Various symptoms have been reported to persist beyond acute phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which is referred as long coronavirus disease 19 (long COVID-19). Over 65 million individuals suffer from long COVID-19. However, the causes of long COVID-19 have been largely unknown. Since long COVID-19 symptoms are observed throughout the body, vascular endothelial dysfunction may be a strong candidate to induce long COVID-19. The angioten-sin-converting enzyme 2 (ACE2), the entry receptor of SARS-CoV-2, is ubiquitously expressed in endothelial cells. We previously found that the risk factors for athero-sclerotic cardiovascular disease (ASCVD) and the history of ASCVD can be the risk for severe COVID-19, suggesting a contribution of pre-existing endothelial dysfunction to severe COVID-19. Here, we show a significant association of endothelial dysfunction with development of long COVID-19 and show that biomarkers for endothelial dysfunction in patients with long COVID-19 are also crucial players in development of ASCVD. We consider the influence of long COVID-19 on development of chronic kidney disease (CKD) and ASCVD. Furthermore, we suggest the therapeutic interventions for long COVID-19 by considering endothelial dysfunction as the treatment tar-gets for long COVID-19. Such interventions may prevent pandemic of CKD and ASCVD in post COVID-19 era.

Long COVID, a name often given to the persistent symptoms following acute SARS-CoV-2 infection, poses a multifaceted challenge for health. This review explores the intrinsic relationship between comorbidities and autoimmune responses in shaping the trajectory of long COVID. Autoantibodies have emerged as significant players in COVID-19 pathophysiology, with implications for disease severity and progression. Studies show immune dysregulation persisting months after infection, marked by activated innate immune cells and high cytokine levels. The presence of autoantibodies against various autoantigens suggests their potential as comorbid factors in long COVID. Additionally, the formation of immune complexes may lead to severe disease progression, highlighting the urgency for early detection and intervention. Furthermore, long COVID is highly linked to cardiovascular complications and neurological symptoms, posing challenges in diagnosis and management. Multidisciplinary approaches, including vaccination, tailored rehabilitation, and pharmacological interventions, are used for mitigating long COVID's burden. However, numerous challenges persist, from evolving diagnostic criteria to addressing the psychosocial impact and predicting disease outcomes. Leveraging AI-based applications holds promise in enhancing patient management and improving our understanding of long COVID. As research continues to unfold, unravelling the complexities of long COVID remains paramount for effective intervention and patient care.

The intricate mechanisms of the immune response elicited by vaccines and the interplay between the immune system and the central nervous system (CNS) are poorly understood. This review explores these mechanisms, emphasizing the interplay between the immune system and the central nervous system (CNS). A critical aspect is the examination of how vaccine-induced immune responses can interact with the CNS, influencing neuroinflammation and neuroimmune interactions. Furthermore, the link between vaccination and persistent symptoms observed in long-COVID patients is discussed. Vaccination initiates a complex cascade of events, starting with the production of specific proteins, such as S1/S2 spike proteins, leading to robust immune activation in the axillary lymph nodes. The role of macrophages and antigen-presenting cells (APCs) in cytokine production, antigen presentation, and the stimulation of B and T cells highlights the sophistication of the adaptive immune response. The migration of immune cell-derived exosomes to the brain plays a dynamic role in CNS inflammation, neurodegenerative processes and long COVID. On the other hand, the prolonged presence of viral and vaccine-derived spike proteins may contribute to the complex pathophysiology of Long-COVID, shedding light on the delicate balance between beneficial immune responses and possible adverse neurological outcomes of vaccination. It is worth rigorous monitoring and further research to understand the mechanisms of neuroinflammation and the persistence of spike proteins and their long-term effects on the brain, emphasising the importance of a nuanced approach to vaccine safety and efficacy in the context of COVID-19 and beyond.Principio del formulario

Long-lasting insecticidal nets (LLINs) have been the main contributor to the reduction of malaria in the past two decades in sub-Saharan Africa. Development of pyrethroid insecticide resistance threatens the effectiveness of these LLINs, especially when nets become holed and the insecticide decays. Three classes of dual active ingredient (AI) LLINs, have been assessed for their physical durability as follows: 1) Royal Guard®, combining pyriproxyfen, which is known to disrupt female reproduction and fertility of eggs, and a pyrethroid alpha-cypermethrin; 2) Interceptor® G2, two adulticides with differing modes of action; chlorfenapyr and alpha-cypermethrin; 3) OlysetTM Plus incorporates permethrin (pyrethroid) and a synergist, piperonyl butoxide, to enhance the potency of pyrethroid insecticides; all nets were compared to standard pyrethroid only net (Interceptor®). About 40,000 nets of each type were distributed in February 2019 to different villages in Misungwi. A total of 3072 LLINs were followed at 6, 12, 24, 30 and 36 months to assess survivorship and fabric integrity in a community setting. The median functional survival were less than three years with Interceptor®, Interceptor® G2 and Royal Guard® having 1.9 year each and 0.9 years for OlysetTM Plus . After 36 months, 90% of OlysetTM Plus and Royal Guard® and 87% of Interceptor® G2 were no longer present (thrown away) in the households due to wear and tear, compared to 79% for standard Interceptor®. Short life spans of all assessed LLINs were driven by material of the net, rather than social economic status and housing material. All dual AI LLINs have a poor textile durability with OlysetTM Plus being the worst of the three.

Despite the fact that SMA restrainers exhibit a superelastic strain capacity of 7%, this capacity appears inadequate for isolated bridges due to the typically greater than 20cm relative dis-placements between girders during intense seismic events. In order to perform such a stroke, a SMA restrainer of greater than 3 metres in length might be required. In order to reduce the length of restrainers, a novel honeycomb damper constructed from superelastic shape memory alloy (SMA) is proposed. The proposed device, denoted as the superelastic SMA honeycomb damper (SHD), is comprised of steel plates to prevent the SMA plane from collapsing and superelastic SMA honeycomb to provide self-centering capability. By incorporating the large strain capacity of SMA and the geometrically nonlinear deformation of honeycomb structures, SHD has been developed to satisfy the requirements of bridge restrainers with large strokes. It is capable of functioning as a restrainer and energy dissipation device when subjected to dynamic tension and compression loads. The SHD was initially investigated from a theoretical perspective. Following this, a mul-ti-cell SHD specimen was manufactured. The specimen underwent axial tensile and compressive experiments in order to examine the mechanical properties of SHDs. Finally, experimental results were investigated through numerical simulation analyses of the SHDs using a three-dimensional high-fidelity finite element model. Additionally, a method for enhancing SHD was proposed. The findings indicate that SHD is capable of exhibiting superior self-centering capability and sta-ble hysteretic responses when subjected to earthquakes.

Most natural language processing (NLP) tasks operate an input sentence as a sequence with token-level embeddings and features, despite its clausal structures. Taking Abstract Meaning Representation (AMR) parsing as an example, recent parsers are empowered by Transformers and pre-trained language models, but long-distance dependencies (LDDs) introduced by long sequences are still open problems. We argue that LDDs are not superficially blamed on the sequence length but are essentially related to the internal clause hierarchy. Typically, non-verb words in a clause cannot depend on words outside, and verbs from different but related clauses have much longer dependencies than those in the same clause. With this intuition, we introduce a type of clausal feature, hierarchical clause annotation (HCA), into AMR parsing and propose two HCA-based approaches, HCA-based self-attention (HCA-SA) and HCA-based curriculum learning (HCA-CL), to integrate HCA trees of complex sentences for addressing LDDs. We conduct extensive experiments on two in-distribution (ID) AMR datasets (AMR 2.0 and AMR 3.0) and three out-of-distribution (OOD) ones (TLP, New3, and Bio). Experimental results show that our HCA-based approaches achieve significant and explainable improvements against the baseline model and outperform the state-of-the-art (SOTA) model when encountering sentences with complex clausal structures that introduce most LDD cases.

Coastal areas are influenced by natural coastal hazards such as hurricanes, storm surges and tsunamis. For centuries coastal structures such as seawalls, detached breakwaters, groins, and revetments have been constructed to protect coastal properties. However, their effectiveness diminishes with time, and they are not adaptable to changing coastal conditions. Ecosystem-based approaches offer protection against erosion and the creation or restoration of coastal habitats. However, the protection properties and the sustainability provided by these systems are not well understood. Salt marshes have been known as one of the ecosystem-based protection systems. They protect coasts and lands by dissipating energy, stabilizing sediments and producing organic matter through blow ground production. Stems of plants dissipate waves propagating over salt marsh and plant roots stabilize soils and sediments. The dissipation rate varies with wave frequency; the low-frequency swell wave is dissipated less on the edge of the marsh than wind-sea waves. Salt and wetlands can also be used for reducing coastal flooding and storm surges, but a wetland is required to successfully attenuate storm surges. A salt marsh can be resilient to sea-level rise in certain conditions. Large sediment supply and gentle upland slope increase salt marsh resiliency to relative sea-level rise. Connecticut marshes, like other marshes in the world, are vulnerable to anthropogenic and climate change effects. However, an assessment of current sea level rise and average marsh accretion rates in Connecticut demonstrates sea level rise is not the main vulnerable factor for salt marshes loss. The study on the feasibility of developing an ecosystem based on two coastlines in Connecticut, Guilford and Stratford, shows that both coastlines, like other coastlines in Connecticut, have limited wave energy, which is a positive factor for marsh growth. The available data assessment represents that sediment supply is the most important parameter to guarantee the resilience and sustainability of a newly developed salt marsh system in Connecticut. In Stratford, conditions for establishing a new ecosystem seem to be better, as the fetch length is pretty small, and there is some sediment supply for the ecosystem. In Guilford, wave energy is limited, but it is more than in Stratford case. In addition, sediment availability is low and the coastline experienced a large erosion during Hurricane Sandy and has not recovered yet.

The treatment of insulin-dependent diabetes mellitus is characterized by artificial supplementation of pancreatic β-cell ability to regulate sugar levels in the blood. Even though various insulin analogs are crucial for reasonable glycemic control, understanding the dynamic mechanism of the insulin analogs may help to improve the best-protracted insulin analog to assist people with Type 1 Diabetes (T1D) to live comfortably while maintaining tight glycemic control. Here we present the high-resolution crystal structure of NN304, known as insulin detemir, to 1.7 A resolution at cryogenic temperature. We computationally further investigated our crystal structure's monomeric-dimeric conformation and dynamic profile by comparing it with a previously available detemir structure (PDB ID: 1XDA). Our structure (PDB ID: 8HGZ) obtained at elevated pH provides a distinct alternative dimeric conformation compared to the previous structure, suggesting it might induce an intermediate state in the dissociation pathway of the insulin detemir’s hexamer:dihexamer equilibrium. Combined with orientational cross-correlation analysis by Gaussian Network Model (GNM), this alternate oligomeric conformation offers the distinct cooperative motions of a protracted insulin analog that has not been previously observed.

The rapid penetration of social media has been redefining every facet of the old marketing and customer engagement tactics, not only for the low-end and mass products but also for luxury brands. In this context, brands are dealing with the challenge of keeping the balance between using mass marketing strategies concurrent with accentuating the exclusivity of their offerings. Social media can be considered a boon if brands employ them to reach the right audience and use the right platform by incorporating the right content. In this work, we propose a sector-specific, integrated, and holistic investigation of the social media strategies of luxury brands, together with the impact they generate in terms of the engagement level of the users as an indicator of their success. We provide empirical validation of the method in the sector of luxury fashion brands in the Italian market, providing qualitative and quantitative analysis of the content shared on social media, considering the type, timing, and modality of the sharing. We evaluate consumer-brand engagement in different contexts, including important live events in the field.

Autonomic dysfunction is an increasingly recognised complication in chronic neurological conditions such as Parkinson’s disease , and other medical conditions, including diabetes mellitus, chronic fatigue syndrome, postural tachycardia syndrome with and without Ehlers-Danlos syndrome, fibromyalgia and recently Long Covid. Despite laboratory-based tests to evaluate normal and abnormal autonomic function, there are no home-based tests to record neuro-cardiovascular autonomic responses to common stimuli in daily life that are dependent on the normal functioning of the autonomic nervous system. We have developed an adapted blood pressure/heart Autonomic Profile (aAP) that can be used by an individual independently and repeatedly in a domiciliary setting to determine the physiological and symptomatic response to standing, food, and physical and mental (cognitive, emotional) activities. The aAP aids separating autonomic failure (often irreversible) from autonomic dysfunction. This helps the individual and attending healthcare professional understand the relationship between symptoms and common triggers in daily life and informs on self-management in debilitating conditions such as the postural tachycardia syndrome (PoTS) and Long Covid.

Long-haul COVID-19 illness first gained widespread recognition among social support groups and later in scientific and medical communities. This illness is mysterious as it affects COVID-19 survivors at all levels of disease severity, even younger adults and children. While the precise definition may be lacking, the defining symptoms are fatigue, dyspnea, and headache that last for months after hospital discharge. The less typical symptoms may include cognitive impairments, chest and joint pains, myalgia, smell and taste dysfunctions, cough, mood changes, and gastrointestinal and cardiac issues. Presently, there is limited literature discussing the possible pathophysiology, risk factors, and treatments in long-haul COVID-19, which the current review aims to address. In brief, long-haul COVID-19 may be driven by long-term lung and brain damage and unresolved inflammation from multiple sources. The associated risk factors may include female sex, more than five early symptoms, early dyspnea, and specific biomarkers like D-dimer. While only rehabilitation training has been useful for long-haul COVID-19, therapeutics repurposed from mast cell activation syndrome, myalgic encephalomyelitis/chronic fatigue syndrome, and pulmonary fibrosis also hold potential. In sum, this review hopes to provide the current understanding of what is known about long-haul COVID-19.

A small phylogenetically conserved sequence of 11,231 bp termed FAM247 is repeated in human chromosome 22 by segmental duplications. This sequence forms part of diverse genes that span evolutionary time, the protein genes being the earliest as they are present in zebrafish and/or mice genomes, the long non-coding RNA genes and pseudogenes the most recent as they appear to be present only in the human genome. We propose that the conserved sequence provides a nucleation site for new gene development at evolutionary conserved chromosomal loci where the FAM247 sequences reside. The FAM247 sequence also carries information in its open reading frames that provides protein exon amino acid sequences; one exon plays an integral role in immune system regulation, specifically, the function of ubiquitin specific protease (USP18) in the regulation of interferon. An analysis of this multifaceted sequence and the genesis of genes that contain it are presented.

The cytokinins play important roles in plant growth and development by regulating gene expression at genome wide level. DNA methylation is responsive to the external environment, but whether DNA methylation changes in response to cytokinin treatment to regulate gene expression is still unclear. Here, we used bisulfite sequencing and RNA sequencing to examine genome-wide DNA methylation and gene expression patterns in poplar (Populus tomentosa) after treatment with the synthetic cytokinin 6-benzylaminopurine (6-BA). We identified 566 significantly differentially methylated regions (DMRs) in response to 6-BA treatment. Transcriptome analysis showed that 501 protein-coding genes, 262 long non-coding RNAs, and 15,793 24-nt small interfering RNAs were differentially expressed under 6-BA treatment. Among these, 79% were differentially expressed between alleles in P. tomentosa. Combined DNA methylation and gene expression analysis demonstrated that DNA methylation plays an important role in regulating allele-specific gene expression. To further investigate the relationship between these 6-BA-responsive genes and phenotypic variation, we performed SNP analysis of 507 6-BA-responsive DMRs via re-sequencing using a natural population of P. tomentosa and identified 206 SNPs that were significantly associated with growth and wood properties. Association analysis indicated that 53% of loci with allele-specific expression had primarily dominant effects on poplar traits. Our comprehensive analyses of P. tomentosa DNA methylation and the regulation of allele-specific gene expression suggest that DNA methylation is an important regulator of imbalanced expression between allelic loci.

The NA61/SHINE experiment studies hadron production in hadron-hadron, hadron-nucleus and nucleus-nucleus collisions. The physics programme includes the study of the onset of deconfinement and search for the critical point as well as reference measurements for neutrino and cosmic ray experiments. For strong interactions, future plans are to extend the programme of study of the onset of deconfinement by measurements of open-charm and possibly other short-lived, exotic particle production in nucleus-nucleus collisions. This new programme is planned to start after 2020 and requires upgrades to the present NA61/SHINE detector setup. Besides the construction of a large acceptance silicon detector, a 10-fold increase of the event recording rate is foreseen, which will necessitate a general upgrade of most detectors.

Clupeiformes, such as sardines and herrings, represent an important share of worldwide fisheries. Among those, the European sardine (Sardina pilchardus, Walbaum 1792) exhibits significant commercial relevance. While the last decade showed a steady and sharp decline in capture levels, recent advances in culture husbandry represent promising research avenues. Yet, the complete absence of genomic resources from sardine imposes a severe bottleneck to understand its physiological and ecological requirements. We generated 69 Gbp of paired-end reads using Illumina HiSeq X Ten and assembled a draft genome assembly with an N50 scaffold length of 25579 bp and BUSCO completeness of 82.1% (Actinopterygii). The estimated size of the genome ranges between 655 and 850 Mb. Additionally, we generated a relatively high-level liver transcriptome. To deliver a proof of principle of the value of this dataset, we established the presence and function of enzymes (elovl2, elovl5 and fads2) that have pivotal roles in the biosynthesis of long chain polyunsaturated fatty acids, essential nutrients particularly abundant in oily fish such as sardines. Our study provides the first omics dataset from a valuable economic marine teleost species, the European sardine, an essential resource for their effective conservation, management and sustainable exploitation.

Long COVID comprises persistent symptoms which extend beyond four weeks post-SARS-CoV-2 infection. The potential association between long COVID and the endorsement of COVID-19 conspiracy theories has not been explored, particularly in Arab countries where high endorsement of these theories has been reported. This study aimed to explore the association between endorsing COVID-19 conspiracy theories and the prevalence of self-reported long COVID symptoms among adults in Jordan and Kuwait in addition to other Arab countries. The study employed a cross-sectional design using an electronic self-administered survey in Arabic language. Recruitment utilized snowball sampling via social media and the survey was distributed in July 2024. The survey instrument included sections on demographic information, the history of COVID-19 infection, and vaccination status. Long COVID manifestations were assessed using a score reflecting the frequency and intensity of ten recognized long COVID symptoms with subsequent categorization into three categories: low, middle, and high. The beliefs in COVID-19 conspiracy theories were measured via a 5-point Likert scale across five items. The final study sample comprised 756 respondents, the majority of whom self-reported a history of confirmed COVID-19 diagnosis at least once (n = 493, 65.2%). The results indicated a neutral average attitude towards COVID-19 conspiracy theories (mean score = 15.18±4.64 out of 30.00). Participants with high conspiracy theories scores were significantly more likely to report high (aOR = 6.85, 95% CI: 2.90–16.13, p < 0.001) and middle long COVID symptoms (aOR = 2.82, 95% CI: 1.32–6.06, p = 0.008) compared to those with lower scores. Additional predictors of higher long COVID reporting included female sex and lower self-reported household income. Frequent COVID-19 infections and hospitalizations were also associated with higher long COVID symptom reporting. The study results revealed a significant correlation between the endorsement of COVID-19 conspiracy theories and the higher frequency and magnitude of long COVID symptom reporting. The findings also highlighted the influence of sociodemographic factors and COVID-19 infection history on long COVID reporting, which suggests that public health strategies should address these factors to mitigate long COVID challenges effectively.

The SARS-CoV-2 virus, responsible for the COVID-19 pandemic, has impacted the health of millions globally, with many individuals experiencing persistent symptoms even after testing negative, a condition known as Post-acute Sequelae of SARS-CoV-2 infection (PASC), or “Long COVID”. This study analyzes demographic influences on the severity and timeline of PASC symptoms, with emphasis on physiological and cognitive effects. Using a self-reporting survey method, data was collected from a sample of 110 participants (n=110) and analyzed using techniques such as Exploratory Factor Analysis (EFA), Pearson Correlation, and Two-Factor ANOVA Test. Based on the study, females generally reported higher severity for cognitive and physiological symptoms compared to males, and symptom severity was generally lower among vaccinated individuals. Correlation analysis revealed a significant relationship between depression and cognitive impairments, underscoring the psychological impact of PASC. This study emphasizes the complexity of PASC, demonstrating how demographic characteristics such as age, sex, and vaccination status influence the severity and duration of symptoms, contributing to the growing understanding of PASC. Further research should consider SARS-CoV-2 variant-specific impacts and broader population samples.

The rapid increase in unstructured data across various fields has made multi-document comprehension and summarization a critical task. Traditional approaches often fail to capture relevant context, maintain logical consistency, and extract essential information from lengthy documents. This paper explores the use of Long-context Large Language Models (LLMs) for multi-document summarization, demonstrating their exceptional capacity to grasp extensive connections, provide cohesive summaries, and adapt to various industry domains and integration with enterprise applications/systems. The paper discusses the workflow of multi-document summarization for effectively deploying long-context LLMs, supported by case studies in legal applications, enterprise functions such as HR, finance, and sourcing, as well as in the medical and news domains. These case studies show notable enhancements in both efficiency and accuracy. Technical obstacles, such as dataset diversity, model scalability, and ethical considerations like bias mitigation and factual accuracy, are carefully analyzed. Prospective research avenues are suggested to augment the functionalities and applications of long-context LLMs, establishing them as pivotal tools for transforming information processing across diverse sectors and enterprise applications.

The rapid expansion of flexible and wearable electronics has necessitated a focus on ensuring their safety and operational reliability. Gel Polymer Electrolytes (GPEs) have become preferred alternatives to traditional liquid electrolytes, offering enhanced safety features and adaptability to the design requirements of flexible lithium-ion batteries. This review provides a comprehensive and critical overview of recent advancements in GPEs technology, highlighting significant improvements in their physicochemical properties, which contribute to superior long-term cycling stability and high-rate capacity compared to traditional organic liquid electrolytes. Special attention is given to the development of smart GPEs endowed with advanced functionalities such as self-protection, thermotolerance, and self-healing properties, which further enhance battery safety and reliability. The review also critically examines the application of GPEs in high-energy cathode materials, including Lithium Nickel Cobalt Manganese (NCM), Lithium Nickel Cobalt Aluminum (NCA), and thermally stable Lithium Iron Phosphate (LiFePO4). Despite the advancements, several challenges in GPE development remain unresolved, such as improving ionic conductivity at low temperatures and ensuring mechanical integrity and interfacial compatibility. The review concludes by outlining future research directions and the remaining technical hurdles, providing valuable insights to guide ongoing and future efforts in the field of GPEs for lithium-ion batteries, with a particular emphasis on applications in high-energy and thermally stable cathodes.

Machine reading comprehension is a crucial area of research in natural language processing, aiming to enable machines to read and understand text as humans do, and to answer questions related to the text content. The pre-trained language model, represented by BERT, has achieved superior results compared to traditional models in many NLP tasks, leading to the rise of the pre-trained paradigm in the field of natural language processing. This paper addresses the issue that the pre-trained language model lacks the ability to extract long-distance semantic relations and make efficient use of linguistic features. Firstly, the recent developments of the pre-trained language model are described. Then, two feature maps are used to intuitively express the structured long-distance semantic correlation features, and the traditional sequence structure features are integrated. The influence of different feature map construction methods on machine reading comprehension is compared. Finally, the application of the pre-trained language model in machine reading comprehension is summarized and prospected. By fusing graph structure features, the model can learn more abundant language knowledge, thus further improving its reasoning ability.

Alpha emitters like plutonium pose severe health risks when ingested, damaging DNA and potentially causing cancer. Traditional detection methods require proximity within millimeters of the contamination source, presenting safety risks and operational inefficiencies. Long-range detection through alpha radioluminescence (RL) offers a promising alternative. However, most of the previous experiments have been carried out under controlled conditions that preclude the overwhelming effect of ambient light. This study demonstrates successful detection of a 3 MBq alpha emitter in an open environment using a newly developed, lightweight compact alpha camera. This camera incorporates a deep-cooled CCD and a specially designed lens system with a low f-number to maximum the signal intensity. The lens was also designed to minimize blue shift effects of filters. Nighttime imaging was achieved with a dual-filter system using a sandwich filters assembly centered at 337 nm and 343 nm for capturing alpha RL and subtracting background light, respectively. At night, the alpha source was detected from 1 meter away within one minute. The system was also evaluated under simulated urban lighting conditions. For daytime imaging, a stack of tilted 276 nm short pass filters minimized sunlight interference, enabling clear detection of the alpha source at 70 cm within 10 minutes under indirect sunlight. This research not only underscores the viability of long-range optical detection of alpha emitters for environmental monitoring and scientific research but also highlights its ability to enhance nuclear safety and public health in real-world settings.

Precision metagenomic approaches using Oxford Nanopore Technology (ONT) sequencing has been shown to allow recovery of complete genomes of Escherichia coli O157:H7 from overnight enrichments of agricultural waters. This study tests the applicability of a similar approach for Cronobacter genome recovery from powdered infant formula (PIF) overnight enrichments, where Cronobacter typically dominates the overall microbiome (>90%). In this study, we aimed to test whether using ONT sequencing of overnight PIF enrichments could recover a completely closed Cronobacter genome for further genomic characterization. Ten PIF samples, each inoculated with different Cronobacter strains, covering Cronobacter sakazakii, C. muytjensii, C. dublinensis, C. turicensis, and C. universalis, were processed according to the Bacteriological Analytical Manual (BAM) protocol. qPCR was used for initial screening (detection and quantification) of the overnight enrichments and confirmed that the spiked PIF samples after the overnight enrichment have high levels of Cronobacter (107 to 109 CFU/mL). DNA from overnight PIF enrichments was extracted from the enrichment broth and sequenced using ONT. Results showed that ONT sequencing could accurately identify, characterize, and close the genomes of Cronobacter strains from overnight PIF enrichments in 3 days, much faster than the nearly two weeks required by the current BAM method. Complete genome recovery and species differentiation were achieved. This suggests that combining qPCR with ONT sequencing provides a rapid, cost-effective alternative for detecting and characterizing Cronobacter in PIF, enabling timely corrective actions during outbreaks.

Earthquake-triggered landslides are one of the most significant hazards worldwide. These landslides, involving small or large volumes, can develop in debris flow or avalanche with high mobility and long-runout distance. The motion processes of this kind of landslide also quite complicated. This study reproduced the motion processes of two landslides using the LS-RAPID program. The Aso Bridge landslide occurred on April 16, 2016, with rapid and long-runout distance characteristics. The Kataragai landslide occurred on April 9, 2018, travelling with flow-like behavior. Through field investigations and laboratory experiments, features and mechanical parameters of these two landslides were obtained. In the LS-RAPID program, the pre-failure models and motion processes of these two landslides were established and reproduced. Results indicated that sliding speed and travelling morphology at different intervals were considered as two indicators to describe their motion process. However, while sliding speed of these two landslides have significant differences with sliding speeds of actual landslides, the final morphologies after failure were consistent with those observed in the field investigation.

Reconstructing the Tree of Life remains a central goal in biology. Early methods, relying on small numbers of morphological or genetic characters, often yielded conflicting evolutionary histories, undermining confidence in the results. Investigations based on phylogenomics, which use hundreds to thousands of loci for phylogenetic inquiry, have provided a clearer picture of life's history, but certain branches remain problematic. To resolve difficult nodes on the Tree of Life, two recent studies tested the utility of synteny, the conserved collinearity of orthologous genetic loci in two or more organisms, for phylogenetics. Synteny exhibits compelling phylogenomic potential while also raising new challenges. We identify and discuss specific opportunities and challenges that bear on the value of synteny data and other rare genomic changes for phylogenomic studies. Synteny-based analyses of highly contiguous genome assemblies mark a new chapter in the phylogenomic era and the quest to reconstruct the Tree of Life.

The coronavirus disease 2019 (COVID-19), instigated by the zoonotic Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), rapidly transformed from an outbreak in Wuhan, China, into a widespread global pandemic. A significant post-infection condition, known as ‘long- COVID’, emerges in a substantial subset of patients, manifesting with a constellation of over 200 reported symptoms that span multiple organ systems. This condition, also known as 'post-acute sequelae of SARS-CoV-2 infection' (PASC), presents a perplexing clinical picture with far-reaching implications, often persisting long after the acute phase. While initial research focused on the immediate pulmonary impact of the virus, the recognition of COVID-19 as a multiorgan disruptor has unveiled a gamut of protracted and severe health issues. This review provides a summary of the primary effects of long COVID on the cardiovascular, nervous, and respiratory systems. It also delves into the mechanisms underlying these impacts and underscores the critical need for a comprehensive understanding of long COVID's pathogenesis.

Introduction: Post-COVID-19 syndrome (PCS) is a multisystemic disorder marked by impaired physical performance as one lead symptom. Since it has been suggested that endurance training as part of medical rehabilitation may be effective to improve physical performance capacity in PCS, this study aimed to compare different modes of aerobic endurance training. Methods: Hundred-ten PCS patients (49.3±11.8 years, 38% women, time after infection=260.2±127.5 days) underwent detailed clinical screening including symptom-limited cardiopulmonary exercise testing at admission and after 4-6 weeks of inpatient medical rehabilitation. Questionnaires were used to assess disease perception. Patients performed controlled isocaloric cycle ergometer training (3-5 sessions/week, 18 min) as either continuous training (CT) at 50% of maximal workload or as interval training (IT, load=60%, relief=30%). Outcomes of PCS patients were compared to coronary artery disease patients (CAD, n=96) to evaluate overall training effectiveness. Results: Training participation was comparable between both groups with no indication of training-specific exercise-induced fatigue. Overall, PCS patients improved significantly by a mean of 6.8±12.1% for W at VT1, 3.1±10.0% for VO2 at VT1, 5.5±14.7% for O2-pulse at VT1, 7.5±15.0% for W at VO2peak, 2.7±11.0% for VO2peak and 4.6±12.4% for O2-pulse at VO2peak (all p<0.05) with no significant differences between groups (p>0.05). Both groups showed reduced levels of fatigue, anxiety and depression as well as improved quality of life and wellbeing (all p<0.05). Compared to guideline-based cardiac rehabilitation, PCS patients showed a similar improvement in workload and oxygen uptake compared to CAD patients. Conclusion: PCS patients benefit from aerobic endurance training, performed as moderate continuous or interval training as part of a medical rehabilitation program in terms of improved physical exercise capacity and disease perception. Results for PCS patients are comparable to guideline-based rehabilitation of CAD patients. Clinical Trial: NCT06016192

In this study, we resequenced the mitogenomes of P. megacephalus from different regions using a “primer bridging” approach with Sanger sequencing technologies. The mitogenome of this species was found to contain two copies of the ND5 genes and three copies of the control regions. Furthermore, multiple tandem repeats were identified in the control regions. Notably, we observed that there was no correlation between the distribution of species and their genetic distance. However, our research revealed the discovery of the “missing” ATP8 gene in P. megacephalus as well as three other previously published Polypedates, as a result of manual data curation. Using the mitogenome, gene expression analysis was performed via RT-qPCR of liver samples and determined that COIII, ND2, ND4, and ND6 were reduced to 0.64±0.24, 0.55±0.34, 0.44±0.21 and 0.65±0.17 under the low-temperature stress (8℃), respectively, as compared with controls (P<0.05). Remarkably, the transcript of long non-coding RNA (LncRNA) between positions 8029 and 8612 decreased significantly with exposure to low-temperature stress (8℃). Antisense ND6 gene expression showed a downward trend but this was not significant. These results reveal that modulations of protein-coding mitogenomes genes and lncRNAs of P. megacephalus play a crucial part in the molecular response to cold stress.

The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines unable to halt transmission it is important to continue our quest for safe, effective, affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of 7,817 approved drugs, 214 candidates were systematically down-selected using a combination of 11 filters including approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These drugs were subjected in this study to virtual screening against various targets of SARS-CoV-2 followed by molecular dynamic studies of the best scoring ligands against each target. The chosen molecular targets were Spike receptor binding domain, Nucleocapsid protein RNA binding domain, and key non-structural proteins 3, 5, 12, 13 and 14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in silicostudies to warrant further in vitro and in vivo investigations as appropriate to ascertain their extent of anti-viral activities.

The preparation of sulfur-single walled carbon nanohorns active material via a simple and sustainable evaporation method for application as cathode in lithium-sulfur batteries is reported. We show that the synthesis process enables the infiltration of elemental sulfur within the carbon nanohorns thus obtaining a morphology responsible for the ameliorating of the shuttle effect. The sulfur-carbon composite is characterized in terms of structure, morphology, and composition through x-ray diffraction, transmission electron microscopy, and thermogravimetric analyses. From the electrochemical point of view, cyclic voltammetry, rate capability, and galvanostatic cycling tests are performed employing a solution of bis(trifluoromethane)sulfonimide lithium salt and lithium nitrate in a mixture of 1,2-dimethoxyethane and 1,3-dioxolane in order to evaluate the electrode design applicability within lithium-sulfur cells. In this respect, further insights are provided by the estimation of the lithium-ion diffusion coefficient through the Randles-Sevcik equation, and by electrochemical impedance spectroscopy. The obtained results reveal a remarkable cycle life lasting around 800 cycles with a stable capacity of 520 mA h g-1 for the first 400 cycles at C/4, while reaching a value around 300 mA h g-1 at the 750th cycle. These results suggest sulfur-carbon nanohorns active material as a potential candidate for the next-generation battery technology.

Acute SARS-CoV-2 infections in children and adolescents are usually mild. However, they can suffer from ongoing symptoms generally referred as long COVID. Sleep disorders are one of the most frequent complaints in long COVID although precise data are missing. We assessed the sleep behavior of children and adolescents who presented at our outpatient clinic between January 2021 and May 2022 with the Children's Sleep Habits Questionnaire (CSHQ-DE). We compared sleep behavior at three different time points: pre-COVID-19, post-COVID-19 at initial presentation and post-COVID-19 at re-presentation. Data from 45 patients were analyzed. Of those, 64% were female and the median age was 10 years (range 0-18 years). Asymptomatic or mild COVID-19 disease was experienced in 89% of patients, whilst 11% experienced moderate disease. Initial presentation occurred at a median of 20.4 weeks (6 weeks - 14 months) after infection. The CSHQ-DE score increased significantly from pre-COVID-19 (45.82+8.7 points) to post-COVID-19 (49.40+8.3 points; p=&lt;0.01). The score then normalized at re-presentation (46.98+7.8; p=0.1). The greatest changes were seen in the CSHQ-DE subscale score "daytime sleepiness". Our data show that children and adolescents with long COVID often suffer from sleep disturbance. For most children and adolescents these sleep disorders decreased over time without further medical intervention, aside from a basic sleep consultation.

Background: Some patients who have recovered from COVID-19 have experienced a range of persistent symptoms or the appearance of new ones after a SARS-CoV-2 infection. These symptoms can last from weeks to months, impacting everyday functioning to a significant number of patients. Methods: A cross-sectional analysis based on an online, self-reporting questionnaire was conducted in Ecuador from April to July 2022. Participants were invited by social media, radio, and TV to voluntarily participate in our study. A total of 2103 surveys were included in this study. We compared socio-demographic variables and long-term persisting symptoms at low (&lt; 2,500 m) and high altitude (&gt;2,500 m).Results: Overall, 1100 (52.3%) responders claimed to have long-term symptoms after SARS-CoV-2 infection. Most of these symptoms were reported by women (64.0%), the most affected group was young adults (68.5%), and the majority of long-haulers were mestizos (91.6%). We found that high altitude residents were more likely to report persisting symptoms (71.7%) versus those living at lower altitudes (29.3%). The most common symptoms were fatigue or tiredness (8.4%), hair loss (5.1%) and difficulty concentrating (5.0%). The highest proportion of persisting symptoms was observed among those who received an incomplete vaccine scheme.Conclusions: This is the first study describing post-COVID symptoms' persistence in low and high-altitude residents. Our findings demonstrate that women, especially those aging between 20-40, are more likely to describe sequalae associated with post-COVID. We also found that living at a high altitude was associated with earlier onset and longer symptom duration. Finally, we found a greater risk to report long lasting symptoms among women, those with previous comorbidities and those who had a severer acute SARS-CoV-2 infection.

Long-acting injectable antipsychotics (LAIs) offer many benefits to patients with schizophrenia spectrum disorder (SSD). They are used with very different frequencies due to questions of eligibility or patients’ and prescribers’ attitudes towards LAI use. We assessed the prescribing rates of LAIs in a large academic psychiatric hospital with public service mandate in Switzerland and compared them with other countries and health care systems. To our knowledge this study is the first to investigate the inpatient LAI-use in Europe. Medical records of all patients diagnosed with SSD discharged from the Clinic of Adult Psychiatry of the University Hospital of Psychiatry Zurich over a 12-month period from January to December 2019 were evaluated regarding the prescribed antipsychotics at the time of discharge. The rates of use of LAIs among all patients and among patients receiving LAI eligible antipsychotic substances were assessed retrospectively. We assessed records of 885 patients with SSD. Among all cases 13.9% received an LAI. Among patients who received antipsychotic medication that was eligible for LAI use 28.3% (n=434) received an agent as LAI. These included paliperidone palmitate (69.9%), aripiprazole monohydrate (14.6%), risperidone (4.9%) and first-generation LAIs (9.8%). Compared to international frequencies of LAI administration, the prescription rate of LAIs in SSD patients was low. Further studies will evaluate patient- and prescriber-related reasons for this low rate.

This paper addresses crashes involving heavy goods vehicles (HGV) in Europe focusing on long-haul trucks weighing 16 tons or more (16t+). The identification of the most critical scenarios and their characteristics is based on a three-level analysis: general crash statistics from CARE addressing all HGVs, results about 16t+ trucks from national crash databases and a detailed study of in-depth crash data from GIDAS, including a crash causation analysis. Most European HGV crashes occur in clear weather, during daylight, on dry roads, outside city limits, and on non-highway roads. Three main scenarios for 16t+ trucks are characterized in-depth: (1) rear-end crashes in which the truck is the striking partner, (2) conflicts during right turn maneuvers of the truck and a cyclist riding alongside and (3) pedestrians crossing the road in front of the truck. Among truck-related crash causes, information admission failures (e.g. distraction) were the main causing factors in 72% of cases in scenario (1) while information access problems (e.g. blind spots) were present for 72% of cases in scenario (2) and 75% of cases in scenario (3). The results provide both a global overview and sufficient depth of analysis in the most relevant cases and thereby aid safety system development.

Evidence indicates that the long noncoding RNAs are involved in the metformin-mediated anti-cancer processes. However, the potential effects of the long noncoding RNAs in metformin-mediated anti-tumor processes in esophageal squamous cell carcinomas (ESCC) are still elusive. This study uncovered that metformin decreases the level of long noncoding RNAs CCAT1 and SPRY4-IT1 thereby contributing to the down-regulation of c-Myc and vimentin. Also, the RNA level test of human ESCC tissue confirmed the positive correlation between CCAT1 and c-Myc. These findings demonstrated that metformin facilitated anti-cancer effects by targeting the 2 long noncoding RNAs (CCAT1 and SPRY4-IT1) and their consequential targets c-Myc and vimentin. Therefore, the CCAT1 and SPRY4-IT1 might act as novel molecular targets that mediate the anti-tumor effects in esophageal squamous cell carcinoma. This helps in predicting the treatment response of metformin in patients diagnosed with esophageal squamous cell carcinoma.

In Cameroon, alcoholic beverages remain the main consumed drink. In the Northern regions, indigenous sorghum beers are popular and widely consumed in an actively fermenting state by the people. In this study, some physicochemical parameters of the alcoholic sorghum beverages and correlations between them were evaluated during fermentation for 10 days. The indigenous white and red beers were produced at the laboratory scale assisted by experimented producers and some parameters (pH, total acidity, alcohol, sugars, density, total solids, temperature, and conductivity) were measured on the wort and fermented beverages. The pH decreases from 3.2 to 2.4 and 3.11 to 2.41; total acidity increases from 1.07 to 5.1 g/l and 0.5 to 4.6 g/l; alcohol enhances from 0 to 9.5% and 0 to 6.8% (v/v); total solids drop from 13.6 to 5°P and 12.2 to 3.3°P were observed respectively in the white and red sorghum beers. The multivariate analysis showed a good correlation between consumption of sugar, the decrease of total solids and density with the decrease in pH. It was also shown that, a perfect link exist between the production of alcohol and organic acids. The hierarchical analysis showed that indigenous red beer samples fermented for 1 and 2 days and those fermented for 4 to 10 days are related and could be separate in two distinct groups, whereas white turbid beer samples are separated in three different groups, those fermented for 1 to 4 days, those 5 to 6 days and those 7 to 10 days. The results obtained could serve as a guide to better understand the fermentation process of the indigenous alcoholic sorghum-based beverages.

In the case of long-stator linear drive, unlike rotative drives for which speed or position sensors are a single unit attached to the shaft, these sensors extend along the guideway. The position signals transmitted from maglev vehicle can’t meet the need of the real-time propulsion control in the on-ground inverter power substations. In this paper the design of the propulsion inverter control system with a position estimator for driving long-stator synchronous motor in high speed maglev train is proposed. The experiments have been carried out at the 150m long guideway in O-song test track. To investigate the performance of the position estimator, the propulsion control system with and without the position estimator are compared. The result confirms that the proposed strategy can meet the dynamic property need of propulsion inverter control system for driving long-stator linear synchronous motors

Asthma is a chronic inflammatory airway disease induced by many environmental factors. The inhalation of allergens and pollutants promote the reactive oxygen species (ROS) production leading to airway inflammation, hyper-responsiveness and remodeling in allergic asthma. The effects of asthma medications on ROS production are unclear. The present study investigated the anti-ROS effects of current asthma medications including inhaled corticosteroid (ICS; budesonide and fluticasone), leukotriene receptor antagonist (LTRA; montelukast), long acting β2 agonists (LABAs; salmeterol and formoterol) and a new extra-LABA (indacaterol). The human monocyte cell line THP-1 cells were pre-treated with different concentrations of the asthma medications at different time-points after hydrogen peroxide (H₂O₂) stimulation. H₂O₂ production was measured with DCFH-DA by flow cytometry. Montelukast, fluticasone and salmeterol suppressed H₂O₂-induced ROS production. Indacaterol enhanced H₂O₂-induced ROS production. Budesonide and formoterol alone had no anti-ROS effects, but the combination of these two drugs significantly suppressed H₂O₂-induced ROS production. Different asthma medications have different anti-ROS effects on monocytes. The combination therapy with LABA and ICS seemed not be the only choice for asthma control. Montelukast may be also a good supplemental treatment for the poorly-controlled asthma because of its powerful anti-ROS effects. Our findings provide a novel therapeutic view in asthma.

This paper compares Demand Response algorithms suitable for Short-term Forecasting based on Advanced Metering Infrastructure (AMI). It selects ARIMA (AutoRegressive Integrated Moving Average), SARIMA (Seasonal ARIMA), LSTM (Long Short-Term Memory), and SVM (Support Vector Machine) as the primary research algorithms and delves into their theoretical foundations and functional characteristics. The theoretical background section explores each algorithm’s applicability in analyzing time-series data, recognizing nonlinear patterns, and solving optimization and classification problems. The methodology section will detail the methods of AMI data collection, the implementation of the algorithms, and the experimental setup. In the experiments and results section, the performance of each algorithm will be assessed by applying AMI data and presenting the outcomes of comparative analyses, with a focus on evaluating the predictive accuracy of the algorithms. The discussion will interpret the experimental results, analyzing the advantages and disadvantages of each algorithm and their applicability in the AMI system. It will also explore the limitations of the current research and directions for future research. The conclusion will summarize the key findings of the study and affirm how this research contributes to understanding and improving short-term forecasting and demand response systems based on AMI.

Remote sensing (RS) is a compulsory component in studying and monitoring ecosystems suffering from the disruption of natural balance, productivity, and degradation. Current study attempted to assess the feasibility of multisource RS for assessing and monitoring mountainous natural grasslands in Armenia. Series of the different spatial resolution RS data (Landsat 8, Sentinel 2, Planet Scope, and multispectral UAV data) were used to obtain various vegetation spectral indices: NDVI, NDWI, GNDVI, GLI, EVI, DVI, SAVI, MSAVI, and GSAVI, and the relationship among the indices were assessed via Spearman correlation method, which shows a significant positive correlation for all cases (p &lt; 0.01). A comparison of all indices shows a significant high correlation between UAV and the PlanetScope imagery. The comparison of UAV, Sentinel and Landsat data show moderate and low significant correlation (p &lt; 0.01) correspondingly. Also, trend analysis was performed to explore their spatial-temporal changes using Mann-Kendall statistical tests (MK, MKKH, MKKY, PW, TFPW), which indicated no significant trend. However, Sen’s slope as second estimator shows decreasing trend. Though the best result received for PlanetScope and Sentinel 2, Sentinel-2 data seem to have better alignment making it a reliable tool for an accurate monitoring of small mountainous grasslands in Armenia.

Scholars of the English Literature unanimously say that J.R.R. Tolkien and C.S. Lewis influenced each other writings. For the first time we have investigated this issue mathematically by using an original multi–dimensional analysis of linguistic parameters, based on surface deep–language variables and linguistic channels. To set our investigation in the framework of the English Liter-ature, we have considered some novels written by earlier authors, such as C. Dickens, G. Mac-Donald and others. The deep–language variables and the linguistic channels, discussed in the paper, are likely due to writers’ unconscious design and have revealed connections between texts far beyond writers’ awareness. In summary, the capacity of the extended short–term memory required to readers, the universal readability index of texts, the geometrical representation of texts and the fine tuning of linguistic channels within texts – all tools largely discussed in the paper – have revealed strong connections between The Lord of the Rings (Tolkien), The Chronicles of Narnia, The Space Trilogy (Lewis) and novels by MacDonald, therefore in agreement with what scholars of the English Literature say.

The mathematical structure underlying a sentence is made of two independent processing units in series. The conditional probability density function of sentence length (measured in words) recordable in the extended short–term memory (E–STM) buffer made of CF cells is Gaussian. The number of sentences that authors of Italian and English Literatures have written is compared to that theoretically available to them. The multiplicity factor α describes this comparison. α&gt;1 is more likely than α&lt;1 and often α≫1, therefore the same sentence pattern is reused many times. These texts are easier to read. Very few novels show α&lt;1. In these cases, there are enough diverse sentence patters to convey meaning, but most of them are not used. Texts are more difficult to read, as measured by a universal readability index GU. A mismatch index IM synthetically describes the process. α, GU. and IM increase with year of publication. Future work will concern other literatures – including ancient ones as Greek and Latin – to confirm what, in our opinion, is general feature of human mind.

The response of plasmonic metal particles to an electromagnetic wave undergoes significant features at the nanoscale level. Different properties of the internal composition of a metal, such as its ionic background and the free electron gas, begin to manifest more prominently. As the dimensions of the nanostructures decrease, the classical local theory gradually becomes inadequate. Therefore, Maxwellʹs equations need to be supplemented with a relationship determining the dynamics of current density which is the essence of nonlocal plasmonic models. In this field of physics, the standard (linearized) hydrodynamic model (HDM) has been widely adopted with great success, serving as the basis for a variety of simulation methods. However, ongoing efforts are also being made to expand and refine it. Recently, the GNOR (general nonlocal optical response) modification of the HDM has been used, with the intention of incorporating the influence of electron gas diffusion. Clearly, from the classical description of fluid dynamics, a close relationship between viscosive damping and diffusion arises. This offers a relevant motivation for introducing the GNOR modification in an alternative manner. The standard HDM and its existing GNOR modification also do not include the influence of interband electron transitions in the conduction band and other phenomena that are part of many refining modifications of the Drude‐Lorentz and other models of metal permittivity. In this article, we present a modified version of GNOR‐HDM that incorporates the viscosive damping of the electron gas and a generalized Drude‐Lorentz term. In the selected simulations, we also introduce Landau damping which corrects the magnitude of the standard damping constant of the electron gas based on the size of the nanoparticle. We have chosen a spherical particle as a suitable object for testing and comparing HD models and their modifications because it allows finding precise analytical solutions for the interaction and, simultaneously, it is a relatively easily fabricable nanostructure in practice. Our contribution also includes our own analytical method for solving the HDM interaction of a plane wave with a spherical particle. This method forms the core of calculations of the characteristic quantities, such as the extinction cross‐sections and the corresponding components of electric fields and current densities.

This paper delves into the dynamics of asset pricing within Bachelier’s market model (BMM), elucidating the representation of risky asset price dynamics and the definition of riskless assets. It highlights the fundamental differences between BMM and the Black-Scholes-Merton market model (BSMMM), including the extension of BMM to handle assets yielding a simple dividend. Our investigation further explores Bachelier’s term structure of interest rates (BTSIR), introducing a novel version of Bachelier’s Heath-Jarrow-Morton model and adapting the Hull-White interest rate model to fit BMM. The study concludes by examining the applicability of BMM in real-world scenarios, such as those involving environmental, social, and governance (ESG)-adjusted stock prices and commodity spreads.

This paper has a twofold objective. The first aim is to present a comprehensive bibliographical analysis of journal articles and book chapters on fuzzy-random option pricing (FROP) over the WoS and SCOPUS databases. It follows PRISMA criteria and takes special care of developments in continuous time. Thus, we described the principal findings about the research streams, outlets and authors of this topic and lets us suggest further research. The second contribution is motivated by the fact that the bibliographical revision has identified a lack of developments on equilibrium models on the yield curve. This question motivates extending Vasicek’s yield curve equilibrium model to introduce fuzziness in the parameters that govern interest rate movements (speed of reversion, equilibrium short-term interest rate, and volatility). Likewise, this paper develops an empirical application on the term structure of fixed income public bonds with the highest credit rating in the Euro area.

This study focuses on Tsunami detection using SIMRAD Radar. A tsunami is a condition in which sea waves overflow the land and cause severe damage, which can claim human lives, as well as important infrastructure such as schools, buildings, and housing on the coast. As a sovereign country and has resilience in various fields including security and ocean exploration, Indonesia must apply appropriate technology, in this case, a smart radar that can detect high sea waves from tens of km away even 100 km if radar capacity is maximized. And able to provide fast information for disaster emergency response teams to swiftly notify the surrounding community about the arrival of a tsunami, even predict before this tsunami hits the coast. In this research, a comprehensive measurement of the radar system is carried out. The radar used and developed is SIMRAD Radar Helo 6 and can be integrated with data from other hardware such as SBE 26Plus, to obtain comprehensive data about the marine environment. In the measurement process, several combinations of measurements are needed starting from how to get digital data, process digital data, and turn it into a real-time image in the form of a Graphical User Interface SIMRAD Radar Hello 6. In the search, SIMRAD Radar is placed on the coast, while SBE26Plus is placed in the ocean with a certain depth in the coastal area for seawater pressure and sea level measurement. This radar system can be converted from the SBE26Plus data results from the Acoustic Doppler Current Profiler (ADCP), and also SIMRAD real-time monitoring at the coastal position in a higher area to avoid obstacles.

Road safety and the effectiveness of the transportation system as a whole are significantly impacted by driver comfort. Road surface quality can play a significant part in the driver’s comfort experienced on roads in any country. This study employs a Random Forest technique to examine the association between road roughness and drivers' comfort during long-distance driving. Using Random Forest, a dependable machine learning technique that can handle big datasets and detect nonlinear correlations, this work aims to shed light on the complex dynamics between road conditions and driver’s comfort. 1,048,576 rows of data from MIRANDA, an application developed at the University of Gustave Eiffel, were used in this study as part of the data collected from a probe vehicle. The data collected includes an International Roughness Index (IRI). The IRI thresholds offer a simple method for assessing driver comfort and road irregularity. While highlighting how uneven and uncomfortable the road is, the research's findings (Road Roughness: SD – 0.73; Driver's Comfort: - Mean, 10.01, SD – 0.64) also contribute to the standardization of road condition evaluation and maintenance communication. This finding is anticipated to aid in the development of strategies for improving the welfare of long-haul drivers and fixing road infrastructure to comply with standard road index, ultimately leading to the creation of more efficient and sustainable transportation systems.

Long noncoding RNAs (lncRNAs) are known to play key roles in breast cancers; however, detailed mechanistic studies of lncRNA function have not been conducted in large cohorts of breast cancer tumors, nor have inter-donor and inter-subtype variabilities been taken into consideration. Here we provide the first identification and annotation of the human BORG lncRNA gene. Using multiple tumor cohorts of human breast cancers, we show that while BORG expression is strongly induced in breast tumors as compared to normal breast tissues, the extent of BORG induction varies widely between breast cancer subtypes and even between different tumors within the same subtype. Elevated levels of BORG in breast tumors are associated with the acquisition of core cancer aggression pathways, including those associated with basal tumor and pluripotency phenotypes, and with epithelial-mesenchymal transition (EMT) programs. While a subset of BORG-associated pathways was present in high BORG-expressing tumors across all breast cancer subtypes, many were specific to triple-negative breast cancer tumors. Finally, we show that genes induced by heterologous expression of BORG in murine models of TNBC both in vitro and in vivo strongly overlap with those associated with high BORG levels in human TNBC tumors, indicating that human BORG is a novel driver of the highly aggressive basal TNBC tumor phenotype.

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10-20% of individuals following COVID-19 infection. FM and LC shares similarities with regards to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCA) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n= 48 FM and n= 46 LC) and volumetric absorptive micro sampling tips (VAMS, n= 39 FM and n= 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra was acquired using SERS with gold nanoparticles (AuNPs). Soft Independent Modelling of Class Analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNPs SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

It is challenging to precisely measure the slow interseismic crustal deformation rate from SAR data. The long-wavelength orbital errors, owing to the uncertainties in satellite orbit vectors, commonly exist in SAR interferograms, which degrade the precision of the InSAR products and become the main barrier of extracting interseismic tectonic deformation. In this study, we propose a novel temporal network orbital correction method that is able to isolate the far-fault tectonic deformation from the mixed long-wavelength signals based on its spatio-temporal characteristic. The proposed approach is straightforward in methodology but could effectively separate the subtle tectonic deformation from glaring orbital errors without ancillary data. Both synthetic data and real Sentinel-1 SAR images are used to validate the reliability and effectiveness of this method. The derived InSAR velocity fields clearly present the predominant left-lateral strike-slip motions of the Tuosuo Lake segment of the Kunlun fault in western China. The fault-parallel velocity differences of 5-6 mm/yr across the fault between areas ~50 km away from the fault trace are addressed. The proposed method presents significantly different performance from traditional quadratic approximate method in the far-field. Through the implementation of the proposed method, the RMSE between the LOSGPS and our derived descending InSAR LOS is reduced to less than one-third of the previous study, suggesting its potential to enhance the availability of InSAR technology for interseismic crustal deformation measurement.

Noncoding RNA regions have emerged as pivotal players in the regulation of various cellular processes, and their involvement in HIV/AIDS pathogenesis is an evolving field of research. This review article delves into the intricate interplay between noncoding RNA regions and AIDS, shedding light on the diverse mechanisms by which these RNA molecules influence viral replication, immune responses, and disease progression. The review highlights recent discoveries, potential therapeutic applications, and the challenges ahead, illustrating the promising prospects of noncoding RNA research in the context of HIV/AIDS.

The early detection of small cracks in large structures is a crucial requirement for the implementation of structural health monitoring (SHM) system with a low transducer density. This work presents the results of the analysis of scattering of a submillimeter notch type defect with semielliptical shape with a groove at constant width 100µm in a 4.1mm thick aluminum plate. The defect is investigated with an ultrasonic guided wave (UGW) A0 mode at 550 kHz to cover long range in a thick plate. The mode selection is obtained by interdigital transducers designed to operate with 5mm central wavelength. The novel contribution is the assessment of the scattering amplitudes at different orientations of the defect when the distance is large as 35 cm in pulse-echo mode or 70 cm in pitch-catch mode. The system model is based on Finite Element Model (FEM) simulations and the results are in good agreement with experimental tests. The detection of the defect is obtained by comparing the scattered signals from the defect with base line signals of the pristine laminate. The analysis of scattering features and the efficient excitation with a probing UGW show the potential implementation in real structural health monitoring (SHM) systems.

We propose a new methodology for long-time biopotential recording based on MEMS multisensor integrated platform featuring a commercial electrostatic charge transfer sensor. That family of sensors was originally intended for presence tracking in automotive, so the existing setup has been engineered for the acquisition of electrocardiogram, electroencephalogram, electrooculogram and electromyography, designing a dedicated front-end and writing a proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in domestic environment will be discussed in detail. The excellent results candidate this technology to provide a low power, unexplored solution to biopotentials acquisition. The technology breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, they open to additional possibilities for wearable sensing and strengthen the role of MEMS technology in medical wearable applications for long time synchronous acquisition of a wide range of signals.

The thermal degradation of brakes has a significant impact on the stability of pure electric commercial vehicles during long downhill braking. Based on road slope and using fuzzy control method, design strategies for motor regenerative braking force and friction braking force distribution, with the aim of reducing friction braking force, improving braking stability, and recovering braking energy. By establishing driving conditions on roads with different slopes and using numerical analysis methods to verify the proposed control strategy. the results show that under the 6% constant slope driving condition, the vehicle maintains a constant speed of 30km/h downhill driving, and the braking energy recovery rate reaches 50.93%; Under the condition of 3% -6% gradient driving, the vehicle speed fluctuates slightly, but it can still be maintained at a constant speed of 30km/h for downhill driving through the adjustment of the motor's reverse drag characteristic, with a braking energy recovery rate of 49.97%; During the process of driving downhill at a constant speed, the frictional braking force does not participate in braking; The braking energy recovery rate is determined by the slope and braking deceleration.

Flexible energy storage devices, such as solid-state supercapacitors, are becoming increasingly attractive due to their characteristics of high electrochemical performance, reliability, light weight, flexibility, absence of electrolyte leakage, high power density, and long lifetime. For the optimization of the solid-state symmetrical supercapacitor proposed in this work, it was employed in sodium and lithium form Aquivion electrolyte membrane, which serves as the separator and electrolyte. As electrode materials, carbon xerogels, synthesized by microwave-assisted sol-gel methodology, with designed and controlled properties were obtained. Commercial activated carbon (YP-50F, 'Kuraray Europe' GmbH) was used for comparison. Specifically, the developed solid-state symmetrical supercapacitors deliver sufficient high specific capacitances of 105−110 F g−1 at 0.2 A g−1, along with an energy density of 4.5 Wh kg−1 at 300 W kg−1, and in a voltage window of 0-1.2 V in an aqueous environments, also demonstrating excellent cycling stability up to 10,000 charge/discharge cycles. These results can demonstrate the potential applications of carbon xerogel as an active electrode material and cation exchange membrane as the electrolyte in the development of solid-state supercapacitor devices

With growing regulations on ship emissions, specifically carbon dioxide and nitrogen oxides, this study emphasizes the critical need for improving the performance of existing ship diesel engines. Focusing on easily modifiable injection conditions within the fuel system, the research aims to enhance combustion characteristics for operational ships. The study provides a concise analysis of the combustion performance improvements achievable in the field. The study employed a range of calculation conditions, spanning from fuel injection pressures of 20 MPa to 160 MPa, injection timing from 15 degrees before top dead center (BTDC) to 5 degrees after top dead center (ATDC), and spray angles varying between 10 degrees and 50 degrees. A comprehensive analysis was conducted, focusing on fuel distribution behavior, combustion dynamics, carbon monoxide (CO) production and extinction, as well as nitrogen oxide (NO) production. This thorough examination aimed to provide insights into the complex interplay of these factors in order to optimize combustion performance in ship diesel engines. The analysis indicated that substantial unburned fuel occurred at injection pressures below 40 MPa and spray angles less than 20 degrees. This issue was significantly mitigated when injection pressures exceeded 80 MPa or a spray angle of 40 degrees was employed. High flame propagation speeds were observed at injection pressures over 80 MPa and injection timings before BTDC 10. Carbon monoxide emissions were notably low when injection pressures exceeded 80 MPa and a 40-degree spray angle was used. Nitrogen oxide emissions were minimized under conditions of injection pressure below 40 MPa, injection timing after BTDC 5 degrees, and a spray angle between 30 and 40 degrees. The study concludes that the most effective injection conditions for concurrently reducing fuel consumption, minimizing incomplete combustion products, and lowering nitrogen oxide emissions in the target engine are optimal when the injection pressure is set at 80 MPa, the injection timing is positioned at 5 degrees before top dead center (BTDC), and the spray angle is maintained at 40 degrees.

Background: In March 2020, a COVID-19 outbreak associated with the Falles Festival in Borriana, Spain, led to significant infections. Methods: In June 2022, we conducted a cross-sectional follow-up study of 473 socially engaged adults aged 18 to 64, examining the cumulative experience after SARS-CoV-2 infection and vaccination responses. Data included demographic details, lifestyle habits, medical history, infection records, and vaccinations from a population-based vaccine registry. Blood samples were analyzed for SARS-CoV-2 antibodies and cellular immunity. We employed a doubly robust inverse weighted probability analysis to estimate the booster vaccine dose's impact on long COVID prevalence and symptom count. Results: 28.1% of participants met the WHO criteria for long COVID, with older individuals showing higher rates. Not complying with long COVID criteria associated with factors including O blood group, higher occupational status, physical activity, three vaccine doses, strong SARS-CoV-2-S-reactive IFNγ‐producing‐CD8+ response, and infection during the Omicron period. Conversely, increased age, high or low social activity, underlying health conditions, a severe initial COVID episode, and reinfection associated with higher long COVID likelihood. A booster dose, compared to one or two doses, reduced long COVID risk by 74% (95% CI: 56.4% to 91.7%) and symptom count by 55.2% (95% CI: 31.6% to 78.7%). Conclusion: Long COVID was prevalent in a significant portion of those who contracted COVID-19, underscoring the need for sustained follow-up and therapeutic strategies. Vaccinations, notably the booster dose, had a substantial beneficial effect on long-term infection outcomes, affirming the vaccination’s role in mitigating SARS-CoV-2 infection consequences.

Hypertension is one of the most common and significant cardiovascular risk factor. With the emergence of COVID-19, concerns have arisen about its potential to exacerbate cardiovascular morbidity and mortality. Several theories have emerged linking hypertension with COVID-19. However, the relationship between SARS-CoV-2 infection and long-term risk of hypertension remains insufficiently explored. Therefore, our study aimed to investigate the impact of COVID-19 infection on blood pressure and long-term risk of hypertension developing. A comprehensive search was conducted in the PubMed and SCOPUS databases up to 10th August 2023 for relevant papers. The analysis included 35 eligible articles. The majority of the latest studies pointed to increase BP after COVID-19 infection. However, several observations contradicted the influence of SARS-CoV-2 on the hypertension development or suggesting a transient effect. The possible role of the loss of angiotensin-converting enzyme 2, cytokine storm, increased sympathetic activity, and endothelial dysfunction were considered. On the other hand, BP changes following COVID-19 could be a consequence of lifestyle changes, which often accompanied COVID-19 infection. Our findings highlight the urgent need for comprehensive research on the COVID-19 and hypertension link. These insights are crucial for implementing effective prevention and management strategies for individuals with the history of COVID-19 infection.

Some recent studies show that filters in convolutional neural networks (CNNs) have low color selectivity in datasets of natural scenes such as Imagenet. CNNs, bio-inspired in the visual cortex, are characterized by their hierarchical learning structure, which appears to gradually transform the representation space. Inspired by the direct connection between the LGN and V4, which allows V4 to handle low-level information closer to the trichromatic input in addition to processed information that comes from V2/V3, we propose the addition of a long skip connection (LSC) between the first and last blocks of the feature extraction stage to allow deeper parts of the network to receive information from shallower layers. This type of connection improves classification accuracy by combining simple-visual and complex-abstract features to create more color-selective ones. We have applied this strategy to classic CNN architectures and quantitatively and qualitatively analyzed the improvement in accuracy while focusing on color selectivity. The results show that, in general, skip connections improve accuracy, but LSC improves it even more and enhances the color selectivity of the original CNN architectures. As a side result, we propose a new color representation procedure for organizing and filtering feature maps, making their visualization more manageable.

Allergies are a common and increasing health problem affecting millions of people worldwide. In addition to genetic predisposition, this increase in allergic cases is attributed to air pollution, climate change, more time spent indoors, lack of physical activity, and alterations in eating habits. The Mediterranean diet (MD), which includes a lot of fruits and vegetables, whole grains, legumes, nuts, olive oil and fish has been linked to a variety of health benefits, including a lower risk of chronic and allergic diseases. The purpose of this paper is to explore the effects of the dietary components of the MD on food allergies. Electronic databases PubMed, Scopus, Science Direct, and EBSCO were used to conduct this systematic review up to March 2023. 696 studies were initially identified and nine were included (five human and four animal studies). The findings of this review showed an overall beneficial effect between the food components of the MD and food allergies. Although the results are promising, the limited number of studies highlights the need for more research.

Improper lifting measures of long-span spatial steel structures during construction process may delay the construction period and even cause safety accidents. Few studies on long-span spatial steel structures considered time-varying mechanical characteristic during construction process. In order to achieve safe and efficient installation in a long-span spatial steel structure, this research presents a time-varying mechanical analysis of the synchronous and asynchronous integral lifting and a single and interlaced point’s asynchronous integral lifting analysis method of a long-span spatial steel structure. The results showed that in the case of asynchronous lifting of single point, the displacement influence on other members is related to the distance. The closer the distance from the lifting point, the greater the influence. In asynchronous integral lifting, the lifting point with large lifting force is first installed to the specified position, and the lifting point with small lifting force is installed to the specified position.

This study estimates the effects of double long memory and structural breaks on the persistence level of six major cryptocurrency markets. We apply the Bai and Perron’s structural break test, Inclán and Tiao’s iterated cumulative sum of squares (ICSS) algorithm, and the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model with different distributions. The results show that long memory and structural breaks characterize the conditional volatility of cryptocurrency markets and confirm our hypothesis that ignoring structural breaks leads to an underestimation of the persistence of volatility modelling. The ARFIMA-FIGARCH model with structural breaks and a skewed Student–t distribution fits the cryptocurrency market’s price dynamics well.

Fractal behavior and long-range dependence are widely observed in measurements and characterization of traffic flow in high-speed computer networks of different technologies and coverage levels. This paper presents the results obtained when applying fractal analysis techniques on a time series obtained from traffic captures coming from an application server connected to the Internet through a high-speed link. The results obtained show that traffic flow in the dedicated high-speed network link have fractal behavior when the Hurst exponent is in the range of 0.5, 1, the fractal dimension between 1, 1.5, and the correlation coefficient between –0.5, 0. Based on these results, it is ideal to characterize both the singularities of the traffic and its impulsiveness during a fractal analysis of temporal scales. Finally, based on the results of the time series analyses, the fact that the traffic flows of current computer networks exhibit fractal behavior with a long-range dependency is reaffirmed.

PM2.5 and PM>2.5 were separately collected in Kanazawa, Japan in every season from the spring of 2017 to the winter of 2018, and nine polycyclic aromatic hydrocarbons (PAHs) and six nitropolycyclic aromatic hydrocarbons (NPAHs) were determined by HPLC with fluorescence and chemiluminescence detections, respectively. Atmospheric concentrations of both PAHs and NPAHs showed seasonal changes (highest in the winter and lowest in the summer), which were different from the variations of TSP and PM2.5 (highest in the spring). Contributions of major sources to combustion-derived particulate (Pc) in PM2.5 were calculated by the NP-method using pyrene and 1-nitropyrene as representative markers of PAHs and NPAHs, respectively. The annual average concentration of Pc accounted for only 2.1% of PM2.5, but showed the same seasonal variation as PAHs. The sources of Pc were automobiles (31%) and coal heating facilities/industries (69%). The source of Pyr was almost entirely coal heating facilities/industries (98%). A backward trajectory analysis showed that automobile-derived Pc was mainly from Kanazawa and its surroundings and that coal heating facilities-derived Pc was transported from city areas in central and northern China in the winter and during the Asian dust event in the spring. These results show that large amounts of PAHs were long-range transported from China in the winter. Even in spring when the coal heating season was over in China, PAHs came over to Japan after Asian dust storms passed through Chinese city areas. The main contributor of NPAHs was automobiles in Kanazawa and its surroundings. The recent Pc concentrations were much lower than those in 1999. This decrease was mostly attributed to the decrease in the contribution of automobiles. Thus, changes of atmospheric concentrations of Pc, PAHs and NPAHs in Kanazawa were strongly affected not only by the local emissions but also long-range transport from China.

DNA double-strand breaks (DSBs) are deleterious lesions that are generated in response to ionizing radiation or replication fork collapse that can lead to genomic instability and cancer. Eukaryotes have evolved two major pathways, namely homologous recombination (HR) and non-homologous end joining (NHEJ) to repair DSBs. Whereas the roles of protein-DNA interactions in HR and NHEJ have been fairly well defined, the functions of small and long non-coding RNAs and RNA-DNA hybrids in the DNA damage response is just beginning to be elucidated. This review summarizes recent discoveries on the identification of non-coding RNAs and RNA-mediated regulation of DSB repair

Congenital Pouch Colon (CPC) is a rare anorectal anomaly common to North Western India specifically Rajasthan. Despite efforts to understand the clinical genetic makeup of CPC, no attempt on identifying non-coding RNAs was done. We have earlier reported CPC's rare variants from whole exome sequencing across 18 affected samples in a total of 64 subjects. A Smith-Waterman algorithm was used to infer a couple of lncRNAs from WES samples of CPC with predictions from the Noncode database. Further screening and quantification using PCR, we ascertained interactions using Micro Scale Thermophoresis (MST). We report the role of lnc-EPB41-1-1 shown to be promiscuously interacting with KIF13A substantiating their role in regulation.

A comprehensive model for designing robust all-in-fiber microresonator-based optical sensing setups is illustrated. The investigated all-in-fiber setups allow light to selectively excite high-Q whispering gallery modes (WGMs) into optical microresonators, thanks to a pair of identical long period gratings (LPGs) written in the same optical fiber. Microspheres and microbubbles are used as microresonators and evanescently side-coupled to a thick fiber taper, with a waist diameter of about 18 µm, in-between the two LPGs. The model is validated by comparing the simulated results with the experimental data. A good agreement between the simulated and experimental results is obtained. As an application example, the sensing of the concentration of an aqueous glycerol solution is demonstrated. The model is general and by exploiting the refractive index and/or absorption characteristics at suitable wavelengths, the sensing of other substances or pollutants can be also predicted.

Formalin-Fixed Paraffin Embedded (FFPE) tissues are a valuable resource in studying different markers and mechanistic molecules (protein, DNA and RNA) in order to understand the etiology of different cancers as well as many other diseases. Degradation and modification of RNA is the major challenge in utilizing FFPE tissue samples in medical research. Recently, non-protein coding transcripts long non-coding RNAs (lncRNAs), have gained significant attention due to their important biological actions and potential involvement in cancer. There is no validated method except qRTPCR or RNAseq to evaluate and study lncRNA expression. We have standardized and are reporting a sensitive Z probe based in situ hybridization method to identify, localize and quantitate lncRNA in FFPE tissues. This assay is sensitive to single transcript and localizes lncRNA in individual cells within tumor. We have characterized a tumor suppressor lncRNA-NRON (non coding repressor of NFAT), which is scarcely expressed, a moderately expressed oncogeneic lncRNA UCA1 (urothelial cancer associated 1), and a highly studied and expressed lncRNA MALAT1 (metastasis associated lung adenocarcinoma transcript1) in different cancers. High MALAT1 staining was found in colorectal, breast and pancreatic cancer. MALAT1 expression increased with the progression of the stage in colorectal cancer and invasiveness in breast cancer.

Accurate, rapid, and stable prediction of electrical energy consumption is essential for decision-making, energy management, efficient planning, and reliable power system operation. Errors in forecasting can lead to electricity shortages, wasted resources, power supply interruptions, and even grid failures. Accurate forecasting enables timely decisions for secure energy management. However, predicting future consumption is challenging due to the variable behavior of customers, requiring flexible models that capture random and complex patterns. Existing forecasting methods, both traditional and modern, have limitations and do not fully meet accuracy expectations. To address these issues, this research introduces a hybrid models that combine FCRBM based forecaster, and GWDO based optimizer, namely FS-FCRBM-GWDO approach to enhance the model performance in STLF have been developed. While some models excel in accuracy and others in convergence rate, both aspects are crucial. The main objective is to create a forecasting model that provides reliable, consistent, and precise predictions for effective energy management. This led to the development of a novel two-stage hybrid model. The first stage predicts electrical energy usage through four modules using deep learning, support vector machines, and optimization algorithms. The second stage optimizes energy management based on predicted consumption, focusing on reducing costs, managing demand surges, and balancing electricity expenses with customer inconvenience. This approach benefits both consumers and electricity corporations by lowering bills and enhancing power system stability. Simulation results validate the proposed model's efficacy and efficiency compared to benchmark models.

The statistical analysis of impact of the top 50 solar flares of X-class (1997-2023) on the global seismic activity, as well as on the earthquake preparation zones located in illuminated part of the globe and in the area of 5000 km radius around the subsolar point was carried out. It is shown by a method of epoch superposition that for all cases the increase of seismicity is observed, especially in the region around the subsolar point (up to 38%) during 10 days after the solar flare in comparison with preceding 10 days. The case study of aftershock sequence of strong M=9.1 earthquake (Su-matra-Andaman Islands, 26.12.2004) after the solar flare of X7.2 class (20.01.2005) demonstrated that the number of aftershocks with magnitude M≥2.5 increases more than 20 times after the solar flare with a delay of 7 days. For the case of the Darfield earthquake (M=7.1, 04.09.2010, New Zealand) it was shown that strong solar flares of class X and M probably triggered two strong aftershocks (M>6) with the same delay of 6 days on the Port Hills fault, which is the most sensitive to external electromagnetic impact from point of view of the fault electrical conductivity and orientation. Based on the obtained results the possible application of natural electromagnetic triggering of earthquakes is discussed for a short-term earthquake prediction using confidently recorded strong external electromagnetic triggering impacts on the specific earthquake preparation zones, as well as ionospheric perturbations due to aerosol emission from the earthquake sources recorded by satellites.

Natural Fibre Composites (NFC) are eco-friendly, sustainable alternatives to synthetic polymers. However, some intrinsic natural fillers´ properties hinder their widespread implementation as re-inforcement in polymeric matrices and require further investigation. In the scope of this study, the thermal, rheologic, mechanical (tension and flexural modes), morphological properties, water ab-sorption and dimensional stability of the NF polypropylene (PP) based injection moulded compo-sites with the rice husk (rh) and olive pits (op) of 20 wt% and 30% wt%, were investigated. The results suggest that the higher content of the rice husk and olive pits led to a similar reduction of the Melt Flow Index (MFI), independent of the additive type compared to virgin polypropylene (PPv). The melting and crystallization temperatures of the PPrh and PPop composites did not change with statistical significance. The composites are stiffer than the PP matrix by up to 49% and possess higher mechanical strength in what concerns the tension mode at the expense of de-creased ductility. PPrh and PPop have superior flexural modulus in the bending mode, while the flexural strength improvement was accomplished for the PP30%rh. The dimensional stability of the composites was improved as the linear shrinkage in the flow direction was decreased by 49% for PPrh and 30% for PPop, positively correlating with an increase in the filler content and stiff-ness. PPop was less susceptible to water sorption than PPrh due to fibres' composition and larger surface-to-area volume ratios.

While thunderstorms can pose severe risks to property and life, forecasting remains challenging, even at short lead times, as these often arise in meta-stable atmospheric conditions. In this paper, we examine the question of how well we could perform short-term (up to 180min) forecasts using exclusively multi-spectral satellite images and past lighting events as data. We employ representation learning based on deep convolutional neural networks in an “end-to-end” fashion. Here, a crucial problem is handling the imbalance of the positive and negative classes appropriately in order to be able to obtain predictive results (which is not addressed by many previous machine-learning-based approaches). The resulting network outperforms previous methods based on physically-based features and optical flow methods (similar to operational prediction models) and generalizes across different years. A closer examination of the classifier performance over time and under masking of input data indicates that the learned model actually draws most information from structures in the visible spectrum, with infrared imaging sustaining some classification performance during the night.

The power-generation capacity of grid-connected photovoltaic (PV) power systems is increasing. As output power forecasting is required by electricity market participants and utility operators for the stable operation of power systems, several methods have been proposed using physical and statistical approaches for various time ranges. A short-term (30 min ahead) forecasting method has been previously proposed by our laboratory for geographically distributed PV systems using motion estimation. This study focuses on an important parameter for estimating the proposed motion and optimizing the parameter. This parameter is important because it is associated with the smoothness of the vector field, which is the result of motion estimation and influences the forecasting accuracy. In the periods with drastic power output changes, the evaluation was conducted on 101 PV systems located within a circle of 15-km radius in the Kanto region of Japan. The results indicate that the absolute mean error of the proposed method with the optimized parameter is 10.3%, whereas that of the persistent prediction method is 23.7%. Therefore, the proposed method is effective in forecasting for periods when PV output changes drastically in a short time.

In the present trend of constructing taller and longer structures, the application of lightweight aggregate concrete is becoming an increasing important advanced solution in the modern construction industry. In engineering practice, the analysis of lightweight concrete elements is performed using the same algorithms used for normal concrete elements. As an alternative to traditional engineering methods, nonlinear numerical algorithms based on constitutive material models may be used. The paper presents a comparative analysis of curvature calculations for flexural lightweight concrete elements, incorporating analytical code methods EN 1992-1 and ACI 318-14, as well as a numerical analysis using the constitutive model of cracked tensile lightweight concrete recently proposed by the authors. To evaluate the adequacy of the theoretical predictions, experimental data of 51 lightweight concrete beams tested during five different programmes were collected. A comparison of theoretical and experimental results showed that the most accurate predictions are obtained using numerical analysis and the constitutive model proposed by the authors. In the future, the latter algorithm can be used as a reliable tool for improving the design standard methods or numerical modelling of lightweight concrete elements subjected to short-term loading.

Statistics of languages are calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G – the semantic index G_C, proportional to the number of characters per word, and the syntactic index G_F, proportional to the reciprocal of the number of words per sentence −, G_F is dominant because G_C is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y=mx, but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is, in author’s opinion, that between the short−term memory capacity, described by Miller’s “7∓2 law”, and the word interval, a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval is spread in the same of Miller’s law, and the time interval is spread in the same range of short−term memory response times. The connection between the word interval (and time interval) and short−term memory appears, at least empirically, justified and natural, and should further investigated. Technical and scientific writings (papers, essays etc.) ask more to their readers. A preliminary investigation of these texts shows clear differences: words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as Greek or Latin, could bring us a flavor of the short term−memory features of these ancient readers.

The glucocorticoid receptor alpha (GRα), a pivotal component of the ancient glucocorticoid (GC) signaling system that emerged nearly 450 million years ago, has been instrumental in directing vertebrate evolution and is essential for survival, regulating fertility and fetal development, the function of every organ and circulating cells, metabolism, immune responses, and adaptation to stress. While its anti-inflammatory properties have been recognized since the mid-20th century, GRα’s broader role as the master regulator of homeostatic corrections, particularly in health and critical illness, has only recently been fully appreciated.GRα orchestrates three key phases of homeostatic correction: the Priming Phase, where it rapidly activates early immune responses, mobilizes energy reserves, and prepares the body to mount an immediate defense against various physiological stressors, including infection and injury. During this phase, GRα enhances glucose metabolism, supports mitochondrial function, and facilitates the release of key immune cells to the site of damage, ensuring the body is equipped to handle the initial assault. The Modulatory Phase follows, in which GRα fine-tunes the inflammatory response to prevent excessive tissue damage. By balancing pro- and anti-inflammatory signals, GRα helps contain the immune response, preventing the harmful effects of prolonged inflammation while maintaining immune surveillance. This phase also involves the regulation of oxidative stress, vascular tone, and the preservation of cellular integrity to protect vital organs from injury. Finally, in the Restorative Phase, GRα plays a critical role in resolving inflammation and initiating tissue repair. During this phase, GRα supports cellular regeneration, promotes the clearance of apoptotic cells and debris, and restores anatomical and physiological balance. It aids in rebuilding tissue architecture and returning the neuroendocrine-immune system to its baseline state, ensuring long-term recovery and stability.Throughout these phases, GRα manages complex interactions, including recently discovered co-regulation with pro-inflammatory transcription factors, while also regulating mitochondrial function to ensure bioenergetic and metabolic stability during stress. In critically ill patients, depletion of bioenergetic and micronutrient reserves severely impairs GRα’s capacity to regulate immune responses, heightening the risk of morbidity and mortality.This review, in light of this new understanding, underscores the need to re-evaluate current glucocorticoid (GC) treatment strategies, emphasizing the incorporation of micronutrient support to optimize GRα function across all phases of homeostatic correction. This integrated therapeutic approach has the potential to enhance both immediate immune responses and long-term recovery in critically ill patients, offering a more comprehensive strategy for managing the complex pathobiology of critical illness. Furthermore, this integrative approach could decrease glucocorticoid dose and duration requirements and potential side effects.

In our recent publications pertaining to 4G model of final unification and based on strong and electroweak interactions, we have developed a completely new formula for estimating nuclear binding energy. With reference to currently believed Semi Empirical Mass Formula (SEMF), we call our formula as ‘Strong and Electroweak Mass Formula’ (SEWMF). Our formula constitutes 4 simple terms and only one energy coefficient of magnitude 10.1 MeV. First term is a volume term, second term seems to be a representation of free nucleons associated with electroweak interaction, third term is a radial term and fourth one is an asymmetry term about the mean stable mass number. Considering this kind of approach, nuclear structure can be understood in terms of strong and weak interactions and cold nuclear fusion like complicated concepts can be understood in a theoretical approach positively. In this paper, by considering the accountability of we are making an attempt to improve the applicability and effectiveness of SEWMF. Number 0.00125 being a workable electroweak coefficient for Z=6 to 132 and A=2Z to 3.5Z, number of free nucleons assumed to be associated with electroweak interaction can be expressed as Improved asymmetry term can be expressed as, where represents the light house like stable mass number. With reference to old version, our improved binding energy formula can be expressed as, We are working on its possible modification for mass numbers less than the stable mass numbers. Following this approach, it is possible to show that nuclear binding energy scheme is associated with strong and weak interactions and is practically independent of Coulombic repulsions. Proceeding further, currently believed cold nuclear fusion assumed be associated with hydrated metals can be understood and can be confirmed with strong and weak interactions independent of coulombic repulsions. We are very confident to say that our approach will certainly motivate modern science community in this new direction.

We present an innovative method for dual band mid-wave infrared (MWIR) and long-wave infrared (LWIR) reflectors. By using double-sided metasurfaces, two high reflection bands can be generated with a single device. As individual guided-mode resonance (GMR) reflectors are combined with interlayer (or substrate) on the top and bottom sides, we achieve high reflection in the MWIR and LWIR bands simultaneously. Each GMR reflector is optimized as a germanium (Ge) grating structure on a potassium bromide (KBr) substrate. In our analysis, it is found that the transparency of the interlayer is critical to produce the dual-band reflection. The simulation results on the Ge/KBr/Ge double-sided metasurfaces demonstrate wideband reflection from ~3.3 to 4.8 μm and ~8.8 to 11 μm. Additionally, the device exhibits favorable angular tolerance. The work contributes to developing capability of metasurface technologies in various application fields.

Background: The term “Long COVID” is commonly used to describe persisting symptoms after acute COVID‑19. Until now, proposed mechanisms for the explanation of Long COVID have not related quantitative measurements to basic laws. In this work, a common framework for the Long COVID pathophysiological mechanism is presented, based on the blood supply deprivation and the flow diffusion equation. Methods: Case-control studies with statistically significant differences between cases (post-COVID patients) and controls, from multiple tissues and geographical areas, were gathered and tabulated. Microvascular loss (ML) was quantified by vessel density reduction (VDR), foveal avascular zone enlargement (FAZE), capillary density reduction (CDR), and percentage of perfused vessels reduction (PPVR). Both ML and hemodynamic decrease (HD), were incorporated in the tissue blood supply reduction (SR) estimation. Results: ML data were found from 763 post-COVID patients with an average VDR, FAZE, CDR, and PPVR of 16%, 31%, 14%, and 21%, respectively. The average HD from 72 post-COVID patients was 37%. The estimated SR for multiple tissues with data from 634 post-COVID patients reached a sizeable 47%. This large SR creates conditions of lower mass diffusion rates, hypoxia, and undernutrition, which at a multi-tissue level, for a long time, can explain the wide variety of the Long COVID symptoms. Conclusions: Disruption of peripheral tissue blood supply by the contribution of both ML and HD is proposed here to be the principal cause of the mechanism leading to Long COVID symptoms.

(1) Background: Sudden Infant Death Syndrome (SIDS) represents unexplained and sudden deaths during the sleep of infants under one year of age, despite thorough investigation. Screening for prolonged QTc or Long QT Syndrome (LQTS) should be conducted on all newborns to reduce the incidence of SIDS. Neonatal electrocardiogram (ECG) could identify congenital heart defects (CHD) early, especially those not detected at birth. Infants with prolonged QT intervals typically undergo genetic analysis for Long QT Syndrome; (2) Methods: The study involved infants aged 20-40 days, born clinically healthy, with initial ECG screening. Infants with prenatal diagnoses or signs/symptoms of CHD identified immediately after birth, as well as those who underwent ECG or echocardiogram for other clinical or historical indications, were excluded from the study. The data were analyzed using SPSS version 22.0; (3) Results: Of the 42,200 infants involved, 2,245 were enrolled, with 39.9% being males. Subsequently, 164 children (37.8% males) with prolonged QT intervals underwent further diagnostic investigations. Genetic mutations were identified in 11 out of 18 tested children. The most common mutations were LQT1 (54.5%), LQT2 (36.4%), and LQT3 (1 patient). Medications used included propranolol (39.8%), nadolol (22.2%), inderal (11.1%), metoprolol (11.1%), and no treatment (16.7%). The most common abnormalities were focal right bundle branch block (54.5%), left axis deviation (9.2%), and nonspecific ventricular repolarization abnormalities (7.1%). Multiple anomalies were found in 0.47% of children with focal right bundle branch block. Structural abnormalities were associated with specific features in 267 patients (11.9%), primarily isolated patent foramen ovale (PFO) at 61.4%; (4) Conclusions: The screening has proven effective in early diagnosing Long QT Syndrome and other cardiac rhythm anomalies, with additional benefits in detecting mutations and/or QTc prolongations in family members. Identifying other ECG abnormalities and congenital heart malformations further enhances the benefits of the screening.

The novel coronavirus disease (COVID-19) pandemic has resulted in over 720 million confirmed cases and 7 million deaths worldwide, with insufficient treatment options. Innumerable efforts are being made around the world for faster identification of therapeutic agents to treat the deadly disease. Postacute sequelae of SARS-CoV-2 infection or COVID-19 (PASC), also called Long COVID, is still being understood and lacks treatment options as well. A growing list of drugs are being suggested by various in silico, in vitro and ex vivo models, however currently only two treatment options are widely used: the RNA-dependent RNA polymerase (RdRp) inhibitor remdesivir, and the main protease inhibitor nirmatrelvir in combination with ritonavir. Computational drug development tools and in silico studies involving molecular docking, molecular dynamics, entropy calculations and pharmacokinetics can be useful to identify new targets to treat COVID-19 and PASC, as shown in this paper. We have investigated bisphosphonates which can bind competitively to nidovirus RdRp-associated nucleotidyl (NiRAN) transferase domain, and systematically down selected seven candidates for further evaluation (CHEMBL608526, CHEMBL196676, CHEMBL164344, CHEMBL4291724, CHEMBL4569308, CHEMBL387132, CHEMBL98211). Interestingly, one of these (CHEMBL608526) very closely resembles the approved drug minodronate, and another (CHEMBL98211) resembles the approved drug zoledronate.

Deformation monitoring is beneficial to ensure the service safety of long tunnel. An three-direction (vertical, transverse and axial) deformation estimation method using long-gauge fiber Bragg grating (FBG) sensing technology is proposed and applied to a long tunnel by integrating mechanical analysis and field monitoring during the service state. The key issues of the proposed method for identifying the three-direction deformation are discussed, such as establishing the separation model of coupling strain on cross section, deriving the theory of deformation identification in three directions, and determining the sensor layout of the long tunnel. A major advantage of the proposed method is that the three-direction deformation of the tunnel can be monitored in real time using distributed long-gauge strain sensors. The numerical analysis and field test results verify the feasibility of the proposed method.

As the name implies, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus and a member of the corona virus family, primarily affecting the upper respiratory system and the lungs. Like many other respiratory viruses, SARS-CoV-2 can spread to other organ systems. Apart from causing diarrhea, another most common but debilitating complication caused by the SARS-CoV-2 is neurological symptoms and cognitive difficulties, which occur in up to two thirds of hospitalized covid patients and ranging from shortness of concentration, overall declined cognitive speed to executive or memory function impairment. Neuro-cognitive dysfunction and “brain fog” are frequently present in COVID-19 cases, which can last several months after the infection, leading to disruption of daily life. Cumulative evidence suggests that SARS-CoV-2 affects vasculature in the extra pulmonary systems directly or indirectly, leading to impairment of endothelial function and even multi-organ damage. The post COVID-19 long-lasting neurocognitive impairments have not been studied fully; and the underlying mechanism remains elusive. In this review, we summarize the current understanding of the effects of COVID-19 on vascular dysfunction and how vascular dysfunction leads to cognitive impairment in patients.

Cross-species investigations on cancer invasiveness are a new approach that identified new biomarkers potentially useful for improving tumor diagnosis and prognosis in clinical medicine and veterinary science. In this study, we combined proteomic analysis of four experimental rat malignant mesothelioma (MM) tumors with analysis of ten patient-derived cell lines to identify common features associated to mitochondrial proteome rewiring. The comparison of significant abundance changes between invasive and non-invasive rat tumors rat tumors gave a list of 433 proteins, including twenty-six proteins reported to be exclusively located in mitochondria. Next, we analyzed the differential expression of genes encoding the mitochondrial proteins of interest in five primary epithelioid and five primary sarcomatoid human MM cell lines, and the most impressive increase was observed in the expression of the long-chain acyl coenzyme A dehydrogenase (ACADL). To evaluate the role of this enzyme in the migration/invasiveness, two epithelioid and two sarcomatoid human MM cell lines derived from patients with the highest and lowest overall survival were studied. Interestingly, sarcomatoid vs epithelioid cell lines were characterized by higher migration and fatty oxidation rates, in agreement with ACADL findings. These results suggest that evaluating mitochondrial proteins in MM specimens might identify tumors with higher invasiveness.

Based on the example of wintering waterbirds in the Baltic Sea, we show a method that is useful in setting priorities for species management. The Value Factor (VF) shows which species in the region are the most valuable and on which ones conservation measures need to focus. Every year 4,400,000 waterbirds winter in the Baltic. Among which the highest priority species are velvet scoter Melanitta fusca (VS, VF=153) and long-tailed duck Clangula hyemalis (LTD, VF=204): 74% and 40%, respectively, of the world populations and over 90% of the EU populations of both species spend the winter there. Management plans (MP) regulating the protection of marine Natura 2000 sites (MPA) and dedicated to the protection of VS and LTD have been implemented in 65% and 51%, respectively, of MPAs in the Baltic. Poland, a key country for the survival of these species, has not implemented a single MP despite the existence of documentation confirming their crucial importance for seaducks, and on the pressures occurring there. We suggest using the VF concept to define priority species. On this basis, it will be possible to identify gaps in the protection of the most seriously threatened species and implement conservation measures in the most appropriate sites

Despite advances in algorithms and computational platforms, de-novo genome assembly remains a challenging process. Due to the constant innovation in sequencing technologies (Sanger, SOLiD, Illumina, 454, PacBio and Oxford Nanopore), genome assembly has evolved to respond to the changes in input data type. This paper includes a broad and comparative review of the most recent short-read, long-read and hybrid assembly techniques. In this review, we provide (1) an algorithmic description of the important processes in the workflow that introduces fundamental concepts and improvements; (2) a review of existing software that explains possible options for genome assembly; and (3) a comparison of the accuracy and the performance of existing methods executed on the same computer using the same processing capabilities and using the same set of real and synthetic datasets. Such evaluation allows a fair and precise comparison of accuracy in all aspects. As a result, this paper identifies both the strengths and weaknesses of each method. This comparative review is unique in providing a detailed comparison of a broad spectrum of cutting-edge algorithms and methods.

In the case of vascular plants the process of water loss by leafs and water absorption by the root is well known. There is agreement on the passive nature of long-distance moisture movement in the dead cells of the xylem; however, controversy exists focusing on the long-distance water transport principle. Hales (1726) founded a view of bulk flow based on water suction after experiments with cut twigs. The previous doctrine of long-distance water transport within vessel elements and tracheid of the xylem of intact plants – the relevant cohesion theory in text books – was developed mainly by Boehm (1893), Renner (1911) and Dixon (1914) with plant artefacts. Water movement according to this theory is based on an assumed hydrodynamic bulk fluid flow in xylem in continuous water columns (free of water vapour space), under tension, according to the law of Poiseuille (see e.g. Dixon 1914). Physically hydrodynamics is part of fluid mechanics, as a result Poiseuille’s law is usually valid only for hydrodynamic bulk flow in ideal capillaries (Sutera & Skalak, 1993). Besides the basic requirement for transport, according to cohesion theory, the existence of ideal capillaries is not compatible with either: “Because vessel elements and tracheid do not stand as ideal capillaries. …” (Bresinsky et al. 2008, translated from German). Unlike ideal capillaries, the walls of vessel elements and tracheid interact with the transported water. These walls are able to function as a source or as a sink for the transported water because of interaction with the cell walls. With the interaction, vessel elements and tracheid, part of the xylem, can shrink and swell, unlike ideal capillaries. Because the xylem (in woody plants part of the wood) is inconsistent with the basic law of fluid flow, the equation of mass balance (Zimmermann et al. 2004) and cohesion theory are not strictly followed.Many plant physiologists view the cohesion theory as appropriate, however, this theory remains controver­sial, i.e. by Eisenhut (1988), Laschimke (1990) and Hahn (1993). Nultsch (1996) gives doubts referring to the present doctrine of plant water transport. Zimmermann et al. (2004) reject the cohesion theory and conclude: “... that the arguments of the proponents of the Cohesion Theory are completely misleading” (Zimmermann et al. 2004). Hence cohesion theory can be treated as inapplicable and the question arises: how does water transport in fact function? In the following, it is gone into in more detail. A sorption hypothesis of actual water transport, based on empirical fact, shall be addressed in this paper.

Prestress loss evaluation in prestressed strand is essential for prestressed structures. However, the sensors installed outside the duct can only measure the total prestress loss. The sensors attached on strand inside the duct also have several problems, such as inadequate durability in an aggressive environment, vulnerable damage at tensioning and so on. This paper proposes a new installation method for long-gauge fiber Bragg grating (LFBG) sensor to prevent accidental damage. Then the itemized prestress losses were determined in each stage of the pre-tensioning and post-tensioning according to the LFBG measurements. We verified the applicability of the LFBG sensors for prestress monitoring and the accuracy of the proposed prestress loss calculation method during pre-tensioning and post-tensioning. In the pre-tensioning case, the calculated prestress losses had less deviation from the true losses than those obtained from foil-strain gauges, and the durability of the LFBG sensors was better than foil-strain gauges, whereas in post-tensioning case, the calculated prestress losses were close to those derived from theoretical predictions. Finally, we monitored prestress variation in the strand for 90 days. The itemized prestress losses at each stages of post-tensioning were obtained by the proposed calculation method to show the prospect of the LFBG sensors in practical evaluation.

The main features of the instrumental global mean surface temperature (GMST) are reasonably well described by a simple linear response model driven by anthropogenic, volcanic and solar forcing. This model acts as a linear long-memory filter of the forcing signal. The physical interpretation of this filtering is the delayed response due to the thermal inertia of the ocean. This description is considerably more accurate if El Ni\~{n}o Southern Oscillation (ENSO) and the Atlantic Multi-decadal Oscillation (AMO) are regarded as additional forcing of the global temperature and hence subject to the same filtering as the other forcing components. By considering these as predictors in a linear regression scheme, more than 92\% of the variance in the instrumental GMST over the period 1870-2017 is explained by this model, and in particular all features of the 1998 -- 2015 hiatus, including its death. While the more prominent pauses during 1870 -- 1915 and 1940 -- 1970 can be attributed to clustering in time of strong volcanic eruptions, the recent hiatus is an unremarkable phenomenon that is attributed to ENSO and a small contribution from solar activity.

Background Acute right heart failure (RHF) is associated with high morbidity and mortality. Temporary mechanical circulatory support (tMCS) is now part of the advanced management strategy for refractory cardiogenic shock (CS). Among such support systems, VA-ECMO remains the fastest MCS system to set up. The ProtekDuo cannula can be used as a temporary and percutaneous right ventricular assist device (RVAD) in relay with VA-ECMO in the context of prolonged weaning. Case Summary This case report describes the clinical course of a 69-year-old patient who underwent elective aortic valve replacement surgery complicated by acute RHF due to iatrogenic ligation of the right coronary artery. VA-ECMO was initiated in the context of refractory cardiogenic shock. Faced with prolonged MCS weaning, due to lack of recovery of the right ventricle associated with the absence of any other therapeutic option, a percutaneous RVAD via a ProtekDuo cannula was implanted as a bridge to recovery. The ProtekDuo was gradually weaned while the patient began rehabilitation. The patient was transferred to the medical ward after 5 weeks in the ICU, stayed 5 months in an acute medical setting, went to a rehabilitation center afterward and returned home 6 months after the initial surgery without any neurological sequalae or organ failures. In total, she remained on MCS for 39 days (21 on VA-ECMO and 18 on ProtekDuo). Discussion In cases of refractory RHF, after stabilization and organ perfusion restoration under VA-ECMO, it is feasible to switch to a percutaneous RVAD, allowing early mobilization of patients during prolonged MCS weaning until the right ventricle adapts to new loading conditions.

In the modern construction industry, lightweight aggregate concrete (LWAC) is often used in the production of load-bearing structural members. LWAC can be up to 40% lighter by volume in comparison to normal strength concrete. On the other hand, the lack of adequate numerical models often limits the practical application of innovative building materials, such as lightweight concrete, in real projects. This trend is due to the uncertainties in design standard methods and calculation errors, the level of which is generally unacceptable to civil engineers in terms of safety and reliability. In the present paper, a comparative numerical deformation analysis of a full-scale bridge deck slab and girder has been carried out. Using the physical model proposed by the authors and the finite element software ATENA, the deformations of full–scale lightweight and traditional reinforced concrete elements under short-term effects of permanent and variable loads was compared. Depending on the safety and serviceability limit requirements, it was found that the amount of longitudinal reinforcement in lightweight reinforced concrete elements can be reduced compared to normal reinforced concrete elements with the same parameters. The results of the numerical analysis show that the deformation analysis model proposed by the authors can be a reliable tool for the design of lightweight concrete flexural members by selecting the optimum geometrical and reinforcement parameters limited by the stiffness condition.

Balancing the levels of ammonia, in poultry facilities plays a role in enhancing the welfare and productivity of animals. Various environmental factors such as temperature, humidity, ammonia concentrations, carbon dioxide concentration and exposure to light have an impact on the wellbeing and efficiency of poultry. It is essential to monitor these elements to achieve outcomes necessitating practical, reliable and cost-effective solutions. Leveraging the Internet of Things (IoT) in conjunction with LoRa-WAN (Long Range Wide Area Network) technology presents an opportunity in the industry by enhancing connectivity among devices and facilitating real time data transmission. This research introduces a hardware and software setup for monitoring conditions at poultry farms through LoRa WAN and IoT technologies. More-over researchers employed Random Forest Machine Learning prediction models to tune the concentration of Ammonia (NH3) in poultry facilities across a wide area or multiple Poultry houses. Comparative assessments were conducted to evaluate the proposed system against devices revealing a correlation exceeding 0.9830 between the sensors and standard equipment while costing 28% less than traditional tools. The prototype displayed outcomes underscoring its potential, for managing poultry facilities across multiple farms with centralized oversight.

It is meaningful to monitor and identify the concrete cracks as they will seriously reduce the fatigue life of pavement. In this paper a new method based on distributed long-gauge optic fiber sensing is proposed to implement the crack identification. Firstly, the damage indicator, namely strain curve envelope area ratio (SCEAR), is proposed and calculated with the measured strain in time series when the plane goes across the pavement where the sensors are installed. Then the indicators with different sensors are normalization by the value of the indicator from one referenced sensor where damage normally will not happen. If the crack happens within the sensing gauge of the sensor, the value of damage indicator SCEAR from the sensor will increase. Therefore, the crack will be identified with the change of the damage indicator. The effect of the proposed method is first verified by some simulations of prefabricated pavement as the cracks can be accurately identified by the proposed method. Moreover, the influence from the aircraft, such as taxiing position, aircraft load and aircraft type, is not obvious enough to mislead the identification results. Lastly the static loading tests were implemented with one small-scale model of prefabricated concrete pavement in the lab. From the experimental results the prefabricated cracks inside the pavement slab can be identified accurately with the proposes method as the parameter SCEAR is increased by about 100% at the crack position, while it is only changed by about 3% at the undamaged position.

Coronaviruses constitute a global threat to human and animal health. It is essential to investigate the long-distance RNA-RNA interactions that approximate remote regulatory elements in strategies, including genome circularization, discontinuous transcription, and transcriptional enhancers, aimed at rapid replication of their large genomes, pathogenicity, and immune evasion. Based on the primary sequences and modeled RNA-RNA interactions of two experimentally de-fined coronaviral enhancers, we detected via in silico primary and secondary structural analysis potential enhancers in various coronaviruses, from the phylogenetically ancient avian IBV to the recently emerged SARS-CoV-2. These potential enhancers possess a core duplex-forming region that could transition between closed and open states, as molecular switches directed by viral or host factors. The open state would permit the enhancer to pair with remote sequences in the viral genome and modulate the expression of crucial genes involved in viral replication and host immune evasion. Consistently, variations in the predicted IBV enhancer region or its distant targets coincide with cases of viral attenuation possibly driven by decreased expression of the ORF3a immune evasion protein. The annotated enhancer sequences could inform structural prediction tools and antiviral interventions if validated experimentally.

Exosomal microRNAs (miRNAs) from cancer cells play a key role in mediating the oral squamous cell carcinoma (OSCC) microenvironment. The objective aimed to investigate how long non-coding RNA (lncRNA) MEG3 affects OSCC angiogenesis through exosomal miR-421. Global miRNA microarray analysis and quantitative real-time PCR (qRT-PCR) were performed to determine the level of miRNAs in OSCC cells-derived exosomes. Cell migration, invasion, tube formation, immunohistochemistry and hemoglobin concentration were used to study the effects of exosomal miR-421 in angiogenesis. Western blotting was used to determine the expression level of HS2ST1 and VEGFR2-related downstream proteins. MiRNA array and qRT-PCR identified upregulation of miR-421 in OSCC cell-derived exosomes. Furthermore, exosome-miR-421 can be taken up by human umbilical vein endothelial cells (HUVEC) and then targets HS2ST1 through VEGF-mediated ERK and AKT phosphorylation, thereby promoting HUVEC migration, invasion, and tube formation. Additionally, enforced expression of lncRNA MEG3 in OSCC cells reduced exosomal miR-421 levels and then increased HS2ST1 expression, thereby reducing the VEGF/VEGFR2 pathway in HUVEC. Our results demonstrate a novel mechanism by which lncRNA MEG3 can act as a tumor suppressor and regulate endothelial angiogenesis through the exosomal miR-421/HS2ST1 axis, which provides a potential therapeutic strategy for OSCC angiogenesis.

The knowledge of COVID-19 impact on the human body has increased rapidly. Although many people recover from COVID-19, some continue to experience persistent symptoms that have been identified as Long COVID. This condition can have a severe impact on quality of life, and it remains a significant concern for medical professionals and researchers. One of the key components of the SARS-CoV-2 virus that enables it to enter human cells is the spike (S) protein. Recent studies have revealed a complex network of interactions between G proteins, spike (S) protein, and the Renin-Angiotensin System (RAS) may be responsible, at least in part, for long COVID. SARS-CoV-2 can also affect the brain, leading to neurological symptoms such as confusion, memory loss, and fatigue. Increasing evidence suggests that COVID-19 is not just a respiratory illness since it is likely that the virus could influence signal transduction pathways such as G-protein-coupled receptor (GPCR), among others, in the brain, either directly or indirectly, affecting neural functions. These interactions with the spike (S) protein and RAS, alongside the brain, are complex and require deep research to understand their implications for Long COVID-19 manifestation fully. While recent research has shed light on the complex interactions between G proteins, spike (S) protein, the brain, and the angiotensin system, this article explores these interconnected pathways and their implications for long COVID-19 manifestations. The present review summarises current research on different molecular mechanisms in Long COVID pathophysiology and may help identify possible targets or new strategies for the diagnosis and treatment.

Docosahexaenoic acid (DHA) is an essential fatty acid (FA) with proven health effects, whom bioavailability improvement is becoming a public health issue. Unlike fish oils, the bioavailability of DHA from microalgal (A) has not been fully assessed, particularly with regard to the molecular structuring capabilities offered by A-oil. We explored the impact of 5 formulas rich in DHA, different by i) the molecular structure: ethyl ester (EE) or monoglyceride (MG) or Triglyceride (TG) and ii) the supramolecular form: emulsified TG or TG+phospholipids (blend PL), on the lymphatic kinetics of DHA absorption and the lipid characteristics of resulting lipoproteins. We demonstrated that in rat, the DHA absorption of the conventional A-DHA TG structure was more effective than the EE structure (+ 23%). More, the A-DHA MG and A-DHA Emulsion were the most favourable DHA-vectors (AUC: 89% and +42%, respectively), thanks to an improved lipolysis. The A-DHA MG and -Emulsion presented the richest DHA content in TG (+40%) and PL (+50%) of lymphatic chylomicrons, which could impact the metabolic fate of DHA. We concluded that structuring A-DHA in TG or EE would be more prone for tissue and hepatic metabolism whereas in A-DHA MG and A-DHA Emulsion could target nerve tissues.

Post-viral fatigue syndrome (PVFS) encompasses a wide range of complex neuroimmune disorders of unknown cause characterized by disabling post-exertional fatigue, myalgia and joint pain, cognitive impairments, unrefreshing sleep, autonomic dysfunction, and neuropsychiatric symptoms. It includes myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS), fibromyalgia (FM), and more recently post-COVID-19 condition (Long COVID). To date, there are no definitive clinical case criteria and no FDA-approved pharmacological therapies for PVFS. Given the current lack of effective treatments, there is a need to develop novel therapeutic strategies for these disorders. Mitochondria, the cellular organelles responsible for tissue energy production, have recently garnered attention in research into PVFS due to their crucial role in cellular bioenergetic metabolism in these conditions. Accumulating literature has identified a link between mitochondrial dysfunction and low-grade systemic inflammation in ME/CFS, FM, and Long COVID. To address this issue, this article aimed to critically review the evidence relating to mitochondrial dysfunction in the pathogenesis of these disorders; in particular, to evaluate the effectiveness of coenzyme Q10 supplementation on chronic fatigue and pain symptoms as a novel therapeutic strategy for the treatment of PVFS.

Aging induces numerous physiological alterations, with immunosenescence emerging as a pivotal factor. This phenomenon has attracted both researchers and clinicians, prompting pro-found questions about its implications for health and disease. Among the contributing factors, one intriguing actor in this complex interplay is human cytomegalovirus (CMV), a member of the herpesvirus family. Latent CMV infection exerts a profound influence on the aging immune system, potentially contributing to age-related diseases. This review delves into the intricate relationship between immunosenescence and CMV, revealing how chronic viral infection im-pacts the aging immune landscape. We explore the mechanisms through which CMV can im-pact both the composition and functionality of immune cell populations and induce shifts in in-flammatory profiles with aging. Moreover, we examine potential role of CMV in such pathol-ogies as cardiovascular diseases, cancer, neurodegenerative disorders, COVID-19, and Long COVID. This review underlines the importance of understanding the complex interplay be-tween immunosenescence and CMV. It offers insights into the pathophysiology of aging and age-associated diseases, as well as COVID-19 outcomes among the elderly. By unraveling the connections between immunosenescence and CMV, we gain a deeper understanding of aging's remarkable journey and the profound role that viral infections play in transforming the human immune system.

As sessile organisms, plants face a wide range of abiotic stresses, with salinity being a prominent constraint affecting their growth, development, and productivity, particularly in arid and semi-arid regions. This study focused on understanding how salinity impacts Jatropha curcas, an important oilseed plant for biodiesel production. By examining the anatomy and ultrastructure of stomata and chloroplasts, we investigated the effects of prolonged salinity stress on J. curcas. This stress led to changes in stomatal density, stomatal index, and ostiole aperture, which case an imbalance of water conductivity in the xylem. Through transmission electron microscopy, we explored the subcellular organization of J. curcas chloroplasts and their contribution to plant photosynthetic efficiency, providing insights into their role in this process. Notably, salinity treatment resulted in a significant increase in starch granules accumulation, leading to impaired the granal and stromal grana lamellae, destroying this ultrastructure. Our findings indicate that the anatomy and ultrastructure of chloroplasts play a crucial role in influencing photosynthetic efficiency and hydraulic conductivity. This study offers new perspectives on the structure and function of chloroplasts in J. curcas, presenting innovative opportunities to develop strategies that enhance biofuel production in areas with high soil salinity.

This paper presents a methodology for indirectly estimating the scale of seabird bycatch using existing data, eliminating the need for regular monitoring. The study focuses on five species of ducks that winter in the Polish waters of the Baltic Sea and are highly susceptible to bycatch: Long-tailed Duck, Velvet Scoter, Common Scoter, Greater Scaup, and Tufted Duck. The evaluation units used are divided into the Bornholm and Gotland Groups within the Polish Exclusive Economic Zone (PEEZ). The analysis acknowledges the lack of data for certain areas known to have high concentrations of diving birds and fishing activity. The population sizes of waterbirds were assessed using ship-based surveys and a distance sampling approach. Fishing effort data from the winter seasons between 2015/2016 and 2019/2020 were analyzed. Bycatch rates were estimated based on surveys conducted in previous seasons, and threshold values for bycatch were established using the concept of "small numbers" defined in EU directives. The results show that within the Gotland subdivision of the PEEZ, the estimated average abundance of all diving waterbirds was 207,114 individuals, with an average bycatch of 7,921 birds (3.8% of the total). The Velvet Scoter was the most abundant species, followed by the Long-tailed Duck. Benthivorous ducks constituted the majority of the bird population in the area. In the Bornholm subdivision, the estimated average abundance of diving waterbirds was 600,845 individuals, with an average bycatch of 5,056 birds (0.8% of the total). The Long-tailed Duck was the most numerous species, followed by the Velvet Scoter. Benthivorous ducks also dominated in this area. The findings highlight the need for effective management and conservation measures to address the high mortality of seabirds due to bycatch. The methodology presented in this study offers a valuable approach for estimating bycatch scale and can support efforts to minimize the impact on seabird populations in the Baltic Sea.