically, we develop AIC, BIC and Minimum Message Length (MML) ARMA (autoregressive moving average) time series models - with this Bayesian information-theoretic MML ARMA modelling already being new work. We then study deep learning based algorithms in time series forecasting, using Long Short Term Memory (LSTM), and we then combine this with the ARMA modelling to produce a hybrid ARMA-LSTM prediction. Part of the purpose of the use of LSTM is to seek capture any hidden information in the residuals left from the traditional ARMA model. We show that MML not only outperforms earlier statistical approaches to ARMA modelling, but we further show that the hybrid MML ARMA-LSTM models outperform both ARMA models and LSTM models.

Heat stress during the grain-filling period is the main abiotic stress factor limiting grain yield and quality in wheat (Triticum aestivum L.). In this study, 64 wheat genotypes were exposed to heat stress during reproduction caused by delayed sowing in two growing seasons. Grain yield, 1000 grain weight (GW), grain hardness (GH), and grain-quality related traits were investigated using wholemeal flour. Heat stress caused a significant decrease in GW through reducing starch content (SC) and a non-compensating rise in protein content (PC), and thereby resulted in lower yield. In addition, significant increases in flour water absorption (WA), Zeleny sedimentation volume (ZT), ash content (AC), lipid content (LC), loaf volume (LV), wet gluten content (WG), dry gluten content (DG), gluten index (GI), and amylopectin content (APC) were found following heat stress. In contrast, decreases in grain moisture content (MC) and amylose content (AMC) induced by heat stress were observed. The heat-tolerant genotypes were superior in grain yield, GW, SC, AMC, and MC. While the sensitive genotypes contained higher PC, LV, GI and AMP. A group of wheat genotypes characterized with a higher yield, AMC, GW, and SC as well as lower PC, WA, GH, ZT, and LV; and was found to be the most heat tolerant by principal component analysis. Decreases in the ratio of carbohydrates to proteins induced by heat stress, and lower protein content of normal grown wheat genotypes were observed. Therefore, lighter weight and smaller grains produce a smaller starchy endosperm with lower quality (less amylose) and higher grain protein content in heat stress compared to normal conditions. Heat stress caused by delayed sowing improves some of the baking-quality related traits. Whether this improvement in grain quality attributes will translate into better human health outcomes requires further investigation.

Background-The outbreak of COVID-19 pandemic has affected the global economy from its starting. Indian economy is also affected by the pandemic and experienced a lot of economic damages. India has become the global hotspot of COVID-19 during the second wave of the pandemic and recorded the second-highest position in terms of positivity rate after China. The present study attempts to analyze the economic issues that emerged in the first and second waves of the pandemic in India. Method/Approach-There is no econometric tools or analytical models used in the present study. This study attempts to evaluate the two research questions which are formed on the basis of some previous studies by various organizations and researchers. The research questions are as follow, First, what are the sectors those are primarily affected at the time of the first COVID-19 outbreak? Second, which economic issues and impacts emerged in the second wave of the pandemic? Results/ Findings-From the study, it is found that the second wave of COVID-19 is not much affected by the Indian economy. At this time, no nationwide lockdown was announced by the Government. But so, it was much severe in the time of the first wave of COVID-19. Many sectors were affected by the pandemic like agriculture, MSMEs, Tourism, etc., and these resulted in substantial unemployment problems in the economy. The study is trying to analyze these problems and concluding it with a few policy recommendations for the economy of India.

The main purpose of bovine colostrum, being the milk secreted by a cow after giving birth, is to transfer passive immunity to the calf. The calves have an immature immune system as they lack immunoglobulins (Igs). Subsequently, the supply of good quality bovine colostrum is required. The quality of colostrum is classified by low bacterial counts and adequate Ig concentrations. Bacterial contamination can contain a variety of human pathogens or high counts of spoilage bacteria, which becomes more challenging with emerging use of bovine colostrum as food and food supplements. There is also a growing risk for the spread of zoonotic diseases originating from bovines. For this reason, processing based on heat treatment or other feasible techniques are required. This review provides an overview of literature on the microbial quality of bovine colostrum and processing methods to improve its microbial quality and keep its nutritional values as food. The highlights of this review are: high quality colostrum is a valuable raw material in food products and supplements, the microbial safety of bovine colostrum is increased using appropriate processing-suitable effective heat treatment, which does not destroy the high nutrition value of colostrum, the heat treatment processes are cost-effective compared to other methods, and heat treatment can be performed in both small- and large-scale production.

The Sugarcane yellow leaf virus (SCYLV) is associated with sugarcane yellow leaf disease (SCYLD) and is considered to be the most economically deleterious emerging pathogen that represents a potential threat and danger to sugarcane cultivation in China. Over the last two decades, high genetic diversity in the SCYLV genotypes was observed worldwide, with a greater chance of YLD incidence for sugarcane injury. SCYLV infection has significantly damaged its economic traits and is responsible for substantial losses in biomass production in sugarcane cultivars. This study aims to identify and comprehensively analyze sugarcane microRNAs (miRNAs) as therapeutic targets against SCYLV using plant miRNA prediction tools. Mature sugarcane miRNAs are retrieved and are used for hybridization of the SCYLV. A total of seven common sugarcane miRNAs were selected based on consensus genomic positions. The biologically significant, top ranked ssp-miR528 was consensually predicted to have a potentially unique hybridization site at nucleotide position 4162 for targeting the ORF5 of the SCYLV genome; this was predicted by all the algorithms used in this study. Then, the miRNA–mRNA regulatory network was generated using the Circos algorithm, which was used to predict novel targets. There are no acceptable commercial SCYLV-resistant sugarcane varieties available at present. Therefore, the predicted biological data offer valuable evidence for the generation of SCYLV-resistant sugarcane plants.

Senna alata (Linn) Roxb. plant is widely used to manage various infections in folkloric medicine. Methicillin-resistant Staphylococcus aureus (MRSA) infection continues to be a major global public health problem. This study aims to investigate the bioactive components of S. alata leaves active against MRSA. The leaves of S. alata were sequentially extracted and fractionated using standard methods and screened for activities against MRSA. The diethyl ether active thin layer chromatography (TLC) spot was subjected to infrared (IR) and gas chromatography-mass spectroscopic (GC-MS) studies. The aqueous extract and diethyl ether fraction of S. alata leaves elicited the highest activity against the MRSA. The GC-MS analysis of the fraction produced 15 eluates; only the sub-fraction 13 was effective. The TLC analysis of the sub-fraction 13 revealed three spots; only the second spot produced activity. The GC-MS result of the spot showed six peaks. The spectral results for peak 3 match the data from the IR study suggestive of 9-octadecenoic acid methyl ester. Senna alata leaves possess bioactive compounds closely related to 9-octadecenoic acid methyl ester with potent antibacterial activity against MRSA.

Work from the last years indicate that the extracellular matrix (ECM) plays a direct role in vari-ous cellular processes including proliferation, migration and differentiation. Besides homeostat-ic processes, its regulatory function in inflammation becomes more and more evident. In in-flammation like inflammatory bowel disease, the ECM composition is constantly remodeled which can result in a structuring of fistulizing disease course. Thus, tracking early ECM changes might bear the potential to predict the disease course. In this review, we will provide an over-view of relevant diagnostic methods focusing on ECM changes.

Augmented and Virtual Reality have been experiencing a rapidly growth in recent years, but there is not still a deep knowledge on their capabilities and where they could be explored. In that sense, this paper presents a study on the accuracy and repeatability of the Microsoft's HoloLens 2 (Augmented Reality device) and HTC Vive (Virtual Reality device) using an OptiTrack system as ground truth. For the HoloLens 2, the method used was hand tracking, while in HTC Vive, the object tracked was the system's hand controller. A series of tests in different scenarios and situations were performed to explore what could influence the measures. The HTC Vive obtained results in the millimetre scale, while the HoloLens 2 revealed not so accurate measures (around 2 centimetres). Although the difference can seem to be considerable, the fact that HoloLens 2 was tracking the user's hand and not an inherit controller made a huge impact. The results were considered a significant step for the on going project of developing a human-robot interface to program by demonstration an industrial robot using Extended Reality, which shows great potential to succeed based on this data.

The pop-in effect in nanoindentation of metals represents a major collective dislocation phenome-non that displays sensitivity in the local surface microstructure and residual stresses. To under-stand the deformation mechanisms behind pop-ins in metals, large scale molecular dynamics simulations are carried out to investigate the pop-in behavior and indentation size effect in unde-formed and deformed Cu single crystals. Tensile loading, unloading and reloading simulations are performed to create a series of samples subjected to a broad range of tensile strains with/without pre-existing dislocations. The subsequent nanoindentation simulations are con-ducted to study the coupled effects of pre-strain, the presence of resulting dislocations and surface morphology, as well as indenter size effects on the mechanical response in indentation processes. Our work provides detailed insights into the deformation mechanisms and microstruc-ture-property relationships of nanoindentation in the presence of residual stresses and strains.

Although artificial insemination can mean a slow and progressive improvement of animal genetics, in buffalo-cow its practical application is difficult the results are incomparably lower then cattle. The purpose of this article is to develop a new methodology, a well-known technique to make AI biotechnology more applicable to the buffalo, in order to improve the conception rate. The protocol we follow is to stimulate hormonal ovarian activity, inducing the dominant follicle, causing ovulation and scheduling the moment of sexed artificial insemination deep in the uterine horn only ipsilateral to the ovary that will ovulate. The experiment was performed on 40 primiparous buffaloes-cows in two groups for AI separated by two bulls whit 2 Millions female sperm straws. The groups was compiled after a thorough gynecological examination, and subsequently the OvSynch therapeutic protocol was started. The results were 82,5% buffaloes (33/40) had dominant follicle (DF) and inseminated, on hot/cold seasons the distribution was 75%vs90%. The conception rate was 63,6% (21/33), on hot/cold seasons 60%vs66,6%, and after calving 92.5% (20/21) female cattle were obtained. Thus, by implementing UcFTAI protocol, we state that the goal of increasing the genetic potential of CIB by becomes achievable and can be extended to a larger scale. Our Improved Protocol (UcFTAI) aims to reduce waste and maximize OvSynch hormone therapy.

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can effectively improve the spectrum efficiency and energy efficiency of the wireless networks with extend coverage. An important design issue is to incentivize a relaying center user to participate in the cooperative process and achieve a win-win situation to both the BS and the center user. Some private information of the center users are hidden from the BS in the networks. We apply a contract theory-based incentive mechanism under such asymmetric information scenario to incentives center user to join the cooperative communication to maximize the BS profit utility and to guarantee the center user’s expect payoff. A match theory-based Gale-Shapley algorithm is proposed to obtain the optimal strategy with low computation complexity. Simulation results indicated the network performance of our proposed cooperative transmission is much better than the conventional NOMA transmission and the benefit utility of the BS with the stable match strategy is nearly close to the complete channel state information multi-users scenario while the center users get the satisfied expect payoffs.

Nowadays, we use social networks such as Twitter, Facebook, WeChat and Weibo as means to communicate with each other and get to know others. Gradually social networks has become indispensable in our everyday life, and we cannot absolutely imagine what the daily life would be like without social networks. Through social networks, we can access friends' opinions and behaviors easily and are influenced by them in turn. Thus, an effective algorithm to find the top-K influential nodes (the problem of influence maximization) in the social network is critical for various downstream tasks such as viral marketing, anticipating natural hazards, reducing gang violence, public opinion supervision etc. Solving the problem of influence maximization in real-world propagation scenarios often involves estimating influence strength (influence probability between two nodes), which cannot directly observed. To estimate influence strength, conventional approaches propose various humanly-devised rules to extract features of user interactions, the effectiveness of which heavily depends on domain expert knowledge. Besides, they are often applicable for special scenarios or specific diffusion models. Consequently, they are difficult to be generalized into different scenarios, diffusion models and even domains. Inspired by the powerful ability of neural networks in the field of representation learning, we design a deep hierarchical network embedding model HGE to map nodes (with attributes) into latent space automatically. In general, HGE takes an attributed social network as the input for learning latent network representation of each node, incorporating hierarchical community structure, node attributes and general network structure into a unified deep generative framework. Then, with the leaned latent representation of each node, we propose a HGE-GA algorithm to predict influence strength and compute the top-K influential nodes through a greedy-based maximization algorithm. Extensive experiments on real-world attributed networks demonstrate the outstanding superiority of the proposed HGE model and HGE-GA algorithm compared with the state-of-the-art methods, verifying the effectiveness of the proposed model and algorithm.

Low pressure fluid transport (1) applications often require low and precise volumetric flow rates (2) including low leakage to reduce additional costly and complex sensors. A peristaltic pump de-sign (3) was realized, with the fluid’s flexible transport channel formed by a solid cavity and the wobbling plate comprising a rigid and a soft layer (4). In operation, the wobbling plate is driven externally by an electric motor, hence, the soft layer is contracted and unloaded (5) during pump-cycles transporting fluid from low to high pressure sides. A thorough characterization of the pump system is required to design and dimension the components of the peristaltic pump. To capture all these parameters and their dependencies on various operation-states, often complex and long-lasting dynamic 3D FE-simulations are required. We present, here, a holistic design methodology (6) including analytical as well as numerical calculations, and experimental valida-tions for a peristaltic pump with certain specifications of flow-rate range, maximum pressures, and temperatures. An experimental material selection process is established and material data of candidate materials (7) (liquid silicone rubber, acrylonitrile rubber, thermoplastic-elastomer) are directly applied to predict the required drive torque. For the prediction, a semi-physical, analyti-cal model was derived and validated by characterizing the pump prototype.

An embryonic version of membrane theory can be date back to the Bernstein's work reported more than a hundred years ago. Such an originally old work has evolved conceptually and mathematically up until today, and it plays a central role in current membrane theory. Goldman-Hodgkin-Katz equation (GHK eq.) is one of the math-based monumental works, which constitutes the present membrane theory. Goldman theoretically derived GHK eq., but its physiological meaning was provided by the two renowned scientists, Hodgkin and Katz. These two employed an assumption that the electric field (EF) across the plasma membrane is constant to validate the GHK eq. physiologically. Proposal of Hodgkin-Huxley model (HH model) is another math-based monumental works developed from the membrane theory and now forms a fundamental part of the current membrane theory. GHK eq. and HH model are quite fundamental central concepts in the current physiology. Despite the broad acceptance of GHK eq. at present time, its prerequisite that the EF within the plasma membrane is constant is hardly believable. Especially when the action potential is generated, it sounds totally nonsense. Furthermore, the existence of constant EF within the plasma membrane is conceptually almost in conflict with the HH model. The authors will discuss those problematic issues the membrane theory inherits.

With the depletion of shallow surface resources, the future mining work will develop towards the deep surface, and the objective conditions such as the mining environment will be more complex and dangerous than now, and the requirements for personnel and equipment will be higher and higher. The efficient exploitation of deep space cannot be separated from such mobile and flexible production and transportation equipment as scraper. In the new era, intelligence is the development trend of the LHD, and path tracking control technology is the key to the intelligent LHD, and it is also an urgent problem to be solved for its unmanned driving. This paper describes the realization of the automatic operation function of articulated LHD from two aspects of mathematical model and trajectory tracking control method, and focuses on the research of the path tracking control scheme in the field of unmanned driving, that is, LQR controller. On this basis, the parameters of the LQR controller are optimized by combining different intelligent cluster algorithms to find the optimal solution of the LQR controller.

Oxidative phosphorylation (OxPhos) is the basic function of mitochondria although the land-scape of mitochondrial functions is continuously growing to include more aspects of cellular homeostasis. Thanks to the application of -omics technologies to the study of the OxPhos system, novel features emerge from the cataloging of novel proteins as mitochondrial thus adding de-tails to the mitochondrial proteome and defining novel metabolic cellular interrelations, espe-cially in the human brain. We focussed on the diversity of bioenergetics demand and different aspects of mitochondrial structure, functions, and dysfunction in the brain. Definition as ‘mitoexome’, ‘mitoproteome’ and ‘mitointeractome’ have entered the field of ‘mitochondrial medicine’. In this context, we reviewed several genetic defects that hamper the last step of aerobic metabolism mostly involving the nervous tissue as one of the most prominent energy-dependent tissues and, as consequence, as a primary target of mitochondrial dysfunction. The dual genetic determination of the OxPhos complexes is one of the reasons for the complexity of the geno-type-phenotype correlation when facing human diseases associated with mitochondria defects; clinically, are characterized by extremely heterogeneous symptoms, ranging from organ-specific to multisystemic dysfunction with different clinical courses. Finally, we briefly discuss the fu-ture directions of the multi-omics study of human brain disorders.

Peanut (Arachis hypogaea) contains allergenic proteins, which make it harmful to the sensitised population. The presence of peanut in foods must be indicated on label, to prevent accidental consumption by allergic population. In this work, we use chloroplast markers for specifically detection of peanut by real-time PCR, in order to increase the assay sensitivity. Binary mixtures of raw and processed peanut flour in wheat were performed at concentrations ranging from 100000 to 0.1 mg/kg. DNA isolation from peanut, mixtures and other legumes was carried out following three protocols for obtaining genomic and chloroplast-enrich DNA. Quantity and quality of DNA was evaluated, obtaining better results for protocol 2. Specificity and sensitivity of the method has been assayed with specific primers for three chloroplast markers (mat k, rpl16 and trnH-psbA) and Ara h 6 peanut allergen-coding region was selected as nuclear low-copy target and TaqMan probes. Efficiency and linear correlation of calibration curves were within the adequate ranges. Mat k chloroplast marker yielded the most sensitive and efficient detection for peanut. Moreover, detection of mat K in binary mixtures of processed samples was possible up to 10 mg/kg even after boiling, and autoclave 121°C 15 min, with acceptable efficiency and linear correlation. Applicability of the method has been assayed in several commercial food products.

The combination of snowfall, snow water equivalent (SWE), and precipitation rate measurements from 39 Snow Telemetry (SNOTEL) sites in Alaska are used to assess the performance of various precipitation products from satellites, reanalysis, and rain gauges. Observation of precipitation from two water years (2018-2019) of the high resolution radar/rain gauge data (Stage IV) product was also utilized to add insights into scaling differences between various products. The outcomes were also used to assess two popular methods for rain gauge undercatch correction. It was found that SWE and precipitation measurements at SNOTELs, as well as precipitation estimates based on Stage IV data, are generally consistent and can provide a range in which other products can be assessed. Time-series of snowfall and SWE accumulation suggests that most of the products can capture snowfall events; however, differences exist in their accumulation. Reanalysis products tend to overestimate snow accumulation in the study area, while current combined passive microwave remote sensing products (i.e., IMERG-HQ) underestimate snowfall accumulation. We found that corrections factors applied to rain gauges are effective in improving their undercatch, especially for snowfall. However, no improvement in correlation is seen when correction factors are applied, and rainfall is still estimated better than snowfall. Even though IMERG-HQ has less skill in capturing snowfall than rainfall, analysis using Taylor plots showed that the combined microwave product does have skill in capturing the geographical distribution of snowfall and precipitation accumulation, so bias adjustment might lead to reasonable precipitation estimates. This study demonstrates that other snow properties (e.g., SWE accumulation at the SNOTEL sites) can complement precipitation data to estimate snowfall. In the future, gridded SWE and snow depth data from GlobSnow and Sentinel-1 can be used to assess snowfall and its distribution over broader regions.

Background: transcriptome data provide a valuable resource for the study of cancer molecular mechanisms, but technical biases, samples’ heterogeneity and small sample sizes result in poorly reproducible lists of regulated genes. Additionally, the presence of multiple cellular components contributing to cancer development complicate the interpretation of bulk transcriptomic profiles. Methods: we collected 48 microarray datasets of laser capture microdissected breast tumors, and performed a meta-analysis to identify robust lists of genes differentially expressed in these tumors. We created a database with carefully harmonized metadata to be used as a resource for the research community. Results: combining the results of multiple datasets improved the statistical power, and the analysis of stroma and epithelium separately allows identifying genes with different contribution in each compartment. Conclusions: our database can profitably help biomarkers’ discovery and is readily accessible through a user-friendly web interface (https://aurorasavino.shinyapps.io/metalcm/).

Over the past four decades, China has experienced a nutritional transition and has developed the largest population of internet users. In this study, we evaluated the impacts of internet access on the nutritional intake in Chinese rural residents. An IV-Probit-based propensity score matching method was used to determine the impact of internet access on nutritional intake. The data were collected from 10042 rural households in six Chinese provinces. The results reveal that rural residents with internet access have significantly higher energy, protein, and fat intake than those without. Chinese rural residents with internet access consumed 1.35% (28.62 kcal), 5.02% (2.61 g), and 4.33% (3.30 g) more energy, protein, and fat, respectively. There was heterogeneity as regards the intake of energy, protein, and fat among those in different income groups. Moreover, non-staple food consumption is the main channel through which internet access affects nutritional intake. The results demonstrate that the local population should use the internet to improve their nutritional status. Further studies are required to investigate the impact of internet use on food consumed away from home and micronutrients intake.

The use of heart rate variability (HRV) in research has been greatly popularized over the past decades due to the ease and affordability of HRV collection, coupled with its clinical relevance and significant relationships with psychophysiological constructs and psychopathological disorders. Despite the wide use of electrocardiogram (ECG) in research and advancement in sensors technology, the analytical approach and steps applied to obtain HRV measures can be seen as complex. Thus, posing a challenge to users who may not have the adequate background knowledge to obtain the HRV indices reliably. To maximize the impact of HRV-related research and its reproducibility, parallel advances in users’ understanding of the indices and the standardization of analysis pipelines in its utility will be crucial. This paper addresses this gap and aims to provide an overview of the most up-to-date and commonly used HRV indices, as well as common research areas that these indices have shown to be very useful, particularly in psychology. In addition, we also provide a step-by-step guide on how to perform HRV analysis using an integrative neurophysiological toolkit, NeuroKit2.

We investigated the radioclinical outcomes of naviculectomy and limited/tailored soft-tissue releases in a short series of ambulatory children with complex/intractable congenital vertical talus subsets namely neglected, multiple operated and recurrent patients. We postulated that this technique will yield satisfactory radioclinical outcomes and minimal complications because it avoids extensive surgical release/trauma that is otherwise classically recommended for complex congenital vertical talus (CVT). The cohort consisted of five -four boys, one girl- complex CVT children with neglected, multiple operated and/or recurrent subsets. Patients were included if manipulative casting techniques were deemed unlikely to produce a plantigrade foot. Patients underwent naviculectomy with variable on-demand limited soft tissue releases. Two patients had bilateral affection and two had a non-idiopathic aetiology. The mean age was 5.2 years (4 to 6.25) and mean follow-up was 2.3 years (1 to 3). We reported satisfactory outcomes as per foot posture, function, overall parent satisfaction including pain and radiography per lateral views of talar-axis-first metatarsal base angle on the short/intermediate term. Whereas manipulative casting is unlikely to yield lasting outcomes in ambulatory children with complex subsets of CVT, extensive surgical soft-tissue releases have unfavourable long-term complications. As a substitute, naviculectomy as a form of resection arthroplasty created a practical and affordable third way between manipulative casting with minimally invasive surgery and the extensive surgical soft tissue releases on the short/intermediate term.

Triple negative breast cancer (TNBC) is the most aggressive breast cancer accounting for around 15% of identified breast cancer cases. TNBC, by lacking estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), is unresponsive to current targeted therapies. Existing treatment relies on chemotherapeutic treatment but, despite an initial response to chemotherapy, the inception of resistance and relapse is unfortunately common. Dasatinib is an approved second-generation inhibitor of multiple tyrosine kinases and literature data strongly support its use in the management of TNBC. However, dasatinib binds to plasma proteins and undergoes extensive metabolism through oxidation and conjugation. To protect dasatinib from fast pharmacokinetic degradation and to prolong its activity, it was encapsulated on poly(styrene-co-maleic acid) (SMA) micelles. The obtained SMA-dasatinib nanoparticles (NPs) were evaluated for their physicochemical properties, in vitro antiproliferative activity in different TNBC cell lines, and in vivo anticancer activity in a syngeneic model of breast cancer. Obtained results showed that SMA-dasatinib is more potent against 4T1 TNBC tumor growth in vivo compared to free drug. This enhanced effect was ascribed to the encapsulation of the drug protecting it from a rapid metabolism. Our finding highlights the often-overlooked value of nanoformulations in protecting its cargo from degradation. Overall, results may provide an alternative therapeutic strategy for TNBC management.

Research Highlights: (1) Reed canary grass (RCG) is analysed in Sweden compared to willow and poplar for 2001-2020 (2) Each crop presents a different land-use and climatic profile (3) Average yield records of reed canary grass are similar to willow and poplar (4) There are divergences between trial-based and commercial yields (5) Existing LUC patterns suggest meadow>RCG and RCG>cereal (6) RCG land area is very sensitive to policy incentives. Background and objectives: RCG is an alternative crop for biomass-to-energy due to high yield and frost tolerance. We assess the cultivation in Sweden by using an extensive compilation of data, with emphasis on the extension of the cultivation, areas planted, climatic profile, land use patterns and yield levels. Material and methods: All RCG plantations are analysed for 2001-2020. A geostatistical analysis is performed to characterize where is cultivated and the land uses associated. Climatic, productivity and yield profiles are compared to willow and poplar plantations, from experiments and from commercial plantations. Results: The results show that the cultivation of reed canary grass expanded after 2005, with a maximum of 800 ha in 2009 to then decrease to the current levels of about 550 ha. It is mainly grown in colder climatic areas, with lower agricultural productivity than willow and poplar. Mean yields from trials are 6 odt ha-1 yr-1; commercial yields are 3.5 odt ha-1 yr-1. RCG replace meadow land and is replaced by cereals, when abandoned. Conclusions: Reed canary grass is an interesting alternative, growing on colder areas but on similar yield levels than other energy crops. The cultivation is more sensitive to policy incentives

Depletion of ore deposits, increasing demand for raw materials, the need to process low-grade, complex and finely disseminated ores and the reprocessing of tailings are challenges, especially for froth flotation separation technologies. Even though capable of handling relatively fine grain sizes the flotation separation of very fine and ultrafine particles faces many problems still. Further, the flotation of low-contrast semi-soluble salt-type minerals with very similar surface properties, many complex interactions between minerals, reagents and dissolved species often result in poor selectivity. This study investigates the flotation beneficiation of ultrafine magnesite rich in dolomite from de-sliming, currently reported to the tailings. The paper especially focuses on the impact of the depressant sodium hexametaphosphate (SHMP) on: (i) the froth properties using dynamic froth analysis (DFA), (ii) the separation between magnesite and dolomite/calcite and (iii) its effect on the entrainment. Furthermore, the application of 1-hydroxyethylene-1,1-diphosphonic acid (HEDP) is a more environmentally friendly and low-cost alternative to SHMP is presented and discussed. The paper contributes to understanding on the complexity of depressant responses in froth flotation.