Our results demonstrated that SWT stimulates osteoblastogenesis and increase the cell number of osteoblasts, suggesting positive regulatory effects on osteoblast differentiation. However, the effect of SWT on bone formation need further examination, since the expression of alp gene is downregulated. On the other hand, SWT appears to negatively regulate osteoclast differentiation and bone resorption, as number of osteoclasts and the expression of critical bone resorptive genes are all downregulated. Collectively, SWT might change the equilibrium of bone remodeling and increase the bone mass. Our data provided supportive evidences that this medicine formulation can be applied to treat osteoporosis or bone destructive diseases.

GaN ultraviolet photodetector with metal-semiconductor-metal structure is achieved by growing on a periodic trapezoid column-shape patterned sapphire substrate using metalorganic chemical vapor deposition. Under 5-V reverse bias, the photodetector fabricated on such patterned sapphire substrate exhibits a lower dark current, a higher photocurrent, and a 476 % enhancement in the maximum responsivity as compare with those of the photodetector fabricated on conventional flat sapphire substrate. It is also found that the much larger UV-to-visible rejection ratio and the fact that responsivity drops in a smaller cut-off region are observed from photodetector fabricated by using a periodic trapezoid column-shape patterned sapphire substrate. These phenomena may all be attributed to the reduction of threading dislocation density and the improved quality of GaN film, as well as the internal reflection and/or scattering effect on the interface between GaN film and the periodic trapezoid column-shape pattern of the substrate.

Wireless sensor networks are widely used in many applications such as environmental monitoring, health care, smart grid and surveillance. Many security protocols have been proposed and intensively studied due to the inherent nature of wireless networks. In particular, Wu et al. proposed a promising authentication scheme which is sufficiently robust against various attacks. However, according to our analysis, Wu et al.'s scheme has two serious security weaknesses against malicious outsiders. First, their scheme can lead to user impersonation attacks. Second, user anonymity is not preserved in their scheme. In this paper, we present these vulnerabilities of Wu et al.'s scheme in detail. We also propose a new scheme by fixing such vulnerabilities and improving the performance of the protocol.

Biotechnological potential of Thermoanaerobacter strain AK15 to produce ethanol and valuable alcohols from carbohydrates and amino acids were evaluated in present study. The strain is highly ethanologenic, producing a maximum of 1.57 mol ethanol per mol of glucose degraded at high liquid-gas phase ratios. The strain degrades most of the sugars tested as well as starch and pretreated hydrolysates of biopolymers (Whatman paper, newspaper, Timothy grass, Rhubarb leaves, and several macroalgae species) to ethanol mainly. The strains degraded serine and threonine when used as a single substrate, producing mainly acetate and ethanol as end products, and the branched-chain amino acids (leucine, isoleucine, valine) when cultivated in the presence of thiosulfate. The main end products from branched-chain amino acids were a mixture of their corresponding branched-chain fatty acids and alcohols. Finally, the strain was also shown to use butyrate as an electron sink during glucose degradation resulting in the reduced product butanol in addition to end products produced from glucose. Thus, strain AK15 is a promising candidate for ethanol and fine chemical production from a range of lignocellulosic and algal biomass.

Soil CO2 efflux (FCO2) plays a dominant role in the terrestrial carbon (C) cycle but interpreting constraints on local observations is impeded by challenges in disentangling belowground CO2 sources. Trees contribute most C to forest soils, so linking aboveground properties to FCO2 could open new avenues to study plant-soil feedbacks and facilitate scaling; furthermore, FCO2 responds dynamically to meteorological conditions, complicating predictions of total FCO2 and forest C balance. We tested for proximity effects of individual Acer saccharum Marsh. trees on FCO2, comparing FCO2 within 1 m of mature stems to background fluxes before and after an intense rainfall event. Wetting significantly increased background FCO2 (6.4±0.3 vs. 8.6±0.6 s.e. μmol CO2 m-2s-1), with a much larger enhancement near tree stems (6.3±0.3 vs. 10.8±0.4 μmol CO2 m-2s-1). FCO2 varied significantly among individual trees and post-rain values increased with tree diameter (with a slope of 0.058 μmol CO2 m-2s-1 cm-1). Post-wetting amplification of FCO2 (the ‘Birch effect’) in root zones often results from the improved mobility of labile carbohydrates and further metabolization of recalcitrant organic matter, which may both occur at higher densities near larger trees. Our results indicate that plant-soil feedbacks change through tree ontogeny and provide evidence for a novel link between whole-system carbon fluxes and forest structure.

This paper explores the suppression of ideas within academic scholarship by academics, either by self-suppression or because of the efforts of other academics. Legal, moral, and social issues distinguishing freedom of speech, freedom of inquiry, and academic freedom are reviewed. How these freedoms and protections can come into tension is then explored by an analysis of denunciation mobs who exercise their legal free speech rights to call for punishing scholars who express ideas they disapprove of and condemn. When successful, these efforts, which constitute legally protected speech, will suppress certain ideas. Real-world examples over the past five years of academics who have been sanctioned or terminated for scholarship targeted by a denunciation mob are then explored.

Introduction Prostate Cancer (PCa) exhibits one of the widest racial and socioeconomic disparities. PCa disparities have also been widely linked to location as living in more deprived regions was associated with lower healthcare access and worse outcomes. This study aims to examine PCa survival across various US counties in function of different socioeconomic profiles and discuss the role of potential intermediary factors. Methods The SEER database linked to county-level SES was utilized. Five-year PCa-specific survival using the Kaplan Meier method was performed for 5 racial/ethnic categories in function of SES quintiles. Multilevel Cox proportional hazards regression was performed to assess the relationship between county-level SES and PCa survival. Multivariate regression analysis was performed to examine the role of healthcare utilization and severity. Results 279,000 PCa records were extracted, 5-year PCa-specific survival was 94%. Overall, living in counties with worst poverty/income quintile and highest proportions of foreign-born/language-isolated increased PCa mortality by 23% each. No association was observed with county-level High-School education, while Bachelor’s-level education decreased mortality risk by 23%. Associations varied considerably upon racial/ethnic stratification. Multilevel analyses showed varying contributions of individual and area-level factors to survival within minorities. The relationship between SES and PCa survival appeared to be influenced by healthcare utilization and disease stage/grade. Discussion Racial/ethnic categories responded differently under similar county-level SES and individual-level factors to the point where disparities reversed in Hispanics. The inclusion of Healthcare utilization and severity factors may provide partial early support for their role as intermediaries. Healthcare access (insurance) might not necessarily be associated with better PCa survival, through performing biopsy and or/surgery. County-level education plays an important role in PCa decision-making as it might elucidate discussions of other non-invasive management options. Conclusion Findings of this study demonstrate that interventions need to be tailored according to each group's needs. This potentially informs the focus of public health efforts in terms of planning and prioritizing. This study could also direct further research delving into pathways between area-level characteristics with PCa survival.

Foundational and state-of-the-art anomaly detection methods through power system state estimation are reviewed. The traditional components for bad data detection such as chi-square testing, residual-based methods, and hypothesis testing are discussed to explain the motivations for recent anomaly detection methods given the increasing complexity of power grids, energy management systems, and cyber-threats. In particular, state estimation anomaly detection based on data-driven quickest change detection and artificial intelligence are discussed and directions for research are suggested with particular emphasis on considerations of the future smart grid.

In this paper we focus on an implicit assumption in the BSM framework that limits the scope of market network connections to seeking gains in the currency basis, i.e., on trading strategies between the numeraire and the stock and between the numeraire and the option, separately. We relax this assumption and derive the equivalent of the standard BSM approach under a more general market network framework in order to assess its implications. In doing so, we find that it is not possible to hedge the implicit option that allows one to directly trade the option and stock. This represents a potential challenge to the BSM framework, since the missing market network connection provides a potentially useful mechanism for risk-bearing portfolio managers to alter their portfolios.

This paper examines an important problem in smart grid energy scheduling; peaks in power demand are proportionally more expensive to generate and provision for. The issue is exacerbated in local microgrids that do not benefit from the aggregate smoothing experienced by large grids. Demand-side scheduling can reduce these peaks by taking advantage of the fact that there is often flexibility in job start times. We focus attention on the case where the jobs are non-preemptible, meaning once started, they run to completion. The associated optimization problem is called the Peak Demand Minimization problem and has been previously shown to be NP-hard. Our results include an optimal fixed-parameter tractable algorithm, a polynomial-time approximation algorithm, as well as an effective heuristic that can also be used in an online setting of the problem. Simulation results show these methods can reduce peak demand by up to 50% versus on-demand scheduling for household power jobs.

In recent years, many researchers have begun to shift their focus onto the synthesis of nanomaterials as this field possesses immense potential that may provide incredible technological advances in the near future. The downside of conventional synthesis techniques, such as co-precipitation, sol-gel and hydrothermal methods, is that they necessitate the use of toxic chemicals, produce harmful by-products and require a considerable amount of energy; therefore, more sustainable fabrication routes are sought after. Biological molecules have been previously utilised as precursors to nanoparticle synthesis, thus eliminating the negative factors involved in traditional methods. In addition, transition-metal nanoparticles possess a wide scope of applications due to their multiple oxidation states and large surface areas; thereby allowing for a higher reactivity when compared to their bulk counterpart and rendering them an interesting research topic. However, this field is still relatively unknown and unpredictable. Therefore, this review aims to obtain a better understanding on the plant-mediated synthesis process of the major transition-metal and transition-metal oxide nanoparticles, and how different parameters affect their unique properties.

Pyrolyzed waste biomass, or biochar, has been suggested as a means to increase plant growth and to mitigate soil salinization, which is a widespread agricultural issue and can reach extreme levels in urban soils impacted by de-icing salts. Soil mixing is enhanced by reduced biochar particle size; however, biochar properties vary with particle size and recent studies suggest that plant growth responses may be maximized at intermediate particle sizes. We examined the responses of two plant species (cowpea (Vigna unguiculata) and velvetleaf (Abutilon theophrasti)) to biochar amendments that spanned a wide range of particle sizes obtained by sieving, with and without de-icing salt additions. The smallest size fractions of biochar reduced plant growth relative to unamended controls. Plant biomass production was generally maximized at intermediate biochar particle size treatments, with particles sizes of 0.5-2.0 mm showing the best response. Mitigation of salt effects was also improved at intermediate biochar particle sizes in this particles size range. Our results emphasize the importance of optimizing biochar particle size to best enhance plant responses to biochar, with particular reference to saline soils.

Many tropical invasive species have allelopathic effects that contribute to their success in native plant communities. Pyrolyzed biomass (“biochar”) can sorb toxic compounds, including allelochemicals produced by invasive plants, potentially reducing their inhibitory effects on native species. Strawberry guava (Psidium cattleianum) is among the most important allelopathic invasive species in tropical islands and recognized as the most serious invasive species threat in the global biodiversity hotspot of Mauritius. We investigated the effects of additions of locally produced biochar on native tree species in a field experiment conducted in areas invaded by strawberry guava within Mauritius’ largest national park. Growth and survivorship of native tree species were monitored over 2 ½ years in plots subjected to four treatments: non-weeded, weeded, weeded + 25 t/ha biochar and weeded + 50 t/ha biochar. Native tree growth and survivorship were strongly suppressed by strawberry guava. Biochar treatments dramatically increased native tree performance, with more than a doubling in growth, and substantially increased native tree survivorship and species diversity, while suppressing strawberry guava regeneration, consistent with growth-promoting properties and sorption of allelochemicals. We conclude that biochars, including “sustainable biochars” produced from locally accessible biomass using low-tech pyrolysis systems, have considerable potential to counteract effects of allelopathic invaders and increase the capacity for native species regeneration in tropical island ecosystems.

The 2019-nCoV has been identified as the cause of an outbreak of respiratory illness in Wuhan, Hubei Province, China beginning in December 2019. This epidemic had spread to 19 countries with 11,791 confirmed cases, including 213 deaths, as of January 31, 2020. The World Health Organization declared it as a Public Health Emergency of International Concern. This study analyzed and discussed 70 research articles published until January 31, 2020 for a better understanding of the epidemiology, causes, clinical diagnosis, prevention and control of this virus. Studies thus far have shown origination in connection to a seafood market in Wuhan, but specific animal association has not been confirmed. The reported symptoms include fever, cough, fatigue, pneumonia, headache, diarrhea, hemoptysis, and dyspnea. Preventive measures such as masks, hand hygiene practices, avoidance of public contact, case detection, contact tracing, and quarantines are effective for reducing the transmission. To date, no specific antiviral treatment is proven effective, hence, infected people primarily rely on symptomatic treatment and supportive care. Although these studies had relevance to control a public emergency, more research need to be conducted to provide valid and reliable ways to manage this kind of public health emergency in both short- and long- term.

Volatile compounds, abundant in breath, can be used to accurately diagnose and monitor a range of medical conditions. This offers a non-invasive, low-cost approach with screening applications; however, uptake of this diagnostic approach has been limited by conflicting published outcomes. Most published reports rely on large scale screening of the public, at single time points and without reference to ambient air. Here, we present a novel approach to volatile sampling from cellular headspace and mouse breath that incorporates multi-time point analysis and ambient air subtraction revealing compound flux as an effective proxy of active metabolism. This approach to investigating breath volatiles offers a new avenue for disease biomarker discovery and diagnosis. Using gas chromatography mass spectrometry (GC/MS), we focus on low molecular weight, metabolic substrate/by-product compounds and demonstrate that this non-invasive technique is sensitive (reproducible at ~1 µg cellular protein, or ~500,000 cells) and capable of precisely determining cell type, status and treatment. Isolated cellular models represent components of larger mammalian systems and we show that stress- and pathology-indicative compounds are detectable in mice, supporting further investigation using this methodology as a tool to identify volatile targets in human patients.

As our understanding of the thalamocortical system deepens, the questions we face become more complex. Their investigation requires the adoption of novel experimental approaches complemented with increasingly sophisticated computational modeling. In this review, we take stock of current data and knowledge about the circuitry of the somatosensory thalamocortical loop in rodents, discussing common principles across modalities and species whenever appropriate. We review the different levels of organization, including the cells, synapses, neuroanatomy, and network connectivity. We provide a complete overview of this system that should be accessible for newcomers to this field while nevertheless being comprehensive enough to serve as a reference for seasoned neuroscientists and computational modelers studying the thalamocortical system. We further highlight key gaps in data and knowledge that constitute pressing targets for future experimental work. Filling these gaps would provide invaluable information for systematically unveiling how this system supports behavioral and cognitive processes.

Matrix metalloproteinases (MMPs) have been demonstrated to have both detrimental and protective functions in inflammatory diseases. Several MMP inhibitors, with the exception of Periostat®, have failed in Phase III clinical trials. As an alternative strategy, recent efforts have been focussed on the development of more selective inhibitors or targeting other domains than their active sites (e.g., exosites, ectosites) through specific small molecule inhibitors or monoclonal antibodies. Here, we present some examples that aim to better understand the mechanisms of conformational changes/allosteric control of MMPs functions. In addition to MMP inhibitors, we discuss unbiased global approaches such as proteomics and N-terminomics to identify new MMP substrates and achieve a better understanding of the roles of these proteases in diseases.

Sustainable development advocates for an environmentally friendly and resource-saving approach, fostering a new quality of productivity that is green and sustainable, and achieving a sustainable development where the economy and the environment are in harmony. The paper is based on clarifying the effects of coordinated development between the economy and the environment, and by establishing an indicator system, applying a remote sensing ecological index, entropy weight method, gray relational degree model, and a coupling coordination model, the relationship of coordinated development of Ordos in 2016-2022 is analyzed from a spatial-temporal perspective. The results are as follows: ① The years of coordinated development between the ecological environment and the economy are in the majority, while the uncoordinated years are fewer. ② The level of coordinated development between the ecological environment and the economy in the various regions of Ordos has been increasing year by year, but it still remains at the barely coordinated and primary coordinated levels. ③ The types of coordinated development between the ecological environment and the economy in Ordos exhibit significant spatial differentiation in terms of spatial distribution and clustering.Therefore, it is necessary to formulate coordinated development policies and measures according to the constraining factors of different regions.

The gastrointestinal (GI) tract is innervated by the enteric nervous system (ENS), an extensive neuronal network that traverses along its walls. Due to local reflex circuits, the ENS is capable of functioning with and without input from the central nervous system. The functions of the ENS range from the propulsion of food to nutrient handling, blood flow regulation and immunological defense. Records of it first being studied emerged in the early 19th century when the submucosal and myenteric plexuses were discovered. This was followed by extensive research and further delineation of its development, anatomy, and function during the next two centuries. The morbidity and mortality associated with the underdevelopment, infection or inflammation of the ENS highlights its importance and the need for us to completely understand its normal function. This review will provide a general overview of the ENS to date and connect specific GI disorders such as short bowel syndrome with neuronal pathophysiology. Exciting opportunities in which the ENS could be used as a therapeutic target for common GI diseases will also be highlighted, as the further unlocking of such mechanisms could open the door to more therapy-related advances, and ultimately change our approach to GI disorders.

Single particle tracking (SPT) is a powerful class of methods for studying the dynamics of biomolecules inside living cells. The techniques reveal the trajectories of individual particles, with a resolution well below the diffraction limit of light, and from them the parameters defining the motion model, such as diffusion coefficients and confinement lengths. Most existing algorithms assume these parameters are constant throughout an experiment. However, it has been demonstrated that they often vary with time as the tracked particles move through different regions in the cell or as conditions inside the cell change in response to stimuli. In this work, we propose an estimation algorithm to determine time-varying parameters of systems that discretely switch between different linear models of motion with Gaussian noise statistics, covering dynamics such as diffusion, directed motion, and Ornstein-Uhlenbeck dynamics. Our algorithm consists of three stages. In the first stage, we use a sliding window approach, combined with Expectation Maximization (EM) to determine maximum likelihood estimates of the parameters as a function of time. These results are only used to roughly estimate the number of model switches that occur in the data to guide the selection of algorithm parameters in the second stage. In the second stage, we use change detection (CD) techniques to identify where the models switch, taking advantage of the off-line nature of the analysis of SPT data to create non-causal algorithms with better precision than a purely causal approach. Finally, we apply EM to each set of data between the change points to determine final parameter estimates. We demonstrate our approach using experimental data generated in the lab under controlled conditions.

Generating a range-wide population status of the diamondback terrapin (Malaclemys terrapin spp.) is challenging due to a combination of species ecology and behavior, and limitations associated with traditional sampling methods. Visual counting of emergent heads offers an efficient, non-invasive and promising method for generating abundance estimates of terrapin populations across broader spatial scales and can be used to explain spatial variation in population size. We conducted repeated visual head count surveys at 38 predetermined sites along the shoreline of Wellfleet Bay in Wellfleet, Massachusetts. We analyzed the count data using a hierarchical modeling framework designed specifically to analyze repeated count data: the so-called N-mixture model. This approach allows for simultaneous modeling of imperfect detection to generate estimates of true terrapin abundance. We found detection probability was lowest when skies were overcast and when wind speed was highest. Site specific abundance varied but we found that abundance estimates were, on average, higher in unexposed sites compared to exposed sites. We demonstrate the utility of pairing visual head counts and N-mixture models as an efficient method for estimating terrapin abundance and show how the approach can be used to identifying environmental factors that influence detectability and distribution.

Pyrolyzed organic matter – commonly referred to as biochar – generally has positive effects on plant growth and can enhance early seedling development. Biochar-based seed coatings may thus be beneficial, specifically under adverse soil conditions such as high soil salinity. We evaluated germination and early plant development in radish (Raphinus sativa) seeds coated with conifer-feedstock slow-pyrolysis biochar; following the precedent of prior studies, polyvinyl acetate (PVAc) was used as the binding agent. Biochar-based seed coatings reduced germination rates and radicle extension in Petri dish trials; however, leaching of coated seeds largely eliminated this effect. PVAc applied in solution inhibited seed germination to a similar extent, suggesting that toxicity of PVAc or chemical products derived from it is the main mechanism for germination inhibition; a meta-analysis of published literature also indicates negative effects of biochar-based seed coatings using PVAc. In greenhouse trials the same biochar seed coatings improved aspects of plant growth and physiological status relative to controls, specifically enhancing root development. We conclude that biochar-based seed coatings have promise in promoting early seedling growth, and in combating salinity stress in agronomic and restoration applications. However, our findings contraindicate PVAc use as a binding agent. Further research is needed to test non-phytotoxic, readily biodegradable binding agents and to optimize biochars and seed coating processes for specific applications in agronomy and ecological restoration.

This study is part of a project designed to simulate the long-term landform equilibrium of a rehabilitated mine site. The project utilizes event fine suspended sediment (FSS) fluxes in a receiving stream following a rainfall event as an indicator of landform stability. The aim of this study was to use HEC-HMS to determine sediment and discharge quantity upstream to determine how it affects the downstream development of the catchment landform, in terms of sediment changes and geomorphology. Thus, the study focused on hydrology and sediment modelling of the upper catchment with HEC-HMS (Hydrologic Engineering Center-Hydrologic Modeling System) to determine daily discharge and sediment output at the catchment outlet. HEC-HMS was used to calibrate the stream discharge and FSS quantities at the catchment outlet to observed continuous discharge and FSS values. Calibration of the HEC-HMS model was done for two water years and then the same model parameters were used to validate the model for a third water year. Catchment discharge and FSS were calibrated and validated for continuous rainfall events against observed discharge and FSS data at the catchment outlet. The model was then run for a projected rainfall of 50 years. The denudation rate predicted by the model falls in the range previously determined for the region. The simulated sediment output was compared to the rainfall trends over the years. As a result, the sediment spikes following a rainfall-runoff event gradually decreased over time. Reducing FSS spikes indicate that the landform gradually attains stability. This modeling study can be used for long-term simulations to determine erosion equilibrium over the years and to quantify sediment yield in catchments for projected wet and dry rainfall scenarios.

Breast cancer pathogenesis, treatment, and patient outcomes are shaped by tumor-intrinsic genomic alterations that divide breast tumors into molecular subtypes. These molecular subtypes often dictate viable therapeutic interventions, and ultimately, patient outcomes. However, heterogeneity of therapeutic response may be a result of underlying epigenetic features that may further stratify breast cancer patient outcomes. In this review we examine non-genetic mechanisms that drive functional changes to chromatin in breast cancer to contribute to cell and tumor fitness, and highlight how epigenetic activity may inform therapeutic response. We conclude by providing perspectives on the future of therapeutic targeting of epigenetic enzymes, an approach which holds untapped potential to improve breast cancer patient outcomes.

Cymbidium faberi Rolfe is one of the traditional Chinese orchids with important ornamental value, and the cultivation of Cymbidium faberi Rolfe mutant strains with different appearances is essential to increase its economic value, but at present, the acquisition of Cymbidium faberi Rolfe mutant strains basically relies on natural mutation.The objectives of this research were to mutagenize Cymbidium faberi Rolfe protocorm-like bodies (PLBs) and shoots in vitro using sodium azide (NaN3), and to screen and evaluate mutants in mutagenized Cymbidium faberi Rolfe seedlings using morphological characteristics.Cymbidium faberi Rolfe PLBs and shoots were used as mutagenic materials, and co-cultivated in induced shoots growth medium with the addition of 0.0 (control), 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 mg/L and 0.0 (control), 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, and 10.0 mg/L NaN3 to induce the mutations, and the mortality rates of the PLBs and shoots were increased with the increase of the NaN3 concentration.At 14 d of co-cultivation, PLBs and shoots were most efficiently mutagenized with 1.5 mg/L and 4.0 mg/L NaN3, respectively.After the explants were cultured for 3 months, changes in leaf and flower morphology were observed in some mutants: shorter and thicker leaves, shorter node length, reduced height, and mid-translucent leaves compared with controls; and some Cymbidium faberi Rolfe bloomed prematurely, with single flowers with large, thick petal sepals and small inflorescences, and colours include light green throughout, and a few with purple stamens.This suggests that NaN3 can effectively mutagenise Cymbidium faberi Rolfe PLBs and shoots to satisfy people's demand for Cymbidium faberi Rolfe's ornamental properties while increasing its economic value.

Wild-caught shrimp and prawns are the single most numerous group of animals directly killed for human food consumption on the planet. Recent scientific developments have led to greater understanding of the probability that at least some species of shrimp are sentient beings and, should that be the case, policies that could improve shrimp welfare. We begin with an overview of global shrimp fisheries and their characteristics. The world's shrimp fisheries can be understood as a spectrum between large, industrial trawlers in developed and developing countries (e.g. Western Europe, the Americas, Russia) and small-scale fisheries for subsistence in developing countries (e.g. South-East Asia, East Africa). Each has different implications for animal welfare, particularly in light of human wellbeing challenges associated with shrimp fisheries. Secondly, we turn to the emerging science of shrimp welfare and examine recent developments in government and industry policy. In large-scale trawl fisheries, animal welfare can be improved by installing electrical stunning equipment; continuing existing work on bycatch reduction; and optimising on-board processes to reduce the stress endured by shrimp during capture and slaughter. In small-scale fisheries, improving government capacity and supply chain practices may bring benefits for communities in the short-term while opening up opportunities for more specific shrimp welfare policies in the long-term. Thirdly, we provide a new dataset of the estimated numbers of individual shrimp caught by country and species. Drawing on this data, we provide a description of the shrimp fishing industry in the world's top 25 countries by estimated catch of individual shrimp. By our estimates, the wild-catch shrimp industry catches 37.4 trillion individual shrimp (36.3 trillion sergestids, 781 billion carideans, and 287 billion penaeids). Finally, we explore the ethical implications of the probability that shrimp and prawns are capable of feeling pain and the welfare policies that could be adopted.

Earthquakes are one of the most catastrophic natural phenomena. After an earthquake, earthquake reconnaissance enables effective recovery by collecting building damage data and other impacts. This paper aims to identify state-of-the-art data sources for building damage assessment and provide guidance for more efficient data collection. We have reviewed 38 articles that indicate the sources used by different authors to collect data related to damage and post-disaster recovery progress after earthquakes between 2014 and 2021. The current data collection methods have been grouped into seven categories: fieldwork or ground surveys, omnidirectional imagery (OD), terrestrial laser scanning (TLS), remote sensing (RS), crowdsourcing platforms, social media (SM) and closed-circuit television videos (CCTV). The selection of a particular data source or collection technique for earthquake reconnaissance includes different criteria depending on what questions are to be answered by this data. We conclude that modern reconnaissance missions can not rely on a single data source and that different data sources should complement each other, validate collected data, or systematically quantify the damage. The recent increase in the number of crowdsourcing and SM platforms used to source earthquake reconnaissance data demonstrates that this is likely to become an increasingly important source of data.

The members within the genus Thermoanerobacter have been much less investigated for protein and amino acid metabolism as compared with carbohydrates. The present study investigates the biotechnological potential of Thermoanaerobacter mathranii (DSM 11426) concerning its ability to produce high energy alcohols from amino and fatty acids. End-product formation was analyzed from glucose in the presence and absence of butyric acid as well as from selected proteins, and all amino acids. T. mathranii did not degrade any of the proteins tested to a large extent but de-grade several amino acids, namely serine and the branched-chain amino acids (leucine, isoleu-cine, valine) when cultivated in the presence of thiosulfate. The main end products from the branched-chain amino acids were a mixture of their corresponding branched-chain fatty acids and alcohols. 13C2-labeled leucine revealed that the strains degraded the amino acid in the pres-ence of thiosulfate, producing 3-methyl-1-butyrate, which was then used as an electron acceptor which led to the accumulation of 3-methyl-1-butanol. The strain is highly ethanologenic, pro-ducing more than 1.2 mol ethanol per mol of glucose degraded. The strain was able to reduce volatile fatty acids during glucose fermentation to their corresponding alcohol, further suggest-ing this strain may be of greater biotechnological value beyond bioethanol production.

The increasing prevalence of obesity and sedentary lifestyles has led to an increased incidence of metabolic syndrome (MetS) worldwide. In Taiwan, middle-aged women are at a greater risk of MetS, type 2 diabetes, and cardiovascular disease than men are because they have more subcutaneous fat and larger waist circumferences compared to men with equal visceral fat levels. This study investigated the effects of calorie restriction supplemented with fish oil (CRF) in middle-aged women with MetS. For 12 weeks, 75 eligible participants were randomly assigned either calorie restriction (CR) or CRF. Both dietary intervention groups were further divided into two age groups: ≤45 and >45 years. The changes in MetS severity, inflammatory status, iron status, and red blood cell fatty acid profile were evaluated. Seventy-one participants completed the trial. Both dietary interventions significantly ameliorated MetS and improved the participants’ inflammatory status. CR significantly increased total iron binding capacity, whereas CRF increased hepcidin levels. Furthermore, CRF significantly increased the n-6/n-3 and arachidonic acid/docosahexaenoic acid ratios. In conclusion, CR and CRF improved the anthropometric and MetS characteristics of early-middle aged women, including body weight, blood glucose levels, triglyceride levels, as well as the scores for the homeostasis model assessment of insulin resistance and quantitative insulin sensitivity cheque index. Dietary intervention was more effective in >45-year-old women than ≤45-year-old women.

The objective of this research is to establish a better understanding of the current landscape of digital learning research and sustainable development by using CiteSpace. First, we retrieved published publications from the Web of Science (2004–2022). Following that, we examined the primary research strengths and important subjects of digital learning from two perspectives: collaboration networks (including collaborative networks across countries, institutions, and authors) and co-citation networks. We examined the co-citation network from three perspectives: cluster analysis, the most active citers, top references. Furthermore, referenced journals, popular themes, and rising trends were examined. These findings indicate the primary study subjects in the field of digital learning, the most intriguing research literature, and each period's emerging research hotspots. Finally, we proposed further study ideas for future paths.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

Accompanied by increasing population growth and urban sprawl, most coastal cities are unprecedentedly vulnerable to climate change and its impacts, such as sea level rise, increasing extreme storm events, and coastal flooding. Coastal resilience and sustainable development are antidotes to vulnerability; they aim to enhance the adaptive capability of absorbing disturbances and resisting uncertainty. This study explores building a quantitative assessment framework to measure resilience and provide an objective and comparable method to understand the strengths and weaknesses in a given region. The proposed 25 resilience indicators incorporate the aspects of essential livelihood protection, infrastructure and natural resource maintenance, emergency facilities and institutions, floodplain management regulations, and adaptive planning process. Each indicator is assigned the resilience quality that includes robustness, resourcefulness, redundancy, and rapidity. The aggregated resilience quality scoring reflects the systematic performance of the city to cope with the coastal hazards. The innovative part of this framework is combining hazard mitigation measures, climate adaptation strategies, and sustainable development goals together to achieve a comprehensive assessment method. In the case of New Haven, the resilience assessment is taken as a practical monitoring tool and decision-making support.

This project designed a set of network security mechanisms for cloud applications in VANETs. At present, cloud computing is one of the government’s development priorities in the industry. We divide cloud into public, private, and hybrid clouds in this project. Vehicles or passengers can access road conditions or public transport information through the public cloud; public transportation can access current driving records and users can access relevant enterprise information on the private cloud and hybrid cloud is a combination of public and private clouds. Both cloud computing or VANETs require network and information security. At present, many researches on VANETs security only focus on message communication, and neglect information storage. Researches on cloud computing security only focus on information protection, and neglect user privacy and anonymity. This project designed a set of network and information security mechanisms in line with the requirements of Confidentiality, Authentication, Non-repudiation, Conditional Anonymity, and Conditional Untraceability. This project primarily needs to achieve the following: 1.an authentication mechanism to verify the identity of each other between the passenger and the vehicle and to verify the identity with Single Sign-On; 2. vehicle or user privacy and anonymity, which need to be able to replace the anonymous ID and related parameters for the vehicle or the user; 3. a private communication mechanism, which enables any vehicle or user to communicate privately; and 4. an information security encryption method, which can encrypt the information on a cloud server to avoid unauthorized access by internal personnel or hackers.

The sustainability of agriculture depends as much on the natural resources required for production as it does on the stakeholders that manage those resources. It is thus essential to understand the variables that influence the decision-making process of agricultural stakeholders to design educational programs, interventions, and policies geared towards their specific needs, a required step to enhance agricultural sustainability. We examined the perceptions, experiences, and priorities that influence management decisions of five major groups of agricultural stakeholders (conventional small grain producers, organic small grain producers, organic vegetable producers, extension agents and agro-industry crop consultants, and researchers) across the Montana, United States. Results revealed that while stakeholder groups have distinct perceptions, experiences, and priorities, there were similarities across groups. Specifically, organic vegetable and organic small grain producers showed similar responses that were, in turn, divergent of conventional producers, researchers, and crop consultants. Conventional small grain producers and researchers showed overlapping response patterns while crop consultants formed an isolated group. Our results reinforce the need for agricultural education and programs that address unique and shared experiences, priorities, and concerns of multiple stakeholder groups. This study endorses the call for a paradigm shift from the traditional top-down agricultural extension model to one that accounts for participants’ socio-ecological contexts to facilitate the adoption of sustainable agricultural systems that support environmental and human wellbeing.

The paper examines the various uncertainties encountered in high-frequency trading (HFT) environments and delves into the multiple challenges faced by HFT firms in navigating the Dodd-Frank Wall Street Reform and Consumer Protection Act (referred to as the "Dodd-Frank Act"), particularly during the initial stages of its enactment. These challenges include the ambiguity surrounding the definition of HFT, the lack of clarity regarding regulatory requirements and boundaries, inconsistencies in enforcement resulting from deviations in understanding the content, and the absence of detailed descriptions of the Act’s provisions. These hurdles significantly impact not only the daily operations of HFT firms but also pose higher demands on their long-term strategic planning and risk management. Drawing upon the Data, Information, Knowledge, Wisdom, and Purpose (DIKWP) model, this study employs an innovative analytical framework. Through the comprehensive application of conceptual space, cognitive space, and semantic space, it provides a systematic methodology for identifying and analyzing the aforementioned issues. This approach not only aids firms in better comprehending and adhering to complex regulatory requirements but also enables them to explore new business opportunities and competitive advantages while ensuring compliance.

End-to-end learned image compression codecs have notably emerged in recent years. These codecs have demonstrated superiority over conventional methods, showcasing remarkable flexibility and adaptability across diverse data domains while supporting new distortion losses. Despite challenges such as computational complexity, learned image compression methods inherently align with learning-based data processing and analytic pipelines due to their well-suited internal representations. The concept of Video Coding for Machines has garnered significant attention from both academic researchers and industry practitioners. This concept reflects the growing need to integrate data compression with computer vision applications. In light of these developments, we present a comprehensive survey and review of lossy image compression methods. Additionally, we provide a concise overview of two prominent international standards, MPEG Video Coding for Machines and JPEG AI. These standards are designed to bridge the gap between data compression and computer vision, catering to practical industry use cases.

The G-protein-coupled estrogen receptor (GPER; G protein-coupled estrogen receptor 30, also known as GPR30) is a novel estrogen receptor and has emerged as a promising target for ovarian cancer. GPER, a seven-transmembrane receptor, suppresses cellular viability and migration in studied ovarian cancer cells. However, its impact on the fallopian tube, which is the potential origin of high-grade serous (HGSC) ovarian cancer, has not been addressed. This study was conducted to evaluate the relationship of GPER, ovarian cancer subtypes, i.e., high-grade serous cell lines (OV90 and OVCAR420), as well as potential HGSC ovarian cancer origin (i.e., the fallopian tube cell line FT190). The selective ligand assessed here is the agonist G-1, which was utilized in an in vitro study to characterize its effects on cellular viability and migration. As a result, this study has addressed the effect of a specific GPER antagonist in combination with an agonist on cell viability, providing a better understanding of the effects of these compounds on our diverse group of studied cell lines. Strikingly, attenuated cell proliferation and migration behaviors were observed in the presence of G-1. Thus, our in vitro study reveals the impact of the origin of HGSC ovarian cancers and highlights the GPER agonist G-1 as a potential therapy for ovarian cancer.

Zooplankton and ichthyoplankton community assessments depend on species diagnostics, yet morphological identifications are time consuming, require taxonomic expertise, and are hampered by lack of diagnostic characters –particularly for larval stages. Metabarcoding can identify multiple species in communities from short DNA sequences in comparison to reference databases. To evaluate species resolution across phylogenetic groups and food webs of zooplankton and ichthyoplankton, we compare five metabarcode mitochondrial (mt)DNA markers from gene regions of (a)cytochrome c oxidase subunit I, (b) cytochrome b, (c) 16S ribosomal RNA, and (d) 12S ribosomal RNA for DNA extracted from net tows in the Northeastern Pacific Ocean’s Salish Sea across seven sites and two seasons. Species resolved by metabarcoding are compared to invertebrate morphological identifications and biomass estimates. Results indicate that species resolution for different zooplankton and ichthyoplankton taxa can markedly vary among gene regions and markers, and in comparison to morphological identifications. Thus, researchers seeking “universal” metabarcoding should take caution that several markers and gene regions likely will be needed; all will miss some taxa and yield incomplete overlap. Species resolution requires careful attention to taxon marker selection and coverage in reference sequence repositories. In summary, combined multi-marker metabarcode and morphological approaches improve broadscale zooplankton diagnostics.

The continuous casting process of helical fiber reinforced metal matrix composites was proposed, and the experimental equipment was designed and manufactured. The relationship model be-tween the process parameters and the helical shape of the fibers in the metal matrix is analyzed by differential geometry. Helical carbon fiber reinforced lead matrix composites were prepared under different conditions. When the melting temperature and cooling intensity were increased, the helical radius of helical carbon fiber in lead matrix was increased. When the fiber rotation speed was increased, the helical radius was decreased, and the helical pitch was de-creased proportionally. The experimental results are consistent with the process model. Carbon fiber rein-forced aluminum composites were prepared. Scanning electron microscopy showed that the infiltration between the aluminum matrix and the carbon fiber was not complete. As the volume fraction of carbon fiber which was added in composites is too small, the mechanical properties of the composites have not been significantly improved.

Background: Erythropoietic protoporphyria (EPP) and X-linked protoporphyria (XLP) are the two most common subtypes within rare genetic photodermatoses, which can lead to incapacitating pain episodes. Methods: We reviewed previous and current treatment options for EPP/XLP, notably with a focus on metabolism, pharmacokinetics, mechanism of action, key clinical trial results, and limitations of Dersimelagon [MT-7117]. Results: In review of treatment modalities for EPP/XLP, Dersimelagon has demonstrated an acceptable safety profile with the ease of once-daily oral dosage. Conclusions: Dersimelagon should be a considered as a potential treatment for EPP/XLP. Ongoing studies will provide additional insights into expanding the treatment options for those suffering from EPP/XLP.

The epistemology of the traditional risk assessment examined has a taxonomy based upon deterministic, behaviouristic and compatibilist methodologies which are likely driven by neo-liberal market related requirements for bigger, faster cheaper wind-turbines. Analysis of available risk assessments suggested that there is no conscious effort to deceive the reader although the intended audience is unclear. The language, and scoring mechanisms utilized indicates the presence of conformity bias, confirmation bias, and numerical inconsistency leading to data ossification. By reverse engineering risk assessment content, Pragmatic and Social Psychological aspects can be investigated, and the adequacy of the document can be evaluated using evidence-based models.

Vibration problems have become one of the most important factors affecting robot performance. To this end, a terminal residual vibration suppression method based on joint trajectory optimization is proposed to improve the accuracy and stability of robot motion. Firstly, based on the characteristics of the friction nonlinearity due to joint coupling and physical feasibility of dynamic parameters, a semidefinite programming method is used to identify dynamic parameters with actual physical meaning, thereby obtaining an accurate dynamic model. Then, based on the result of the residual vibration time domain analysis, a joint trajectory optimization model with the goal of minimizing joint tracking error is established. The Chebyshev collocation method is used to discretize the optimization model. The dynamic model is used as the optimization constraint, and barycentric interpolation is used to obtain the optimized joint motion trajectory. Finally, industrial robot experiments prove that the vibration suppression method proposed in this article can reduce the maximum acceleration amplitude of residual vibration by 62% and the vibration duration by 71%. Compared with the input shaping method, the method proposed in this paper can reduce the terminal residual vibration more effectively and ensure the consistency of running time and trajectory.

The impact of antecedent soil moisture content on soil erosion is a complicated phenomenon, which is still under argument with contradictions in research results. Hence, the objective of this study is to investigate the impact of antecedent soil moisture content to soil loss on clay soil by conducting two-year field experiments under natural rainfall on runoff plots with length of 10 meters, width of 3 meters, and uniform slope of 9%. Volumetric soil moisture sensors were used to log soil moisture changes, and soil moisture readings were used along with rainfall records to quantify the antecedent soil moisture conditions for each rainfall event. Results of this study show duration of the effective erosion event outranks the antecedent volumetric soil moisture content. Field study also suggests that accumulative rain falling within 48 hours (Pp48) prior to an effective erosion event strongly correlated with soil loss per Rainfall-Runoff Erosivity Index (Soil Loss / EI30), particularly when the duration of an effective erosion event is either between 3 ~ 7 hours or 10~ 30 hours. Hence, Pp48 can be considered as an alternative to replace antecedent soil moisture content in RUSLE 2’s cover and management factor.

Based on the dynamic strength variation mechanism of concrete under complex loading conditions, two approaches were devised: numerical testing and CT scanning, guided by the principle of minimizing energy dissipation. A methodology for calculating concrete's failure area and measuring its strength was developed. The analysis delves into the mechanisms behind failure patterns and variations in concrete specimen strength, focusing on crack initiation, development, and the resultant failure surface formed by crack propagation, along with the stress distribution in concrete specimens subjected to diverse loading conditions. Through evaluating the strength and computed failure area of concrete specimens, it is evident that the loading method influences both the strength and failure area of concrete specimens. In general, a larger failure area correlates with a higher measured strength.

Background: Complex bone defects are challenging to treat. Autografting is the gold standard for regenerating bone defects, however limitations include donor site morbidity and increased surgical complexity. Advancements in 3D bioprinting (3DBP) offer a promising alternative for viable bone grafts. Methods: Design of Experiments (DoE) was used to design 12 hydrogel bioinks of various Gelatin meth-acrylate/hydroxyapatite (GelMA/HA) concentrations. These bioinks were assessed for pipettability and equilibrium modulus. An optimal bioink was designed using the DoE data to produce the greatest stiffness while still being pipettable. Two bioinks, the DoE designed maximal stiff-ness and the experimentally defined maximal stiffness vs. a literature based control were then printed using a 3D bioprinter and assessed for print fidelity. The resulting hydrogels were combined with human bone-marrow-derived mesenchymal stromal cells (hMSCs) and evaluated for cell viability. Results: DoE ANOVA analysis indicated that the augmented 3 level factorial design model used was a good fit (p < 0.0001). Using the model, DoE correctly predicted that a composite hydrogel consisting of 12.3% GelMA, 15.7% HA, and 2% Gelatin would produce the maximum equilibrium modulus while still being pipettable. The hydrogel with the most optimal print fidelity was 10% GelMA, 2% HA, and 5% Gelatin. There were no significant differences in cell viability within hydrogels from day 2 to day 7 (p > 0.05). There was however a significantly lower cell viability in the gel composed of 12.3% GelMA, 15.7% HA, and 2% gelatin compared to the other gels with lower HA concentration (p < 0.05), showing that higher HA or print pressure may be cytotoxic within hydrogels. Conclusions: Extrusion-based 3DBP offers significant advantages for bone-tissue implants due to its high customizability. This study demonstrates it is possible to create printable bone-like grafts from GelMA and HA with increased HA levels, favorable mechanical properties (145kPa) and >80% cell viability.

p53 is among the most frequently mutated tumor suppressor genes given its prevalence in >50% of all human cancers, including high grade serous endometrial cancers and ovarian cancers. In addition to loss of tumor suppression function, many mutated p53 (Mutp53) proteins acquire gain-of-function (GOF) activities as oncogenes to promote cancer progression, which manifest through aberrant expression of p53. As we have come to see, statins induce CHIP-mediated degradation of mutp53 by blocking the interaction between mutp53 and DNAJA1. Therefore, targeting critical downstream pathways of mutp53 provides an alternative strategy for treating cancers expressing mutp53. In this review, we summarize recent advances with Wee1 inhibitors and mevalonate pathway inhibitors, particularly statins, regarding their use in gynecological cancers with p53 mutations.

Contaminants of Emerging Concern (CECs), a new category of contaminants in limelight, is a major issue of global concern. The pervasive nature of CECs and its harmful effects, such as cancer, reproductive disorders, neurotoxicity etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentration of CECs can cause great impacts on living beings. It also has a nature of bioaccumulation. Thus, it is the ultimate need to have efficient sensors for detection of CECs to ensure safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in literatures under each category for the detection of major CECs.

External hoof characteristics, balance, and conformation have been extensively studied in horses; however, mules remain understudied in these aspects. This study evaluated the size, shape, and symmetry of untrimmed and unshod forelimb hooves, compared the symmetry between forelimb hooves and stratified external forelimb hoof measurements based on the body condition score of mules raised in the foothill plains of northern Thailand. The forelimb hooves of 38 mules were photographed and 33 parameters, including angular and linear measurements, were analyzed. Despite the absence of shoeing and trimming, these mules exhibited optimal left-right forelimb hoof symmetry, with no significant (p < 0.05) differences in: outer wall length and inner wall length (OWL - IWL); sole length and sole width (SLS - SW); dorsal hoof wall length and heel length (DHWL - HL); and frog length and frog width (FL - FW). However, significant (p < 0.05) differences were observed within each body condition score group for forelimb hoof measurements for DHWL, IWL, heel separation (HS), heel bulb distance (HBD), SW, FW, and FL. These findings provide valuable insights into mule welfare and management, contributing to understanding of the interplay between overall health and hoof conformation in the study area.

Odontogenic infections are infections of the orofacial structures arising from dental disease. Despite its preventability, it exerts a significant burden on healthcare infrastructure worldwide. Our study explored the various different microbiological, social, and epidemiological characteristics of 103 cases of odontogenic infections at our regional center which demonstrated specific predilections for the young and middle-aged, those with diabetes mellitus, African American/Black and Hispanic ethnicities, posterior teeth, left-sided dentition, and male gender. However, nuances and exceptions to these trends were also seen with specific groups that may complicate treatment.

This study investigates the effects of Zinc (4wt.%) and severe plastic deformation on the mechanical properties of AZ61 magnesium alloy through the stir-casting process. The severe plastic deformation (equal channel angular pressing (ECAP)) has been done followed by T4 heat treatment. The microstructural examinations revealed that the addition of 4wt.%Zn enhances the uniform distribution of β-phase, contributing to a more uniformly corroded surface in corrosive environments. Additionally, dynamic recrystallization (DRX) significantly reduces the grain size of as-cast alloys after undergoing ECAP. The attained mechanical properties demonstrate that after a single ECAP pass, AZ61 + 4wt.%Zn alloy exhibits optimal yield strength (YS), ultimate compression strength (UCS), and hardness. This research highlights the promising potential of AZ61 + 4wt.%Zn alloy for enhanced mechanical and corrosion-resistant properties, offering valuable insights for applications in diverse engineering fields.

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Accurate measurement of systemic financial risk is critical to maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was con-structed by integrating six dimensions and employing Gray Relation Analysis (GRA) for dimensionality reduction of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA) optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trend of financial pressure indicators, the relationship between financial pressure and economic activity can be effectively identified. The research findings indicate that: (1) The CFSI is capable of accurately reflecting the current financial stress situation in China; (2) The IGSA-RBFNN demonstrates good robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology benefits policymakers and regulatory authorities to formulate preventive measures and risk management by identifying potential risks and vulnerabilities in advance.

Recent advances in embedded antenna and sensor technologies for 5G communications have galvanized a response toward the investigation of their electromagnetic (EM) performance for urban context and civil engineering applications. This article quantitatively investigates the effects of material loading on an evolved antecedent-based design of a hexagonal-stubbed Complementary Split-Ring Resonator (CSRR)-loaded antenna through simulation and experimentation. The optimized antenna design is first conceptualized within a simulation environment to achieve EM resonance at 3.50 GHz before delving into the analysis of operational performance characteristics. As a proof-of-concept, a physical antenna prototype is fabricated on a printed circuit board for the in-situ evaluation of S11 parameter plot. Subsequently, a simulation-based parametric study is conducted on antenna prototypes embedded into Ordinary Portland Cement pastes with varying weight percentages of iron(III) oxide. Simulation-derived and experimental results are mutually verified, achieving a systemic downward shift in resonant frequency and corresponding variations in impedance matching induced by changes in the loading reactance. Finally, an inversion modeling procedure is employed using perturbation theory to extrapolate the relative permittivity of the dielectric embedding materials. Our proposed analysis contributes to optimizing concrete-embedded 5G antenna sensor designs and establishes a foundational framework for estimating unknown EM parameters of cement-based composites.

Tailed phages are the most abundant and diverse group of viruses on the planet. Yet, the smallest tailed phages display relatively complex capsids and large genomes compared to other viruses. The lack of tailed phages forming the common icosahedral capsid architectures T = 1 and T = 3 is puzzling. Here, we extracted geometrical features from high-resolution tailed phage capsid reconstructions and built a statistical model based on physical principles to predict the capsid diameter and genome length of the missing small tailed phage capsids. We applied the model to 3,348 isolated tailed phage genomes and 1,496 gut metagenome-assembled tailed phage genomes. Four isolated tailed phages were predicted to form T = 3 icosahedral capsids, and twenty-one metagenome-assembled tailed phages were predicted to form T < 3 capsids. The smallest capsid predicted was a T = 4/3 ≈ 1.33 architecture. No tailed phages were predicted to form the smallest icosahedral architecture, T = 1. We discuss the feasibility of the missing T = 1 tailed phage capsids and the implications of isolating and characterizing small tailed phages for viral evolution and phage therapy.

(1) Background: Ectopic pregnancy (EP) is when fertilized ovum implanted outside of uterine cavity. The incidence was 1.5% to 2.0% of all pregnancies [1, 2]. EP decreases fertility ability [3]. This study focused on the pregnancy rate after EP and various parameters influencing pregnancy. (2) Methods: The data was extracted from National Health Insurance Research Database (NHIRD) during 2000-2013. The study group enrolled women with one EP history. Those who did not have EP was put into the control group. Chi-square/Fisher exact test was performed on category variable and t-test was used on continue variables. (3) Results: The EP group had a higher cumulative rate of conceive, 41.55% than control group, 37.14% and 1.16 times higher risk in developing pregnancy (P&lt;0.001). The conceiving rate was lower than the control group in the first 5 years, but higher than the control group in the 10th to 14th years. (4) Conclusions: The fecundability after EP is lower at the beginning, but regained after long term follow.

In 2020 the world experienced the threat of the COVID-19 epidemic, as seniors and chronic disease patients typically try to reduce their exercise and social activities to avoid increasing the risk of infection, which could lead to increased loneliness and even many diseases. This research combining golf croquet games with AIoT companion robots constructs a home-based intelligent exercise system thus uses the Technology Acceptance Model (TAM), deduces users’ intention to use this system based on perceived usefulness and perceived ease of use, and adds the needs of love and belonging, esteem, cognitive, aesthetic, and self-actualization in Maslow’s needs theory to conduct system needs analysis. The analysis results show that participants have a high level of acceptance of this system, believing that it is easy to learn and operate, can increase interaction with others, also found that this system can improve self-confirmation, satisfying the third for knowledge, feeling happy, and self-actualization needs are easier to fulfill. In the future, we shall collect and record the seniors in the process of use, so as to find out their health problems as soon as possible, expand their daily life through this exercise, and achieve the goal of happy living and health care.

Urban cities in sub-Saharan Africa (SSA) are faced with ambient air pollution. This is an important public health problem with models and limited monitoring data indicating high concentrations of pollutants such as fine particulate matter (PM_2.5). Going through most global air quality index maps, however, information about ambient pollution from SSA is scarce. We evaluated the feasibility and practicality of longitudinal measurements of ambient PM_2.5 using low-cost air quality sensors (Purple Air-II-SD) across thirteen locations in seven countries in SSA. Devices were used to gather data over a 30-day period with the aim of assessing the efficiency of its data recovery rate and identifying challenges experienced by users in each location. The median data recovery rate was 94% (range: 72% to 100%). The mean 24-hour concentration measured across all sites was 38 µg/m³ with the highest PM_2.5 period average concentration of 91 µg/m³ measured in Kampala, Uganda and lowest concentrations of 15 µg/m³ measured in Faraja, The Gambia. Kampala-Uganda and Nnewi-Nigeria recorded the longest periods with concentrations>250µg/m³. Power outages, SD memory card issues, internet connectivity problems and device safety concerns were important challenges experienced when using Purple Air-II-SD sensors. Despite some operational challenges, this study demonstrated that it is reasonably practicable and feasible to establish a network of low-cost devices to provide data on local PM_2.5 concentrations in SSA countries. Such data are crucially needed to raise public-, societal and policymaker awareness about air pollution across SSA.

Wetlands are recognized as one of the world’s most valuable natural resources. With the increasing world population, human demands on wetland resources for agricultural expansion and urban development continue to increase. In addition, global climate change has pronounced impacts on wetland ecosystems through alterations in hydrological regimes. To better manage and conserve wetland resources, we need to know the distribution and extent of wetlands and monitor their dynamic changes. Wetland maps and inventories can provide crucial information for wetland conservation, restoration, and management. Geographic Information System (GIS) and remote sensing technologies have proven to be useful for mapping and monitoring wetland resources. Recent advances in geospatial technologies have greatly increased the availability of remotely sensed imagery with better and finer spatial, temporal, and spectral resolution. This chapter presents an introduction to the uses of GIS and remote sensing technologies for wetland mapping and monitoring. A case study is presented to demonstrate the use of high-resolution light detection and ranging (LiDAR) data and aerial photographs for mapping prairie potholes and surface hydrologic flow pathways.

This study addresses the critical issue of cardiovascular diseases (CVD) as the leading cause of death globally, emphasizing the importance of stent delivery catheter manufacturing. Traditional manufacturing processes, reliant on destructive end-of-batch sampling, present significant financial and quality challenges. The research highlights the need for non-destructive Process Analytical Technologies (PAT) to meet the increasing demand for these life-saving devices. The study employs a mixed-method approach, combining qualitative literature review and quantitative artefact development, to propose a closed-loop Cyber Physical Production System (CPPS). The proposed system aims to enhance real-time quality control, minimize costs, and improve manufacturing efficiency. Initial results demonstrate the system's effectiveness in reducing cycle times, improving stability, and significantly decreasing production misses. The findings suggest substantial financial savings and quality improvements, underscoring the potential of advanced control strategies in regulated medical device manufacturing. This study proposes a generalized CPPS framework to be applicable across diverse regulated manufacturing environments, ensuring optimal processing conditions and adherence to regulatory standards. The research concludes with the successful demonstration of innovative approaches and technologies, leading to improved product quality, patient safety, and operational efficiency in the medical device industry.

During planetary exploration mission operations, one of the key responsibilities of the instrument teams to determine data viability for subsequent analysis. During the 2019 CanMoon Lunar Sample Return Analogue Mission, the Lead Raman Specialist manually examined each spectra to provide quality assurance/validation. This non-trivial process requires years of experience to complete accurately. With the proven efficacy of Convolutional Neural Networks (CNNs) in classification tasks, and the increased use of automation and control loops on planetary space platforms for navigation and science targeting, an opportunity presents itself to approach this validation problem utilising CNNs. We present the Generalised Raman Validation Network (GRaVN), an neural network focused specifically on extracting the generalised structure of Raman spectra for quality assurance/validation. This work demonstrates the viability of utilising a CNN network in validation activities for Raman spectroscopy. Utilising only two hidden layers, a configuration was developed that provided good levels of accuracy on a manually curated dataset. This indicates that such a system could be useful as part of an autonomous control loop during planetary exploration activities.

The river Teign in Devon has come under scrutiny for failing to meet Environmental Quality Standards for ecotoxic metals due to past mining operations. A disused mine known as Bridford Barytes mine, has been found to contribute a significant source of Zn, Cd and Pb to the river. Recently, studies have been focused on the remediation of such mine sites using low-cost treatment methods to help reduce metal loads to the river downstream. Red mud is a waste product from the aluminium industry, the utilization of this resource has proven an attractive low-cost treatment method for adsorbing toxic metals. Adsorption kinetics and capacity experiments reveal metal removal efficiencies of up to 70% within the first 2 hours when red mud is applied in pelletized form. Biochar is another effective adsorbent with the potential to remove >90% Zn using agricultural feedstock. Compliance of the Teign has been investigated by analysing dissolved metal concentrations and bioavailable fractions of Zn to assess if levels are of environmental concern. By applying a Real-World Application Model, this study reveals that compressed pellets and agricultural biochar offer an effective, low-cost option to reducing metal concentrations and thus improving the quality of the river Teign.

Unmanned aerial vehicles (UAVs) equipped with multispectral sensors present an opportunity to monitor vegetation with on-demand high spatial and temporal resolution. In this study, we use multispectral imagery from quadcopter UAVs to monitor the progression of a water manipulation experiment on a common shrub, Baccharis pilularis (coyote brush), at the Blue Oak Ranch Reserve (BORR) near San Jose, California. We recorded multispectral data from the plants at several altitudes with nearly hourly intervals to explore the relationship between two common spectral indices, NDVI and NDRE, and plant water content and water potential, as physiological metrics of plant water status, across a gradient of water deficit. An examination of the spatial and temporal thresholds at which water limitations were most detectable revealed that the best separation between levels of water deficit were at higher resolution (lower flying height), and in the morning (NDVI) and early morning (NDRE). We found that both measures were able to identify moisture deficit in plants and distinguish them from control and watered plants; however, NDVI was better able to distinguish between treatments than NDRE and was more positively correlated with field measurements of plant water content than NDRE. Finally, we explored how relationships between spectral indices and water status changed when the imagery was scaled to courser resolutions provided by satellite-based imagery (PlanetScope) and found that PlanetScope data was able to capture the overall trend in treatments but was not able to capture subtle changes in water content. These kinds of experiments that evaluate the relationship between direct field measurements and UAV camera sensitivity are needed to enable translation of field-based physiology measurements to landscape or regional scales.

Virtual reality (VR) describes a family of technologies which immerse users in sensorily-stimulating virtual environments. Such technologies have increasingly found applications in the treatment of neurological and mental health disorders. Depression, anxiety, and other mood abnormalities are of concern in the growing elderly population – especially those who reside in long-term care facilities (LTCFs). The transition from the familiar home environment to the foreign LTCF introduces a number of stressors that can precipitate depression. However, recent studies reveal that VR therapy (VRT) can promote positive emotionality and improve cognitive abilities in the elderly, both at home and in LTCFs. VR thus holds potential in allowing elderly individuals to gradually adapt to their new environments – thereby mitigating the detrimental effects of place attachment and social exclusion. Nevertheless, while the current psychological literature is promising, the implementation of VR in LTCFs faces many challenges. LTCF residents must gain trust in VR technologies, care providers require training to maximize the positive effects of VRT, and decision makers must evaluate both the opportunities and obstacles in adopting VR. Here, we concisely review the implications of depression related to place attachment in LTCFs, and explore the potential therapeutic applications of VR.

Over the past couple of decades, Global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., need much money to buy devices, forget to take devices to collect data, limit the simple size because of the number of devices, etc.), and the phenomenon that the smartphone is becoming one of necessities of life, there is a great chance for the smartphone to replace dedicated GPS devices. Although, several general reviews have been done about smartphone-based GPS travel survey in the literature review section in some articles, a systematic review from smartphone-based GPS data collection to travel mode detection has none. The included studies were searched from six databases. The purpose of this review is to critically assess the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to the systematic comparison among different methods from data-preprocessing to travel mode detection, this paper could carefully provide the Strengths and Weaknesses of existing methods. Furthermore, it is the crucial step to develop the methodologies and applications of GPS raw data collected by smartphones.

A multispectral superconducting nanowire single photon detector sensitive to different incident photon wavelength bands, is proposed. The SNSPD consists of a Distributed Bragg Reflector, a gold mirror, and two regions employing four NbN nanowires. Using the DBR both as a filter and a reflector, two distinct detection bands are created. The first detection band has a peak absorbance of > 0.75 at a wavelength of 1143 nm, while the second band has an absorbance of > 0.70 in the wavelength range 1440 to 2000 nm. The design of the device can be tuned to provide sensitivity in different wavelength bands. While SNSPDs do not typically provide photon wavelength sensitivity, the band-selection design proposed in this work opens up potential applications for future quantum communication technology.

The foot-mounted inertial navigation system is an important application of pedestrian navigation as it in principle does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial sensors with ZUPT (zero-velocity update) and range decomposition constraint perform better than in either single way. This paper recommends that the distance of separation between the position estimates of feet-mounted inertial navigation systems be restricted in the ellipsoidal constraint which relates to the maximum step and leg height. The performance of the proposed method is studied utilizing experimental data. The results indicate that the method can effectively correct the dual navigation systems’ position over the existing spherical constraint.

Trypanosoma cruzi infection results in debilitating cardiomyopathy, which is a major cause of mortality and morbidity in the endemic regions of Chagas disease (CD). The pathogenesis of Chagasic cardiomyopathy (CCM) has been intensely studied as a chronic inflammatory disease until recent observations reporting the role of cardio-metabolic dysfunctions. In particular, we demonstrated accumulation of lipid droplets and impaired cardiac lipid metabolism in the hearts of cardiomyopathic mice and patients, and their association with impaired mitochondrial functions and endoplasmic reticulum (ER) stress in CD mice. In the present study, we examined whether treating infected mice with an ER stress inhibitor can modify the pathogenesis of cardiomyopathy during chronic stages of infection. T. cruzi infected mice were treated with an ER stress inhibitor 2-Aminopurine (2AP) during the indeterminate stage and evaluated for cardiac pathophysiology during the subsequent chronic stage. Our study demonstrates that inhibition of ER stress improves cardiac pathology caused by T. cruzi infection by reducing ER stress and downstream signaling of phosphorylated eukaryotic initiation factor (P-elF2α) in the hearts of chronically infected mice. Importantly, cardiac ultrasound imaging showed amelioration of ventricular enlargement, suggesting that inhibition of ER stress may be a valuable strategy to combat the progression of cardiomyopathy in Chagas patients.

This paper proposed emotion recognition methods for consecutive facial images, and implements the inference of neural network model on a field-programmable gate array (FPGA). The proposed emotion recognition methods are based on a neural network model architecture that combines convolution neural networks (CNNs), long short-term memory (LSTM), and fully connected neural networks (FCNNs), called CLDNN or ConvLSTM-FCN. This type of neural network mod-el can analyze the local feature sequences obtained through convolution of data, making it suita-ble for processing time-series data such as consecutive facial images. In this paper, sequences of facial images are sampled from videos corresponding to various emotional state of subjects. The sampled images are then pre-processed with the processes includes facial detection, greyscale conversion, resize, and data augmentation if necessary. The 2-D CNN in ConvLSTM-FCN is used for feature extraction for these pre-processed facial images. These sequences of facial im-age features are time sequences with dependent properties between the elements within them. The LSTM is then used to model these time sequences followed by fully connected neural net-works (FCNNs) for classification. The proposed consecutive facial emotion recognition method achieves an average recognition rate of 99.51% on RAVDESS dataset, 87.80% on BAUM-1s dataset and 96.82% on eNTERFACE’05 data set, using 10-fold cross-validation on the PC. Some com-parisons of recognition accuracies between the proposed method and the other existing related works are conducted in this paper. According to the comparisons, the proposed emotion recog-nition methods outperform the existing related researches. The proposed emotion recognition methods are then implemented on an FPGA chip using the neural network model inference algo-rithms in this paper, and the accuracies of the experiments conducted on the FPGA chip are iden-tical to those obtained on the PC. This verifies that the proposed neural network model imple-mented on the FPGA chip performs well.

Background: Mutations in TBCK can generate truncated TBCK protein aggregates that abolish the normal function of the gene. Alterations in TBCK function have been implicated in developmental and neurogenetic disorders, as well as the progression of certain forms of cancer. Despite TBCK's involvement in various human diseases, the underlying mechanism for cancer pathogenesis remains poorly understood. Methods: To further explore loss of function mutations in TBCK, we introduced a CRISPR-mediated knockout system capable of deleting the human TBCK gene. Transcriptome analysis based on RNA-seq data was utilized to illustrate important roles of TBCK in cancer initiation and progression. Results: The effectiveness of our targeted CRISPR knockout system (sgTBCK) was validated in multiple human cancer models, including PDAC MIAPaCa-2 and Fibrosarcoma HT1080. Our clear and straightforward workflow, detailed protocol, and schematic diagram for knocking out human TBCK via CRISPR can be applied to any gene of interest, which highlights the versatility, reproducibility, and user-friendliness of this approach. The application of our TBCK knockout system for transcriptome analysis showed TBCK's involvement in multiple hallmark cancer pathways, such as TNF-α signaling, Apoptosis, Hypoxia, P53, and Epithelial Mesenchymal Transition, emphasizing the importance of TBCK mutations in cancer initiation and progression. Conclusions: We generated a straightforward workflow, detailed protocol, and schematic diagram for knocking out human TBCK via CRISPR and confirmed that the sgRNA against TBCK (GTTCGAGAAAGGAAACCTGTG) was specific for human TBCK. To date, this is the first report that has combined a CRISPR-Cas9 knockout system with transcriptome analysis to uncover potential mechanisms of TBCK in cancer progression.

Dye/salt separation has gained increasing attention in recent years, prompting the quest for cost-effective and environmentally-friendly raw materials for synthesis high performance nanofiltration (NF) membrane for effective dye/salt separation. Herein, a high-performance loose structured NF membrane was fabricated by via a simple vacuum filtration method using a green nanomaterial, 2,2,6,6-tetramethylpiperidine-1-oxide radical (TEMPO)-oxidized cellulose nanofiber (TOCNF), by sequentially filtrating larger-size and finer-size TOCNFs on a microporous substrate, followed by cross-linked with trimesoyl chloride. The resultant TCM membrane possesses a separating layer composed entirely of pure TOCNF, eliminating the need for other polymer or nanomaterials additives. TCM membranes exhibits high performance and effective dye/salt selectivity. Scanning Electron Microscope (SEM) analysis shows that the TCM membrane with Fine-TOCNF layer has a tight layered structure. Further characterizations via Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) confirm the presence of functional groups and chemical bonds of the crosslinked membrane. Notably, the optimized TCM-5 membrane exhibits a rejection rate of over 99% for various dyes (Congo red, orange yellow) and 14.2% for NaCl, showcasing a potential candidate for efficient dye wastewater treatment.

Microwave radiation diagnosis technology can detect thermal changes in skin tissue earlier than anatomical changes, but its detection accuracy is limited by non-target radiation interference in the measurement environment, additional measurement errors of system units, and energy scattering and transmission between skin tissues. This paper aims to address the scientific challenges of analyzing the forward and inversion modelling detection mechanism of layered accurate temperature measurement of human skin tissue based on multi-band. The study focuses on the construction of a pencil beam antenna optimization system, the optimization strategy of high-sensitivity correlated radiometer architecture, and the high-precision multi-band forward and inversion modelling detection algorithm. The key technologies include: (1) A new method of integrated modeling and multi-index optimization of antenna with high directivity and small aperture is proposed, and a priori knowledge-guided neural network of pencil beam distribution is constructed to realize the inversion model of antenna structural parameters; (2) The influence mechanism of high sensitivity correlated radiometer architecture error is analyzed, and a periodic phase shift error correction algorithm based on uniform polar circle is designed; (3) Combining deep learning theory and hyperparameter optimization framework, an iterative model is established, and the objective function modified by the penalty factor is defined to realize a new detection method combining forward and inversion. This paper presents a theoretical foundation for the industrialization of microwave radiation diagnostic technology.

Reduced glutathione (GSH) is an antioxidant in plants and is one of the important ways for plants to combat low-temperature stress. In this paper, Eriobotrya japonica Lindl. cv. Zaozhong No. 6 seedlings were used to study the effects of exogenous 5-aminolevulinic acid (ALA) application on glutathione synthesis and cyclic metabolism of loquat seedlings under low-temperature stress and to explore the regulatory mechanism of ALA on loquat cold tolerance. The results showed that ALA treatment could increase the content of GSH and the reduced glutathione/oxidized glutathione (GSH/GSSG) ratio in loquat leaf slices under low-temperature stress; reduce the electrolyte leakage rate and GSSG, H₂O₂ and MDA contents in leaf tissues; and alleviate the peroxidation damage caused by low temperature. ALA treatment increased the activity of γ-glutamine synthetase (γ-ECS) in loquat leaf slices under low-temperature stress and promoted the biosynthesis of reduced glutathione, thereby increasing the GSH content in leaf tissues. On the other hand, ALA treatment could also improve the activities of glutathione reductase (GR), glutathione S-transferase (GST) and glutathione peroxidase (GPX) and promote the cyclic regeneration of GSH, accordingly maintaining a high GSH/GSSG ratio, promoting the removal of reactive oxygen species (ROS), and enhancing the antioxidant capacity of leaves. The regulatory effect of ALA on enhancing the antioxidant capacity of loquat seedlings under low-temperature stress can be inhibited by L-buthionine-sulfoximine (BSO, GSH biosynthesis inhibitor). The results showed that ALA improved the antioxidant capacity of loquat seedlings under low-temperature stress, and GSH was involved in the regulation of the antioxidant effect of ALA on loquat seedlings under low-temperature stress.

MicroRNA (miRNA) is small non-coding RNAs that play vital roles in post-transcriptional gene regulation by inhibiting mRNA translation or promoting mRNA degradation. Dysregulation of miRNA has been implicated in numerous human diseases, including cancers. The family members of miR-34 (miR-34s), composed of miR-34a, miR-34b, and miR-34c, have emerged as the most extensively studied tumor-suppressive miRNAs. In this comprehensive review, we aim to provide an overview of the major signaling pathways and gene networks regulated by the miR-34s in various cancers and highlight the critical tumor suppressor role of miR-34s. Furthermore, we will discuss the potential of using miR-34 mimics as a novel therapeutic approach against cancer, while also addressing the challenges associated with their development and delivery. It is anticipated that gaining a deeper understanding of the functions and mechanisms of miR-34s in cancer will greatly contribute to the development of effective miR-34-based cancer therapeutics.

Abstract: Thermostability of vaccines, particularly enveloped viral vectored vaccines, remains a challenge for their delivery wherever needed. Freeze-drying of viral vectored vaccines is a prom-ising approach but remains challenging due to the water removal process from the outer and in-ner parts of the virus. In the case of enveloped viruses, freeze-drying induces increased stresses on the envelope, which often leads to inactivation of the virus. In this study, we design a method to freeze-dry a recombinant Vesicular Stomatitis Virus (VSV) expressing the SARS-CoV-2 spike glycoprotein. Since the envelope of VSV is composed of 50% lipid and 50% protein, the formula-tion study focused on both the protein and lipid portions of the vector. Formulations were pre-pared primarily using sucrose, trehalose, and sorbitol as cryoprotectants; mannitol as a lyopro-tectant; and histidine as a buffer. Initially, the infectivity of rVSV-SARS-CoV-2 and cake stability were investigated at different final moisture contents. High recovery of the infectious viral titer ( 0.5 to 1 log loss) was found at 3-6% moisture content with no deterioration of the freeze-dried cakes. To further minimize infectious viral titer loss, the composition and concentration of the ex-cipients were studied. An increase from 5 to 10% of both cryoprotectants and lyoprotectant, to-gether with the addition of 0.5% gelatin, resulted in the improved recovery of infectious virus titer and stable cake formation. Moreover, the secondary drying temperature of the freeze-drying pro-cess showed a significant impact on the infectivity of rVSV-SARS-CoV-2. The infectivity of the vector declined drastically when the temperature was raised above 20°C. Throughout a long-term stability study, formulations containing 10% sugar (sucrose/trehalose), 10% mannitol, 0.5% gelatin, and 10 mM of histidine showed satisfactory stability for six months at 2-8°C. The development of this freeze-drying process and the optimized formulation minimizes the need for a costly cold chain distribution system.

Public safety and intelligent surveillance systems critically depend on anomaly behavior detection for effective monitoring. In real-world pedestrian detection scenarios, prevalent challenges such as missed detections, complex background interference, and small target sizes hinder accurate anomaly identification. To address these issues, this study introduces YOLO-ABD, a lightweight method for anomaly behavior detection that integrates small target detection and channel shuffling. This method employs YOLOv8n as the baseline model, incorporating a small target detection mechanism in the Head part and utilizing GSConv convolution in the Backbone to enhance perceptual capability. Additionally, the SimAM attention mechanism is integrated to mitigate complex background interference, thereby improving target detection performance. Evaluation on the IITB-Corridor dataset demonstrated mAP50 and mAP50-95 scores of 89.3% and 60.6%, respectively. Generalization testing on the street-view-gdogo dataset further highlighted the superiority of YOLO-ABD over advanced detection algorithms, underscoring its effectiveness and generalizability. With a relatively small parameter count, YOLO-ABD presents an excellent lightweight solution for pedestrian anomaly behavior detection.

Antibiotic resistance (ABR) is concerning issue due to its direct and indirect repercusions on public health, since decreased therapeutic effect of certain antibiotic to treatment complications that can cause death. There are several mechanism as to how ABR can be transferred from one microoorganisms to another, and many of them are dependant many environmental factors. The food supply chain is a environment in which ABR gene transfer can occur is multiple pathways, which generate concerns regarding food safety. Here, we summarize relevant mechanisms which are implied in ABR in food supply chain but also we are addressing routes of transmission and prevalence of ABR, implications on public health, and the application of new alternatives to antibiotics such as antimicrobial peptides, mainly bacteriocins, in order to countermeasure ABR.

The ketogenic diet and walking exercise training activity are two key public health lifestyle factors. The potential of combined lifestyle factors interventions focused on getting to compliance in forced exercise. A balanced ketogenic diet and regular exercise activity is a key modifiable factor to the prevention and management of chronic diseases. Influence health across the lifespan and reduction of the risk of premature death through several biological mechanisms. Community older group’s lifestyle factors interventions contribute identity in their natural living environment. While the older health benefits of walking exercise training strategies are commonly to study, combined ketogenic diet and walking exercise interventions have induced greater benefits in community older groups.

Abstract：This paper uses the balanced panel data from 29 provinces (autonomous regions and municipalities) in China for a total of 17 years from 2000 to 2016 as a research sample, and establishes an empirical model to examine the impact of environmental regulations and technological innovation on the quality of economic growth. Then this paper test technological innovation as a threshold variable, in which play a regulatory role. Taking the provincial balanced panel data as a research sample, a fixed effect model, a system GMM model, and a panel threshold model were established for empirical testing and the robustness test. Based on the empirical results, this article draws the following conclusions: from a national perspective, environmental regulations and technological innovation can significantly promote the quality of economic growth; from a regional perspective, there are regional differences in impact effects. Under the constraints of environmental regulations, the promotion effect of technological innovation on the quality of economic growth will be reduced; the impact of environmental regulation on the quality of economic growth will have a "threshold effect", and environmental regulation can significantly promote the quality of economic growth only after crossing the threshold and the threshold of technological innovation.

Chinese texts often feature a substantial volume of normative content, and their analysis has increasingly become a focal point in recent semantic analysis endeavors. Enhancing the effectiveness of text classification and clustering is pivotal in unveiling the intricate semantics within extensive textual data. Empirical research within the realm of computational social science has underscored the need for improved explanatory power when it comes to general text clustering methods applied to normative texts. This study introduces an innovative hierarchical clustering method that incorporates part-of-speech (POS) features and pioneers a novel semantic network model. It achieves this by amalgamating a POS-based feature weight calculation method with hierarchical clustering techniques. To assess its efficacy, the method is rigorously evaluated across three diverse text datasets, encompassing normative reports, news articles, and social media content. The experimental results unequivocally demonstrate the superior performance of the POS-HC method, surpassing the traditional TF and TF-IDF feature extraction methods in terms of clustering accuracy, and surpassing some existing clustering methods. Furthermore, its classification effectiveness exhibits notable advantages, particularly in the semantic classification of normative texts.

Atopic dermatitis (AD) is a chronic inflammatory skin disease, which can cause skin barrier function damaged. Although co-incubation with docosahexaenoic acid (DHA) exerts a positive effect in deficient skin model, there is no study to investigate the effects of topical treatment with DHA in inflammatory reconstructed human epidermis (RHE) model. The effects of DHA on monolayer normal human epidermal keratinocyte (NHEK) cells were evaluated via CCK-8, qPCR and ELISA. The skin related barrier function was assessed by hematoxylin-eosin (HE) staining, western blot (WB), Immunohistofluorescence (IF) and ELISA in normal and inflammatory RHE models. DHA upregulated filaggrin and loricrin expression at mRNA levels in addition to suppress overexpression of TNF-α，IL-1α and IL-6 stimulated by poly I:C plus LPS (stimulation cocktail) in cultured NHEK cells. After topical treatment with DHA, cocktail induced inflammatory characteristics of skin diseases including barrier morphological, differentiation proteins and TSLP secretion, which were alleviated in RHE models. Supplementation with DHA can improved related barrier function and have anti-inflammation effects in monolayer keratinocytes and RHE models, which indicated that DHA may have a potential value for the treatment of inflammation-associate skin diseases.

Trichothecene mycotoxin T-2 toxin is an important environmental pollutant and poses a global threat to human and animal health. T-2 toxin could induce nephrotoxicity, however, the precise molecular mechanism remains unclear. In this study, the mice were intraperitoneally administrated with a single dose of 2 mg/kg T-2 toxin. The kidney function and ultrastructural observation were also assessed and found T-2 toxin exposure could cause kidney damage. Transmission electron microscopy showed a significant swelling and vacuolization of the mitochondria of renal cell. A total of 1122, 58, and 391 differential expression genes (DEGs) that were predominantly expressed in kidney tissues at 1 d, 3 d, and 7 d after T-2 toxin exposure, respectively. Early transcriptomic changes at 1 d after exposure were down-regulation of DEGs involved in the cell cycle, p53 signaling pathway, and cellular senescence, while up-regulation of DEGs referred to the ribosome pathway. The temporal variations in gene expression pattern in T-2 toxin exposure in mice kidney were presented and cellular metabolism was disturbed at the exposure recovery period with 7 d. In conclusion, this study, for the first time, provided a comprehensive comparative transcriptomic analysis of gene regulation in T-2 toxin exposure-induced nephrotoxicity at different temporal periods and explored the nephrotoxicity mechanism of T-2 toxin at the mRNA level.

Positron emission tomography (PET) imaging of Colony Stimulating Factor 1 Receptor (CSF1R) is a new strategy for quantifying both neuroinflammation and inflammation in the periphery since CSF1R is expressed on microglia. AZ683 has high affinity for CSF1R (K_i = 8 nM; IC₅₀ = 6 nM) and >250-fold selectivity over 95 other kinases and, in this paper, we report the radiosynthesis of [¹¹C]AZ683 and initial evaluation of its use in CSF1R PET. [¹¹C]AZ683 was synthesized by ¹¹C-methylation of the desmethyl precursor with [¹¹C]MeOTf in 3.0% non-corrected activity yield (based upon [¹¹C]MeOTf), >99% radiochemical purity and high specific activity. Preliminary PET imaging with [¹¹C]AZ683 revealed no brain uptake in rodents and nonhuman primates suggesting that [¹¹C]AZ683 is a poor candidate for imaging neuroinflammation, but that it could still be useful for peripheral imaging of inflammation.

The research fills the policy research gap for the women entrepreneurship and sustainability performance for examining key successful factors. Previous women entrepreneurship research fails to offer policy recommendations. The research purpose is to investigate these factors affect women entrepreneurship capabilities and sustainability performance by using SEM analysis and making policy recommendation. This research employs online and mail survey and obtains 175 women entrepreneur sample. The study finds that family support and motivation have positive effect on women entrepreneurship capabilities and sustainability performance. Barriers have no effect on performance. Hopefully, the research can provide the guidance to contribute to women’s entrepreneurship opportunities for achieving SDGs. Policy recommendation and managerial implication are discussed in the article.

Epitranscriptomic RNA modifications play a crucial role in the posttranscriptional regulation of gene expression. N6-methyladenosine (m6A) is the most prevalent internal modification of eukaryotic RNA and plays a pivotal role in RNA fate. RNA m6A modification is regulated by a group of cellular proteins, methyltransferases (writers) and demethylases (erasers), which add and remove the methyl group from adenosine, respectively. m6A modification is recognized by a group of cellular RNA-binding proteins (readers) that specifically bind to m6A-modified RNA, mediating effects on RNA stability, splicing, transport, and translation. The functional significance of m6A modification of viral and cellular RNA is an active area of virology research. In this review, we summarize and analyze current literature on m6A modification of HIV-1 RNA, the multifaceted functions of m6A in regulating HIV-1 replication, and the role of viral RNA m6A modification in evading the innate immune responses to infection. Furthermore, we briefly discuss future directions and therapeutic implications of mechanistic studies of HIV-1 epitranscriptomic modifications.

Threshing device is the core component of grain combine harvester, and its working performance determines the working quality and production efficiency of the harvester to a great extent. The straw guide plate plays an important role in the threshing device to dredge the threshing matter and control the threshing time of the combine harvester matter in the threshing chamber. In the past, the guiding structure of threshing device could not optimize the working performance of the machine by adjusting the spiral angle, that is, most cereal combine harvester may not be fed smoothly or even clogged when operating under different crop types, yield differences and operating environments, a kind of threshing device with adjustable guide straw board was studied. In this study, the movement model of the straw on the straw guide plate was analyzed, and it was found that the spiral angle “α”of the straw guide was 0<α<58°.Three-factor and three-level response surface method was used to carry out field experiment on drum speed, working speed and guide grass plate spiral angle, and the experimental data were analyzed by quadratic polynomial regression.The results show that the drum speed, working speed and the spiral angle of the guide grass plate have significant effects on the loss rate (PLR) , impurity content (PIR) and breakage rate (PBR) , the drum speed and working speed have an interactive effect on the impurity ratio (PIR) , and the working speed and the helical angle of the guide grass plate have an interactive effect on the loss ratio (PLR) and breakage ratio (PBR) , there is an interaction between the rotary speed of the roller and the helical angle of the guide grass plate on the crushing rate (PBR) .Further optimization analysis showed that the predicted value was PLR = 1.18% , PIR = 0.72% , PBR = 0.53% , the experimental verification value was PLR = 1.26% , PIR = 0.73% , PBR = 0.61% . The absolute error between the experimental value and the predicted value was very small, however, the optimized field test verified value decreased by 8.31% , 50.04% and 60.30% respectively, which indicated that the optimized harvester had better operation quality, in particular, PIR, PBR and other two indicators have a greater increase in the effect.

Economic development and advancements in information technology contributed to the shift on accounting objective from commission responsibility view to decision-making useful view. The decision-making useful view claims that the accounting measurement methods should be changed to improve the usefulness of accounting information, to enable information users to make correct decisions. In addition, the development of financial instruments leads to the birth of fair value accounting. In recent years, fair value has been one of the most important measurement methods in the International Accounting Standard and US Generally Accepted Accounting Principles. However, China has been quite cautious when it comes to applying fair value full time, especially after the global financial crisis happened in 2008, wherein fair value accounting was exposed to strong suspicion. Hence, studying the value relevance of fair value is of great significance to exploring the accounting profession and reforming accounting standards. This paper attempts to investigate the value-relevance of fair value based on the data of listed financial companies and manufacturing companies in China. The results indicate that the fair value information in the financial industry has a strong explanatory influence to corporate share price. In contrast, the fair value information shows limited relevance in the manufacturing industry. Finally, consulting with the results of normative analysis and empirical study, this paper suggests several rational advices for the application of fair value in China.

Technology can be seen everywhere and has been integrated into our lives.We are always using technology and enjoying the convenience brought by technology. However, physical retailers and e-commerce companies are also gradually adopting advanced technologies. Technology improves the purchasing environment and purchasing experience. Virtual reality and augmented reality have been hotly discussed in recent years. Technology, although virtual reality and augmented reality technology have not yet matured, it can be said that they will in the future It has great development potential. Virtual reality and augmented reality are also beginning to sprout in the retail industry. However, research on the acceptance of the use of virtual reality and augmented reality in the apparel shopping process is still lacking because This study explores how usefulness, ease of use, hedonicity, customer experience, customer engagement and satisfaction. To influence customer loyalty, this study adopted questionnaire survey and convenience sampling methods, and collected a total of 308 valid questionnaires. The analysis method used confirmatory factor analysis and structural equation model to verify the research hypothesis relationship. The results of this study found. Hedonic has a significant impact on customer loyalty, while usefulness, ease of use, customer experience, customer engagement and satisfaction Satisfaction does not have a significant impact on customer loyalty. This study explains the academic contribution of the research results. The practical implications in marketing are put forward, and specific suggestions and directions for future research are given.

Proteomics research has become one of the most important topics in the fields of life science and natural science. At present, research on protein–protein interaction networks (PPINs) mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate function module detection mechanisms in PPIN, including open databases, existing detection algorithms and recent solutions. After that, we describe the proposed solution based on simplified swarm optimization (SSO) algorithm and gene ontology knowledge. The proposed solution implements SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species dataset for experiment: Fruitfly, Mouse, Scere, and Human. The testing and analysis result show that the proposed solution is feasible, efficient and could achieve a higher accuracy of prediction than existing approaches.

In this study, we investigated the effects of three surface treatment techniques on 316L stainless steel, low-temperature immersion corrosion, shot peening followed by immersion corrosion, and electrochemical corrosion. Surface alterations were analyzed using scanning electron microscopy, Raman spectroscopy, and α-step thin-film thickness profiling. Human osteoblast adhesion was evaluated using Liu’s stain and metallographic optical microscopy. The results revealed weak cell adhesion after low-temperature immersion and shot peening followed by immersion corrosion. By contrast, electrochemical corrosion, particularly with a high current density and low corrosive solution concentration, resulted in a uniformly corroded surface, thus promoting dense cell adhesion. All three techniques resulted in porous oxide layers. Overall, our experimental findings highlighted shot peening (1 kg/cm2 for 20 s) and electrochemical corrosion (0.5 M HCl) as effective processes. Electrochemical corrosion produced uniformly dense corrosion pits, whereas shot peening produced semicircular grooves with small corrosion pits, both favorable for cell adhesion. Electrochemical corrosion also yielded excellent cell adhesion, emphasizing its suitability for biomedical activity. We developed a process for creating a porous surface layer and thereby enhancing the cell adhesion to 316L stainless steel for potential biomedical implant applications.

To understand lung damage caused by COVID-19, we deduced two-phase lung damage mechanisms. After the lungs are infected with SARS-CoV-2 virus, the affected lung tissue swells and surface properties of pulmonary capillaries change, resulting in an increased flow resistance of affected capillaries. If a sufficient number of capillaries are affected by the infection, the swelling and increased cell wall adhesion collectively raise pulmonary vascular resistance. The increased vascular resistance further increases the dwell times of WBCs in affected capillaries and nearly capillaries. When pulmonary pressure is sufficiently higher, WBCs are forced to squeeze into interstitial spaces or alveolar spaces when local pressures are higher than what the capillaries can withstand. When more and more WBCs are dynamically retained, the flow resistance of more capillaries rises, pulmonary vascular resistance rises, and pulmonary pressure rises. The rise in the pulmonary pressure in turn results in elevated capillary pressures. When capillary pressures around the alveoli are sufficiently high, they cause interstitial pressures to change from normally negative values to positive values. The positive pressures cause fluid leakage to the alveolar space and thus degrade lung function. Tissue swelling, and occupation of WBCs in interstitial spaces and alveolar spaces further reduce compressible volume, and thus cause further rise in the pulmonary vascular resistance and pulmonary pressure. When the pulmonary pressure has reached a critical point as in the second phase, the blood breaks capillary walls and squeezes through interstitial spaces to reach alveolar spaces, resulting in irreversible lung damages. The available free volume in the thorax cage, organ usable capacities, temperature and humid are expected to have great impacts on degree of lung damages. The free volume in the thorax cage, lung usable surplus capacity, and other organ usable capacities determine the arrival time of last-phase irreversible damage. The mechanisms imply that the top priority for protecting lungs is maintaining pulmonary micro-circulation and preserving organ functions in the entire disease course while controlling viral reproduction should be stressed in the earliest time possible. The mechanisms also explain leukecytes are recruited and migrated into inflamed tissues by increasing their dwell times caused by increased local flow resistance.

We aimed to evaluate the protective effects of acetyl-xylogalactan on the activity of RAW264.7 macrophages against heat stress. To this end, we assessed cell survival, phagocytic activity, in-tracellular Ca2+ level, mitochondria potential exchange, apoptotic assay findings, galactosidase activity and the RNA-seq by NGS and real-time polymerase chain reaction (PCR) expression. In our evaluation of macrophage morphology at 37°C and 41°C, the macrophages showed an oval shape at 41°C , unlike the spindle shape at 37°C. Therefore, 41°C was chosen as the heat stress condition. Subsequently, we designed an experiment to evaluate changes in the RAW264.7 macrophages after acetyl-xylogalactan treatment under heat stress. The survival of RAW264.7 macrophages treated with acetyl-xylogalactan was higher than that of controls that were not treated with acetyl-xylogalactan. Moreover, on the basis of the results of the annexin-V detection assay, the apoptotic activity of macrophages appeared to have reduced after treatment with ac-etyl-xylogalactan. Moreover, treatment with acetyl-xylogalactan resulted in a stronger recovery trend in the intracellular Ca2+ and mitochondrial membrane potential after heat stress. RNA sequencing and real-time polymerase chain reaction (PCR) illustrated that Sarcodia suieae acetyl-xylogalactan could upregulate the expression of the anti-apoptosis Cflar gene and down-regulate the expression of the apoptosis factors Ddit3, and Hyou1 to protect macrophages under heat stress.

In numerical simulations, achieving high accuracy without significantly increasing computational costs is often challenging. To address this, this paper presents an improved finite volume weighted essentially non-oscillatory (WENO) scheme tailored for applicability in computational fluid dynamics (CFD) and implemented in the flow solver NUAA-Turbo for simulating turbomachinery flows using both RANS and RANS/LES coupling. Firstly, the new WENO scheme is validated against classic numerical test cases to assess its stability and reliability in handling discontinuities, the Double problem, and Raleigh-Taylor (RT) instability issues. Compared to the original format, this enhanced finite volume WENO scheme demonstrates superior stability near discontinuities and resolves flow features with the same grid resolution more effectively. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, computations are performed using RANS, and the results obtained using WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupled simulations of turbine wakes and film cooling. The results show that the enhanced finite volume WENO scheme offers improved stability and accuracy in engineering applications, allowing for high-precision calculations with fewer grid points to capture more detailed flow physics, thereby reducing computational costs in aerodynamic applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

It is well established that the interacting effects of temperature and precipitation will alter agroecological systems on a global scale. These shifts will influence the fitness of specialty crops, specifically strawberries (Fragaria x ananassa), an important crop in the Northeastern United States. In this study, four precipitation scenarios were developed that are representative of current and probable-future growing season precipitation patterns. Using a precipitation simulator, we tested these scenarios on potted day neutral strawberries. This study generated four primary results: (1) though treatments received different amounts of precipitation, little difference was observed in soil volumetric water content or temperature. However, treatments designed to simulate future conditions were more likely those designed to simulate current conditions to have higher nitrate-in-leachate (N-leachate) concentrations; (2) neither total precipitation nor seasonable distribution were associated with foliar or root disease pressure; (3) while there was a slightly higher chance that photosynthetic potential and capacity would be higher in drier conditions, little difference was observed in the effects on chlorophyll concentration, and no water stress was detected in any treatment; and (4) leaf biomass was likely more affected by total rather than seasonal distribution of precipitation, but interaction between changing rainfall distribution and seasonal totals is likely to be an important driver of root biomass development in the future.

The fatigue delamination damage is one of the most important fatigue failure modes of laminated composite structures. However, the developments of the theoretical framework, mathematical/physical model and numerical simulation of fatigue delamination are still challenging issues, and there is a lack of systematic classification. This article reviews the experimental phenomena of the onset and propagation stage of delamination under fatigue loading, and summarizes the commonly used phenomenological models for laminated composite structures. The research methods, general modeling formulas and development prospects of the phenomenological models are presented in detail. In the light of the analysis of finite element model (FEM) for the laminated composite structures, a number of simulation methods of fatigue delamination crack propagation damage model are carefully classified. Furthermore, within the theoretical framework of strength theory model (SM), fracture mechanics model (FM), damage mechanics model (DM) and hybrid model (HM), the complete procedure, application, capability assessment, advantages and limitations of the models are also discussed in detail. Finally, several valuable suggestions are given for the research interests, and challenging technical problems that need to be overcome on the fatigue delamination prediction of laminated composite structures in the future.

Passion fruit is a valued tropical fruit crop that faces environment-related growth strains. TCP genes are important for both growth modulation and stress prevention in plants. Herein, we systematically analyzed the TCP gene family in passion fruit, recognizing 30 members. Genes exhibiting closer phylogenetic relationships exhibited similar protein and gene structures. Gene members of the TCP family showed developmental stage or tissue-specific expression profiles during the passion fruit life cycle. Transcriptome data also demonstrated that many PeTCPs showed induced expression in response to hormonal treatments and cold, heat, and salt stress. Based on transcriptomics data, eight candidate genes were chosen for preferential gene expression confirmation under cold stress conditions. Additionally, four TCP genes exhibited in silico binding with cold stress-related miRNA319s. This study will aid in the establishment of novel germplasm, as well as the further investigation of the roles of PeTCPs and their cold stress resistance characteristics.

By introducing environmental mediator, for avoiding randomness in selecting indicators and subjectivity in deciding interaction path coefficients to reveal interaction mechanism among forest industry, ecology and environmental capacity, structural Pressure–State–Impact–Response (PSIR) and quantitative Structural Equation Modeling (SEM) are utilized with data on thirty–one provinces of China. We can find that: (i) forest industry has a negative influence on ecology, whereas ecology has a positive influence on industry; (ii) the destructive influence that industry has on ecology is much greater than the positive effect ecology has on industry; and (iii) environmental capacity plays a partial mediating role between industry and ecology. According to these results we can conclude that: (i) forest industry and ecology are not in a symbiotic relationship and have not reached a level of ecological security; (ii) the interaction between industry and ecology is in a period of transition from antagonistic to beneficial; and (iii) industry dominates ecology. However, we prospect the following advice: (i) methods of forest industry should be changed; (ii) new modes of industrial integration and circular economy should be developed; and (iii) the ability of the environment to sustain itself should be enhanced. The level of forest ecological security to discuss the symbiotic mechanism of industry and ecology will propose to be measured in future.

Tremor is a prevalent neurological disorder characterized by involuntary shaking or trembling of body parts. This condition impairs fine motor skills and hand coordination to varying degrees and can even affect overall body mobility. As a result, tremors severely disrupt the daily lives and work of those affected, significantly limiting their physical activity space. This study developed an innovative Spatial Augmented Reality (SAR) system aimed at assisting individuals with tremor disorders to overcome their physical limitations and expand their range of activities. The system integrates eye-tracking and Internet of Things (IoT) technologies, enabling users to smoothly control objects in the real world through eye movements. It employs a virtual stabilization algorithm for stable interaction with objects in the real environment. The study comprehensively evaluated the system's performance through three experiments: 1) assessing the effectiveness of the virtual stabilization algorithm in enhancing the system's ability to assist individuals with tremors in stable and efficient interaction with remote objects; 2) evaluating the system's fluidity and stability in performing complex interactive tasks; 3) investigating the precision and efficiency of the system in remote interactions within complex physical environments. The results demonstrate that the system significantly improves the stability and efficiency of interactions between individuals with tremor and remote objects, reduces operational errors, and enhances the accuracy and communication efficiency of interactions.

After reviewing cancer theories, cancer treatment development histories, randomized clinical trial's performance, cancer treatment strategy, trial follow-up times, and conducting numerous simulations using existing data, the authors found: (1) medical treatments come with three to four lethal factors: treatment side-effects, emotional distress and chronic dress, lack of exercises or physical inactivity, and excessive nutrition in some cases; (2) clinical trial exaggerates the benefits of fast-acting treatments and underestimates the slow-delivering adverse side effects as a result of statistical averaging, interfering effects of personal lifestyle factors, and insufficient follow-up times; (3) the benefits of medical treatments are limited by chain comparison, where surgery sets up a negative standard relative to the best way for resolving cancer; (4) the strategy of destroying the tumor is unworkable; (5) medical treatments can turn natural cancer growth curve into approximately doubly exponential curve; (6) multiple factor non-medical measures are much more powerful than medical treatments in controlling cancer growth and metastasis rates; and (7) cancer early diagnosis and over treatments are bad strategies that have great adverse impacts on cancer patients. Based on huge increases in cancer growth rate constants, substantial of loss of organ functional capacity, and severe systemic aging-like cellular damages, the authors concluded that medical treatments promote cancer growth and metastasis rates and shorten patient lives in most cases, and the claimed benefits are caused by triple biases of clinical trials. The authors believe that the better strategy for ending the global cancer epidemic is abandoning clinical trails as the research model, changing caner treatment strategy from killing cancer cells to slowing down cancer growth rates by using multiple factors optimization approach in personalized medicine.

This paper studies the contemporaneous relationship between S&P 500 index returns and log-increments of the market volatility index (VIX) via a nonparametric copula method. Specifically, we propose a conditional dependence index to investigate how the dependence between the two series varies across different segments of the market return distribution. We find that: (a) the two series exhibit strong, negative, extreme tail dependence; (b) the negative dependence is stronger in extreme bearish markets than in extreme bullish markets; (c) the dependence gradually weakens as the market return moves toward the center of its distribution, or in quiet markets. The unique dependence structure supports the VIX as a barometer of markets' mood in general. Moreover, applying the proposed method to the S&P 500 returns and the implied variance (VIX²), we find that the nonparametric leverage effect is much stronger than the nonparametric volatility feedback effect, although, in general, both effects are weaker than the dependence relation between the market returns and the log-increments of the VIX.