The increasingly used approach of combining different simulation software in testing of automated driving systems (ADS) increases the need for potential and convenient software designs. Recently developed co-simulation platforms (CSP) provide the possibility to cover the high demand on testing kilometers for ADS by combining vehicle simulation software (VSS) with traffic flow simulation software (TFSS) environments. The emphasis on the demand of testing kilometers is not enough to choose a suitable CSP. The complexity level of the used vehicle, object, sensors and environment models is essential for valid and representative simulation results. Choosing a suitable CSP raises the question of how the test procedures should be defined and constructed and what the relevant test scenarios are. Parameters of the ADS, the environments, objects, sensors in VSS as well as traffic parameters in TFSS can be used to define and generate test scenarios. In order to generate a large number of scenarios in a systematic and automated way, suitable and appropriate software designs are required. In this paper we present a software design for CSP based on the Model-View-Controller (MVC) design pattern and implementation of a complex CSP for virtual testing of ADS. Based on this design, an implementation of a CSP is presented using the VSS from IPG Automotive called CarMaker and the TFSS from PTV Group called Vissim. The results have shown that the presented CSP design and the implementation of the co-simulation can be used to generate relevant scenarios for testing of ADS.

Ruminal microorganisms play a pivotal role in cattle nutrition. The discovery of the main microbes responsible for enhancing the gain of weight in beef cattle might be used in therapeutic approaches to increase animal performance and cause less environmental damages. Here, we examined differences in bacterial and fungal composition of rumen samples of Braford heifers raised in a natural grassland from Pampa Biome in Brazil. We aimed to detect microbial patterns in the rumen that could be correlated with the gain of weight. 16S and ITS1 genes were amplified from ruminal samples and sequenced to identify the closest microbial relatives within the microbial communities. A predictive model based on microbes responsible for the gain of weight was build and further tested using the entire dataset. The model detected a set of microorganisms associated with animals in the high gain of weight group, including the bacterial taxa RFN20, Prevotella, Anaeroplasma and RF16 and the fungal taxa Aureobasidium, Cryptococcus, Sarocladium, Pleosporales and Tremellales. Most of these organisms have been correlated to the production of substances that improve the ruminal digestion process. These findings provide new insights about cattle nutrition and suggest the use of these microbes to improve beef cattle breeding.

The Convective Rainfall Rate from Cloud Physical Properties (CRPh) for Meteosat Second Generation Satellites is a day-only precipitation algorithm developed at the Spanish Meteorological Agency (AEMET) for EUMETSAT’ Satellite Application Facility in support to Nowcasting and Very Short Range Forecasting (NWC SAF). It is therefore mainly intended to provide input for monitoring and near-real-time forecasts for the next few hours. This paper critically discusses the theoretical basis of the algorithm with special emphasis in the empirical values and assumptions in the microphysics of precipitation and compares the performances of the CRPh with its antecessor, the Convective Rainfall Rate algorithm (CRR), using an object-based method. The analyses show that AEMET’s CRPh is physically consistent and that outperforms the CRR. The applicability of the algorithm for nowcasting and the challenges to evolve the product to an all-day algorithm are also presented.

In this study we announce the draft genome sequence of a newly identified Acinetobacter species cross-reacting with E. coli serotype 0157:H7. The advent of Next-Generation technology has paved to way to discover new species which could otherwise be misidentified using conventional cultural and serotyping methods. The whole genome sequence of this isolate will help to identify potential marker/s of intervention and further genomic analysis might also shed light onto the virulence properties of this newly identified Acinetobacter species which has been provided the new name of Acinetobacter maqsudiensis.

After human genome sequencing and rapid changes in genome sequencing methods, we have entered in the era of rapidly accumulating genome-sequencing data. This has poses development of several types of methods for representing results of genome sequencing data. Circular genome visualizations tools are also critical in this area as they provide rapid interpretation and simple visualization of overall data. In the last 15 years, we have seen rapid changes in circular visualization tools after the development of the circos tool with 1–2 tools published per year. Herein we have summarized and revisited all these tools until the third quarter of 2018.

An understanding of the cultural conditions that determine the factors affecting nurses’ intention to leave is important for countries suffering from nurse shortage. Aim: to examine factors influencing intention to leave among female hospital nurses in a large Japanese sample, classified into four generations by age considering economic conditions. Methods: a cross-sectional survey with convenience sampling was conducted. Anonymous self-administered questionnaires were distributed to all nurses in 30 hospitals. To assess intention to leave, basic attributes, life conditions, work characteristics, and factors of psychosocial work environment were addressed. After classifying data into four generations based on age cohorts, we conducted multivariate logistic regression analysis using the completed data (N = 5,074, mean age = 36.24). Results: regardless of generational characteristics influenced by economic conditions, effort and monetary reward were generation-common factors. Over-commitment, social support, and the presence of a role model were generation-common factors in three generations. While having children increased intention to leave in the generation born 1965–1979, having family members in need of caregiving other than children decreased the risk in the generation born in the 1980s. Conclusion: generational countermeasures considering factors of psychosocial work environment and life conditions are needed to avert female nurse turnover.

The philosophy of Industry 5.0 recognizes the transformative power of the industrial sector to add value to society and employees. Industry 5.0, distinct from its predecessors, relies on a tripod of sustainability, human-centric, and resilience. These three thematic principles aim to improve work safety, research and innovation, and strengthen industrial resilience and competitiveness. The potential for positive change is immense. However, a perfect storm is brewing for the future of work, brought about by the concerning trends of displacement and low skill levels of work-ers' competencies in handling the new technologies of Industry 5.0 in emerging economies. This paper will discuss Industry 5.0 and provide historical insights on the importance of acquiring the desired twenty-first-century competencies needed in the workforce for Industry 5.0. Two research questions guided the study in identifying these twenty-first-century competencies, how these com-petencies can be cultivated and taught in the education curriculum and policies of emerging economies, and the crucial im-portance of adapting Industry 5.0 to these emerging economies. The study concluded that emerging economies must play an active role in shaping the future, by creating policies that will advance social stability, resource preservation, and climate objec-tives, which will enable more productive production processes with lower waste and energy usage.

Porcine parvovirus 8 (PPV8), a novel virus in the Parvoviridae family, was first identified in 2022 in lung samples of domestic pigs from China. Retrospective analyses showed that it had been circulating in China since 1998, but no other countries had reported its presence so far. A recent study conducted in South America did not detect any PPV8-positive samples in that region. Here we report the detection of PPV8 in Hungarian and Slovakian pig farms and the estimated prevalence of the virus in Hungary. Altogether 2230 serum, 233 oral fluid, and 115 processing fluid samples were systematically collected from 23 Hungarian and 2 Slovakian pig farms between 2020 and 2023. A real-time quantitative PCR method was developed to detect the viral genome. Our results revealed the presence of PPV8 on 65% of the Hungarian farms and on both Slovakian farms included in our study, marking its first detection in Europe. Oral fluid samples showed the highest positivity rates, reaching up to 100% in some herds. The viral genome was successfully detected in serum and processing fluid samples too, but with significantly lower prevalence rates of 4% and 5%, respectively. Genetic analysis of 11 partial VP2 sequences demonstrated high similarity to the original Chinese strain but with unique amino acid mutations, suggesting possible local evolution of the virus. Our study presents the first scientific evidence of PPV8 infection outside of China and offers a comprehensive assessment of its prevalence in the Hungarian pig population. Further research is required to understand its potential impact on swine health.

Transition from basic to higher education is regarded as a ‘juggle of many balls’ because students ought to balance between theoretical and clinical requirements, including social life. As a result, a significant number of undergraduate first-year nursing students succumb to these challenges due to lack of coping mechanisms emanating from poor resilience. As a result, the aim of this study was to determine the factors that influence resilience among undergraduate first-year nursing students at a South African university. A quantitative cross-sectional descriptive research design was followed. Data was collected using an adapted self-administered online questionnaire. Principal component analysis extraction method and Varimax rotation were used to analyse data. A total of 123 participants completed the questionnaire. The eigenvalues showed that the first factor explained 23.9% of the variance, the second factor 11.2%, a third factor 7.5% while the fourth factor explained 5.9% of the variance. The fifth until the eight factor had eigenvalues greater than 1 but less than 2. This study showed that resilience can be dependent on various factors such as lecture support, parental support, academic achievement, peer and mentor support, optimism about the future and being self-determined.

Background: Several studies recently confirmed the emergence of resistance to antimalarial drugs in sub-Saharan Africa. Multiple first-line treatment (MFT) is one of the measures envisaged to respond to the emergence and spread of this resistance. The aim of this study was to identify perceived advantages and disadvantages of several MFT deployment strategies and to better understand potential implementation drivers and barriers. Methods: A qualitative survey was conducted in seven sub-Saharan countries amongst key opinion-leaders, national decision-makers, and end users. A total of 200 individual interviews were conducted and findings were analyzed following a thematic inductive approach. Results: From a policy perspective, the new MFT intervention would require endorsement at the global, national, and regional levels to ensure its inclusion in guidelines. Funding of the MFT intervention could be a bottleneck due to costs associated with additional training of healthcare workers, adaptation of drug delivery mechanisms, and higher costs of drugs. Concerning the MFT deployment strategies, a slight preference for the segmentation strategy was expressed over the rotation and geographic approaches, due to the perception that a segmentation approach is already in place at country level. Conclusions: The findings highlighted the need for a collective approach to MFT deployment through the engagement of stakeholders at all levels of malaria management.

The structural, elastic, and electronic properties of orthorhombic Cd2SiO4 and Hg2GeO4 were examined under varying pressure conditions using first-principles calculations based on densi-ty-functional theory employing the projector augmented wave method. The obtained cell pa-rameters at 0 GPa were found to align well with existing experimental data. We delved into the pressure-dependence of normalized lattice parameters and elastic constants. In Cd2SiO4, all lat-tice constants decreased as pressure increased, whereas in Hg2GeO4, parameters a and b de-creased while parameter c increased under pressure. Employing the Hill average method, we calculated the elastic moduli and Poisson’s ratio up to 10 GPa, noting an increase with pressure. Evaluation of ductility/brittleness under pressure indicated both compounds remained ductile throughout. We also estimated elastic anisotropy and Debye temperature under varying pres-sures. Cd2SiO4 and Hg2GeO4 were identified as indirect band gap insulators, with estimated band gaps of 3.34 eV and 2.09 eV, respectively. Interestingly, Cd2SiO4 exhibited a significant increase in band gap with increasing pressure, whereas the band gap of Hg2GeO4 decreased under pres-sure, revealing distinct structural and electronic responses despite their similar structures.

The severe acquired respiratory coronavirus–2 (SARS–CoV-2) infection has initiated both acute and chronic COVID–19 disease between 2020 and 2023, currently evolving with other homologous prior coronavirus strains of the Nidoviridae order, which encompasses other prevalent alpha/ beta coronaviruses, but also the Middle East Respiratory Syndrome (MERS-CoV) and SARS-CoV-1, with recent SARS–CoV–2 variants, increasing demands for effective immunogens and therapeutic approaches that will reduce global disease burden and further infection from SARS–CoV-2 affected individuals that may experience post acute sequelae (PASC) or “Long COVID”. Following a worldwide programme of prophylactic vaccination, there is still a dilemma in the efforts to find prophylactic and early therapeutic approaches that would treat novel SARS-CoV-2 variants and prevent future epidemics or pandemics within host human and animal populations, where zoonotic or cross species transfer naturally occurs. Concerns about viral immune escape intersect at a specific point; a gained evolutionary ability of several viruses to co–infect and compete against previous scientific advances since 1796 that remain undetected or asymptomatic during the early stages of infection progressing to symptomatic and severe disease via the double methylation of the 5' end of eukaryotic DNA or RNA-based viral genomes, the 7-MeGpppA2’-O-Me cap, and its double methylation capping process is performed by the activated viral 2’ - O - Methyltransferase (MTase) enzyme, a complex of two viral non-structural proteins (NSPs) joined together through an activation process (NSP10/16) and by N7-Methyltransferase (N7-MTase/NSP14), respectively. Moreover, it was discovered that polymorphic viruses translate NSP1, which prevents the activation of various Pattern Recognition Receptors (PRRs), and consequently, detection of Pathogen-Associated Molecular Patterns (PAMPs) and Damage-Associated Molecular Patterns (DAMPs) alike. NSP1 also silences important interferon-encoding genes (INGs) and interferon-stimulated genes (ISGs), is signalled in a paracrine manner to neighbouring cells, and that induces the apoptosis of host cells, inducing an effect of “trace erase” effect and making the viral infection as immunologically “invisible” as possible during the initial, key stages of viral replication and distribution, all such mechanisms occurring independently of the viruses in cause. Another important viral NSP is NSP14, as it plays two functional roles that are independent of each other; to produce new viral genetic material for the purpose of maintaining the validity of the viral genome as well, and not just transfer a methyl group to the 5’ end of the viral genome. Other viral NSPs share a role with NSP1, 10, 14 and 16 in directly suppressing the activation of PRRs and ISGs, and all such viral proteins help the virus in its process of self-camouflaging against first- and second-line immunity, thereby often severely impacting the quality of the produced adaptive immune responses. The outcome of all such phenomena is the sharp decrease in the host Type I and Type III interferons' (IFNs) rate of synthesis by the host cells, that would usually occur and affect homeostatic cellular pathways, resulting in further viral replication and induced apoptosis. Nonetheless, effects of microbial immune evasion during the development of other viral or carcinogenic pathologies are not widely known. In short, polymorphic viruses developed a proportionate evolutionary response against developed adaptive immune responses, by currently relying on gaps mostly situated in the natural immune system in their process of molecular self-camouflaging. Scientists developed numerous approaches of early treatment that generally showed good success rates and fewer risks of adverse events, and the still early present stages of COVID-19 research should also be taken into consideration whilst filtering for the most appropriate solutions. For example, the administration of recombinant human interferons I and III into the nasal mucosa cellular layer, as key mediators of anti–viral activity, can simulate intracellular infection and stimulate cellular activity in a timely manner, training the innate and adaptive immune system cells to develop and appropriately stimulate an adequate immune response through B and T cells. Another example could involve the treatment of natural and adaptive lymphocytes with a low dose of IFNs I and possibly III, prior to their insertion into the host lymphatic system, possibly alongside additional recruitment of plasmacytoid dendritic cells (pDCs) as further interferon “factories”, all with the purpose of early infection management. It might be that focusing on directly offering the immune system the information about the genetics and protein structure of the pathogen, rather than training its first-line mechanisms to develop faster, excessively increases its specificity, making it reach a level that brings the virus the opportunity to evolve and escape previously-developed host immune mechanisms. It is until the scientific community realises this potentially crucial aspect that large proportions of the world population will probably continue to face serious epidemics and pandemics of respiratory diseases over the coming several decades, evidenced with dengue fever and more recently, monkeypox and possibly avian flu. Of note, it has been indicated that IFN I and / or III display significant immunising, early therapeutic and clinical disease onset-attenuating effects for many other microbial evoked diseases, as well as for a number of oncological diseases.

In the search for new 2D materials beyond graphene with similar exemplary properties Stanene the new graphene relative was successfully synthesized and characterized in 2016 [14]. This new material which consists of atomically thin tin (Sn) atoms arranged in a hexagonal lattice has shown great promise in gas sensing applications in its pristine, doped and functionalized forms as evidenced by the recent research outputs following its discovery. Researchers have discovered that with its exotic properties it is highly efficient in the detection of the environmentally harmful gases like SO2, NO2, CO2, NH3 and can serve as a multifunctional gas sensor. In this focused and up-to-date review we aim to group the literature on first principles studies of stanene regards to its application for gas sensing and critically examine the success/failures of its multifunctional gas sensing properties as compared to graphene. We systematically present and discusses how structural deformations, defects and doping effect the gas sensing performance. Despite the impressive progress in the field of gas sensing with stanene shown by first principles calculations, many challenges in large scale synthesis, device fabrication and commercialization need to be addressed. The current review can help understand the current status and drawbacks of stanene and identify future directions in this field.

Although the jellyfish species that inhabit the Mediterranean coastal waters are not lethal, their sting can cause severe pain and systemic effects that pose a health risk to humans. Despite the frequent occurrence of jellyfish stings, currently no consensus exists regarding the most appropriate first aid protocol among the scientific community. Over the years, several different rinse solutions have been proposed of which vinegar, or acetic acid, is one of the most noticeable as a rinse solution with efficacy data published. We investigated the effect of vinegar and seawater on the nematocyst discharge process in species representative of the Mediterranean region such as Pelagia noctiluca (Scyphozoa) and Carybdea marsupialis (Cubozoa) by means of: (1) direct observation on the nematocyst discharge by light microscope (Tentacle solution assay) and (2) the quantification of hemolytic area (Tentacle skin blood agarose assay). The nematocyst discharge of both species was not stimulated by seawater, and it was classified as a neutral solution. In P. noctiluca, vinegar produced nematocyst discharge per ser while inhibiting the nematocyst discharge of C. marsupilais. These results suggest that the use of vinegar cannot be universally recommended. While in case of a cubozoan C. marsupialis sting, the inhibitory effect of vinegar makes it the best rinse solution par excellence, in case of a scyphozoan P. noctiluca sting, its application can be counterproductive, worsening the pain and discomfort of the stung area.

Given a quasi-definite linear functional u in the linear space of polynomials with complex coefficients let us consider the corresponding sequence of monic orthogonal polynomials (SMOP in short) (Pn)n≥0. For the Christoffel transformation u˜=(x−c)u with SMOP (P˜n)n≥0, we are interested to study the relation between u˜ and u(1)˜, where u(1) is the linear functional for the associated orthogonal polynomials of the first kind (Pn(1))n≥0 and u(1)˜=(x−c)u(1) is its Christoffel transformation. This problem is also studied for the Geronimus transformations.

The aim of this article is to understand the symbolic representations of the assistance strategies aimed at disabled children, expressed in two newspapers published on the island of Faial, in the Azores, in the second half of the 19th and early 20th centuries (covering the time horizon between the end of the monarchic period and the implementation of the First Republic). The technique of documentary analysis and a subsequent qualitative thematic content analysis of childcare news collected in two local newspapers was used. The discursive records produced by the press on the assistance strategies value, on the one hand, an axiological dimension and forms of charitable intervention and, on the other hand, aggregate and reconcile the discourses and techniques inherent to charitable and philanthropic models. This mutual assimilation underlies the achievement of the same objective: the moralisation and integration of invalid childhood and, above all, the protection of the existing social order. We conclude that, perhaps contrary to what would be expected, the charitable logic articulated in a concomitant way with the philanthropic logic survived even with the stabilization of the republican period (result of a revolution that deposed the regime of the constitutional monarchy and implemented the republican regime in 1910 in Portugal whose political elites mobilized an official discourse that advocated the separation between the State and Religion, assigning the State the function of social assistance for children and youth). This demonstrates a certain dissociation, as well as a relative autonomy of conceptions about child and youth care between republican political ideology and current social practices at least in this specific context.

This work presents the mathematical framework of the Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “2nd-CASAM-L”), which enables the most efficient computation of exactly obtained mathematical expressions of first- and second-order sensitivities of a generic system response with respect to functions (“features”) of model parameters. Subsequently, the first- and second-order sensitivities with respect to the model’s uncertain parameters, boundaries, and internal interfaces are obtained analytically and exactly, without needing large-scale computations. Within the 2nd-FASAM-L methodology, the number of large-scale computations is proportional to the number of model features (defined as functions of model parameters), as opposed to being proportional to the number of model parameters, which are considerably more than the number of features, being incomparably more efficient and more accurate than any other methods (statistical, finite differences, etc.) for computing exact expressions of response sensitivities (of any order) with respect to the model’s features and/or primary uncertain parameters, boundaries, and internal interfaces. The application of the 2nd-CASAM-L methodology is illustrated using a simplified energy-dependent neutron transport model of fundamental significance in nuclear reactor physics.

This paper examines the quantitative and qualitative situation of the current fixed and mobile Internet and its expected future. First, the number of users and penetration rate of the Internet, various types of services in different countries, the ranking of countries in terms of the mean and median download and upload Internet data speeds, Internet data volume, and number and location of data centers in the world are presented. The second task introduces and details twelve performance evaluation metrics for broadband Internet access. Third, different wired and wireless Internet technologies are introduced and compared based on data rate, coverage, type of infrastructure, and their advantages and disadvantages. Based on the technical and functional criteria, in the fourth work, two popular wired and wireless Internet platforms, one based on optical fiber and the other based on the 5G cellular network, are compared in the world in general and Australia in particular. Moreover, this paper has a look at Starlink as the latest satellite Internet candidate, especially for rural and remote areas. The fifth task outlines the latest technologies and emerging broadband Internet-based services and applications in the spotlight. Sixthly, it focuses on three problems in the future Internet in the world, namely the digital divide due to the different quality of the Internet and new Internet-based services and applications of emerging technologies, the impact of the Internet on social interactions, and hacking and insecurity on the Internet. Finally, some solutions to these problems are proposed.

A genome represents the complete collection of genetic material in an organism or cell. This genetic information is encoded in nucleic acids, which can be either single or double-stranded and arranged in linear or circular forms. DNA, the most common type of genetic material, consists of just four nucleotides: adenine, guanine, thymine, and cytosine. These nucleotides are organized in a double helix structure, a discovery made by Watson and Crick. The sequence of these nucleotides forms the basic blueprint of a gene or genome. The process of determining this sequence is known as genome sequencing. The field of genome sequencing has evolved dramatically over time, advancing from sequencing short DNA fragments to analyzing millions of base pairs. Initially, efforts were focused on determining the sequence of individual genes, but now whole genome sequencing is both rapid and widely accessible. Recent improvements in sequencing technology emphasize faster, more accurate results, lower costs, and better data analysis. Sanger sequencing, which became the gold standard for DNA sequencing for about thirty years, was instrumental in completing various genome sequences, including the human genome. It laid the groundwork for newer sequencing methods. Today, these newer methods, known collectively as “Next-Generation Sequencing” (NGS), include several generations of technology. Second-generation methods, such as Illumina, Pyrosequencing, ABI/SOLiD, and Ion Torrent Sequencing, and third-generation methods like PacBio and Helicos Sequencing, have advanced the field further. Fourth-generation technology, such as Nanopore sequencing, is also emerging. Most modern research now relies on NGS for analyzing biological sequences, and understanding these technologies offers insight into current methods and future developments.

The use of Retrieval-augmented generation (RAG) using large language models (LLMs) has shown potential for addressing issues such as hallucinations and inadequately contextualized responses. A pivotal stage in the RAG process involves a retriever for retrieving chunks based on semantic similarity with the query. In this study, we advocate for and provide experimental evidence supporting integrating and maintaining questions and answers (QA) formatted databases to improve retrieved-context representations and response quality. Our experiments evaluate our approach on benchmark RAG datasets using standard evaluation metrics and provide comparative analyses against state-of-the-art retrieval methods, showing the potential of our approach.

Recent advancements in cognitive neuroscience, particularly in Electroencephalogram (EEG) signal processing, image generation, and brain-computer interfaces (BCI), have opened up new avenues for research. This study introduces a novel framework, Bridging Artificial Intelligence and Neurological Signals (BRAINS), which leverages the power of AI to extract meaningful information from EEG signals and generate images. The BRAINS framework addresses the limitations of traditional EEG analysis techniques, which struggle with nonstationary signals, spectral estimation, and noise sensitivity. Instead, BRAINS employs Long Short-Term Memory (LSTM) networks and contrastive learning, which effectively handle time-series EEG data and recognize intrinsic connections and patterns. The study utilizes the MNIST dataset of handwritten digits as stimuli in EEG experiments, allowing for diverse yet controlled stimuli. The data collected is then processed through an LSTM-based network employing contrastive learning and extracting complex features from EEG data. These features are fed into an image generator model, producing images as close to the original stimuli as possible. This study demonstrates the potential of integrating AI and EEG technology, offering promising implications for the future of brain-computer interfaces.

The proposed method deals with the problem of data privacy and sharing when processing personal mobility tracking data. Previous methods concentrate on producing highly detailed data on short-term and restricted areas, e.g. for autonomous driving scenarios. Another possibility consists of city-wide scales and beyond, that are used to predict general traffic flows. The presented approach takes the tracked mobility behavior of individuals to create coherent new mobility data that reflects the long-term mobility behavior of the person, guaranteeing location persistency and sound embedding within the point-of-interest structure of the observed area. After an analysis and clustering step with the original data, the area is distributed into a geospatial grid structure (H3 is used here), and the neighborhood relationships between the grids are interpreted as a graph. A feed-forward-autoencoder and a graph encoding-decoding network generate a latent space representation of the area. The original clustered data is associated with their respective H3 grids. With a greedy algorithm approach and concerning privacy strategies, new combinations of grids are top-level patterns for individual mobility behavior. Concrete locations are found and connected within the grids based on the original data. The described method is then applied to a study with 1000 participants from the city of Munich in Germany, and the results are described, showing the application of the approach in generating synthetic data, enabling further research on individual mobility behavior and patterns. The result is a sharable dataset on the same abstraction level as the input data, which makes it interesting, particularly for machine learning applications.

Background: The microbiome of the ocular surface has been characterised, but only limited in-formation is available on a possible silent intraocular microbial colonisation in normal eyes. Therefore, we performed next generation sequencing (NGS) of 16S rDNA genes in aqueous hu-mor. Methods: Aqueous humor was sampled from three patients during cataract surgery. Air swabs, patient’s and healthy donor conjunctival swab served as controls. Following DNA extraction, the V3 and V4 hypervariable regions of the 16S rDNA gene were amplified and sequenced fol-lowed by denoising. The resulting Amplicon Sequence Variants were matched to a subset of the Ribosomal Database Project 16S database. The deduced bacterial community was then statis-tically analysed. Results: DNA content in all samples was low (0-1.49 ng/µl) but sufficient for analysis. Main phyla in all samples were Acinetobacteria (48%), Proteobacteria (26%), Firmicutes (14%), Acidobac-teria (8%) and Bacteroidetes (2%). Patients conjunctival control samples and anterior chamber fluid showed similar patterns of bacterial species containing many waterborne species. Non-disinfected samples showed a different bacterial spectrum than the air swab sample. Conclusions: The data confirm the existence of an ocular surface microbiome. A distinct intraoc-ular microbiome was not discernable from the background, suggesting the absence of an intra-ocular microbiome in normal eyes.

In this work various sample of primary aluminum dross were investigated for composition and evaluation of hydrogen generation via hydrolysis in low concentration alkali solution. Composi-tion revealed low to moderate aluminium content and hydrolysis reactions showed low hydrogen generation volumes per sample mass as well as purity, where composition plays substantial role in the hydrogen evolution, yet showing that there is possible place for dross use in hydrogen generation. It was revealed that some dross samples in addition to hydrogen also release methane via hydrolysis. Rection rate was obtained by the shrinking core model, written for spherical solid particles. Sample composition on hydrogen generation volume is compared to known literature.

Osteosarcoma (OS) are the most prevalent malignant bone tumors in adolescents and young adults.. OS cells grow in a permissive local microenvironment which modulates their behavior and facilitates all steps in tumor development (e.g., proliferation/quiescence, invasion/migration, drug resistance) and contributes to their intrinsic heterogeneity. The lung parenchyma is the most common metastatic site in OS, and metastatic foci are frequently associated with a poor clinical outcome. Although multiple factors may be responsible for the disease, including genetic mutations (e.g., Rb, p53), the molecular mechanism of development of OS remains unclear and the conventional treatment for OS is still based on a sequential approach that combines chemotherapy and surgery. Also, despite the increase in clinical trials, the survival rates for OS have not improved. Non-specific targeting therapies thus show poor therapeutic effects with side effects at high doses. For these reasons, many efforts have been done to characterize the complex genome of osteosarcoma thanks to the whole exome analysis with the aim to identify predictive biomarkers to give to these patients a better therapeutic option. This review aims to summarize and discuss the main recent advances in OS molecular research for precision medicine.

Physical layer secret key (SK) generation is known to be an efficient means to achieve high secrecy rate, on the condition that dynamic channel state information (CSI) is provided. For this reason, the secrecy performance is highly degraded in a static environment. The intelligent reflecting surface (IRS) is a promising solution to create dynamic randomness, and thus lead to enhanced secrecy performance regardless of the user environments. This paper proposes an IRS-assisted physical layer SK generation scheme, by efficiently combing phase information of the direct and reflected channel information in a hybrid way. In particular, the initial SKs are obtained by adopting efficient phase quantization method with symmetric bit allocation to complex numbered channel estimates. Simulation results show that the proposed hybrid phase quantization (PQ) can improve the SK generation rate and the key disagreement probability in a static environment.

Parvovirus B19 infection is associated with a wide range of clinical manifestations, from asymp-tomatic to severe neurological disorders. Its major clinical symptoms, fever and rash, are com-mon to multiple viruses, and laboratory tests to detect B19 are frequently not available. Thus, the impact of B19 on public health remains unclear. We report the case of a 38-day old girl ad-mitted to São Paulo Clinical Hospital, Brazil, with an initial diagnosis of bacterial meningitis, seizures, and acute hydrocephalus. Antibiotic therapy was maintained for one week after admis-sion and discontinued after negative laboratory results were obtained. Nine days after symp-toms onset, a cerebral spinal fluid (CSF) sample revealed persistent pleocytosis. The complete B19 complete genome was subsequently identified in her CSF by a metagenomic next-generation sequencing approach. This report highlights the possible involvement of B19 in the occurrence of acute neurological manifestations, and emphasizes that its possible involve-ment might be better revealed by the use of metagenomic technology to detect viral agents in clinical situations of unknown or uncertain etiology.

Molecular diagnostics in healthcare relies increasingly on genomic and transcriptomic method-ologies and requires appropriate tissue specimens from which nucleic acids (NA) of sufficiently high quality can be obtained. Besides suration of ischemia and fixation type, NA quality depends on a variety of other pre-analytical parameters, like storage conditions and duration. It has been discussed that improper dehydration of tissue during processing influences quality of NAs and shelf-life of fixed tissue. Here we report on establishing a method to determine the amount of residual water in fixed, paraffin-embedded tissue (fixed by neutral buffered formalin, or a non-crosslinking fixative) and its correlation to the performance of NAs in qRT-PCR analyses. The amount of residual water depended primarily on the fixative type and the dehydration pro-tocol and, to a lesser extent on storage conditions and time. Moreover, we found that these pa-rameters were associated with the qRT-PCR performance of extracted NAs. Besides cross-linking of NAs and modification of nucleobases by formalin, hydrolysis of NAs by residual water was found to contribute to reduced qRT-PCR performance. The negative effects of residual water on NA stability are not only important for the design and interpretation of research, but must also be taken into account in clinical diagnostics where reanalysis of archived tissue from a primary tumour may be required, e.g., after disease recurrence. We conclude that improving shelf-life of fixed tissue requires meticulous dehydration and dry storage to minimize the degradative in-fluence of residual water on NAs.

Enhanced supercontinuum generation (SCG) is experimentally demonstrated in integrated silicon nitride (Si₃N₄) waveguides incorporating highly nonlinear graphene oxide (GO) in the form of two-dimensional (2D) films. On-chip integration of the 2D GO films with precise control of their thickness is realized by using a transfer-free and layer-by-layer coating method. The control of the film length and coating position is achieved via window opening in the upper silica cladding of the photonic integrated chips. Detailed SCG measurements are performed using the fabricated devices with different waveguide geometries and GO film thicknesses, and the results are compared with devices without GO. Significantly improved spectral broadening of ultrashort optical pulses with ultrahigh peaks powers exceeding 1000 W is observed for the hybrid devices, achieving up to 2.4 times improvement in the spectral bandwidth relative to devices without GO. Theoretical analyses for the influence of GO film thickness, coating length, coating position, and waveguide geometry are also provided by fitting the experimental results with theory, showing that there is still significant room for further improvement. This work opens up a promising new avenue towards improving the SCG performance of photonic integrated devices by incorporating functional 2D materials.

Nowadays the practice of developing algorithms to maintain the confidentiality of data shows that there is a lack of some features, such as velocity, predictability, etc. Generating pseudorandom numbers is one such problem that lies in the basement of many algorithms, even in hardware microprograms. An unreliable generator can cause cyberattacks on it, despite the security in the upper layers. At the same time, the algorithm should be fast enough to provide uninterrupted circuit work for the entire system. The paper presents a new algorithm generating pseudorandom numbers on cellular automata, which is not only fast and easy-repeating, but unpredictable enough and can be used in cryptographic systems. Using the NIST statistical test suite for random and pseudorandom number generators (PRNG), it is shown that the presented algorithm is more than three times superior to the state-of-the-art methods and algorithms in terms of ? − ?????. A high level of the presented algorithm’s parallelization allows for implementation it effectively on calculators with parallel structure. CPU-based architecture, FPGA-based architecture, CUDA- based architecture of PRNG and different PRNG implementations are presented to confirm high performance of the proposed solution.

Sweet cucumber (Solanum muricatum) sect. Basarthrum, is a neglected horticultural crop native of the Andean region. It is naturally distributed very close to potatoes (Solanum sect. Petota) and tomatoes (Solanum sect. Lycopersicon), two groups of high economic importance. To date, molecular tools for this crop are still undetermined. We here obtained the first complete chloroplast (cp) genome of sweet cucumber and compared with seven Solanaceae species. Pair-end clean reads were obtained by PE 150 library and the Illumina HiSeq 2500 platform. The complete cp genome of S. muricatum had a 155,681 bp with typical quadripartite structure, containing a large single copy (LSC) region (86,182 bp) and a small single-copy (SSC) region (18,360 bp), separated by two inverted repeat (IR) regions (25,568 bp). The annotation of chloroplast genome predicted 88 protein-coding genes (CDS), 8 ribosomal RNA (rRNA) genes, 37 transfer RNA (tRNA) genes, and one pseudogene. A total of 48 perfect microsatellites were identified, divided in mononucleotide repeats (32), followed by tetranucleotide (6) and dinucleotides (5). SSRs with trinucleotides repeats (3), pentanucleotide (1) and hexanucleotide (1) repeats motifs in these genomes were identified in lower quantity. Most of these repeats were distributed in the noncoding regions. Whole chloroplast genome comparison with the other seven Solanaceae species revealed that the small and large single copy regions showed more divergence than inverted regions. Finally, phylogenetic analysis resolved that S. muricatum is a sister species to members of sections Petota + Lycopersicum + Etuberosum. This study reports for the first time the genome organization, gene content, and structural features of the cp genome of S. muricatum. Also, this study may provide the basis for evaluating genetic diversity within Solanum, and will be useful to examine the evolutionary processes in sweet cucumber landraces.

Interface solar steam generation (ISSG) are charming for its applications in desalination and wastewater treatment. Biomass is an attractive substrate for utilizing solar vapor evaporators because of its natural pore structure and water transportability. Polymers like polydopamine (PDA) and polypyrrole (PPy) with broadband spectrum absorption are fascinating in photothermal materials (PTMs). Herein, PDA coated daikon-based (PDA-DK) and PPy coated daikon-based (PPy-DK) PTMs have been exploited for solar steam generation. When polyethylene foam (PEF) was used as an insulating layer to limit heat loss from the PTMs to bulk water, the evaporation rate of PDA-DK and PPy-DK was raised from 0.82 kg m–2 h–1 and 0.96 kg m–2 h–1 to 1.50 kg m–2 h–1 and 1.60 kg m–2 h–1, respectively. Meanwhile, the corresponding photothermal conversion efficiency was increased to 89.01% and 98.97%, which was increased by nearly 40% under 1-sun irradiation. In addition, PDA-DK and PPy-DK exhibited remarkable stability for the solar steam generation without significant change through 15 cycles. Furthermore, PDA-DK and PPy-DK could effectively desalt seawater and purify dyeing wastewater. All the results indicate that PDA-DK and PPy-DK have great potential in real-world applications for solar steam generation.

Background: Currently, Indonesia is entering an era that is all digital and uses technology in all fields of activity. The internet has a lot to do with their behavior or character. Millennials are the nation's next generation. The emergence of the digital era caused by globalization has made the millennial generation less appreciative and practicing the values ​​of Pancasila. In this case, character education is something that must be applied to the millennial generation. Purpose: This study aims to analyze the characteristics of the millennial generation, the role of character education in realizing the values ​​of Pancasila in the daily life of the millennial generation, how to cultivate an attitude of patriotism and nationalism towards the nation by practicing Pancasila, and provide motivation for the millennial generation to realize these values. Pancasila values. Methods: This study uses a literature review method. The search for journals was carried out using the google scholar database with the keywords “Character Education”, “millenial generation”, and “Pancasila”. The journals selected are journals from 2019 to 2020. Results: By applying character education to the millennial generation, it will make it easier for them to practice the values ​​of Pancasila. Pancasila should be the way of life of the millennial generation. Recommendation and limitation: As millennials, we must protect the country from values ​​that are contrary to Pancasila. Character education must be applied following the nature of the millennial generation itself. Of course, the applied character education must prioritize and be based on the values ​​of Pancasila as well.

Introduction: The imbalance between technological development and ideological strengthening has resulted in the fading of the Pancasila ideological values of millennials. Technology that accompanies everyday life seems to be the main character in human life. Yet if humans themselves do not use technology wisely, technology can be a threat to both individuals and the life of the nation and state. If technology is increasingly out of control, threats to the Pancasila ideology are very likely to occur, such as in the G 30S PKI incident. Therefore, it is necessary to take action both from the government and the community as individuals to safeguard the development of technology to be used wisely. That way, we can prevent the threat to the Pancasila ideology together. Writing this article aims to analyze how the role and influence of the Pancasila ideology on the millennial generation in the 4.0 industrial revolution and to find solutions so that the values of Pancasila remain attached to the next generation of the Indonesian nation. Method: Writing This article uses a qualitative method by using literature reviews from the results of related research journals that have been published online through websites and other online media. Results: Thirteen journals and one book have met the criteria for the inclusion of a predetermined review. Research is based on the stigma of society regarding technological developments in the Industrial revolution 4.0. Therefore, the government is expected to be more severe in implementing human capital management. Conclusion: By procuring human capital management, it will be possible that Human Resources (HR) in Indonesia will be able to carry out the ideals of a golden Indonesian generation with Pancasila values inherent in the hearts of the people and the nation's future generations.

Plasma cell-free DNA (cfDNA) is frequently analyzed using liquid biopsy to investigate cancer markers. Accordingly, we hypothesized this concept could be applied to the field of exercise physiology. Here, we aimed to identify specific cfDNA (spcfDNA) sequences in the plasma of non-treated human participants using next generation sequencing (NGS) and to clearly define the dynamics regarding the amounts of spcfDNA-fragments upon extreme exercise, such as running a full marathon. NGS analysis was performed using cfDNA of pooled plasma collected from non-treated participants. We confirmed the TaqMan-qPCR assay had a high sensitivity and found the spcfDNA sequence abundance was 16,600-fold higher than a normal genomic region. We then used the TaqMan-qPCR assay to investigate the dynamics of the levels of spcfDNA-fragments upon running a full marathon. Quantities of the spcfDNA fragments were significantly increased post marathon. Furthermore, the amounts of spcfDNA fragments strongly correlated with the numbers of white blood cells and plasma myoglobin concentrations. These results suggest the spcfDNA fragments identified in this study were highly sensitive response markers to extreme physical stress. The findings of this study may provide new insights into exercise physiology and genome biology on the human.

The interest in renewable energy to replace fossil fuel is increasing as the problem caused by climate change become more severe. Small hydropower (SHP) is evaluated as a resource with high development value because of its high energy density compared to other renewable energy sources. SHP may be an attractive and sustainable power generation environmental perspective because of its potential to be found in small rivers and streams. The power generation potential could be estimated based on the discharge in the river basin. Since the river discharge depends on the climate conditions, the hydropower generation potential changes sensitively according to climate variability. Therefore, it is necessary to analyze the SHP potential in consideration of future climate change. In this study, the future prospect of SHP potential is simulated for the period of 2021 to 2100 considering the climate change in three hydropower plants of Deoksong, Hanseok, and Socheon stations, Korea. As the results, SHP potential for the near future (2021 to 2040) shows a tendency to be increased and the highest increase is 23.4% at the Deoksong SPH plant. Through the result of future prospect, we have shown that hydroelectric power generation capacity or SHP potential will be increased in the future. Therefore, we believe that it is necessary to revitalize the development of SHP in order to expand the use of renewable energy. Also, a methodology presented in this study could be used for the future prospect of the small hydropower potential.

MCPH1, otherwise known as the microcephalin gene (*607117) and protein, is a basic regulator of chromosome condensation (BCRT-BRCA1 C-terminus). The Microcephalin protein is made up of three BCRT domains and conserved tandem repeats of interacting phospho-peptide. There is a strong connection between mutations of the MCPH1 and reduced brain growth. Specifically, individuals with such mutations have underdeveloped brains which means smaller size, varying levels of mental retardation, delayed speech and poor language skills, individuals with mild microcephaly and normal intelligence notwithstanding. In this case, a fetus with novel homozygous mutation of the MCPH1 gene ((c.348del)), whose parents were recessive heterozygous for (c.348del), displayed severe microcephaly at 22 weeks of gestation. Due to the effect on splice sites in introns, this mutation causes forming of dysfunctional proteins which lack crucial domains of the C-terminus. Our findings portray an association between the new MCPH1 mutation ((c.348del)) and the clinical features of autosomal recessive primary microcephaly (MCPH) contributing to a broader spectrum related to these pathologies.

We show broadband sum-frequency generation (SFG) in the Green-Yellow-Orange-Red spectral range using bismuth triborate, BiB3O6 crystal (BIBO) as nonlinear material. We perform a noncollinear phase-matching configuration within BIBO crystal using the remaining light behind the second harmonic generation stage and the infrared idler of an optical parametric amplifier (OPA). The obtained mixing radiation of ultrafast light sources to generate femtosecond pulses across 520.5 to 742.5 nm region is observed. SFG spectrum from single-pass cross-correlation intensity over such visible range is showed. The SFG wavelengths as a function of tunable wavelength idler OPA agrees with the expectations of parametric conversion condition and open the door to practical multi-beam or multi-color sum-frequency generators.

SARS-CoV-2 is a novel betacoronavirus and the aetiological agent of the current COVID-19 outbreak that originated in Hubei Province, China. While polymerase chain reaction is the front-line tool for SARS-CoV-2 surveillance, application of amplification-free and culture-free methods for isolation of SARS-CoV-2 RNA, partnered with next-generation sequencing, would provide a useful tool for both surveillance and research of SARS-CoV-2. We here release into the public domain a set of bait capture hybridization probe sequences for enrichment of SARS-CoV-2 RNA from complex biological samples. These probe sequences have been designed using rigorous bioinformatics methods to provide sensitivity, accuracy, and minimal off-target hybridization. Probe design was based on existing, validated approaches for detecting antimicrobial resistance genes in complex samples and it is our hope that this SARS-CoV-2 bait capture platform, once validated by those with samples in hand, will be of aid in combating the current outbreak.

We design an asymmetric nonlinear optical nanoantenna composed of a dielectric nanodisk and an adjacent nanobar. The proposed composite structure made of AlGaAs exhibits resonant response at both the fundamental and doubled frequencies. Being driven by the strong magnetic dipole resonance at the pump wavelength and a high-quality mode at the harmonic wavelength, the efficient second-harmonic radiation is generated predominantly along the vertical directions under the normally incident plane-wave excitation.

The term “medical error” is quite often used to refer to any mistake committed in the provision of healthcare services which has caused harm to a patient. Objective: To analyze civil lawsuits involving medical errors in pediatrics by evaluating: 1) causal link; 2) type of medical error; 3) conviction of the court and its legal basis; 4) correlation between medical expert understanding and legal understanding. Materials and Method: Retrospective analysis of 60 pediatric forensic medical examinations carried out by a pediatric expert between April 2009 and February 2014 at the Institute of Medicine and Criminology of the State of São Paulo (IMESC). The expert’s reports were analyzed according to age, gender, type of forensic medical report (direct or indirect), conclusion of the expert’s report (causal link between the medical conduct and complaint or not), type of medical error (negligence, recklessness, malpractice), judgment in the first instance (if in accordance with the expert’s report or not), and basis of judgment as objective or subjective (type of law). Results: Most expert’s examinations (65%) were indirect (death). In 27 reports (45%), the expert’s conclusion determined that there was a causal link between medical care and the damage inflicted to a patient. Of the 27 reports with causal link, the judge was not in accordance with the expert’s report in one case, thus not considering medical error. The vast majority of sentences (55) were in accordance with the expert’s conclusion (91.6%). Subjective law was mostly used to support the judge’s ruling (61.70%), followed by objective law (23.30%). All lawsuits claimed moral damages (100%). In the statistical analysis of distribution of nominal variables (frequency), an excellent agreement (kappa= 0.86), with statistical significance, was verified between the expert’s report and the court ruling. Conclusion: Expert evidence supported 91.6% of the sentences and was considered to be highly valuable evidence. Expert evidence had a major impact on the legal proceedings and has proven statistically significant (p<0.005). Subjective law was used to assess medical error in all cases in which healthcare professionals were involved. Claims for moral damages was requested in all lawsuits, and was fully or partially granted in 100% of the cases.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

Background: To compare the clinical efficacy of Japas osteotomy of the middle foot and first metatarsal sequence osteotomy in treating children with cavovarus foot deformity. Methods: A retrospective analysis was performed on the clinical effect of cavovarus foot surgery from January 2012 to January 2019. Thirty light and medium cavovarus foot cases underwent osteotomy based on soft tissue release. Among them, 16 cases of 22 feet underwent first metatarsal sequence osteotomy, and 14 cases of 21 feet underwent middle foot Japas osteotomy. Ankle-posterior foot (Wicart) scoring system was used to evaluate the good and good rates of the two surgical methods. X-ray films were taken before and after the last follow-up in a standing weight-bearing position, and Meary Angle, Hibb Angle, and Pitch Angle were measured to compare the clinical efficacy of the two surgical methods in correcting the light and medium-cavovarus foot deformity.Results: (1) All patients were followed up for an average of 30 months. There was no significant difference in Meary, Hibb, and Pitch Angle between first metatarsal osteotomy and middle foot Japas osteotomy before surgery, indicating that the severity of malformation was similar between the two groups. (2) The Meary, Hibb, and Pitch Angle of the last follow-up were compared between the two groups (P>0.05), which showed no statistical significance, indicating that the two surgical methods had similar effects on cavovarus deformity correction. (3) At the most recent follow-up, there was no statistically significant difference between the two groups regarding the percentage of patients who achieved an excellent or good Wicart score; for the first metatarsal osteotomy group, the rate was 87%, and for the Japas osteotomy group was 90%; the Fisher test p>0.05 indicates that the postoperative excellent and good rates of the two treatments are comparable.II (4) Comparison of operation time and intraoperative blood loss between the two groups, P<0.05, showed statistically significant differences, indicating that the first metatarsal osteotomy had obvious advantages over Japas osteotomy operation time and intraoperative blood loss. Conclusions: There is no significant difference in postoperative efficacy between first metatarsal osteotomy and Japas osteotomy for light and medium-cavovarus with the apex of the deformity located at the medial cuneus or navicular cuneiform joint. However, the intraoperative blood loss and operative time of first metatarsal osteotomy are superior to Japas osteotomy of the middle foot, and the trauma to children is less. Therefore, the first metatarsal osteotomy can be considered a surgical procedure.

First responders, such as police officers, paramedics, and fire-fighters are at an increased risk of experiencing negative mental health outcomes compared to the general population. This predisposition can partially be attributed to common occupational stressors, such as poor workplace culture and mistreatment from leadership, which may provoke strong feelings of betrayal and humiliation. The Workplace Assessment Scale (WAS) was developed as there is currently no appropriate measure to assess such feelings in the first responder population. The scale consists of the Betrayal Subscale and the Humiliation Subscale, each comprised of 5 Likert scale questions which ask participants to report the frequency at which they experience specific feelings associated with their workplace. This pilot validation study was conducted to assess preliminary reliability and validity of the WAS, using data which was originally collected as part of a larger first responder-based observational study. Based on 21/22 (95%) participant responses, the internal consistency appeared to be strong for both sub-scales as well as the overall questionnaire. However, item 9 will likely require modification or deletion from the scale. The validity analysis found no significant correlations between WAS and other psychiatric scales. Additional research is needed for further analysis and validation of the WAS.

Preterm birth is a leading cause of infant morbidity and mortality in the world. In 2020, 1 in 10 infants were born prematurely in the United States. Globally, the World Health Or-ganization estimates 15 million infants are born prematurely. The efficacy of current ther-apeutic interventions for preterm birth have been called into question due to limited repli-cable success. Recent advancements in the field of nanomedicine have made it possible to utilize the vaginal administration route to effectively and locally deliver drugs to the fe-male reproductive tract. Also, studies using murine models have provided important in-sights about the cervix as a gatekeeper for pregnancy and parturition. It seems plausible that the field of reproductive biology is on the cusp of a paradigm shift in the context of treating preterm birth. The present review focuses on the complexities associated with treating the condition and novel therapeutics that have produced promising results in pre-clinical studies.

In this work, effects of 20 transition element additives on the interfacial adhesion energy and electronic structure of Al (111)/6H-SiC (0001) interfaces have been studied by first principles method. For clean Al (111)/6H–SiC (0001) interfaces, both Si-terminated and C-terminated interfaces have covalent bond characteristics. The C-terminated interface has stronger binding energy, which is mainly due to the stronger covalent bond formed by the larger charge transfer between C and Al. The results show that the introduction of many transition elements, such as 3d transitional group Mn, Fe, Co, Ni, Cu, Zn and 4d transitional group Tc, Ru, Rh, Pd, Ag, can improve the interfacial adhesion energy of the Si-terminated Al (111)/6H-SiC (0001) interface. However, for the C-terminated Al (111)/6H-SiC (0001) interface, only the addition of Co element can improve the interfacial adhesion energy. Bader charge analysis shows that the increase of interfacial binding energy is mainly attributed to more charge transfer.

The lack of defect image data is one of the main factors affecting the accuracy of supervised deep learning-based defect detection models. In response to the insufficient training data of defect images with complex backgrounds such as rust and surface oil leakage in substation equipment, leading to poor performance of the detection model, this paper proposed a novel adversarial deep learning model for substation defect generation: ADD-GAN. In comparison to existing generative adversarial networks, this model generates defect images based on effectively segmented local areas of substation equipment images, avoiding image distortion caused by global style changes. Additionally, the model utilizes a joint discriminator for overall image and defect image to address the issue of low attention to local defect areas, thereby improving the loss of image features. This enhances the overall quality of generated images as well as locally generated defect images, ultimately improving image realism. Experimental results demonstrate that the YOLOV7 object detection model trained on the dataset generated using the ADD-GAN method achieves an mAP of 81.5% on the test dataset, representing an improvement of 9.6% over the original dataset, 5.7% over traditional augmentation methods, and 7% over typical adversarial deep learning methods. This confirms that the ADD-GAN method can generate a high-fidelity dataset of substation equipment defects.

Half-metallic semi-Heusler compounds are currently at the forefront of scientific research due to their potential applications in spintronic devices. Unlike other semi-Heuslers, the p0(d0)-d compounds do not appear to crystallize in the typical variant of the C1b structure. We investigate this phenomenon in the p0-d Heusler compounds LiYGa and LiYGe, where Y varies between Ca and Zn, using first-principles ab-initio electronic band structure calculations. We examine the electronic and magnetic properties of these compounds in relation to the three possible C1b structures. Notably, LiVGa, LiVGe, LiMnGa, and LiCrGe are half-metallic ferromagnets across all three variations of the C1b lattice structure. Our findings will serve as a foundation for future experimental studies on these compounds.

Stochastic modelling of geometrically imperfect steel frame structures requires inputs of statistical values of the imperfection parameters, in some cases also with suitably selected mutual correlations between these input parameters. The paper presents a verification study of two stochastic methods to directly model the initial global geometrical imperfections of the steel frame structures. The stochastic input values of geometrical imperfections are derived from the tolerance criteria of the corresponding European Standard. Two advanced stochastic methods have been developed, referred as #RSS (random story sway) and #RSP (random story position). These methods are verified using random sampling simulations. This study provides useful provisions for the advanced numerical analyses of multi-story steel frames of various geometries. The proposed methods are verified for equidistant story heights and for structures of up to 24 stories, hence might be used for the most types of the standard steel frame structures.

The purpose of this study was to clarify the attachment types of the tibialis anterior tendon (TAT) in Japanese fixed cadavers and to determine the attachment site area in three dimensions. We examined 100 feet from 50 Japanese cadavers. The TAT was classified according to differences in the number of fiber bundles as: Type I, with one fiber bundle; Type II, with two fiber bundles; and Type III, with three fiber bundles. The attachment site area of the TAT was measured using a three-dimensional scanner. Cases were Type II in 95% and Type III in 5%, with no cases of Type I identified. In Type II, mean attachment site areas were 85.2 ± 18.2 mm2 for the medial cuneiform bone (MCB) and 72.4 ± 19.0 mm2 for the first metatarsal bone (1MB), showing a significantly larger area for MCB than for 1MB. These findings suggest the possibility of ethnic differences in TAT attachment types and suggest that TAT attachments in Japanese individuals are highly likely to be Type II, with rare cases of Type III. Accurate measurement of attachment site areas is possible with appropriate three-dimensional measurements.

Microbial immune escape represents the primary cause of induced pathogenesis in humans, and it represents a pivotal method used by viral agents to increase their load and suppress key mechanisms of the innate and adaptive immune system. This phenomenon represents the primary factor that led to the onset of the 1918-1920 A(H1N1) Influenza and 2020-2022 COVID-19 pandemics, and it possibly played a major role in the onset of the AIDS pandemic as well. Moreover, repeated incidents of immune evasion could be associated with higher rates of cellular aging (Jackson et al., 2017), most likely due to the consequent increased demands of energy consumption. Highly developed viral immune evasion ultimately indicates the high inner intelligence of human immunity due to reflective and imitative characteristics of reactions that are produced against initial actions. Ribonucleic acid-based viral genomes contain open reading frames, which consist of genes producing sixteen non-structural proteins. Such proteins play a considerable role in desensitizing first-line immunity during cellular infection, and non-structural proteins 1, 10 and 16 have the strongest effects against a healthy expression rate of Type I and Type III Interferon-encoding genes. Type I Interferons consist of IFN-alpha, -beta, -delta, -epsilon, -omega, -tau and -zeta, whilst Type III Interferons consist of IFN-lambda1, -lambda2 and -lambda3, and they act as stimulators of intracellular signalling cascades that in turn lead to the activation and expression of interferon-stimulated genes (Brown et al., 2022). The earlier the interferon-stimulated genes are activated, the lower the extent of pro-inflammatory mediation and overall, the more effective the antiviral immune response will be, given the exponential nature of the viral load increase. Non-structural protein 16 methylates the 5’ cap of the virus, making the pathogen-associated molecular patterns less recognisable by pattern-recognition receptors, and it requires activation by bonding with non-structural protein 10. It is preserved in the S-Adenosyl-L-Methionine pocket of the SARS-CoV-2 genome. Non-structural protein 1 (NS1) directly cleaves the host cell mRNA producing Type I and possibly Type III Interferons, thereby preventing a translation process of the immune proteins. NS1 has recently been found to often be packaged into exosomes once secreted by the viral genome in the cytosol, meaning that exocytosis and paracrine signalling to neighbouring cells before their actual infection is possible. As a result, NS1 is highly capable of silencing the first-line immune responses of uninfected neighbouring cells as well, thereby highlighting the need to adjust the focus of therapeutics and vaccinology toward first-line immunity and further indicating its foundational importance in the support for the development of precise and balanced defenses against microbial agents of concern (EL SAFADI et al., 2022).

Cameroon's national vaccination campaign was launched on April 12, 2021, amid a nationwide outbreak of COVID-19 with two types of vaccines. This study provides preliminary evidence of the level of coverage of the population and gives an early overview of the challenges, the achievements and the lessons learned. COVID-19 vaccine administration data were obtained from data of the Cameroon Ministry of Public Health. Descriptive statistical analyses were conducted. Thirty days after the introduction of COVID 19 vaccines, five percent of the target population was vaccinated. Women represented one third of the people vaccinated regardless of age and health conditions. Although AEFI reported were minor and scanty with both vaccines, the majority of the vaccinated did not come back for their second dose. There is a need to build confidence among eligible beneficiaries in order to expand the benefits of vaccination to control the current pandemic. The country is still far below the target which could be worrisome given that the uptake is slow and, the 391 200 doses of the AstraZeneca are going to expire in August 2021. This study offers insights into those early efforts as a contribution to significant discussions about upcoming approach to improve service delivery and uptake.

Supported wellbeing centres were set up in UK hospital trusts as an early intervention aimed at mitigating the psychological impact of COVID-19 on healthcare workers. These provided high quality rest spaces with peer-to-peer psychological support provided by National Health Service (NHS) staff volunteers called ‘wellbeing buddies’, trained in psychological first aid. The aim of the study was to explore the views of centre visitors and operational staff towards this COVID-19 workforce wellbeing provision. Qualitative semi-structured interviews were undertaken with twenty-four (20F, 4M) employees from an acute hospital trust in the UK. Interviews were digitally recorded and transcribed, data were handled and analysed using thematic analysis. Interviews generated 3 over-arching themes, and 13 sub-themes covering ‘exposure and job roles’, ‘emotional impacts of COVID-19 and ‘the wellbeing centres’. Supported wellbeing centres were viewed as critical for the wellbeing of hospital employees during the first surge of COVID-19 in the UK. Wellbeing initiatives require managerial advocacy and must be inclusive. Job-related barriers to work breaks and accessing staff wellbeing provisions should be addressed. High quality rest spaces and access to peer-to-peer support are seen to benefit individuals, teams, organisations and care quality. Training NHS staff in psychological first aid is a useful approach to supporting the wellbeing of the NHS workforce during and beyond the COVID-19 pandemic.

In the paper, by virtue of techniques in combinatorial analysis, the authors simplify two families of nonlinear ordinary differential equations in terms of the Stirling numbers of the first kind.

Aerial image classification has become popular and has attracted extensive research efforts in recent decades. The main challenge lies in its very high spatial resolution but relatively insufficient spectral information. To this end, spatial-spectral feature extraction is a popular strategy for classification. However, parameter determination for that feature extraction is usually time-consuming and depends excessively on experience. In this paper, an automatic spatial feature extraction approach based on image raster and segmental vector data cross-analysis is proposed for the classification of very high spatial resolution (VHSR) aerial imagery. First, multi-resolution segmentation is used to generate strongly homogeneous image objects and extract corresponding vectors. Then, to automatically explore the region of a ground target, two rules, which are derived from Tobler’s First Law of Geography (TFL) and a topological relationship of vector data, are integrated to constrain the extension of a region around a central object. Third, the shape and size of the extended region are described. A final classification map is achieved through a supervised classifier using shape, size, and spectral features. Experiments on three real aerial images of VHSR (0.1 to 0.32 m) are done to evaluate effectiveness and robustness of the proposed approach. Comparisons to state-of-the-art methods demonstrate the superiority of the proposed method in VHSR image classification.

Digital twin technology, a cutting-edge approach that creates dynamic digital replicas of physical systems, is increasingly integral to various industrial applications. However, the effective deployment of digital twins often faces challenges associated with data availability, quality, and interoperability, which can impede the development and operational efficacy of these virtual counterparts. This paper presents a systematic review of the application of artificial intelligence (AI) in enhancing and managing digital twin technologies across multiple domains such as industry, healthcare, urban planning, business, education, technology, and others. It specifically examines how machine learning models, particularly neural networks and deep generative models, are being employed to optimize the creation, maintenance, and functionality of digital twins. The review explores the role of artificial intelligence in overcoming data-related limitations by providing robust, scalable data solutions for digital twins. Additionally, it addresses critical considerations of real-time data processing and system interoperability within these applications. This survey not only identifies the prevailing challenges and opportunities within this emerging field but also highlights potential future research directions that could further the integration of AI with digital twin technology. Through a detailed exploration of the intersection between AI and digital twins, this paper aims to contribute significantly to the knowledge base and encourage further innovations in this interdisciplinary area.

Coupling faults that occur simultaneously widely exist in the operation of mechanical equipment, and coupling fault features are formed by nonlinear coupling of multiple base fault features. In this paper, hypergraph neural network is used to obtain the characteristics of coupling faults, and two coupling fault diagnosis frameworks based on hypergraph are provided. 1. Coupling fault diagnosis framework based on feature generation: The hypergraph neural network is used as a generator to provide negative samples for discriminator training. The generator outputs hyperedge vectors as fake samples, and each hyperedge connects a base fault containing a fault type. 2. Coupling fault diagnosis framework based on feature extraction: Each node is regarded as a fault type, and the fault characteristics of each type of fault are extracted through the aggregation operation of hypergraph. The attention mechanism is introduced to realize the dynamic adjustment of the hyperedge, and the dynamic vertex is used to classify the unknown faults. The results show that the diagnostic accuracy of coupling faults under the two frameworks reaches 88.6% and 86.76%, respectively.

Research in renewable energy sources and micro-grid systems is critical for the evolving power industry. Micro-grids can supply diverse loads while reducing dependency on the utility grid. This paper models both pico-grids and nano-grids in the Singapore Institute of Technology Punggol campus, incorporating solar PV, energy storage systems (ESS), power electronics converters, and both DC and AC loads, along with utility grid connections. The pico-grid includes a battery storage system, a single-phase inverter linked to a single-phase grid, and DC and AC loads. The nano-grid comprises solar PV panels, a boost converter, a battery storage system, a three-phase inverter connected to a three-phase grid, and AC loads. Both the pico-grid and nano-grid are configurable in standalone or grid-connected modes. This configuration flexibility allows for detailed operational analysis under various conditions. The study conducts subsystem-level modeling before integrating all components into the simulation environment. MATLAB/Simulink is utilized to model, simulate, and analyze the power flow in both the pico-grid and nano-grid under different operating conditions.

This paper explores the development of a sophisticated system for automatic test generation tailored specifically for Java web applications utilizing REST interfaces. Writing tests ensures the quality of the software solution event after the introduction of subsequent changes, because automated regression testing can detect potential bugs in the code event before the application is resealed into production. By utilizing and comparing various automatic test generators, the system described provides users with a visual representation of code structure and coverage, enhancing insights through call graph visualization. The paper describes the concepts of theoretical automatic test generators, gives an overview of generators, and details the design and implementation of the implemented solution, which integrates the system test generator and the unit test generator based on open source to achieve the maximum code coverage level.

In recent years, bioengineered and biotechnological products have gained tremendous attention to identify unique biologic features associated with oncology. To overwhelm the complexity of tumor personalized medicines (PM) or vaccines could be a promising way-out to be considered. Cancer is a heterogeneous disease. This characteristic variability of cancer provides itself to the emergent era of PM i.e., precision oncology. The prime objective of PM is merely to deliver the right treatment to the right patient at the right time. For instance, imatinib was effectively targeted chronic myeloid leukemia. To date, attainment in using PM approaches to cancer treatment have been mixed. The next-generation sequencing (NGS), and the use of several biomarkers (e.g., HER2, BRAF, ALK, etc.), to drive precise cancer treatment through a timely and cost-effective manner. In current review, author summarizes the advancement in the field of PM such as CRISPR-Cas9, NGS, pharmacogenomics, and the benefits of machine learning techniques. The precise communication between healthcare professionals, regulatory bodies, and patients is essential to translate advances in PM into immense benefits for patients with cancer globally.

Securing funding is a critical yet complex task for organizations and individuals. This study presents an innovative chatbot designed to streamline the process using advanced Natural Language Processing (NLP) techniques and, specifically, a Retrieval-Augmented Generation (RAG) pipeline optimized for real-world applications. Our chatbot assists users in identifying suitable public tenders for financial support through natural language queries and a comprehensive public data database. The chatbot operates in a two-stage interaction model, initially providing summarized tender information for exploratory brainstorming, followed by detailed data upon user selection. A custom filtering mechanism ensures that the user interface elements responsible for swapping the interaction stages are consistent with the responses generated by the conversational agent. Human-evaluation tests demonstrated an average accuracy of 90.4% in document retrieval, with an average of 2.11 interactions required to find a specific tender. User satisfaction, rated on a scale of 1 to 5, averaged 3.14 (±1.73), indicating generally positive user experience with room for improvement. This approach addresses challenges of relevance, accuracy, and conversational flow, resulting in a reliable chatbot that simplifies the process of finding funding opportunities.

The gastrointestinal (GI) tract harbors trillions of microorganisms known to influence human health and disease, and next-generation sequencing (NGS) now enables the in-depth analysis of their diversity and functions. Although a significant amount of research has been conducted on the GI microbiome, comprehensive metagenomic datasets covering the entire tract are scarce due to cost and technical challenges. Despite the widespread use of fecal samples, integrated datasets encompassing the entire digestive process, beginning at the mouth and ending with feces, are lacking. With this study, we aimed to fill this gap by analyzing the complete metagenome of the GI tract, providing insights into the dynamics of the microbiota and potential therapeutic avenues. In this study, we delved into the complex world of the GI microbiota, which we examined in five healthy Japanese subjects. While samples from the whole GI flora and fecal samples provided sufficient bacteria, samples obtained from the stomach and duodenum posed a challenge. Using a principal coordinate analysis (PCoA), clear clustering patterns were identified; these revealed significant diversity in the duodenum. Although this study was limited by its small sample size, the flora in the overall GI tract showed unwavering consistency, while the duodenum exhibited unprecedented phylogenetic diversity. A visual heat map illustrates the discrepancy in abundance, with Fusobacteria and Bacilli dominating the upper GI tract and Clostridia and Bacterioidia dominating the fecal samples. Negativicutes and Actinobacteria were found throughout the digestive tract. This study demonstrates that it is possible to continuously collect microbiome samples throughout the human digestive tract. These findings not only shed light on the complexity of GI microbiota but also provide a basis for future research.

Congenital heart disease (CHD) is the most commonly detected congenital anomaly and affects up to 1 % of all live-born neonates. Current guidelines support the use of Chromosomal Microarray Analysis (CMA) and Next Generation Sequencing (NGS) as diagnostic approaches to identify genetic causes. The aim of our study was to evaluate the diagnostic yield of CMA and NGS in a cohort of neonates with both isolated and syndromic CHD. The present study included 188 infants under 28 days of age with abnormal echocardiography findings hospitalized at the Department of Neonatology, UMC Ljubljana, between January 2014 and December 2023. Phenotypic data were obtained for each infant by retrospective medical chart review. We established the genetic diagnosis of 22 distinct syndromes in 17% of neonates. The most common genetic diagnoses were 22q11.2 microdeletion (22.7%) and CHARGE syndromes (22.7%), Noonan syndrome (9.1%), and Williams syndrome (9.1%). In addition, we detected variants of uncertain significance in 4.8% of neonates. Timely genetic diagnosis is important for the detection of syndrome-related comorbidities, prognosis, reproductive genetic risks and, when appropriate, genetic testing of other family members.

Driven by mounting environmental apprehensions stemming from the over dependence on fossil fuels in energy and transportation sectors, extensive exploration into alternative energy sources, particularly biomass, has stimulated profound research on harnessing the potential of computational and mathematical techniques. This comprehensive survey delves into optimal models and strategies, unveiling their pivotal role in the design of biomass gasification processes.of hydrogen through biomass gasification. In this study, we aim to provide a comprehensive overview of the computational and mathematical techniques employed in optimizing biomass gasification processes, with a specific focus on enhancing hydrogen yield. Through an extensive literature review, various models and strategies will be examined, including thermodynamic analysis, kinetic modeling, reactor design, and process optimization. By uncovering the power of these techniques, we aim to contribute to the advancement of sustainable and efficient biomass utilization for the hydrogen-based future economy.This paper aims to provide an updated and comprehensive coverage of the investigations conducted on the potential of producing hydrogen from biomass through gasification. To achieve this, we incorporate the latest works that have utilized numerical modeling, simulation, optimization techniques, process heat integration, and co-generation in their studies. By encompassing these aspects, we aim to offer a broader and more in-depth re-appraisal of the subject matter. This will ensure that readers gain a holistic understanding of the advances made in the field and the potential for sustainable hydrogen production of biomass gasification.Through a meticulous re-appraisal and analysis of each subject, we can identify their respective strengths and areas that require further research effort. By thoroughly examining numerical modeling, simulation, optimization techniques, process heat integration, and co-generation, we can assess their effectiveness and applicability in the context of biomass gasification for hydrogen production. This analysis shed light on the areas where these techniques excel, as well as pinpoint limitations or gaps in current understanding. By identifying these areas, we can highlight the need for further research and development, enabling us to make significant advancements in biomass gasification processes and pave the way for a sustainable and efficient hydrogen-based future economy..

This research, which focuses on wave energy generating technology, suggests a brand-new oscillating float-type wave energy conversion system that is appropriate for the offshore wave environment. To accurately model the device, a three-dimensional viscous numerical pool is created based on STAR-CCM+. The array-type power generation device is numerically simulated using theoretical analysis and numerical simulation, and the wave energy power generation device is arranged as double floats in the front and rear rows, representing triangular array type and rectangular array type, respectively. The triangular array type is a superior layout and can make greater use of marine resources, according to this paper's analysis of the hydrodynamic and power generation impacts of the three array types. The findings are meant to serve as a guide for engineering practice.

Remote distributed generation control and demand response is nowadays a basic need, especially for the Distributed Network Operators (DNOs). The integration of Renewable Energy Sources (RES) with stochastic production characteristics into the grid in conjunction with the newly appeared stochastic demand consumers (i.e., electric vehicles) hardens the ef-forts of the DNOs to keep the grid’s operation within safe limits and prevent cascading black-outs while staying in compliance with the SAIDI and SAIFI indices during maintenance and re-pair operations. Taking also under consideration the aging of the existing grid infrastructure, making it year by year more prone to failure, it is yet of great significance for the DNOs to have access to real-time feedback from grid’s infrastructure, fast, with low-cost upgrade interventions, easily deployed on the field and with fast response potential, in order to be able to perform real-time grid management (RTGM). In this article, we describe the architecture, development and deployment of a hybrid real-time control system of distributed generation (DG) units, which has the potential to be applied easily to DNO’s substations, RES plants and consumers (i.e. electric vehicles’ charging stations), that combines a low-cost minimum intervention into the electricity grid and its components and eliminates all communication interoperability problems between the different vendors’ installed electrical equipment.

This paper investigates the polarization and heat generation characteristics of batteries under different ambient temperatures and discharge rates by means of using a coupled electric-thermal model. The study found that the largest percentage of polarization is ohmic polarization, followed by concentration polarization and electrochemical polarization. The values of the three types of polarization are generally small and stable under normal-temperature environments and low-discharge rates. However, they increase significantly in low-temperature environments and high-discharge rates and continue to rise during the discharge process. Additionally, ohmic heat generation and polarization generation also increase significantly under these conditions. Reversible entropy heat is less sensitive to ambient temperature but increases significantly with the increase of the discharge rate. Ohmic heat generation and polarization heat generation contribute to the total heat generation of the battery at any ambient temperature, while reversible entropy heat only contributes to the total heat generation of the battery at the end of discharge.

This study explores the potential of data science software solutions like Customer Relationship Management Software (CRM) for increasing the revenue generation of businesses. We focused on those businesses in Accommodation and Food Service sector across the European Union (EU). The investigation is contextualized within the rising trend of data-driven decision making, examining the potential correlation between data science application and business revenue. Employing a comprehensive evaluation of Eurostat datasets from 2014 to 2021, we used both univariate and multivariate analyses, we assessed e-commerce sales data across countries, focusing on the usage of big data and CRM tools. Big data utilization showed a clear, positive relationship with enhanced e-commerce sales. However, CRM tools exhibited a dualistic impact: while their use in marketing showed no significant effect on sales, their application in non-marketing functions had a negative correlation. These findings underscore the potential role of CRM and data science solutions in enhancing business performance in the EU's Accommodation and Food Service industry.

Continuous glucose monitoring devices allow diabetes condition management. However, when limited data is available, one option is to increase their size by generating synthetic samples. From a homemade wearable prototype was created a real dataset with 18 instances and 53 attributes that capture characteristics of capillary and venous blood glucose, oxygen concentration, pulse rate, skin temperature, and 24 modules and 24 phases related to bio-impedance. The objective of this article is to generate synthetic datasets, and also it investigates the ideal features subset and optimal model for non-invasive diabetes prediction. Gaussian-Copulas (GC), conditional generative adversarial networks (CG), variational autoencoders, and Copula-GAN techniques' were used to generate five synthetic datasets. Experiments show that GC1 and GC2 datasets follow min/max boundaries and are not copies of the original data. Multilayer perceptron regressor outperformed (train and test) with 2.17, 2.51 in MAE; 9.29, 13.59 in MSE; 3.05, 3.69 in RMSE, and 0.95, 0.92 in R2 in GC1, and 2.64, 3.02 in MAE; 11.43, 15.11 in MSE; 3.38, 3.89 in RMSE, and 0.94, 0.92 in R2 in GC2 with eight features. Future work is necessary to explore autoencoder and generative architectures, datasets with diverse characteristics, and the effect of the number of features.

Living beings are composite thermodynamic systems in non-equilibrium conditions. Within this context, there are a number of thermodynamic potential differences (forces) between them and the surroundings, as well as internally. These forces lead to flows, which, ultimately, are essential to life itself. Living beings are under the pressures of natural selection, thus are biological flows as well. At the same time, the maintenance of homeostatic conditions, the tenet of physiology, demands regulation of these flows by control of variables. However, due to the very nature of these systems, regulation of flows and control of variables become entangled in closed loops. Therefore, the search for adaptation in flows takes a different path than the search for adaptation in morphological traits. Being at the roots of transfer processes, thermodynamic criteria turn out to be as natural physical candidates. Likewise, being at the roots of physiology, control turns out to be as a natural biological candidate in that path. Here we show how to combine entropy generation, with respect to a generalized process, and control of parameters (in such a generalized process) in order to create a criterium of optimal ways to regulate changes in generalized flows.

This study addresses the motivations behind Generation Z's attendance at conferences and aims to contribute to a better understanding of their conference participation behavior. The study identified six latent factors that influence conference attendance motivation: Green and Digital Conference Experience, Educational and professional opportunities, Conference costs, Destination and conference stimuli, Stimulating factors, and Conference accessibility. These factors align with Generation Z's unique characteristics and preferences, such as their environmental consciousness, reliance on digital technologies, desire for continuous learning, career advancement, and experiences. The study also found that destination characteristics and educational and professional opportunities are significant motivators for Generation Z's conference attendance across different cultural contexts. Additionally, Generation Z's strong interest in sustainability and financial challenges highlights the need for eco-friendly practices and affordable registration fees to make conferences more appealing and accessible. The study further explores the impact of socio-demographic characteristics, revealing the gender and past conference attendance differences in motivation. Finally, the study discusses the implications for the conference industry and suggests areas for future research to enhance the understanding of conference attendance motivation among Generation Z.

Huge-scale video surveillance systems have become essential in crime prevention and situation recording. Traditional surveillance systems relied on human monitoring of video streams, which often led to errors and difficulties in understanding events. Furthermore, locating specific scenes within recorded videos required extensive human investigation. To overcome these challenges of inefficiency, inconvenience, and potential risks, we propose an intelligent analysis scheme that utilizes abnormal behavior recognition and metadata retrieval algorithms to replace human monitoring. The proposed method consists of three stages: i) metadata generation through object detection and tracking, ii) abnormal behavior recognition, and iii) SQL-based metadata retrieval. By incorporating specific information such as object color and aspect ratio, our technique enhances the usability of retrieval. Moreover, our abnormal behavior recognition module demonstrates robust classification capabilities for activities such as pushing, violence, falling, and crossing barriers. The proposed method can be seamlessly deployed on both edge cameras and analysis servers, making it adaptable to various surveillance setups. This approach revolutionizes the traditional surveillance paradigm, enabling more efficient, reliable, and secure video monitoring and analysis.

Wearable thermoelectric generators (w-TEGs) convert thermal energy into electrical energy to realize self-powering of intelligent electronic devices, thus reducing the burden of battery replacement and charging, and improving the usage time and efficiency of electronic devices. Through finite element simulation, this study successfully designed high-performance thermoelectric generator and made it into wearable thermoelectric module by adopting “rigid device - flexible connection” method. It was found that higher convective heat transfer coefficient on cold-end leads to larger effective temperature difference and better power generation performance of device in typical wearable scenario. Meanwhile, at same convective heat transfer coefficient on the cold-end, longer TE leg length leads to larger temperature difference established at both ends of device, larger device output power and open-circuit voltage. However, when the convective heat transfer coefficient increases to a certain level, optimization effect of increasing TE leg length on device power generation performance will gradually diminish. For devices with fixed temperature difference between two ends, longer TE leg length leads to higher resistance of TEG, resulting in lower device output power but slight increase in open-circuit voltage. Finally, sixteen 16×4×2 mm2 TEGs (L=1.38 mm, W=0.6 mm) and two modules were fabricated and tested. At hot end temperature Th=33 ℃ and cold end temperature Tc=30 ℃, the actual maximum output power Pout of TEG is about 0.2 mW, and the actual maximum output power Pout of TEG module is about 1.602 mW, which is highly consistent with the simulated value. This work brings great convenience to research and development of wearable thermoelectric modules and provides new, environmentally friendly and efficient power solution for wearable devices.

We attempted to understand the cervical cancer patient samples through Whole Exome Sequencing. We derived the variants from raw reads via our in-house benchmarked pipeline and validated the variants by IGV. This is the first cervical cancer exome data from the Indian cohort. Background: Cervical cancer (CC) is caused mainly by persistent infections of high-risk HPV, reduced parity, and factors like a decrease in average socioeconomic levels. We keep this because no cervical cancer exome data is available from the Indian cohort. Methods: The CC patient clinical samples were initially subjected to preparation using Qiagen DNA extraction, quantified, and the library preparation using the Agilent target enrichment system. Further, exome capture by Illumina platform (100X), quality check, alignment, and variant calling followed by the downstream analysis and finally visualized by IGV. Results: We observed a large number of SNVs or mutations from an Indian perspective, such as KMT2C, OR4M1, PDPR2P, EPHB1, FAS, OPCML, MGST1, C1QTNF9, HS6ST3, OR4K2, PRPSAP2, KCNJ12, FIGNL1, SFXN1, BAGE2, ARVCF, NAMPT variants of significance, unknown significance and possibly significant are reported. Conclusion: For the first time, KMT2C is observed as a novel potent mutation and pathogenic, showing the variant position at (7:152265091, T>A, SNV 62478356) from the Indian context in CC. Further, we visualized and validated the mutations using the Integrative Genomic Viewer (IGV) browser. Finally, we discuss the inherent challenges through KMT2C mutations.

The biological heterogeneity of glioblastoma (GBM), the most aggressive type of brain cancer, is a critical hallmark, caused by changes in the genomic mutational asset and influencing the clinical progression over the time. The understanding and monitoring of the mutational profile is important not only to reveal novel therapeutic targets in this set of patients, but also to ameliorate the clinical stratification of subjects and the prognostic significance. As neurosurgery represents the primary technique to manage GBM, it is of outmost importance to optimize alternative and less invasive methods to monitor the dynamic mutation profile of these patients. Extracellular vesicles (EV) are included in the liquid biopsy analysis and have emerged as the biological mirror of escaping and surviving mechanisms by many tumors as well as glioblastoma. Very few studies have investigated the technical feasibility to detect and analyze the genomic profile by Next Generation Sequencing (NGS) in circulating EV of patients with grade IV glioblastoma. Here, we attempted to characterize and to compare with the corresponding matched tissue samples, potential variants with pathogenic significance of the DNA contained in peripheral blood derived EV. The NGS analysis has revealed that patients with grade IV glioblastoma, exhibited lesser DNA content in EV than controls and that both in EV and matched cancer tissues, the NF1 gene was consistently mutated in all patients with the c.2568C&gt;G as the most common pathogenic variant expressed. This study supports the clinical utility of the circulating EV in glioblastoma and as eligible tool for personalized medicine.

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.

Forest health is dependent on the variability of microorganisms interacting with the host tree/holobiont. Symbiotic microbiota and pathogens engage in a permanent interplay, which influences the host. Thanks to the development of NGS technologies, a vast amount of genetic information on the virosphere of temperate forests has been gained the last seven years. To estimate the qualitative/quantitative impact of NGS in forest virology, we have summarized viruses affecting major tree/shrub species and their fungal associates, including fungal plant pathogens, mutualists and saprotrophs. The contribution of NGS methods is extremely significant for forest virology. Reviewed data about viral presence in holobionts, allowed us to address the role of the virome in the holobionts. Genetic variation is a crucial aspect in hologenome, significantly reinforced by horizontal gene transfer among all interacting actors. Through virus-virus interplays synergistic or antagonistic relations may evolve, which may drastically affect the health of the holobiont. Novel insights of these interplays may allow practical applications for forest plant protection based on endophytes and mycovirus biocontrol agents. The current analysis is conceived in light of the prospect that novel viruses may initiate an emergent infectious disease and that measures for avoidance of future outbreaks in forests should be considered.

Adhesion systems are very important in robots for infrastructure inspection (especially in vertical walls). They present the challenge of optimizing the ratio vacuum/power consumption in battery-powered robots. In this paper a CFD (Computer Fluid Dynamics) modelling and optimization process of a robot adhesion system is carried out to determine the best performing configuration in terms of vacuum and power consumption. Analytical and numerical models were developed to predict the behaviour of the system for different configurations. The models were validated, using test rig measurements, by calibrating an arbitrary defined inlet height that simulates the leakage flow. Then, different geometric parameters were varied to determine the best performing configuration based on the vacuum/power consumption ratio value. The model presented in the paper was capable of predicting the behaviour of the system for different configurations, with a margin of error of 15% for the vacuum prediction and a 25% for the motor power calculation. Finally, the model was used to optimize parameters of the system, like the number of blades of the impeller. The adhesion system was conceived for the modular autonomous climbing legged robot ROMERIN.

Left ventricular noncompaction (LVNC) and hypertrophic cardiomyopathy (HCM) commonly occur as separate disorders with distinct clinical and pathoanatomical features. However, these cardiomyopathies may have a similar genetic origin with mutations encoding sarcomeric proteins. The described case demonstrates an example, in which phenotypic expression of both diseases occurs in the same patient.

In this paper the problem of sampling from uniform probability distributions is approached by means of space-filling curves (SFCs), a topological concept that has found a number of important applications in recent years. Departing from the theoretical fact that they are surjective but not necessarilly injective, the investigation focused upon the structure of the distributions obtained when their domain is swept in a uniform and discrete manner, and the corresponding values used to build histograms, that are approximations of their true PDFs. This work concentrates on the real interval [0,1], and the Sierpinski space-filling curve was chosen because of its favorable computational properties. In order to validate the results, the Kullback-Leibler distance is used when comparing the obtained distributions in several levels of granularity with other already established sampling methods. In truth, the generation of uniform random numbers is a deterministic simulation of randomness using numerical operations. In this fashion, sequences resulting from this sort of process are not truly random.

We review recent work on narrowband orthogonally polarized optical RF single sideband generators as well as dual-channel equalization, both based on high-Q integrated ring resonators. The devices operate in the optical telecommunications C-band and enable RF operation over a range of either fixed or thermally tuneable frequencies. They operate via TE/TM mode birefringence in the resonator. We achieve a very large dynamic tuning range of over 55 dB for both the optical carrier-to-sideband ratio and the dual-channel RF equalization for both the fixed and tunable devices.

Targeted next-generation sequencing (NGS) technology detects specific mutations that can provide treatment opportunities for colorectal cancer (CRC) patients. We included 145 CRC patients who underwent surgery. We analyzed the mutation frequencies of common actionable genes and their association with clinicopathological characteristics and oncologic outcomes using targeted NGS. Approximately 97.9% (142) of patients showed somatic mutations. Frequent mutations were observed in TP53 (70%), KRAS (49%), and APC (47%). TP53 mutations were significantly linked to higher overall stage (p=0.038) and lower disease-free survival (DFS) (p=0.039). ATM mutation was significantly associated with higher tumor stage (p=0.012) and shorter overall survival (OS) (p=0.041). Stage 3 and 4 patients with ATM mutations (p=0.023) had shorter OS, and FBXW7 mutation was significantly associated with shorter DFS (p=0.002). In multivariate Cox regression analysis, ATM mutation was an independent biomarker for poor prognosis of OS (p=0.022). TP53 and FBXW7 mutations are independent biomarkers for poor prognosis of DFS (p=0.042 and 0.030, respectively). A comprehensive analysis of the molecular markers for CRC can provide insights into the mechanisms underlying disease progression and help optimize a personalized therapy.

We present a method to improve the reconstruction and generation performance of variational autoencoder (VAE) by injecting an adversarial learning. On the other hand, instead of comparing the reconstructed with the original data to calculate the reconstruction loss, we use a consistency principle for deep features. The training process of the VAE is then divided into two steps, training the encoder and then training the decoder. By using this two-step learning process, our method can be more widely used in applications other than image processing. While training the encoder, the label information is integrated to better structure the latent space in a supervised way. The adversarial constraints allow the decoder to generate data with better authenticity and more realistic than the conventional VAE. We present experimental results to show that our method gives better performance than the original VAE.

High frequency knowledge of the spatio-temporal distribution of the Downwelling Surface Shortwave Flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface-atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy sector. The EUMETSAT Satellite Application Facility for Land Surface Analysis operationally delivers estimation of the MDSSFTD (Downwelling Surface Short-wave radiation Fluxes – Total and Diffuse fraction) product with an operational status since the year 2019. The method for the retrieval was presented in the companion paper [40]. The part 2 now focuses on the evaluation of the MDSSFTD algorithm and presents the comparison of the corresponding outputs, i.e. total DSSF and diffuse fraction (fd) components, against in-situ measurements acquired at four BSRN stations over a seven-month period. The validation is performed on an instantaneous basis. We show that the satellite estimates of DSSF and fd meet the target requirements defined by the user community for all-sky (clear and cloudy) conditions. For DSSF, the requirements are 20Wm^-2 for DSSF<200Wm^-2, and 10% for DSSF>=200Wm^-2. The MBE and rMBE compared to the ground measurements are 3.618Wm^-2 and 0.252%, respectively. For fd, the requirements are 0.1 for fd<0.5, and 20% for fd>=0.5. The MBE and rMBE compared to the ground measurements are -0.044 and -17.699%, respectively. The study also provides a separate analysis of the product performances for clear sky and cloudy sky conditions. The importance of representing the cloud-aerosol radiative coupling in the MDSSFTD method is discussed. Finally, it is concluded that the quality of the Aerosol Optical Depth (AOD) forecasts currently available is enough accurate to obtain reliable diffuse solar flux estimates. This quality of AOD forecasts was still a limitation a few years ago.

In these times electricity is big trouble of problem facing by the world. Therefore, there is necessitating for the property basis of energy that is employed for as bio-electricity. Many of the scientists and researchers are trying to find out the sustainable energy generates with the help of plant microbial fuel cell. Plant microbial fuel cell (P-MFCs) could be feasibility technology approach of bio-electricity generation which is mutualism interaction of the plants along with their rhizospheric bacteria. In the present study, Plant-microbial fuel cell was observed in grass e-table evaluated in term of bioelectricity generation from Cynodon dactylon (Dooba Ghas). This e-table was connected with electrode and different condition (physical and chemical) to detect the change in bioelectric potential. It was found that maximum voltage generated among all the conditions was 4.24 ±2V at 15 days by using Cynodon dactylon through P-MFCs. The potential difference generated through P-MFCs was measured using a multimeter. The generation of bioelectricity was observed under different conditions like exposure to light and shade condition measured for voltage was found to be significantly different parameters. The maximum recorded under light and shade conditions were 3.82 ±2 V and 4.25 ±2 V respectively at 15 days of incubation.

Computational Fluid Dynamics (CFD) simulations, based on Reynolds Averaged Navier Stokes (RANS) models, are a useful tool for a wide range of coastal and offshore applications, providing a high fidelity representation of the underlying hydrodynamic processes. Generating input waves in the CFD simulation is performed by a numerical wavemaker (NWM), with a variety of different NWM methods existing for this task. While NWMs, based on impulse source methods, have been widely applied for wave generation in depth averaged, shallow water models, they have not seen the same level of adoption in the more general RANS based CFD simulations, due to difficulties in relating the required impulse source function to the resulting free surface elevation for non-shallow water cases. This paper presents an implementation of an impulse source wavemaker, which is able to self-calibrate the impulse source function to produce a desired wave series in deep or shallow water at a specific point in time and space. Example applications are presented, for a numerical wave tank (NWT), based on the opensource CFD software OpenFOAM, for wave packets in deep and shallow water, highlighting the correct calibration of phase and amplitude. Also, the suitability for cases requiring very low reflection from NWT boundaries is demonstrated. Possible issues in the use of the method are discussed and guidance for good application is given.

Computational Fluid Dynamics (CFD) is utilized to study entropy generation for the rarefied steady state laminar 2-D flow of air-Al2O3 nanofluid in square cavity equipped with two solid fins at the hot wall. Such flows are of great importance in industrial applications, such cooling of the electronic equipment’s and nuclear reactors. In the current study, effects of Knudsen number (Kn), Rayleigh number (Ra) and the nano solid particles volume fraction (ϕ) on the entropy generation are investigated. The values of parameters considered in this work are as follows: 0≤Kn≤0.1, 〖10〗^3≤Ra≤〖10〗^6,0≤ϕ≤0.2. Length of the fins (LF) is considered to be fixed and equals to 0.5 m, whereas the location of the fins with respect to the lower wall (HF) is set to 0.25 and 0.75 m. Simulations demonstrate that there is an inverse direct effect of Kn on the entropy generation. Moreover, it is found that when Ra is less than 104, the entropy generation, due to the flow, increases as ϕ increases. In addition, the entropy generation due to the flow will decrease at Ra greater than 104 as ϕ increases. Moreover, the entropy generation due to heat will increase as both the ϕ and Ra increase. In addition, a correlation model of the total entropy generation as a function of all of the investigated parameters in this study is proposed. Finally, an optimization technique is adapted to find out the conditions at which the total entropy generation is minimized

The prototype misfit layer compound (SnS)1.17NbS2 consists of alternatively a metallic triatomic NbS2 layer in which Nb atoms are sandwiched by S atoms and an insulating SnS double-layer of NaCl-type structure. Here we investigate the effect of lattice misfit on the stability and chemical bonding in the misfit layer compound using a first-principles density-functional theory approach. The calculations show that for the (SnS)1+xNbS2 approximants, the most stable one has x = 0.167, close to the experimental observations. Charge analysis finds a moderate charge transfer from the SnS to NbS2. Sn or S vacancies in the SnS part affect the electronic properties and interlayer interactions. The obtained information here helps understand the mechanism of formation and stability of the misfit layer compounds and ferecrystals, and further to design of novel multilayer compounds and emerging van der Waals heterostructures.

Significant changes to the new National College Entrance Examination (NCEE) and the implementation of the “Double First-Class” (DFC) initiative in China are coincidentally in the national spotlight and fall within the same policy window. However, few studies have investigated the effects of the new NCEE on the quality of students in DFC universities. By leveraging the 2018-2022 college admission data from Shandong Province, these effects are examined via the interrupted time-series technique. Weighted rankings for liberal arts and science disciplines and the admission ranking coefficient are adopted to ensure comparability before and after the reform. The findings reveal that after the reform, the quality of students in both world-class universities and first-class discipline universities improved, with greater improvements seen in world-class universities. Focusing on urban differences, the quality of students in DFC universities located in second-tier cities is found to have experienced a higher increase as compared with students in the first-tier and new first-tier cities. In addition, the reform has had different impacts on the quality of students in different majors. Furthermore, when selecting postsecondary institutions, high-scoring students prioritize the quality of universities and majors over urban factors. Finally, the implications of the new NCEE in relation to a sustainable development of DFC universities for research, policy, and practice are further discussed.

In Spain, the National Health System, of a public nature, provides care to Spaniards and other residents in Spain. It is a system adapted to the State of Autonomies, decentralized. Each Auton-omous Community has legislative capacity in its organization and management. We studied the agreement of private hospitals by the public system in La Rioja, an Autonomous Community of Spain located in the North of the Iberian Peninsula. Documentary sources from the General archives of La Rioja, the Institute of Riojan Studies, municipal funds (Logroño, Haro, Calahorra), and in-formation from catalogs and censuses of hospitals from the Ministry of Health, National Institute of Statistics, and Institute of Statistics of La Rioja have been reviewed. The hospital model of La Rioja is characterized by a predominance of public beds over private ones, although there is a growing trend in the number of private beds from 2013 onwards, due to the incorporation of two conva-lescent socio-health hospitals. A characteristic element of La Rioja has been the promotion of pub-lic-private collaboration, conceived as a strategic alliance. Regarding agreements, in La Rioja there has been a specialization in the socio-health space, whose formulas have been the management service contract and the concession of work. The development of the Health System in La Rioja, 1986-2019, has been determined by the presence of a mixed public-private hospital system and a progressively lower dependence on specialized hospitals from other Autonomous Communities.

In this study, we evaluated the antibacterial effect against Staphylococcus aureus and Salmonella Typhimurium in fried fish paste using floating electrode-dielectric barrier discharge (FE-DBD) plasma (1.1 kV, 43 kHz, N2 1.5 m/s, 1-60 min). In addition, quality evaluation (pH, VBN) of fried fish paste was conducted after FE-DBD plasma treatment. When FE-DBD plasma was treated for 1, 5, 10, 20, 30 and 60 min, S. aureus decreased by 0.16-1.13 log10 CFU/g, and S. Typhimurium decreased 0.25-1.13 log10 CFU/g. Both decreased &gt; log10 CFU/g at 60 min. The D-value was 58.92 and R2 was 0.97 for S. aureus using first-order kinetics, and the D-value was 43.60 and R2 was 0.97 for S. Typhimurium using the Weibull model. There was no significant difference in pH after FE-DBD plasma treatment (p &gt; 0.05). However, volatile basic nitrogen (VBN) significantly decreased as the treatment time increased (p &lt; 0.05), and it was the lowest at 60 min to 3.46. Therefore, FE-DBD plasma treatment could be considered as a technology for preserving the quality of processed foods.

Abstract: Placenta accreta spectrum (PAS) is a severe complication of pregnancy associated with excessive invasion of cytotrophoblast cells at the sites of the endometrial-myometrial interface and the myometrium itself in cases of adherent (creta) and invasive (increta and percreta) forms, respectively. Despite advancements in ultrasound protocols and found associations of alpha-fetoprotein, PAPP-A, hCG, PLGF, sFlt-1, IL-8, and IL-33 peripheral blood levels with PAS, the condition remains undiagnosed before delivery because of the lacking clear evaluation criteria for each of the three grades of PAS. This leads to a high risk of massive blood loss, maternal hysterectomy, and preterm birth. While using deep sequencing, miRNA signatures of placental tissue, myometrium, and blood plasma from women with PAS in the third trimester of pregnancy, as well as miRNA profile in exosomes from the blood serum of women in the first trimester with physiologically progressing pregnancy, complicated by PAS or preeclampsia, were obtained. Two logistic regression models were constructed, both featuring statistically significant parameters related to the levels of miR-26a-5p, miR-17-5p, and miR-101-3p quantified by real-time PCR in native blood serum. These models demonstrated 100% sensitivity in detecting PAS during the first pregnancy screening. These miRNAs were identified as specific markers for PAS, showing significant differences in their blood serum levels during the first trimester in the PAS group compared to those in physiological pregnancies, early- or late-onset preeclampsia groups. Furthermore, these miRNAs exhibited differential expression in the PAS placenta and/or myometrium in the third trimester and, according to literature data, control angiogenesis. Significant correlations were found between extracellular hsa-miR-101-3p and nuchal translucency thickness, hsa-miR-17-5p and uterine artery pulsatility index, and hsa-miR-26a-5p and hsa-miR-17-5p with PLGF. The developed test system for early non-invasive PAS diagnosis based on the blood serum level of extracellular miR-26a-5p, miR-17-5p, and miR-101-3p can serve as an auxiliary method for 1st trimester screening pregnant women, subject to validation on independent test samples.

By making periodic thru-holes in a suspended film, the phonon system can be modified. Motivated by the BCS theory, the technique -- so-called phonon engineering -- was applied to a metallic niobium sheet. It was found that its electrical resistance dropped to zero at 175 K, and the zero-resistance state persisted up to 290 K in the subsequent warming process. Despite the initial motivation, neither these high transition temperatures nor the phase transition with thermal hysteresis can be accounted for by the BCS theory. Therefore, we abandon the BCS theory. Instead, it turns out that the metallic holey sheet is partly oxidized to form a niobium-oxygen square lattice, which has points of resemblance to a copper-oxygen plane, the fundamental component of cuprate high-T_c superconductors. Therefore, the pairing mechanism underlying this study should be related to that of cuprate high-T_c superconductors, which we may not yet understand. In addition to the electrical results of zero resistance, the holey sheet exhibited a decrease in magnetization upon cooling, i.e., the Meissner effect. Moreover, the remnant magnetization was clearly detected at 300 K, which can only be attributed to persistent currents flowing in a superconducting sample. Thus, this study meets the established criteria for a conclusive demonstration of true superconductivity. Finally, the superconducting transition with the unambiguous thermal hysteresis is discussed. According to Halperin, Lubensky, and Ma, or HLM for short, any superconducting transition must always be first order with thermal hysteresis because of the intrinsic fluctuating magnetic field. The HLM theory is very compatible with the highly oriented system harboring two-dimensional superconductivity.

Aim: Aging is companied by deteriorations of insulin resistance (IR) and insulin secretion. However, little is known about the roles of aging on different phases of insulin secretion (ISEC); i.e., the first- and second-phase of insulin secretion (FPIS, SPIS) and glucose effectiveness (GE). Methods: Totally 169 individuals (43 men and 126 women) with the similar fasting plasma glucose (FPG: 90 mg/dL) and BMI (men: 23 kg/m2, women 22 kg/m2) were enrolled. IR, FPIS, SPIS, and GE were estimated using our previously developed equations shown below. Pearson correlation analysis was conducted to assess the correlations between age and four diabetes factors (DFs: IR, FPIS, SPIS and GE). The equations that are used to calculate the DF in the present study were built and published by our group. Results: The age of the participants ranged from 18- to 78-year-old. Men had higher FPIS but lower HDL-C levels than women (2.067±0.159, 1.950±0.186 μU/min and 1.130±0.306, 1.348±0.357 mmol/dl, accordingly). The results of Pearson correlation revealed that age was negatively related to IR and GE in both genders (IR: r = -0.39, p < 0.001 for men, r = -0.24, p < 0.003 for women; GE: r = 0.66, p < 0.001 for men, r = 0.78, p < 0.001 for women). In the meanwhile, FPIS was also only found to be negatively correlated with age in female (r = -0.238, p = 0.003). But there was no different with SPIS and age in both of genders. Conclusions: We have found that in Chinese with normal FPG level (90 mg/dl) and body mass index (men: 23 kg/m2, women: 22: kg/m2), age is negatively related to IR and GE in both genders. At the same time, only FPIS was found to be negatively related to age in women. The tightness of their relationships, from the highest to the lowest are, GE, FPIS and IR accordingly. The importance of GE should be re-evaluated. These results should be interpreted with caution because of the small sample size.

Should our planet be visited by an extraterrestrial civilization, the prevailing assumption would undoubtedly be that the extraterrestrial civilization is Type I i.e. its capacity for interstellar travel results from its technological development. This assumption is dangerous for it unnecessarily leads to the Extraterrestrial Tandem Hypothesis (ETH): the belief than an extraterrestrial civilization technologically capable of interstellar travel must also be technologically compatible with the inexorably rapid annihilation of life on Earth. Such a state of things would compromise the planet’s capacity to stage a confident defense should the extraterrestrials prove belligerent. The presumption of Type I extraterrestrials (on the premise of the capacity for interstellar travel alone) is unfounded as extraterrestrials may be Type II i.e. capable of interstellar travel by virtue of natural intrinsic or extrinsic factors. This paper advances, most importantly, that the fundamental policy of first contact should be the employment of various strategies toward the evaluation of the technological capacity of visiting extraterrestrials. This evaluation must be particularly devoted to the detection of Type II extraterrestrials masquerading as Type I (using concealment and Wizard of Oz strategies). Integral to this detection are the concepts of the precedence relation and The Extraterrestrial Exclusion Principle (EEP). A precedence relation is a qualitative relation expressing the relative difficulty of producing a technological action. The Extraterrestrial Exclusion Principle states that a Type I extraterrestrial life form is excluded from certain actions. Such actions are lower in precedence than interstellar travel and may be described as in violation of the EEP or EEP forbidden. EEP actions reveal extraterrestrials to be Type II. As an example, the value of the Hawking Warning is subjected to EEP analysis. Furthermore, a hypothetical conundrum in linguistics termed the Kryptonian Linguistic Paradox (KLP) is discussed as a case of an EEP forbidden act. Finally, the paper explores the limitations of the stated fundamental policy of first contact.

Introduction. A needle is inserted into a joint for arthrocentesis or injection of a therapeutic medication(s), commonly a corticosteroid. The aim of this paper is to discuss the first theme identified from a scoping review of corticosteroid injections for the pathology of the first metatarsophalangeal joint. Pathology. The two most common pathologies affecting the first metatarsophalangeal joint are osteoarthritis and bunions. An arthritic joint is regularly injected with a corticosteroid, but bunions are not. Other pathologies that may receive an injection include rheumatoid arthritis, gout, sesamoiditis and post-operative arthrofibrosis. Discussion. Most available evidence discusses corticosteroid injections for osteoarthritis, but there is a paucity of high-quality evidence, especially for corticosteroid use in other pathological conditions. Conclusion. Whilst the evidence base suggests that corticosteroid injections are safe short- and mid-term treatment options for a range of soft tissue and joint pathology, the specific indications, and short/long-term outcomes in the first metatarsophalangeal joint pathologies are not clear and warrant further study.

In this chapter we study the unstudy effect on MHD preamble porous medium through with thermal absorption and heat generation in the oscillatory flow of visco-elastic fluid between two plates in the presence of Chemical reaction. The expressions for the velocity, temperature and concentration distributions are arthemitiaclly solved by perturbation method.

The present work provides an updated overview of the application of the Oxford Nanopore^® MinION^™ sequencer in cultural heritage biodeterioration studies, while also providing a holistic discussion of possible future perspectives for their utilization in this research field. Due to the peculiar characteristics of this device, the last few years have seen the steady rise on the application of this system in a variety of cultural heritage materials, having been useful to understand microbial biodeteriogens diversity and some of their metabolic and biodeteriogenic features. Considering the immense potential for application of this system, this manuscript discusses further possibilities of the technique aiming to help understand critical questions on the cultural heritage biodeterioration area. Its application in various differential contexts, has opened the doors for their putative usage on other interesting sub-areas of research worthy of future investigations, including: biodeteriogens genome and transcriptome analysis, metatranscriptomics, biodeteriorative metabolism studies, inter and intra kingdom interactions analysis, resistome profiling, object history and context studies, in situ applications, bioprospecting and biotechnology.

Large Language Models (LLMs) have demonstrated promising capabilities to solve complex tasks in critical sectors such as healthcare. However, LLMs are limited by their training data which is often outdated, the tendency to generate inaccurate ("hallucinated") content and a lack of transparency in the content they generate. To address these limitations, retrieval augmented generation (RAG) grounds the responses of LLMs by exposing them to external knowledge sources. However, in the healthcare domain there is currently a lack of systematic understanding of which datasets, RAG methodologies and evaluation frameworks are available. This review aims to bridge this gap by assessing RAG-based approaches employed by LLMs in healthcare, focusing on the different steps of retrieval, augmentation and generation. Additionally, we identify the limitations, strengths and gaps in the existing literature. Our synthesis shows that proprietary models such as GPT-3.5/4 are the most used for RAG applications in healthcare. Also, there is a lack of standardized evaluation frameworks for RAG-based applications. In addition, the majority of the studies do not assess or address ethical considerations related to RAG in healthcare. It is important to account for ethical challenges that are inherent when AI systems are implemented in the clinical setting. Lastly, we highlight the need for further research and development to ensure responsible and effective adoption of RAG in the medical domain.

This paper provides an exhaustive narrative review of third-generation antipsychotics (TGAs), focusing on aripiprazole, cariprazine, brexpiprazole, and lurasidone for managing substance-induced psychosis. It includes a comprehensive literature review to evaluate the efficacy and tolerability of these medications. The paper emphasizes the distinct challenges in treating substance-induced psychosis, which is a psychiatric condition triggered by the misuse or withdrawal of various substances, leading to symptoms like hallucinations and delusions, and is distinct from primary psychotic disorders. It underscores the potential of TGAs in addressing both psychotic symptoms and substance-related issues, while highlighting the need for more research on long-term effects and advocating for an integrated approach combining pharmacological and psychological interventions