This study presents the utilization of the Microwave InfraRed Thermography (MIRT) technique to identify and analyze the defects in the carbon-fiber-reinforced polymer (CFRP) composite rein-forcement of concrete specimens. At first, a set of the numerical models was created, comprising of the broadband pyramidal horn antenna and the analyzed specimen. The utilization the system operating at a power of 1000W in a continuous mode, operating at frequency of 2.45 GHz was analyzed. The specimen under examination comprised a compact concrete slab that was covered with an adhesive layer, thereafter, topped with a layer of CFRP. An air gap represented a defect at the interface between the concrete and CFRP within the adhesive layer. In the modelling stage the study investigated three separate scenarios: a sample with no defects, a sample with a defect located at the center, and a sample with a numerous additional random defects located at the rim of the CFRP matte, to analyze the effect of the natural reinforcement degradation in this area. The next phase of the study involved conducting experiments to confirm the results obtained from nu-merical modeling. In the experiments the concrete sample aged for 10 years with the defect in the center and naturally developed defects at the CFRP rim was used. The study employed numerical modeling to explore the phenomenon of microwave heating in complex structures. The aim was to assess the chosen antenna design and identify the most effective experimental setup. These con-clusions were subsequently confirmed through experimentation. The observations made during the heating process were particularly remarkable, since they deviated from earlier studies that solely conducted measurements of the sample post-heating phase. The findings demonstrate that MIRT has the capacity to be employed as a technique for detecting flaws in concrete structures reinforced with CFRP.

Minimally invasive surgery for adult spinal deformities (MIS deformity surgery) utilizes MIS lumbar interbody fusion and percutaneous pedicle screw fixation (PPSF) without posterior corrective osteotomy. While MIS reduces issues associated with open deformity surgery, it has limitations in correcting sagittal imbalance. This review discusses the limitations and solutions of lateral lumbar interbody fusion (LLIF) and introduces our experience in addressing marked sagittal deformities. We reviewed the literature and incorporated our clinical experience to evaluate the efficacy of recent MIS techniques, particularly focusing on oblique lumbar interbody fusion (OLIF) at L1-5 and L5-S1. The use of higher profile and greater angle cages and the application of PPSF with curved rods and percutaneous rod compression were discussed. Advances in MIS techniques, such as OLIF, have enabled significant improvements in increasing disc height and angle. Combining these new techniques and concepts, we successfully corrected marked sagittal deformities using MIS deformity surgery. Early onset of proximal junctional kyphosis was identified as a notable complication. Although recent advancements in MIS deformity surgery have shown promise in correcting sagittal deformities, further clinical experience and data are necessary to enhance outcomes and mitigate complications such as proximal junctional kyphosis.

Ensuring precise segmentation of colorectal polyps holds critical importance in the early diagnosis and treatment of colorectal cancer. Nevertheless, existing deep learning-based segmentation methods are fully-supervised, requiring extensive precise manual pixel-level annotation data, which leads to high annotation costs. Additionally, it remains challenging to train large-scale segmentation models when confronted with limited colonoscopy data. To address these issues, we introduce the general segmentation foundation model—Segment Anything Model (SAM) into the field of medical image segmentation. Fine-tuning the foundation model is an effective approach to tackle sample scarcity. However, current SAM fine-tuning techniques still rely on precise annotations. To overcome this limitation, we propose WSPoly-SAM, a novel weakly-supervised approach for colonoscopy polyp segmentation. WSPoly-SAM utilizes weak annotations to guide SAM in generating segmentation masks, which are then treated as pseudo-labels to guide the fine-tuning of SAM, thereby reducing the dependence on precise annotations data. To improve the reliability and accuracy of pseudo-labels, we have designed a series of enhancement strategies to improve the quality of pseudo-labels and mitigate the negative impact of low-quality pseudo-labels. Experimental results on five medical image datasets demonstrate that WSPoly-SAM outperforms current fully-supervised mainstream polyp segmentation networks on the Kvasir-SEG, ColonDB, CVC-300, and ETIS datasets. Furthermore, by using different amounts of training data in weakly-supervised and fully-supervised experiments, it is found that weakly-supervised fine-tuning can save 70% to 73% of annotation time costs compared to fully-supervised fine-tuning. This study provides a new perspective on the combination of weakly-supervised learning and SAM models, significantly reducing annotation time and offering insights for further development in the field of colonoscopy polyp segmentation.

Segment Anything Model 2 (SAM 2) is a state-of-the-art development by Meta AI Research, designed to address the limitations of its predecessor, SAM, particularly in the realm of video segmentation. SAM 2 employs a transformer-based architecture enhanced with streaming memory, enabling real-time processing for both images and videos. This advancement is important given the exponential growth of multimedia content and the subsequent demand for efficient video analysis. Utilizing the SA-V dataset, SAM 2 excels in handling the intricate spatio-temporal dynamics inherent in video data, ensuring accurate and efficient segmentation. Key features of SAM 2 include its ability to provide real-time segmentation with minimal user interaction, maintaining robust performance even in dynamic and cluttered visual environments. This study provides a comprehensive overview of SAM 2, detailing its architecture, functionality, and diverse applications. It further explores the model's potential in improving practical implementations across various domains, emphasizing its significance in advancing real-time video analysis.

The proliferation of Internet of Things (IoT) devices on Linux platforms has heightened concerns regarding vulnerability to malware attacks. This paper introduces a novel approach to investigating the behavior of Linux IoT malware by examining syscalls and library syscall wrappers extracted through static analysis of binaries, as opposed to the conventional method of using dynamic analysis for syscall extraction. We rank and categorize Linux system calls based on their security significance, focusing on understanding malware intent without execution.Feature analysis of the assigned syscall categories and risk ranking is conducted with statistical tests to validate their effectiveness and reliability in differentiating between malware and benign binaries. Our findings demonstrate that potential threats can be reliably identified with an F1 score of 96.86%, solely by analyzing syscalls and library syscall wrappers. This method can augment traditional static analysis, providing an effective preemptive measure to enhance Linux malware analysis. This research highlights the importance of static analysis in strengthening IoT systems against emerging malware threats.

A catastrophic loss of microbial biodiversity on the skin has led to alarming increase in the prevalence of allergies and long-term damage to the skin, which could also have damaging knock on effects to overall health. This study uses 50 human participants, to obtain an average (benchmark) value for the biodiversity of ‘healthy’ western skin, which is crucial in updating our 2017 skin health measuring mechanism to use standardised methodology. Previous work with a larger sample size was unsatisfactory for use as a benchmark due to its use of different and outdated diversity indices. We also investigated the effect of age and sex, two known skin microbiome affecting factors. Although no statistical significance is seen for age- and sex- related changes in diversity, there appear to be changes related to age which elaborates on previous work which used larger, more general age ranges. Our study indicates adults age 28-37 have highest diversity, and age 48-57 the lowest. Crucially, because of this study we are now able to update the skin health measuring mechanism from our 2017 work. This will aid diagnostic assessment of susceptibility to cutaneous conditions or diseases, and treatment. Testing any human subject will be rapidly improved by obtaining future benchmark diversity values for any age, sex, body site and area of residence, to which they can be compared. This improvement means we can also more accurately investigate the ultimate question: What factors in the western world are a main cause of the skin allergy epidemic? This could lead to future restriction of certain synthetic chemicals or products found to be particularly harmful to the skin.

There is a skin allergy epidemic in the western world, and the rate of deterioration has increased significantly in the past 5-10 years. It is probable that there are many environmental contributing factors, yet some studies have linked it primarily to the rise in the use of synthetic chemical ingredients in modern cosmetics. Our challenge, therefore, was to find a mechanism to determine the effect these substances have on skin health, and whether they really are a primary cause of long term damage to the skin. The first problem is the lack of any definitive way to measure skin health. Motivated by the overwhelming evidence for a link between deficient gut flora and ill health, we decided to look at whether our skin microbiota could similarly be used as an indicator of skin health. Our research illustrates how it is microbiota diversity alone that can predict whether skin is healthy or not, after we revealed a complete lack of conclusive findings linking the presence or abundance of particular species of microbe to skin problems. This phenomenon is replicated throughout nature, where high biodiversity always leads to healthy ecosystems. ‘Caveman’ skin, untouched by modern civilisation, was far different to ‘western’ skin and displayed unprecedented levels of bacterial diversity. The less exposed communities were to western practices, the higher the skin diversity, which is clear evidence of an environmental factor in the developed world damaging skin. For the first time we propose benchmark values of diversity against which we can measure skin to determine how healthy it is. This gives us the ability to be able to predict which people are more likely to be prone to skin ailments, and start to test whether cosmetic ingredients and products are a main cause of the skin allergy epidemic.

Conventional traceability systems in Cambodian agriculture, such as Rubber Supply Chain Management (RSCM), often struggle to provide timely data and fair market prices, leading to mistrust among stakeholders, exploitation by intermediaries, and hindering progress towards ethical sourcing and sustainable practices. This research aims to showcase the potential of integrating blockchain technology, the Internet of Things (IoT), the InterPlanetary File System (IPFS), and Differential Privacy (DP) methods to empower Cambodian rubber farmers. By enhancing transparency, facilitating fair pricing, and promoting sustainable methods in the rubber industry, this integrated approach leverages Hyperledger Fabric (HLF) to create a decentralized and secure system for tracking rubber from its source to the end consumer. Integration with IPFS ensures secure and easily accessible data storage, further enhancing the system’s reliability. Additionally, the implementation of differential privacy techniques safeguards confidential data during information sharing among farmers and supply chain stakeholders, minimizing potential privacy concerns. This comprehensive system encourages consumers to make ethical and sustainable alternative options by providing accessible information on harvesting methods, processing procedures, labor conditions, and environmental impacts. The potential benefits extend beyond Cambodia, serving as a model for other developing countries aiming to modernize and enhance the agricultural distribution networks. Our results show that transaction send rates (TPS) and throughput in systems with and without differential privacy grow with increased transaction volumes. However, the system without differential privacy achieves greater scalability and efficiency above a certain threshold. However, it offers a slightly reduced latency, reflecting a trade-off between privacy and performance efficiency in blockchain-based agricultural traceability systems.

Optical coherence tomography (OCT) is a non-invasive imaging technique widely used in ophthalmology for visualizing retinal layers, aiding in early detection and monitoring of retinal diseases. OCT is useful for detecting diseases such as age-related macular degeneration (AMD) and diabetic macular edema (DME), which affect millions of people globally. Over the past decade, the area of application of Artificial Intelligence (AI), particularly Deep Learning (DL), has significantly increased. The number of medical applications is also rising, with solutions from other domains being increasingly applied to OCT. The segmentation of biomarkers is an essential problem that can enhance the quality of retinal disease diagnostics. For 3D OCT scans, AI is beneficial since manual segmentation is very labor-intensive. In this paper, we employ the new SAM 2 and MedSAM 2 for the segmentation of OCT volumes for two open-source datasets, comparing their performance with the traditional U-Net. The model achieved an overall Dice score of 0.913 and 0.902 for macular holes (MH) and intraretinal cysts (IRC) on OIMHS and 0.888 and 0.909 for intraretinal fluid (IRF) and pigment epithelial detachment (PED) on the AROI dataset, respectively.

The open communication is an exigent need for future power system where the time delay is unavoidable. In order to secure the stability of the grid, the frequency must remain within its limited range which is achieved through the load frequency control. The load frequency control signals are transmitted through communication networks which induces time delay that could destabilize the power systems. So, in order to guarantee the stability the delay margin should be computed. In this paper, we present a new method for calculating the delay margin in load frequency control systems. The transcendental time delay characteristics equation is transformed to frequency dependant equation. The spectral radius is used to find the frequencies at which the roots crosses the imaginary axis. The crossing frequencies are determined through the sweeping test and the binary iteration algorithm. A one-area load frequency control system is chosen as case study. The effectiveness of the proposed method has been proved through comparing with the most recent published methods. The method shows its merit with less conservativeness and less computations. The PI controller gains are preferable to be chosen large to reduce the damping, however, the delay margin decreases with increasing the PI controller gains.

Siliceous sandstones used in Khmer temples such as the Prasat Basset, Wat Ek Phnom, Phnom Banan temples in Battambang Province, Phnom Chisor and Ta Prohm temples in Ta Keo Province, and Wat Nokor Bachey temple in Kampong Cham Province in Cambodia were investigated in this study. Chemical composition analyses and magnetic susceptibility measurements were conducted for the sandstone blocks used in these temples. Siliceous sandstone is a primary construction material in all investigated temples. Two types of siliceous sandstone, pale brown and red, were found. Pale brown siliceous sandstone was used for the construction of all the investigated temples. In contrast, red siliceous sandstone was found only in the Wat Ek Phnom, Prasat Basset, and Phnom Banan temples. It is suggested that the pale brown siliceous sandstone originated from the Phra Wihan Formation within the Khorat Group. Based on the chemical composition analysis, the pale brown siliceous sandstone in the Ta Prohm temple at Tonle Bati and the Wat Nokor Bachey temple may have been sourced from the lower level of the Phra Wihan Formation. In contrast, the pale brown siliceous sandstone used in the Prasat Basset, Wat Ek Phnom, and Phnom Banan temples was likely sourced from the upper level. The origin of the red siliceous sandstone is proposed to be from the Sao Khua Formation, which is situated above the Phra Wihan Formation.

This review aims to consolidate varied information regarding Port Scanning, and examine the tools, techniques, and detection algorithms used. It explores TCP SYN, Full TCP, UDP, and stealth scans, and shows their functions and abilities. Paired with these techniques, it also shows the tools that they can be used by, such as NMap, Zmap, and MASSCAN. It discusses the various detection techniques such as Signature and Anomaly based detection, and discusses the real world impact of this technology, while commenting on the legal and ethical issues posed.

The Dph1•Dph2 heterodimer from yeast is a radical SAM (RS) enzyme that generates the 3-amino-3-carboxy-propyl (ACP) precursor for diphthamide, a clinically relevant modification on eukaryotic elongation factor 2 (eEF2). ACP formation requires SAM cleavage and atypical Cys-bound Fe-S clusters in each Dph1 and Dph2 subunit. Intriguingly, the first Cys residue in each motif locates next to another, ill-defined cysteine that we show in-here is conserved across eukaryotes. As judged from structural modeling, the orientation of these tandem cysteine motifs (TCM) suggests a candidate Fe-S cluster ligand role. Hence, we generated by site-directed DPH1 and DPH2 mutagenesis, Dph1•Dph2 variants with cysteines from each TCM replaced individually or in combination by serines. Assays diagnostic for diphthamide formation in vivo reveal that while single substitutions in the TCM of Dph2 cause mild defects, double mutations almost entirely inactivate the RS enzyme. Based on enhanced Dph1 and Dph2 subunit instability in response to cycloheximide chases, the variants with Cys substitutions in their cofactor motifs are particularly prone to protein degradation. In sum, we identify a fourth functionally cooperative Cys residue within the Fe-S motif of Dph2 and show that the Cys-based cofactor binding motifs in Dph1 and Dph2 are critical for the structural integrity of the dimeric RS enzyme in vivo.

Green economy has emerged as a significant pillar of sustainable development in the current global context, and the unpredictability of economic policy has progressively garnered the interest of businesses and government officials as one of the obstacles they must confront. This paper examines how uncertainty in the green economy impacts the green economy's efficacy. The research concentrates on how changes in a particular region can result in geospatial diffusion (spatial spillover), which is a form of spatial spillover wherein the uncertainty of the green economy can impact its efficacy. This paper examines the policy formulation and current state of the green economy across various regions, as well as the diffusion of economic policy uncertainty across geographical areas and the subsequent impact on the green economy's status quo. There is a negative correlation between economic policy uncertainty and green economy efficacy, according to research. There is a spatial spillover effect between economic policy uncertainty and the efficacy of the green economy. Regional variations exist in the impact of economic policy uncertainty on the efficacy of the green economy. The findings indicate that the implementation of AI has a more substantial beneficial effect on carbon emissions. An increase in carbon dioxide emissions poses a growing challenge for the industrial sector in its pursuit of carbon neutrality.

Markets dominate the world’s food systems. Today’s food systems fail to realize the normative foundations of ecological economics: justice, sustainability, efficiency, and value pluralism. I argue that markets, as an institution for governing food systems, hinder the realization of these objectives. Markets allocate food toward money, not hunger. They encourage shifting costs on others, including nonhuman nature. They rarely signal unsustainability, and in many ways cause it. They do not resemble the efficient markets of economic theory. They organize food systems according to exchange value at the expense of all other social, cultural, spiritual, moral, and environmental values. I argue that food systems can approach the objectives of ecological economics roughly to the degree that they subordinate market mechanisms to social institutions that embody those values. But such “embedding” processes, whether through creating state policy or alternative markets, face steep barriers and can only partially remedy food markets’ inherent shortcomings. Thus, ecological economists should also study, promote, and theorize non-market food systems.

An article's tone and framing not only influence an audience's perception of a story but may also reveal attributes of author identity and bias. Building upon prior media, psychological, and machine learning research, this neural network-based system detects those writing characteristics in ten news agencies' reporting, discovering patterns that, intentional or not, may reveal an agency's topical perspectives or common contextualization patterns. Specifically, learning linguistic markers of different organizations through a newly released open database, this probabilistic classifier predicts an article's publishing agency with 74% hidden test set accuracy given only a short snippet of text. The resulting model demonstrates how unintentional 'filter bubbles' can emerge in machine learning systems and, by comparing agencies' patterns and highlighting outlets' prototypical articles through an open source exemplar search engine, this paper offers new insight into news media bias.

This study analyzes the relationship between economic policy uncertainty (hereinafter EPU) and corporate value, and verifies the differential effects of EPU on corporate value according to corporate social responsibility (hereinafter CSR) activities. The study period was from 2010 to 2020, and the EPU indexes measured by Baker et al. (2016)'s method and Hexun's CSR scores for companies listed on the Chinese stock market were used. Hexun is one of the three major evaluation agencies in China, and the CSR scores evaluated by this agency have been widely used in previous studies as a representative indicator of Chinese companies' CSR performance. The results of this study are as follows. First, EPU and corporate value were found to have a negative (-) relationship. Second, active CSR activities relieved the negative (-) relationship between EPU and corporate value. Finally, companies were divided into groups according to CSR activity scores to analyze the relationship and according to the result, the negative (-) relationship between EPU and corporate value was greater in the groups with low CSR activity scores than in the groups with high CSR activity scores. A lag model was applied to control endogeneity, and the results were consistent with the main results above. Previous studies have mainly focused on microscopic factors to investigate factors affecting corporate value. This study focused on macroeconomic policies and paid attention to the effects of changes in the macroenvironment caused by economic policy uncertainty on corporate value. In addition, this study is meaningful in that it expanded previous studies related to CSR activities by confirming that active CSR activities can be an advantageous tool for overcoming EPU.

Vitamin C is an essential nutrient that must be obtained through the diet in adequate amounts to prevent hypovitaminosis C and the potentially fatal deficiency disease scurvy. Global vitamin C status and prevalence of deficiency has not previously been reported, despite vitamin C’s pleiotropic roles in both non-communicable and communicable disease. This review highlights the global literature on vitamin C status and the prevalence of hypovitaminosis C and deficiency. Related dietary intake is reported if assessed in the studies. We also explore if global vitamin C status has changed over time. Overall, the review illustrates the shortage of high quality epidemiological studies of vitamin C status in many countries, particularly low- and middle-income countries. The available evidence indicates that vitamin C deficiency is common in low- and middle-income countries and not uncommon in high income settings. Further high quality studies are required to confirm these findings, including in the countries not yet represented, and to fully understand associations with a range of disease processes. Our findings suggest a need for interventions to prevent deficiency in a range of at risk groups and regions of the world.

A recent review of global vitamin C status indicated a high prevalence of deficiency, particularly in low- and middle-income countries, as well as in specific subgroups within high-income countries. Here we provide a narrative of potential factors influencing vitamin C status. The in vivo status of vitamin C is primarily affected by dietary intake and supplement use. Dietary intake can be influenced by cultural aspects such as staple foods and traditional cooking practices. Environmental factors can also affect vitamin C intake and status; these include geographic region, season and climate, as well as pollution. Demographic factors such as sex, age, and race are known to affect vitamin C status, as do socioeconomic factors such as deprivation, education and social class, and institutionalization. Various health aspects affect vitamin C status; these include body weight, pregnancy and lactation, genetic variants, smoking, and disease states, including severe infections as well as various non-communicable diseases such as cardiovascular disease and cancer. Some of these factors have changed over time, therefore we also explore if vitamin C status has shown temporal changes. Overall, there are numerous factors that can affect vitamin C status to different extents in various regions of the world. Many of these factors are not taken into consideration during the setting of global recommended dietary intakes for vitamin C.

In this paper we aim to help topical probiotics research and development achieve its potential as an incredible future solution for skin problems by investigating whether the current products on the market satisfy criteria for safe and effective use on the skin microbiome. As previously defined, this includes whether they use microbes known to be part of a healthy skin microbiome and in healthy amounts. In addition, we evaluate whether they contain live microbes, and therefore can be classified as probiotics according to the WHO’s definition. Using recent market analysis at least 84% of products do not contain live microbes. Of the products that appeared to use live microbes, they contained those used in research and development of probiotics for the gut. Due to the varying composition of each person’s microbiome, there is not a one size fits all probiotic solution. Personalisation of probiotics products is essential to satisfy the criteria for safe and effective use, but none of the products on the market, understandably, offer this. Upsetting the delicate ecosystem balance of the skin microbiome could have damaging effects and regulation could help to stop a loss of trust between consumers and cosmetics industry. Future work will perform an in-depth evaluation of the topical probiotics on the market in the EU, USA, and Canada. We will also investigate how to move the topic closer to achieving its potential by updating the criteria, including by discussing how to measure the success of a probiotic solution.

This short communication reports on the initial results of a much larger, ongoing project, the aim of which is to investigate the question: could the skin microbiome, just like the gut microbiome, play a role in sports recovery and performance – and if so, could this role be as significant a one as that played by the gut microbiome? 17 high performance college athletes addressed their skin microbiome by minimizing contact with synthetic chemicals and by using topical skin supplements, shown previously to significantly increase skin microbiome biodiversity, for two weeks after training. 76% said their skin softness improved, 35% said their muscle stiffness and recovery after sport improved, 12% said their sleep quality improved, and 100% said they would be likely to use skin supplements again. Future work will use hundreds of athletes.

No research to date has explored the possibility of context-specific, within-relationship fluctuation in attachment security. In this present article, two cross-sectional studies were designed (1) to develop and validate context-specific attachment scales in Traditional-Chinese, and (2) to explore fluctuations in within-parent attachment security between the contexts of sport and academics, in relation to global attachment patterns and indicators of psychological wellbeing. Results indicated that youth can and do perceive within-parent attachment patterns differently depending upon context but that the relationship of such differences to context-specific outcomes is complex. Of particular interest was that the degree of within-parent attachment variability between contexts was clearly and negatively related to indices of psychological wellbeing. This suggests that contextual variation may be a meaningful and useful way to explore within-parent attachment fluctuation.

Vein blood sampling is one of the methods of mass blood sampling, and is an act of drawing blood from a vein for blood type discrimination, confirmation of various physiological indicators, disease diagnosis, and the like, and is the most commonly used blood sampling method. An important point in vein blood sampling is to search for the exact location of the vein and insert the blood sampling. This is influenced by the patient's obesity, skin and blood vessel conditions, and the experience of the clinical technologist, nurse, and resident who performs the blood sampling. It is required to perform blood sampling technique practice. However, due to many limitations of the practice room or laboratory, there is a problem of using only a limited environment and model for clinical practice. As a result, many medical educational institutions have situations in which only fragmentary clinical practices are performed, and it is difficult to per-form a large number of blood sampling skills practices, so they do not provide enough experience to understand the actual skill field. In this paper, we propose a method for developing a virtual reality-based vein blood sampling simulator to practice a large number of blood sampling techniques without restrictions. The proposed vein blood sampling simulator can operate a 3D model related to vein blood sampling using HMD Controller and Haptic in a virtual space for vein blood sampling practice by wearing an HMD (Head mounted display), and can perform vein blood sampling practice through interaction with the patient 3D model. there is. In addition, the effectiveness of the simulator developed for dental students was verified, and as a result of the verification, the potential of the proposed vein blood sampling simulator was confirmed.

Viral integration within the host genome plays a pivotal role in carcinogenesis. Various disruptive mechanisms are involved, leading to genomic instability, mutations, and DNA damage. With next-generation sequencing (NGS), we can now precisely identify viral and host genomic breakpoints and chimeric sequences, which are useful for integration site analysis. In this study, we evaluated a commercial hybrid-capture NGS panel specifically designed for detecting three key viruses: HPV, HBV, and HIV-1. We also tested workflows for Viral Hybrid Capture (VHC) and Viral Integration Site (VIS) analysis, leveraging customized viral databases in CLC Microbial Ge-nomics. By analyzing sequenced data from virally infected cancer cell lines (including SiHa, HeLa, CaSki, C-33A, DoTc2, 2A3, SCC154 for HPV; 3B2, SNU-182 for HBV; and ACH-2 for HIV-1), we precisely pinpointed viral integration sites. The workflow also highlighted disrupted and neigh-boring human genes that may play a crucial role in tumor development. Our results included in-formative virus-host read mappings, genomic breakpoints, and integration circular plots. These visual representations enhance our understanding of the integration process. In conclusion, our seamless end-to-end workflow bridges the gap in understanding viral contributions to cancer development, paving the way for improved diagnostics and treatment strategies.

A university canteen is a queueing system characterised by non-stationary time of arrival with limited resources where the arrival rate is time dependent and has different pattern of arrival for different time interval. This means at certain time of the day, the arrival rate is much higher than other time and for a university canteen, the arrival rate of customer during the lunchtime is much higher and the food (resources) is limited. Non-stationary time dependent queueing system is not easily modelled mathematically hence such queueing systems are modelled using simulation tools such as ARENA. In order to model a non-stationary time dependent queueing system with limited resources and solve queueing problems using ARENA, researchers have to depend on their knowledge and experience in identifying the appropriate and relevant parameters for the system and make modifications to these parameters of the system to solve queueing problems by means of trial and error. Hence, this research work explores the potentials of applying a systematic problem solving tool, TRIZ to help users to make better decisions in deriving solutions to improve a non-stationary time dependent queueing system with limited resources. A case study was carried out to minimize the waiting time of the customers at the cafeteria of the Faculty of Engineering, Universiti Putra Malaysia (UPM), which has queueing problems for years during lunchtime. TRIZ was applied in this case study and the results showed that TRIZ can assist researchers to derive a solution model that lead to shorter waiting time without incurring additional cost and resources.

Helicobacter pylori (H. pylori) is known to play a significant role in the development of peptic ulcer diseases and gastric cancer. Previous studies have reported the existence of polymorphism in the ureC gene of H. pylori. However, the relationship between genetic sequence variations in ureC and the pathogenesis of peptic ulcer diseases remains unclear. We aimed to investigate the associations between ureC sequence variations and the development of gastric ulcer and gastric cancer. PCR amplification and DNA sequencing to analyze ureC sequences, and conducted phylogenetic analysis using MEGA X software. Samples from Taiwanese patients with gastric ulcer and gastric cancer were included in this study. PCR was used to amplify the ureC gene from these samples, followed by DNA sequencing. The obtained sequences were then subjected to phylogenetic analysis using MEGA X software. In addition, ureC sequences from different geographical regions, including China and other countries, were included in the analysis for comparison. Analysis of the ureC se-quences from Taiwanese samples revealed that 6 out of 7 gastric ulcer samples clustered together in one group, while the sequences from 7 out of 8 gastric cancer samples were distributed across other groups. Phylogenetic analysis incorporating ureC sequences from different geographical regions showed that Taiwanese ureC sequences could be divided into two distinct groups, although the bootstrap values supporting this separation were low. Notably, the ureC sequences from China formed a distinct group with a high bootstrap value, separate from sequences from all other countries. There are two genotypes of ureC sequences present in Taiwanese samples, with one genotype showing a closer association with gastric cancer. Additionally, the ureC sequences from China appear to be unique and separate from those obtained from other countries, indicating the presence of genetic diversity in ureC sequences among H. pylori strains from different regions, potentially contributing to differences in disease outcomes. Further research is needed to elucidate the specific mechanisms by which ureC sequence variations may influence the pathogenesis of peptic ulcer diseases and gastric cancer.

The fusion of machine learning, biomedical, and bioengineering research offers novel ways to understand, diagnose, and treat various health conditions. However, the complexities of biomedical and bioengineering data, coupled with the intricate process of developing and deploying machine learning solutions, often pose significant challenges to researchers in these fields. We introduce a new Automatic Semantic Machine Learning Microservice Framework (AIMS) that addresses these challenges by automating key aspects of the machine learning pipeline, from data preprocessing to model evaluation. Our proposed framework emphasizes model interpretability, the integration of domain knowledge, and the efficient handling of biomedical data. Furthermore, it incorporates self-supervised knowledge learning strategies, enabling the automatic generation, optimization, and continuous adaptation of machine learning models in response to new tasks and data. We illustrate the potential of our framework through three case studies in biomedical research, showcasing its capacity to streamline research processes, improve scientific exploration quality, and provide a foundation for significant breakthroughs.

Doping can alter the electronic and thermoelectric attributes of an organic semiconductor system. These alterations can enable viable tunable devices that have applications in temperature sensing for environmental controls. Here we demonstrate a dual-modulation organic field-effect transistor (OFET) where temperature effectively modulates the current-voltage characteristics of the OFET and gate voltage modulates the thermoelectric properties of the active layer. Poly(3-hexylthiophene-2,5-diyl) (P3HT) was utilized as the host donor polymer, iodine was utilized as the dopant acceptor molecule Finished devices were characterized by a semiconductor analyzer system with temperature controlled by two thermoelectric cooling plates. The doping of iodine in the range of 0.25% to 0.5% mole ratio with respect to the P3HT exhibited the greatest on-off ratio of the investigated dopant concentrations. Iodine doping concentrations of 0.5% mole ratio or less can greatly improve the thermoelectric properties of a binary P3HT-based system and the current-voltage performance of the dual-modulation device.

Bowlby’s (1969/1982) attachment theory has been employed as a broad and integrative framework to explore human wellness across a range of disciplines. Attachment theory has even been labelled one of the last surviving “grand theories” not to have been completely dismissed, replaced, or extensively reworked (e.g., Carr, 2012; Mercer, 2011). However, despite the ubiquitous nature of some of the theory’s fundamental tenets, there are always possibilities for new conceptual development, extension, and revision. In this paper, we critically explore the idea of “context-specific” attachment within parent-child relationships. We briefly outline critical assumptions and key areas of attachment and articulate potential rationale, conceptualisation, and relevance of contextual attachment.

Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks whose automation was analyzed consisted in estimating changes in the roughness of a mountain streambed and the extent of floods from images. The Segment Anything Model (SAM) developed this year by Meta was used for this purpose. Images from many years from the Wielka Puszcza mountain stream located in the Polish Carpathians were used as the only input data. The model was not additionally trained for the described tasks. The model can be run in several modes, but the two most appropriate were used in this study. The first one is available in the form of a web application, while the second one is available in the form of a Jupyter notebook run in the Google Colab environment. Both methods do not require specialized knowledge and can be used by virtually any hydrologist. In the roughness estimation task, the average Intersection over Union (IoU) ranges from 0.55 for grass to 0.82 for shrubs/trees. Ultimately, it was possible to estimate the roughness coefficient of the mountain streambed between 0.027 and 0.059 based solely on image data. In the task of estimation of the flood extent, when selecting appropriate images, one can expect IoU at the level of at least 0.94, which seems to be an excellent result considering that SAM is a general-purpose segmentation model. It can therefore be concluded that SAM model can be a useful tool for a hydrologist.

The separation and enrichment can be targeted to enrich the rare and precious metals in fly ash and reduce the cost of leaching and recovering of fly ash. Regarding their different properties, the single-component separation was used to obtain uncompleted burned carbon, glass microbeads, minerals, and other characteristic components from the ash. Also, the mineral composition of each component was analyzed by electron microscopy. The metal minerals were mainly concentrated in the mineral components. Besides, the electron probe micro-analysis shows that the Pt content in the minerals of fly ash was significantly correlated with the metal contents of Ni and Cu. After the obtainment of the characteristics of fly ash metal enrichment, the heavy minerals with Cu, Ni, Pt, Pd, and other target metal elements were enriched by gravity separation and flotation. The enrichment coefficients of Cu, Ni, Pt, and Pd were 1.45, 1.33, 1.90 and 1.60, respectively, and the recovery rates were 77%, 81%, 97% and 88% respectively. Since the yield of heavy minerals obtained by separation was 62.24%, it indicated the physical separation method could significantly reduce the cost of leaching and recovering of fly ash metal resources.

This study aims to tackle the challenge of high noise levels on balconies while preserving natural ventilation. Eight innovative balcony designs, incorporating elements like diffuser edges, undulating ceilings, Helmholtz resonators, grooves, or sound traps, were evaluated via finite element (FE) modeling. The extensive FE studies involved about 10 million elements per analysis case. Results showed that a standard balcony with a front parapet wall could achieve a noise reduction of around 10 dBA, with the jagged ledge design providing an additional 2 dBA improvement. Adding protruded ledge designs led to higher insertion loss (IL) by up to 9.4 dBA, especially at higher stories. Having wall-embedded Helmholtz resonators improved IL by up to 1.5 dBA. The jagged ledge design consistently exhibited positive IL across a broad frequency range from 200 Hz to 2 kHz. Combining beneficial balcony ceilings and wall ledges significantly reduced noise across lower and higher frequency ranges. Front jagged and full wavy ceilings offered positive IL throughout different storeys, proving their effectiveness against human vocal range. This study found that jagged ledge and front jagged ceiling designs, effective across various balcony heights, are viable options for improving balcony noise mitigation, providing valuable insights for architects and designers seeking practical solutions for outdoor noise reduction.

Adherence to the Mediterranean diet has been shown to lower the risk of developing chronic non-communicable diseases like cardiovascular and neurodegenerative diseases and cancer. Improvements in depression, participation in daily activities in older individuals, weight loss and reduction in adverse pregnancy outcomes are associated with adherence to the Mediterranean diet. The number of studies that have evaluated barriers to the adherence of the Mediterranean diet in the US and in particular, in racial and ethnic minority populations within the US are few. Among Native American and Alaskan Native populations, studies evaluating traditional or alternative Mediterranean diet adherence for chronic non-infectious diseases is unavailable. Mediterranean diet scoring instruments used in studies in European and Mediterranean countries and among white participants in the US fail to capture the dietary patterns of racial and ethnic minority populations. In this narrative review the food components of the traditional Mediterranean diet are discussed, adherence to the Mediterranean diet is examined in Mediterranean and non-Mediterranean countries and barriers preventing adherence to the Mediterranean diet in the US and among racial and ethnic minority populations is reviewed. Recommendations for improving nutrition education and intervention, and increasing adherence and cultural adaptions to the Mediterranean diet are provided.

The colpodellids consist of free-living predatory protists phylogenetically related to pathogenic Apicomplexan parasites such as Plasmodium species, Cryptosporidium sp. and Toxoplasma gondii. Among the colpodellids, Colpodella species prey on bodonids, algae, and ciliates. Voromonas pontica preys on Percolomonas species. In the past decade, Colpodella species have been reported to cause opportunistic infections in humans and animals, and having the potential for zoonotic infections in humans due to the presence of Colpodella species in ticks. In the reported cases, transmission and pathogenic stages of Col-podella were not identified by light microscopy. In the colpodellid V. pontica, cyst stages of both the pred-ator and its prey Percolomonas cosmopolitus have not been identified by light microscopy. In this study we evaluated the dye components used for Sam-Yellowe’s trichrome staining, from different major vendors to determine the consistency and reproducibility of the staining protocol to aid the use of the staining proto-col for diagnosis. We show that although slight variations in the color of the stained cells are obtained, life cycle stages of Colpodella ATCC 50594 could be clearly identified, regardless of the vendor used. For the first time, Sam-Yellowe’s trichrome staining series, could identify cysts of V. pontica and its prey, demonstrating that the staining protocol can identify life cycle stages of other colpodellids. Sam-Yellowe's trichrome staining will aid molecular diagnosis of infections caused by colpodellids in human and ani-mals, identify colpodellids in ticks and flies and from environmental samples, when used for staining.

We set up this preliminary study to evaluate one main question: could strengthening the microbiome have potential benefits for patients suffering with adverse effects after stopping long term topical steroid use? We aim to turn it into a much larger study if the results show promise. After commonly being prescribed for eczema, cessation of topical steroid use, especially after long periods of inappropriate use, can leave lasting adverse effects on the body and skin, known by some as topical steroid withdrawal (TSW). Furthermore, the subsequent withdrawal the body experiences when coming off the drug can leave lasting adverse effects on the body and skin, known by some as topical steroid withdrawal (TSW). This preliminary study involved seven human participants suffering with skin problems associated with TSW who approached Dr. Anja Gijsberts-Veens of their own volition because they were interested in more natural recovery methods. Five completed the study in full. Progress in skin condition was tracked by self-assessed symptom severity questionnaires filled out at the beginning and end of the study. The skin microbiome was addressed by using a 100% natural product shown in previous work to significantly increase skin microbiome biodiversity. Three participants implemented dietary changes and supplementation in response to guidance after fecal sample analysis to improve their gut health and biodiversity. The average improvement in skin symptoms for all participants was 40% and average symptom improvement ranged from 14% for Patient 5 to 92% for Patient 1. On average, the participants saw an improvement in 85% of their symptoms and a stagnation or regression in 11% and 4% respectively. We believe these results show enough promise to warrant expansion of this research to use a larger sample size, preferably 50+ participants, in future work. We also aim to swab the skin of participants to assess the effect on the skin microbiome from skin and gut treatments, as well as including more in-depth analysis of skin and gut microbiomes.

Cambodian spices Amomum kravanh, Citrus hystrix and Piper nigrum 'Kampot' have long history of seasoning of food products. In this study, essential oils (EOs) and supercritical CO2 extracts from all three species have been analyzed using GC-MS with two columns of different polarity, whereas EO and CO2 extract from P. nigrum fruits and CO2 extract from the peel of C. hystrix have been isolated and analyzed for the first time. The results showed that A. kravanh EO contained mostly eucalyptol (78.8/ 72.6 %), while CO2 extract was rich in oleic acid (29.26 %) and tricosane (14.74 %). C. hystrix EO was rich in β-pinene (29.95/29.45 %), followed by D-limonene (24.54/23.24 %) and sabinene (9.94/10.23 %). β-pinene (30.2/28.9 %), D-limonene (23.99/23.74 %) and sabinene (13.36/19.55 %) were also predominant in the CO2 extracts. β-Caryophyllene was the main constituent of both EO and CO2 extract from P. nigrum 'Kampot' with contents ranging from 37.84 to 55.84 %, followed by 3-carene (from 7.18 to 18.72 %). Such findings suggest that supercritical CO2 can potentially be used for extraction of all three Cambodian spices. Nevertheless, further research determining the most efficient extraction parameters will be needed before its application in the spice processing practice.

Overweight/obesity is a growing pandemic nowadays that affects many organs and tissues. We have investigated whether a high-lipid diet provokes an imbalance between type 1 and type 2 angiotensin II (Ang II) receptors signaling, leading to liver alterations associated with previously described cardiovascular and kidney disturbances. Chronic administration of a high-lipid diet can provoke an hepatocardiorenal syndrome as the result of activation of the Ang II→type 1 receptor axis, which is completely counteracted by Ang-(3–4) the allosteric enhancer of the Ang II→type 2 receptor pathway.

Overweight/obesity and cardiovascular diseases are associated with high rates of mobility and mortality. We investigated inflammatory lesions and ionic transporters in the left ventricle of male rats chronically fed a high-fat diet (HL). They developed moderate overweight with early expansion of visceral adiposity. The inflammatory markers interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-), Na+-transporting ATPases, sarco-endoplasmic reticulum Ca2+-ATPase (SERCA2a), and the abundance of Angiotensin II receptors were studied together with lipid and glycemic profiles, and the left ventricle echocardiographic parameters fractional shortening (FS) and ejection fraction (EF). HL rats doubled IL-6 and TNF-, which returned to normal levels when signaling coupled to Angiotensin II type 2 receptors (AT2R) was supraregulated by Ang-(3–4) administration. The decreased glucose tolerance was accompanied by significantly reduced plasma triglycerides due to intense hepatic steatosis (Crisóstomo et al. Metabolism Open. 2022, 14, 100176). AT2R (and AT1R) abundance did not change. (Na++K+)ATPase and ouabain-resistant Na+-ATPase were downregulated and upregulated, respectively, normalized with Ang-(3–4). SERCA2a lost its most critical regulatory property, inhibition by excess substrate. The ultrasound showed no changes in FS and EF. We conclude that very moderate overweight can cause silent initial molecular tissue damage in heart, which can evolve to cause systolic dysfunction.

Colpodella species are free-living opportunistic pathogens that cause human and animal infections and use ticks and flies as vectors. Trophozoite and cyst stages of Colpodella species can be distinguished from stages of the prey Parabodo caudatus using Sam-Yellowe’s trichrome staining. Colpodella species obtain nutrients by attaching to their prey, aspirating the prey’s cytoplasmic contents into a posterior food vacuole and encysting. It is unclear whether both trophozoite and cyst stages are present during infection. Molecular techniques identified Colpodella species in all reported infections. However, no morphological information was reported to aid life cycle stage identification in hosts. This review discusses the increased incidence of Colpodella infection in animals and in vectors and the need to identify stages used for transmission and pathogenesis. The potential for zoonotic infections through tick and fly bites is a public health concern. We previously used Sam-Yellowe’s trichrome staining to identify life cycle stages of Colpodella sp. In order to gain a better understanding of transmission and pathogenesis, identifying Colpodella life cycle stages in infected tissue and in vectors will provide important insights regarding nutrient uptake in hosts by determining whether attachment of trophozoites to host cells occurs, and identifying trophozoites and cysts in infected hosts.

Vibration monitoring is a critical aspect of assessing the health and performance of machinery and industrial processes. This study explores the application of machine learning techniques, specifically the Random Forest (RF) classification model, to predict and classify chatter—a detrimental self-excited vibration phenomenon—during machining operations. While sophisticated methods have been employed to address chatter, this research investigates the efficacy of a simplified RF model. The study leverages simulated vibration data, bypassing resource-intensive real-world data collection, to develop a versatile chatter detection model applicable across diverse machining configurations. The feature extraction process combines time-series features and Fast Fourier Transform (FFT) data features, streamlining the model while addressing challenges posed by feature selection. By focusing on the RF model’s simplicity and efficiency, this research advances chatter detection techniques, offering a practical tool with improved generalizability, computational efficiency, and ease of interpretation. The study demonstrates that innovation can reside in simplicity, opening avenues for wider applicability and accelerated progress in the machining industry.

The accurate classification of landfill waste diversion plays a critical role in efficient waste management practices. Traditional approaches, such as visual inspection, weighing and volume measurement, and manual sorting, have been widely used but suffer from subjectivity, scalability, and labour requirements. In contrast, machine learning approaches, particularly Convolutional Neural Networks (CNN), have emerged as powerful deep learning models for waste detection and classification. This paper analyses VGG-16, InceptionResNetV2, DenseNet121, Inception V3, and MobileNetV2 models to classify real-life waste when trained on pristine and unadulterated materials, versus samples collected at a landfill site. When training on DiversionNet, the unadulterated material dataset with labels required for landfill modelling, classification accuracy was limited to 49.69% in the real environment. Using real-world samples in the newly formed RealWaste dataset showed that practical applications for deep learning in waste classification is possible, with Inception V3 reaching 89.19% classification accuracy on the full spectrum of labels required for accurate modelling.

The environmental legacy of post-closure mine sites poses a significant risk to the sustainability of mining operations and natural resource development. This study aims to advance the understanding of sustainable mine site reclamation behavior in Canada by using multi-temporal Landsat satellite images to examine the long-term land cover changes at post-closure mine sites. Six representative post-closure mine sites were selected for the evaluation and comparison. The Normalized Difference Vegetation Index (NDVI) analysis, Landsat image classification, post-classification change detection, and Regrowth Index (RI) analysis were conducted to assess the speed and extent of landscape and vegetation recovery at the target mine sites. A significant vegetation recovery was quantified for the mine sites that have experienced active reclamation activities. In contrast, the post-closure mine area undergoing only the passive revegetation typically demonstrated a slow and minor increase in vegetation over time. The actively revegetated mine sites can typically be restored to a level that equals or better than the pre-mining situation. This work confirms that active reclamation and revegetation at post-closure mine sites is critically important in sustainable mining. The quantified mine site reclamation behavior and the relevant sustainable practices would be useful for evidence-based sustainable resource management in Canada.

The novel coronavirus (SARS-CoV-2) is a human pathogen recently emerged in China, causing a global pandemic of severe respiratory illness (COVID19). SARS-CoV-2 makes entry into human cells through its spike (S) protein that binds to cell surface receptors. Widespread of SARS-CoV-2 has been attributed to high affinity of S protein to its receptor. A homology model of the receptor binding domain of SARS-CoV-2 S protein (RBD) was built. RBD- receptor docking and published molecular dynamics data were used to map the key RBD-receptor interaction hotspot (RBDhp) on the RBD. Primary virtual screening was carried out against RBDhp using more than 3300 compounds approved by U.S Food and Drug Administration (FDA) and other authorities for human use. Compounds that bind to hpRBD with a binding energy ≤ - 6.5 kcal/mol were subjected to secondary screening using a recently published cryo EM (2.9 Å) structure of RBD. A cardiac glycoside (dgitoxin), two anthracyclines (zorubicin and aclarubicin), a tetracycline derivative (rolitetracycline), a cephalosporin (cefoperazone) and a food dye (E-155) were predicted to be most potent inhibitors of RBD – receptor interaction. An anti-asthmatic drug (zafirlukast) and several other drugs (itrazol, fazadinium, troglitazone, gliquidone, Idarubicin, Oxacillin) were found to be high affinity binders that may have a potential to inhibit RBD – receptor interaction.

This study aims to put forth a new method to study the socio-spatial boundaries by using georeferenced community-authored reviews for restaurants. In this study, we show that food choice, drink choice, and restaurant ambience can be good indicators of socio-economic status of the ambient population in different neighborhoods. To this end, we use Yelp user reviews to distinguish different neighborhoods in terms of their food purchases and identify resultant boundaries in 10 North American metropolitan areas. This data-set includes restaurant reviews as well as a limited number of user check-ins and rating in those cities. We use Natural Language Processing (NLP) techniques to select a set of potential features pertaining to food, drink and ambience from Yelp user comments for each geolocated restaurant. We then select those features which determine one’s choice of restaurant and the rating that he/she provides for that restaurant. After identifying these features, we identify neighborhoods where similar taste is practiced. We show that neighborhoods identified through our method show statistically significant differences based on demographic factors such as income, racial composition, and education. We suggest that this method helps urban planners to understand the social dynamics of contemporary cities in absence of information on service-oriented cultural characteristics of urban communities.

Prunus armeniaca L. is the native species of cultivated apricot, which is important information for studying the origin, succession pattern, pest control, sustainable development of biodiversity of economic tree species of the genus Apricot, etc. However, with global climate change and increasingly intense human activities, the survival environment of Prunus armeniaca L. is under serious stress, and exploring the potential survival space of Prunus armeniaca L. is an important way to protect the health and development of Prunus armeniaca L.. Exploring the potential living space of Prunus armeniaca L. is an important way to protect the healthy development of Prunus armeniaca L. The Yili River Valley is a typical distribution area of Prunus armeniaca L. . Exploring the potential distribution suitable area of Prunus armeniaca L. in the Yili River Valley and analyzing its future change trend can provide scientific guidance for the protection, development, and utilization of Prunus armeniaca L.. Based on the Geographic Information System software platform combined with the MaxEnt Model, we simulated the potential distribution areas and the degree of adaptation of Prunus armeniaca L. in the Yili River Valley, and predicted the potential distribution changes of Prunus armeniaca L. in the future under different situations. Based on the above methods, the following results were obtained: (1) The MaxEnt Model simulated the geographic distribution of Prunus armeniaca L. with high accuracy and an AUC value of 0.969, and the area of the currently suitable area for Prunus armeniaca L. in the Yili River Valley was about 10407.77 km2, accounting for about 18.45% of the overall land area of the Yili River Valley; the area of the highly suitable area was about 1380.9 km², accounting for about 13.26%, the area of the medium suitable zone is about 2830.15km², and the area of low suitable zone is about 6196.05km². (2) The maximum increase in the total area of the suitable zone under the future low-radiation forcing scenario is 11.49%, and the minimum increase under the future medium-high forcing scenario is 4.94%. (3) The overall migration was in the southwest direction, with the largest migration angle under the SSP245 scenario and the largest migration distance under the SSP585 scenario. Under the background of future climate change, there is a tendency for the potential habitat of Prunus armeniaca L. in the Yili River Valley to expand from low altitude to high altitude, and altitude is the dominant geographic factor influencing the distribution of Prunus armeniaca L.. By simulating and studying the potential geographic distribution of Prunus armeniaca L. in the Yili River Valley under the background of climate change, we can reveal the response mechanism between the geographic distribution of Prunus armeniaca L. and the natural environment, which can provide scientific guidance and data support for the exploitation and protection of Prunus armeniaca L. in the future.

The Sarcoma Assessment Measure (SAM) was developed as a sarcoma-specific patient-reported outcome measure to be used in clinical practice. We have reported in detail how SAM has been developed in collaboration with patients and healthcare professionals. The aim of this paper is to report the preliminary validation of SAM. The 22-item SAM was administered alongside a validated quality of life questionnaire and measure of activities of daily living. Linear modelling was used to build a measure, which had predictive validity in comparison to more established outcome measures. Of the 762 patients who participated in the study, 44.1% identified as male, and participant age ranged from 13-82 years. Clinically, participants presented with a range of soft tissue (82.2%) and bone (21.8%) sarcomas. Our preliminary analysis indicates that SAM accounts for 35% of the Global quality of life scale and 18% of the TESS so psychometrically it overlaps with quality of life and activities of daily living, but also measures distinct concerns. This demonstrates that this measure picks up issues that are important to patients with sarcoma that are not reflected in other measures. We have established the preliminary validity of SAM and believe it has utility as a patient-reported outcome measure both as a research tool and for assessing the impact of symptoms and dysfunction related to sarcoma as part of clinical care. Further validation using a larger and more clinically diverse sample is now needed.

In this work we explored how solvents can affect olefin oxidation reactions catalyzed by MCM-bpy-Mo catalysts and whether their control can be made with those players. The results of this study evidenced that polar and apolar aprotic solvents modulated the reactions in different ways. Experimental data showed that acetonitrile (aprotic polar) could hinder largely the reaction rate whereas toluene (aprotic apolar) did not. In both cases product selectivity at isoconversion was not affected. Further insights were obtained by means of neutron diffraction experiments, which confirmed the kinetic data allowing to propose a model based on substrate-solvent crosstalk by means of hydrogen bonding. In addition, the model was also validated in the ring-opening reaction (overoxidation) of styrene oxide towards benzaldehyde, which progressed when toluene was the solvent (reaching 31% styrene oxide conversion) but was strongly hindered when acetonitrile was used instead (reaching only 7% conversion), due to the establishment of H-bonds in the latter. Although this model was confirmed and validated for olefin oxidation reactions, it can be envisaged that it may also be applied to other catalytic reaction systems where reaction control is critical, while widening its use.

Both soybean variety and processing affect product characteristics. This study’s objective was to characterize the effect of four extraction methods (variations of soaking and grinding) combined with cooking on the content and composition of phenolic substances, antioxidant and anti-DU145 prostate cancer cell proliferative properties of soymilk prepared from a yellow soybean of the ProSoy variety, which is a high protein variety. Results showed soymilk processing yield was the greatest by Method 4, but Method 2 gave the highest solids and protein yields by about 14 and 12%, respectively. Method 4, a two-step grinding also increased yields (8 and 7%, for solids and protein, respectively), and in all but one instance produced higher total phenolic content (TPC), total flavonoid content (TFC), condensed tannin content (CTC) and total isoflavone content in both raw and cooked soymilk as compared to Method 1. Cooking soymilk reduced 14-17% of total phenolic substances. Cooking reduced anticancer capacity of Method-4-prepared soymilk phenolic extract by increasing IC50 value from about 4.9 mg/mL to 6.8 mg/mL. The increases in phenolic compounds and antioxidants produced in Prosoy soymilk by Methods 2 and 4 with simultaneous increases in product solids yield are significant to benefit the soymilk industry and consumer health. Keywords: ProSoy yellow soybean, soymilk processing, phenolics, isoflavones, antioxidant capacity, anti-DU145 prostate cancer proliferation

Air pollutants such as volatile organic compounds (VOCs), nitrogen oxides (NOx), sulfur dioxide (SO2), as well as water pollutants including heavy metal, are harmful to human and environment. Effective control and reduction of their pollution is therefore an important topic for today’s scientists. Fly ash (FA) is a type of industrial waste that can cause multiple environmental problems if discharged into the air. On the other hand, because of its high porosity, large specific surface area, and other unique characteristics, the FA can also be used as a low-cost and high efficient adsorbent with some simple modifications. This paper reviews the effects of FA on treatment of the above air and water pollution based on our research experience over many years, including to the current status of global FA utilization, physicochemical properties, principle of adsorption, and the application direction of FA in the future. It focuses on the use of nanocomposite technology to fabricate functional FA fibrous membranes to adsorb VOCs from air, and treat heavy metal wastewater. This present review first describes the fabrication technology of FA nanocomposites and their mechanism of adsorption VOCs from air. Utilization of nanofiber technology to fabricate multi-functional FA emerging composite materials to mitigate air and water pollution has great potential in the future, especially use of pollutant material to control other pollutants.

The concept and policies of multiple early cancer detection (MCED) have gained significant attention from governments worldwide in recent years. In the era of burgeoning artificial intelligence (AI) technology, the integration of MCED with AI has become a prevailing trend, giving rise to a plethora of MCED AI products. However, due to the heterogeneity of both the detection targets and the AI technologies, the overall diversity of MCED AI products remains considerable. The types of detection targets encompass protein biomarkers, cell-free DNA, or combinations of these biomarkers. In the development of AI models, different model training approaches are employed, including datasets of case-control researches or real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, and time-wise validation are used. All of the factors show significant impacts on the predictive efficacy of MCED AIs. After the completion of AI model development, deploying the MCED AIs in clinical practice presents numerous challenges, including presenting the predictive reports, identifying the potential locations and types of tumor, and addressing cancer-related information such as clinical follow-up and treatment. This study reviews several mature MCED AI products currently available in the market, detecting their composing factors from serum biomarkers detection, MCED AIs training/validation, and the clinical application. The review illuminates the challenges encountered by existing MCED AI products across these stages, offering insights into the continued development and obstacles within the field of MCED AI.

The present study examined music-induced dopamine release, as measured by a proxy measure of spontaneous eye blinks. Specifically, we explored the effects of uplifting and sombre tones in different sections of Vivaldi's Four Seasons to investigate the affective content of musical pieces within one composition. Seventeen participants listened to four concertos (Major modes: Spring, Autumn, Minor modes: Summer and Winter) and a silence condition while completing the 3-Stimulus Odd-ball attention task. Electrooculograms were recorded from electrodes placed above and under the left eye. Self-reported arousal and music preference measures were also gathered during the testing session. In addition, the P3a Event-Related Potential (ERP) component was analysed as another potential index of dopamine function. Results revealed significant differences in the blink rates during music listening and silence, with the largest effect observed for the sad, melancholic Winter concerto. However, no significant correlation was found between blink rate and music preference or arousal. Furthermore, no reliable association was found between blink rate and the P3a ERP component, suggesting that these measures tap into different aspects of dopamine function. These findings contribute to understanding the link between dopamine and blink rate, particularly in response to classical music. Crucially, the study's discovery that the Winter concerto, with its sorrowful tone, significantly increased the blink rate highlights the significance of sad music and perhaps the programmatic qualities of this concerto to induce a strong emotional response.

The tri-trophic interactions between plants, insects, and insect predators and parasitoids are often mediated by chemical cues. The attraction to Herbivore-Infested Plant Volatiles (HIPVs) has been well documented for arthropod predators and parasitoids, and more recently for insectivorous birds. The attraction to plant volatiles induced by the exogenous application of methyl jasmonate (MeJA), a phytohormone typically produced in response to an attack of chewing herbivores, have provided controversial results, both in arthropod and avian predators. In this study, we aimed to examine whether potential differences in the composition of bouquets of volatiles produced by Herbivore-infested and MeJA-treated Pyrenean oak trees (Quercus pyrenaica) were related to differential avian attraction, as results from a previous study suggested. Results showed that the overall emission of volatiles produced by MeJA-treated and Herbivore-infested trees did not differ, and were higher than emissions of Control trees, although MeJA treatment showed more significant reaction and released several specific compounds in contrast to Herbivore-induced trees. These slight differences in the volatile composition may explain why avian predators were not so attracted to MeJA-treated trees as observed in a previous study in this plant-herbivore system. Unfortunately, the lack of avian visits to the experimental trees in the current study does not allow us to confirm this result and points out the need to perform more robust predator studies.

In eukaryotes, the Dph1•Dph2 dimer is a non-canonical radical SAM enzyme. Using iron-sulfur (FeS) clusters, it cleaves the cosubstrate S-adenosyl-methionine (SAM) to form a 3-amino-3-carboxy-propyl (ACP) radical for synthesis of diphthamide. The latter decorates a histidine residue on elongation factor 2 (EF2) conserved from archaea to yeast and humans and is important for accurate mRNA translation and protein synthesis. Guided by evidence from archaeal orthologues, we searched for a putative SAM binding pocket in Dph1•Dph2 from Saccharomyces cerevisiae. We predict a SAM binding pocket near the FeS cluster domain that is conserved across eukaryotes in Dph1 but not Dph2. Site-directed DPH1 mutagenesis and functional characterization by assays diagnostic for loss of diphthamide reveal the SAM pocket is essential for synthesis of the décor on EF2 in vivo. Further evidence from structural modeling suggests particularly critical residues close to the methionine moiety of SAM. Presumably, they facilitate a geometry specific for SAM cleavage and ACP radical formation that distinguishes Dph1•Dph2 from classical radical SAM enzymes, which generate canonical 5′-deoxyadenosyl (dAdo) radicals.

Secure development is a proactive approach to cyber security. Rather than building a technological solution and then securing it in retrospect, secure development strives to embed good security practices throughout the development process and thereby reduces risk. Unfortunately, evidence suggests secure development is complex, costly, and limited in practice. This article therefore introduces security-focused prototyping as a natural precursor to secure development that embeds security at the beginning of the development process, can be used to discover domain specific security requirements, and can help organisations navigate the complexity of secure development such that the resources and commitment it requires are better understood. Two case studies–one considering the creation of a bespoke web platform and the other considering the application layer of an Internet of Things system–verify the potential of the approach and its ability to discover domain specific security requirements in particular. Future work could build on this work by conducting case studies to further verify the potential of security-focused prototyping and even investigate its capacity to be used as a tool capable of reducing a broader, socio-technical, kind of risk.

One of the drawbacks of natural fibers and their composites is their inherent hydrophilic nature. The effect of moisture on mechanical properties of a composite is irrefutable. This study deals with hygroscopic characteristics of Enset-PLA composites and its effect on the mechanical properties of the composite. To do this, injection molded composite specimens of different fiber volume fraction; plasticizer ratio, fiber length, and fiber age have been considered. The specimens are exposed to distilled water and the moisture absorption was monitored on a daily base. Subsequently, the specimens are subjected to mechanical loading to determine the effect of moisture on their Strength, Stiffness and strain at break strength. Lastly, individual and joint effects of considered factors have been scrutinized using optimal design of experiment. The result from the study shows that maximum and minimum moisture uptake is noticed for 25% and 10% fiber ratio respectively. Due to moisture effect, tensile and bending strength is decreased by 11% and 5% respectively for 15% fiber volume fraction; while 16% and 13% for 25% fiber volume fraction respectively. Increasing amount of plasticizer increases moisture resistance. The result indicate that Enset-PLA composite have competitive properties and stability when exposed to moisture.

People from Black and Asian backgrounds are more likely to die from Covid-19 but less likely to be vaccinated, threatening to exacerbate health inequalities already experienced by ethnic minority groups. Literature suggests that mistrust rooted in structural inequality may be a key barrier to Covid-19 vaccine uptake. We need to better understand how structural inequalities influence vaccine confidence. Understanding and addressing these processes is likely to lead to longer-term impacts than information alone. We draw on health and sociological theories of structure and agency to inform our understanding of structural factors. We conducted qualitative interviews and focus groups with 22 people from London and surrounding areas in December 2021 to March 2022. Fifteen participants were members of the public from ethnic minority backgrounds and 7 were professionals working with the public to address concerns and encourage vaccine uptake. Our findings suggest that people from ethnic minority backgrounds make decisions regarding Covid-19 vaccination based on a combination of how they experience external social structures (including political authority, social positioning and racial inequality) and internal processes (what they believe and understand about Covid-19 vaccines). We may be able to support knowledge accumulation through the provision of reliable and accessible information, particularly through primary and community care. But we recommend a number of changes to research, policy and practice which address structural inequalities. These include working with communities to improve ethnicity data collection, increasing funding allocation to health conditions where ethnic minority communities experience poorer outcomes, greater transparency and public engagement in the vaccine development process, and culturally adapted research recruitment processes.

Light is an electromagnetic radiation that has visible and invisible wavelength spectrum. The visible light can only be detected by the eyes through the optic pathways. With the presence of scalp, cranium and meninges, the brain is seen as being protected from direct exposure to light. For that reason, the brain can be viewed as a black body lying inside a black box. In physics, a black body tends to be in thermal equilibrium with its environment and can tightly regulate its temperature via thermodynamics principles. Therefore, a healthy brain inside a black box should not get exposed to light. On the contrary, photobiomodulation, a form of light therapy to the brain has been shown to have beneficial effects for some neurological conditions. The proposed underlying mechanisms are multiple. Herein we present our intraoperative findings of rapid electrocorticographic brainwave changes when the brain was shone directly with different wavelengths of light during awake brain surgery. Our findings provide literature proof on light’s ability to influence human brain energy and function. Our proposed mechanism for these rapid changes is the presence of plasma-like energy inside the brain which causes fast brain activities that are akin to lightning strikes.

This paper investigates the roll parameter estimation of periodic disturbances where the amplitude, frequency, offset, and phase are hardly recognized in real practice. The key problem is to make an estimation that could eliminate the unknown disturbance parameters. An adaptive mechanism applies these four parameters to the globally exponential convergence using linear second-order filters and parameter estimation errors. Then, a backstepping controller is employed to make an exponential convergence to zero of the state variables. Moreover, reservoir computing is used to forecast chaotic roll motions to support predictability using Lyapunov exponents and the Poincaré map. Numerical simulations are demonstrated to validate the dynamical behaviors and efficacy of the proposed control scheme with machine learning.

Administering intraluminal fluid can improve the acoustic window for visualization of lumen and wall layers in the cavitary organs. Microbubbles in ultrasound contrast agents can also be used for intracavitary applications to enhance visualization of the lesion in human patients. However, there was no literature extending the clinical application of the intraluminal contrast-enhanced ultrasonography (CEUS) to patients with naturally occurring diseases in veterinary medicine. This case series aims to describe the detailed application and diagnostic value of intraluminal CEUS in six clinical cases with naturally occurring gastrointestinal (GI) and urinary tract diseases.

Despite the allergen labeling of peanuts, reducing peanut allergenicity through material selection and breeding may provide an avenue to reduce the severity of allergy due to consumption of foods containing peanuts. This study’s objective is to select peanut lines (cultivar/variety) with lower potent allergenic peptides. One hundred and twenty-two peanut lines (harvested in 2015, New Mexico State, USA.), including 97 lines from the Core USDA- Griffin collections were used for SDS-PAGE analysis in order to find low allergen peanut lines. Eleven peanut lines (Coded MS-1~MS-11) were identified as having lower allergen (Ara h 1, Ara h 2 and Ara h 3) levels and were re-planted in 2016 for further analysis. One line named MS-7 was selected for lower Ara h 1 (8.5-9.5% of total protein) and Ara h 2 (4.2-6.6% of total protein) content in 2015 and 2016. Two-dimensional (2-D) gel electrophoresis (isoelectric focusing plus SDS-PAGE) was conducted to compare the protein (allergens) distributions of MS-7 and check line (MS-9). The 2-D results supported the SDS-PAGE analysis that MS-7 had lower quantities of Ara h 1 and Ara h 2, the two major peanut allergens. The identified peanut line (MS-7) has potential for processing into lower allergenic peanut food products.

Photovoltaic materials convert light into electrical voltages. So far, most research in the field are focused on how to refine/improve the existing or standard photovoltaic cells to yield more efficient electricity, to reduce weight, to make more flexible shape, or to minimize costs under standard and uniform sunlight illuminations. In this project, we explore and demonstrate a hypothesis that non-uniform light illumination photovoltages can also be generated due to photo doping induced mobile charge carrier density gradient between light and dark areas in either p-type or n-type photo doping semiconductors. The term non-uniform light illumination was coined to refer to subjecting our photo sensing thin film devices to areas of high and low intensities of light illumination simultaneously, with an intention of creating a charge density gradient and therefore a voltage. Specifically, a polymeric composite thin film composed of P3HT (p-type photo doping semiconductor) and PCBM (photo doping electron acceptor and trap) at varying p-doping levels were studied. We observed that the fabricated photovoltaic cells with about 80% PCBM doped P3HT thin film devices exhibited 0.5-1.2 volts photovoltages under non-uniform light illuminations.

The wind observations for multiple levels (40–200 m) have been conducted for a long time (2016–2020) on Jeju Island of South Korea. This study aims at understanding the vertical and temporal characteristics of lower atmosphere. Jeju Island is a region located at mid-latitude and is affected by seasonal monsoon wind. The maximum wind speed appears in the lower layer during day time and is delayed in the upper layer during latter time in diurnal cycle. In summer season, the surface layer increases up to 160 m during day time via dominant solar radiation effect, which is higher than those for other seasons. However, the maximum wind speed in winter season appears irregularly among altitudes, and the surface layer is ~100 m, which is lower than that in summer season. It can be attributed to the increase in the mean wind speed in diurnal cycle caused by the strong northwestern wind for winter season. These results imply that the relationship between near-surface and higher altitudes is primarily affected by solar radiation and seasonal monsoon winds. These results are expected to contribute to site selection criteria for wind farms and to the assessment concerning planetary boundary layer modeling.

Rice is considered as the most important crop for most of the world population. Utilization of seaweed as bio-stimulant can be an alternative way to enhance rice plant growth and productivity, as well as a strategic move to reduce the use of inorganic fertilizer that is harmful to the environment. Seaweed and its derivative products have been widely used as bio-stimulant in the agricultural industry because of their potential use in increasing plant growth and productivity. Auxins, gibberellins, and cytokinin are some of growth regulators found in seaweed extract, as well as macro and micronutrients required for plant growth and development. Several studies have found that seaweed extract has a variety of favorable effects as a plant growth promoter, including early seed germination and establishment, improved nutritional quality, increased yield and crop performance, and increased tolerance to environmental stress. The purpose of this paper is to give a comprehensive overview of the impacts of several seaweed species on seed germination, crop development and production, enhancement of rice plants (Oryza sativa) nutritional quality and the modes of action of seaweed extract includes the chemical components that might be causing plant physiological changes.

Bisphenols are widely used in the synthesis of polycarbonate plastics, epoxy resins and thermal paper, which are used in manufacturing items of daily use. Packaged foods and drinks are the main sources of exposure to bisphenols. These chemicals affect humans and animals by disrupting the estrogen, androgen, progesterone, thyroid, and aryl hydrocarbon receptor functions. Bisphenols exert numerous harmful effects because of their interaction with receptors, ROS formation, lipid peroxidation, mitochondrial dysfunction, and cell signal alterations. Both cohort and case-control studies have determined an association between bisphenol exposure and increased risk of cardiovascular diseases, neurological disorders, reproductive abnormalities, obesity, and diabetes. Prenatal exposure to bisphenol results in developmental disorders in animals. These chemicals also affect the immune cells and play a significant role in initiating the inflammatory response. Exposure to bisphenols exhibit age, gender, and dose-dependent effects. Even at low concentrations, bisphenols exert toxicity, and hence deserve a critical assessment for their uses. Since bisphenols have a global influence on human health, the need to discover the underlying pathways involved in all disease conditions is essential. Furthermore, it is important to promote the use of alternatives for bisphenols, thereby restricting their uses.

Dual specificity phosphatase 2 (DUSP2) regulates the activation of members in the mitogen-activated protein kinase (MAPK) family, which is involved in a variety of cellular processes like cell proliferation, differentiation, apoptosis and migration. DUSP2 also regulates the expression of inflammatory mediators in macrophages, however, it remains unknown whether DUSP2 participates in macrophage migration. Here, using the tail fin injury model in zebrafish larvae, we found that deletion of DUSP2 inhibited expression of pro-inflammatory cytokines and macrophage chemokines. Moreover, live imaging results showed that migration of macrophages to the injury site was inhibited after DUSP2 deletion. This inhibitory effect was mediated through reduced activation of extracellular regulated protein kinases (ERK) in DUSP2 knockout zebrafish.

Dye-based angiography is the main imaging modality in evaluating the vasculature of the eye. Although most commonly used to assess retinal vasculature, it can also delineate normal and abnormal blood vessels in the anterior segment diseases – but is limited due to its invasive, time-consuming methods. Thus, anterior segment optical coherence tomography angiography (AS-OCTA) is a useful non-invasive modality capable of producing high-resolution images to evaluate the cornea and ocular surface vasculature. AS-OCTA has demonstrated the potential to detect and delineate blood vessels in the anterior segment with quality images comparable to dye-based angiography. AS-OCTA has a diverse range of applications for the cornea and ocular surface, such as objective assessment of corneal neovascularization and response to various treatments; diagnosis and evaluation of ocular surface squamous neoplasia; and evaluation of ocular surface disease including limbal stem cell deficiency and ischemia. Our review aims to summarize the new developments and clinical applications of AS-OCTA for the cornea and ocular surface.

The textile processing sector is accountable for the extensive utilisation and pollution of freshwater resources. Due to heightened consumer awareness of environmental legislation regarding freshwater contamination, the textile sector is compelled to review and improve their current water consumption practices. Foan dyeing technique is a highly promising alternative that has the ability to contribute to a more sustainable future. This review paper discussed the current state of foam dyeing technology, highlighting its advantages in terms of re-duced consumption of water and energy, as well as minimal usage of dyes and chemicals compared to conventional methods. The foam configuration allows for more effective application of dyes. As a result, there is a decrease in dye consumption and a reduction in processing time. The process is environmen-tally sustainable since it significantly reduces water pollution. Furthermore, foam dyeing method consumes less energy due to its lower dying temperature need compared to conventional processing technology. Additionally, this paper highlights the continued investigation of foam dyeing on many types of textile substrates (such as fibres, yarns, and fabric) and compositions including cotton, polyester, and their mixtures. In addition, the techno-economic comparison of foam dyeing and conventional dyeing is also given. This review paper addi-tionally endorses the Sustainable Development Goals (SDG 6, clean water and sanitation) by examining the preservation of usable water and the decrease in wastewater discharge through foam dyeing technology. Lastly, the potential advantages of foam dyeing in terms of significantly reducing water consump-tion and the generation of waste in the textile industry were also addressed.

Fires are complex multi-physics problems that span wide spatial scale ranges. Capturing this complexity in computationally affordable numerical simulations for process studies and “outer-loop” techniques (e.g., optimization and uncertainty quantification) is a fundamental challenge in reacting flow research. Further complications arise for propagating fires where a priori knowledge of the fire spread rate and direction is typically not available. In such cases, static mesh refinement at all possible fire locations is a computationally inefficient approach to bridging the wide range of spatial scales relevant to fire behavior. In the present study, we address this challenge by incorporating adaptive mesh refinement (AMR) in fireFoam, an OpenFOAM solver for simulations of complex fire phenomena involving pyrolyzing solid surfaces. The AMR functionality in the extended solver, called fireDyMFoam, is load balanced, models gas, solid, and liquid phases, and allows us to dynamically track regions of interest, thus avoiding inefficient over-resolution of areas far from a propagating flame. We demonstrate the AMR capability and computational efficiency for fire spread on vertical panels, showing that the AMR solver reproduces results obtained using much larger statically refined meshes, but at a substantially reduced computational cost. We then leverage the computational efficiency of the AMR solver to demonstrate an optimization framework for fire suppression based on the open-source Dakota toolkit.

SAMHD1 is a deoxynucleotide triphosphate (dNTP) triphosphohydrolase with important roles in the control of cell proliferation and apoptosis, either through the regulation of intracellular dNTPs levels or the modulation of the DNA damage response. However, SAMHD1 role in cancer evolution is still unknown. We performed the first in-depth study of SAMHD1 role in advanced solid tumors, by analyzing samples of 128 patients treated with chemotherapy agents based on platinum derivatives and/or antimetabolites and developing novel in vitro knock-out models to explore the mechanisms driving SAMHD1 function in cancer. Low or no expression of SAMHD1 was associated with a positive prognosis in breast, ovarian and non-small cell lung cancer (NSCLC) cancer patients. A predictive value was associated to low-SAMHD1 expression in NSCLC and ovarian patients treated with antimetabolites in combination with platinum derivatives. In vitro, SAMHD1 knock-out cells showed increased γ-H2AX and apoptosis suggesting that SAMHD1 depletion induces DNA damage leading to cell death. In vitro treatment with platinum-derived drugs significantly enhanced γ-H2AX and apoptotic markers expression in knock-out cells, indicating a synergic effect of SAMHD1 depletion and platinum-based treatment. SAMHD1 expression represents a new strong prognostic and predictive biomarker in solid tumors and thus, modulation of SAMHD1 function may constitute a promising target for the improvement of cancer therapy.

Antibiotic resistant Pseudomonas aeruginosa infections are the primary cause of mortality in people with cystic fibrosis (CF). Yet it has only recently become appreciated that resistance mutations can also increase P. aeruginosa virulence, even in the absence of antibiotics. Moreover, the mechanisms by which resistance mutations increase virulence are poorly understood. In this study we tested the hypothesis that mutations affecting efflux pumps can directly increase P. aeruginosa virulence. Using genetics, physiological assays, and model infections, we show that efflux pump mutations can increase virulence. Mutations of the mexEF efflux pump system increased swarming, rhamnolipid production, and lethality in a mouse infection model, while mutations in mexR that increased expression of the mexAB-oprM efflux system increased virulence during an acute murine lung infection without affecting swarming or rhamnolipid gene expression. Finally, we show that an efflux pump inhibitor, which represents a proposed novel treatment approach for P. aeruginosa, increased rhamnolipid gene expression in a dose-dependent manner. This finding is important because rhamnolipids are key virulence factors involved in dissemination through epithelial barriers and cause neutrophil necrosis. Together, these data show how current and proposed future anti-Pseudomonal treatments may unintentionally make infections worse by increasing virulence. Therefore, treatments that target efflux should be pursued with caution.

The utilization of person centered care is highlighted as essential for health promotion, yet implementation has been inconsistent and multiple issues remain. There is a dearth of applied re-search exploring the facets of successful implementation. In this paper, a person centered wellbeing program spanning various groups is discussed outlining the central principles that have allowed for successful outcomes. The main data emerges from 10 years of pragmatic pre-post service evaluation. Measures of functional capacity and wellbeing were captured using validated measures. The method for this paper is a narrative exploration of the theory and practices that can explain the continual improvement the clinics have achieved over 10 years. Core principles relate to connecting with people, connecting through groups, and connecting with self. The operationalization and theoretical explanation of these principles is outlined alongside 10 years of data which shows sustained improvement in a range of outcomes. The discussion of these principles posits essential factors to prioritize to advance the implementation of person centered care in health promotion for long term conditions.

Fatigue-related subchondral bone injury of the third metacarpal/ metatarsal (McIII/ MtIII) bone is a common cause of wastage and welfare concern in racehorses. Better understanding of bone health and strength would improve animal welfare and be of benefit for the racing industry. Porosity index (PI) of bone is an indirect measure of osseous pore size and number and is therefore an interesting indicator of bone strength. MRI of compact bone using traditional methods even with short echo times fails to generate enough signal to assess bone architecture as the water protons are tightly bound. Ultrashort echo time (UTE) sequences aim to increase the amount of signal detected in the equine McIII/MtIII condyle. Cadaver specimens were imaged using a novel dual-echo UTE MRI technique and PI was calculated and validated against quantitative CT-derived bone mineral density (BMD). BMD and PI are inversely correlated in the equine distal Mc/ MtIII with a mean r value of -0.29. The r value is significantly different between fore- and hindlimbs. Further work is needed to assess how correlation patterns behave in different areas of the bone and to evaluate PI in horses with and without clinically relevant stress injury.

SARS-CoV-2, influenza A/B virus (IAV/IBV) and respiratory syncytial virus (RSV) are among the common viruses causing acute respiratory infections. Clinical diagnosis to differentiate these viruses is challenging due to similar clinical presentations, thus laboratory-based real-time RT PCR is the gold standard for diagnosis. The study aimed to evaluate the diagnostic performance of STANDARD M10 Flu/RSV/SARS-CoV-2 (SD Biosensor Inc, Seoul, Korea). This retrospective study was conducted with archived respiratory samples positive and negative for SARS-CoV-2, IAV, IBV or RSV. The evaluation study involved a total of 322 respiratory samples comprising 215 positive samples (49 SARS-CoV-2, 48 IAV, 53 IBV, 65 RSV) and 107 negative samples. All samples were tested with both STANDARD M10 and either Xpert Xpress SARS-CoV-2 or Xpert Xpress Flu/RSV (Cepheid, USA). The sensitivity, specificity, positive predictive value and negative predictive value rates of STANDARD M10 were very similar to Xpert Xpress SARS-CoV-2 or Xpert Xpress Flu/RSV ranges for each virus (98-100%). The overall agreement was 99.4% with 99.1% agreement for positive samples and 100% agreement for negative samples. In conclusion, the STANDARD M10 point-of-care test is suitable for rapid simultaneous detection of SARS-CoV-2, IAV, IBV and RSV.

In the chronic phase of chikungunya virus (CHIKV) infection, excessive inflammation manifests as incapacitating joint pain and prolonged arthritis. Arthritis resulted from a large influx of infiltrating immune cells driven by pro-inflammatory cytokines and chemokines originating from the toll-like receptor (TLR)-mediated innate antiviral response. This study investigated fisetin's ability to modulate TLR-mediated antiviral responses against CHIKV in Huh7 cells. The CHIKV inhibitory potential of fisetin was assessed by plaque-forming unit assay, virus yield reduction assay, and bright-field microscopy (cytopathic effect, immunofluorescence). Fisetin’s modulatory potential on TLR-mediated antiviral response was evaluated by immunofluorescence assay (expression of TLR proteins), qRT-PCR (mRNA level of antiviral genes), human cytokine array, and immunoblotting of key transcription factors. The present study showed fisetin induced the expression of the antiviral genes at an early time-point by promoting the phosphorylation of IRF3 and IRF7. Fisetin reduced excessive inflammatory cytokine responses in CHIKV-infected Huh7 cells by impeding the over-phosphorylation of NF-κB. Fisetin also reduced CHIKV-induced cytopathic effects in CHIKV-infected Huh7 cells. Altogether, our study suggests that fisetin modulates TLR-mediated antiviral responses by affecting the CHIKV-induced inflammatory responses.

Neural microprobes represent an important component of neural prosthetic systems where implanted microprobes record the electro-potentials generated by specific thoughts in the brain and convey the signals to algorithms trained to interpret these thoughts. Here, we present novel elongated multi-site neural probe that can reach depths greater than 10mm. We hypothesize that reaching such depth allows the recording of cognitive signals required to drive cognitive prosthetics. The impedance of the recording sites on the probes was on the order of 500 kΩ at 1 kHz, which is consistent with probes used for neurophysiological recordings. The probes were made porous using Xenon Difluoride (XeF₂) dry etching to improve the biocompatibility and their adherence to the surrounding neural tissue. Numerical studies were performed to determine the reliability of the porous probes. We implanted the elongated probe in rats and show that the elongated probes are capable of simultaneously recording both spikes and local field potentials (LFPs) from various recording sites.

The integration of deep learning models into financial risk prediction and analysis has significantly transformed traditional approaches. While conventional quantitative methods often rely on simplistic metrics like maximum drawdown, the advent of deep learning necessitates a more nuanced evaluation, emphasizing the model's generalization ability, especially during market crises such as stock market crashes. This paper explores the critical aspects of evaluating deep learning models' risk control capabilities in finance, underscoring the importance of understanding both statistical metrics and generalization abilities, particularly in adverse market conditions. By examining deep learning models' performance in scenarios like stock market crashes and highlighting the significance of cross-validation techniques, this study aims to offer practitioners insights into constructing robust risk management systems. It advocates for a comprehensive approach integrating quantitative analysis with macroeconomic factors to enhance financial risk prediction and analysis in volatile markets. The experimentation reveals that different deep generative models excel in various aspects of financial time series analysis, with generative adversarial networks (GANs) demonstrating superior performance in predicting Value at Risk (VaR) and variational autoencoders (VAEs) excelling in return rate prediction. Moreover, integrating multiple models further enhances predictive performance, leveraging the strengths of each model to compensate for individual weaknesses. Overall, this paper underscores the potential and significance of deep generative models in financial time series analysis, offering a roadmap for improved risk management and decision-making in financial markets.

The body of knowledge on ocean acidification gives a better understanding of biological sensitivity to low pH. Key parameters such as life-history strategies or local adaptation were identified as keys to predict species sensitivity and resolve previously some of the unexplained species- and population-specific differences. Encapsulation has been suggested as one of these keys as it exposed the embryo to low pH conditions, or ontogenetic hypercapnia, leading to physiological adaptation. We tested this hypothesis on the nudibranch Aeolidiella glauca by exposing their egg-strings containing large number of eggs to two different pH (8.1 and 7.3). The fertilized eggs developed 1 egg-cell, over early cleavage up to morula, blastula, gastrula, rhomboid-shaped rotating gastrula, early rotating veliger larvae with developed shell, to free-swimming well developed veliger larvae. Despite a corrosive environment, the exposure to low pH had no significant effect on the developmental rate. The only significant effects were a slightly smaller and narrower shell in larvae raised at low pH as compared to the high pH. Our results showed a remarkable resilient to low pH in a calcifying mollusc and support the idea that ontogenic hypercapnia is leading to low sensitivity to ocean acidification.

Understanding the optimal strategy for a real estate investment and how performance changes based on characteristics is crucial for optimising the achievable return. This is prominent in tourist areas such as Paphos where there is no clear distinction as to whether short or long-term approaches are optimal. The study aimed to develop a model for predicting the optimal rental strategy whilst assessing which model performed best and which property attributes impacted its return the greatest. Short-term data was collected from AirDNA and long-term data was manually collected from real estate agents websites. Furthermore, Random Forest, K-Nearest Neighbour and Multiple Linear Regression models were created to predict the highest and best use for each property. Model accuracy varied between data sets with the best performing model for short-term properties being Random Forest (R-Squared: 0.843), and Distance-Based Multiple Linear Regression for long-term approach (R-Squared: 0.843). The study demonstrated that accurate models could be created to predict the optimal rental strategy with the number of bedrooms being the main driver for rental income, followed by luxury finishes and the presence of a pool. It found that locational characteristics didn’t impact the returns significantly assuming that the property was located within a tourist area.

Cloud computing has become a widespread technology due to ICT advancements. It allows businesses to move and take advantage of the pay-as-you-go price model. Enterprises pay for what they use and don't have to buy, setup, or maintain resources. However, outsourcing core resources such as storage, servers, operating systems, and software applications from a third party needs careful decisions to take advantage of cloud facilities. Choice of appropriate service provider, deployment and service model must be aligned with business needs and goals. In this paper, we will present cloud computing benefits, cloud deployment methods, services, state-of-the-art migration methods, tools and techniques and will conclude with the role of SDN in cloud computing.

Backward electromagnetic waves are extraordinary waves with contra-directed phase velocity and energy flux. Unusual properties of the coherent nonlinear optical coupling of the phase-matched ordinary and backward electromagnetic waves with contra-directed energy fluxes are described which enable greatly-enhanced frequency and propagation direction conversion, parametrical amplification, as well as control of shape of the light pulses. Extraordinary transient processes that emerge in such metamaterials in pulsed regimes are described. The results of the numerical simulation of particular plasmonic metamaterials with hyperbolic dispersion are presented, which prove the possibility to match phases of such coupled guided ordinary and backward electromagnetic waves. Particular properties of the outlined processes in the proposed metamaterial are demonstrated through numerical simulations. Potential applications include ultra-miniature amplifiers, frequency changing reflectors, modulators, pulse shapers, and remotely actuated sensors.

The past few decades have brought tremendous insight into the molecular and pathophysiological mechanisms responsible for thrombus generation. For the clinician it is usually sufficient to explain the incident deep vein thrombosis (DVT) with provoking factors such as trauma with vascular injury, immobilization, hormonal factors, or inherited or acquired coagulation defects. About half of the DVTs are, however, lacking such triggers and are called unprovoked. Venous stasis and hypoxia at the valve sinus level may start a chain of reactions. In order to better understand the mechanisms behind DVT and reach beyond the above-mentioned simplifications animal models and clinical epidemiological studies have informed of the complex interplay between leukocytes, platelets, endothelium, cytokines, complements and coagulation factors and inhibitors. These pathways and the interplay will be reviewed here.

SLEUTH Model (slope, landuse, exclusion, urban extent, transportation and hillshade) is an important tool for landuse planning and land policy. To evaluate the performance of SLEUTH model, implementation of Sensitivity Analysis (SA) is essential. The main limitation of SA in SLEUTH application is a lack of insight into model input self-modification parameters (SMPs) variation, namely, uncertainty involved in the model transfer metrics and model presumptions, which often misled the decision makers and model users. To address this issue, this study divided the forward process into two stages. Firstly, during the transfer process ①, the contribution scores of five SMPs were drawn, and parameters highly sensitive to model output were given. Apart from that, the recommended initial value for SMPs of 0.11, 0.2, 0.87, 1.13, 15, 1.01, 0.49 were found to be subordinated to such a heterogeneous urban area simulation. Secondly, during the transfer process ②, SMP caused imagery metrics indicated the disparity between parameters with Fixed Reference and with Successive Reference. Reversely, it derives reasonable threshold for the best fit values of five prediction coefficients’ initialization by comparing the real image with the predicted one. The framework of SLEUTH model transfer mechanism not only could distinguish highly sensitive SMPs with higher contribution scores, but also could give parametric analysis for simulation imagery based on metrics. The study was found to be a practical tool for quantization response of model input variables for modelling complex urban systems. So, this insight can help geographic information scientists decide how to find out the inner forward transfer mechanism of SLEUTH model for further make good use of it and improve the model.

Incident rates of neurodegenerative diseases have steadily increased globally, but there is no therapeutic access available. We newly prescribed medicinal herbal remedy including five different herbal plants called, Chen-Ma-Dan-Sam-Ga-Mi-Bang (CMST), purposed to prove for pharmacological properties and corresponded actions on hippocampus neuronal cell injury by hypoxia-induced mice model. Mice were adapted to normoxia or hypoxia with or without CMST for 5 days. We gathered pharmacological effects of CMST on cell injury by enhancement of dihydroethidium and 4-hydroxynonenal signals which were correlated with abnormal redox status in the protein or gene expression levels (abnormal elevations of nitric oxide, reactive oxygen species, lipid peroxidation and deteriorations of total glutathione, total antioxidant capacity, and activities of superoxide dismutase and catalase) due to hypoxia. CMST also notably exerted to attenuates molecules for neuronal cell injury markers such as p-tau, cleaved caspase-3 due to DNA oxidations (53bp1and phosphor-histone H2AX), inflammatory cytokines, and hemeoxigenase-1. We further figured out the underlying actions of CMST by in vitro experiment through inactivation of microglial cell which can mediate neuronal cell injury. Collectively, CMST prevented from hippocampal neuronal cells via inactivation of microglial cell with normalization of redox status on hypoxia-induced hippocampus neuronal cell injury.

A digital twin is a virtual representation that serves as the real-time digital counterpart of a physical object or system. Recent advancements have extended the concept of digital twins to humans, incorporating complex biological data such as DNA (Predictiv Care, Inc.) and immune system profiles. These sophisticated models go beyond mere pictorial representations, offering a more holistic digital reflection. However, a significant gap remains. The current human digital twin models are not capable of learning one’s preferences. In this pilot study, we introduce Diginality, a chatbot powered by HyperCLOVA X, a Large Language Model (LLM) developed by NAVER, Inc. Diginality, learns one’s preferences with custom training from data collected by interview-style questions on the user’s topic of interest. Our findings demonstrate that Diginality successfully answers one’s preferences, thereby adding a new dimension to the concept of human digital twins. This work represents a pioneering step towards creating a more comprehensive and psychologically nuanced human digital twin.

With the rapid development of electronic and communication technology in military radar, the demand for microwave absorbing materials in low-frequency with thin layer is growing increasingly. In this study, flexible Co3O4/CC (carbon cloth) composites derives from Co-MOFs (metal-organic frameworks)/CC are prepared by hydrothermal and thermal treatment processes. The flexible precursors of Co-MOFs/CC are calcined with different calcination temperatures, which the material structure, dielectric properties and microwave absorption performance are changed. With the increase of calcination temperature, the minimum reflection loss of the corresponding Co3O4/CC composites gradually moves to the lower frequency with thinner thickness. In addition, the Co3O4/CC composites with 25 wt% filler loading ratio exhibit the minimum reflection loss (RL) of -46.59 dB at 6.24 GHz with 4.2 mm thickness. When the thickness is 3.70 mm, the effective absorption bandwidth is 3.04 GHz from 5.84 to 8.88 GHz. This study not only proves that the composite Co3O4/CC is a kind of outstanding microwave absorbing material with better flexibility, but also provides a useful inspiration for the low frequency and broadband microwave absorbing material.

The objective of this study was to evaluate the effect of in ovo injection of L-arginine (L-Arg) into Ross broiler eggs at different embryonic developmental stages on their survival, hatchability, and body weight (BW). Additionally, we have analyzed the levels of serum glutamic-oxaloacetic transaminase (SGOT) and serum glutamic-pyruvic transaminase (SGPT), protein expression of heat shock proteins (HSPs), also we have the determined micronuclei (MN) and nuclear abnormality (NA). Results showed that survival and hatching rates as well as body weight were increased on the 14th day incubation compared to 8th and 18th day incubation at lower concentration of L-Arg. Moreover, the levels of SGOT and SGPT were also significantly (P < 0.05) increased at 14th day incubation at the same concentration (100μg/μl/egg) of injection. In addition, IgM levels were increased on the 14th day incubation compared to other days. The protein expressions of HSP-47, HSP-60, and HSP-70 in the liver were significantly down-regulated whereas the expression of myogenin and MyoD were significantly up-regulated on the 14th day after incubation in treated with all different doses such as 100μg, 1000μg and 2500μg/μl/egg namely 3T1, 3T2 and 3T3 respectively. However, the treatment with low dose of L-Arg down-regulated expression levels of those proteins on the 14th day incubation. Histopathology of liver by hematoxylin and eosin (H&E) straining showed that the majority of liver damage, specifically intracytoplasmic vacuoles, were observed in 3T1, 3T2, and 3T3. The minimum dose of 100 μg/ml/egg on the 14th day of incubation significantly prevented intracytoplasmic vacuole damages. These results demonstrate that in ovo administration of L-Arg at (100μg/μl/egg) may be an effective method to increase chick BW, hatch rate, increasing muscle growth related proteins and promote the immune response through increasing IgM on the 14th day of incubation period.

Field cricket (Gryllus bimaculatus) is newly emerged as an edible insect in several countries. Anti-inflammatory effect of glycosaminoglycan derived this cricket was not fully investigated on chronic disease animal model such as diabetic mouse. For potential therapeutic agents, anti-diabetic activities of field cricket glycosaminoglycan (GbG) was evaluated in diabetic mice based on their abilities to reduce glucose, ALT, AST, LDL-cholesterol, and BUN levels, compared with dung beetle (Catharsius molossus) glycosaminoglycan (CaG) as a positive control glycosaminoglycan. Db mice were orally administered for one month according to their groups: Db Hetero (normal), Db Homo (type-2 diabetic), CaG (5 mg/kg), GbG (5 mg/kg), and metformin (10 mg/kg). Blood glucose level was decreased after 1^st week treatment with GbG. It also inhibited LDL-cholesterol and alkaline phosphatase levels. Regarding oxidative damage of diabetic state, levels of hepatocellular biomarkers levels and protein carbonyl content were reduced in db mice treated with GbG. Especially anti-oxidative activities of catalase, superoxide dismutase, and glutathione peroxidase were significantly increased in GbG treated group compared to those in the control. GbG was composed of heparin disaccharides and main N-glycan was identified as Hex₉GlcNAc₂ (m/z 1905.7) of with neutral mono-sugar mainly comprising of hexose, L (+) rhamnose by mass spectroscopy. These results from sero-biochemical, hepatocellular anti-oxidant assay in db mice data suggest cricket (G. bimaculatus) glycosaminoglycan might play a role in its anti-diabetic action.

Mandibular advancement devices (MAD) are an effective alternative treatment to CPAP. However, different maneuvers have been performed during the performance of drug sleep-induced endoscopy (DISE) to mimic the effect of MAD. Using the Selector Avance Mandibular (SAM) device, we aimed to identify MAD candidates during DISE using a titratable, reproducible, and measurable maneuver. This DISE-SAM protocol may help to find the relationship between the severity of the respiratory disorder and the degree of response, and to determine the advancement required to improve the collapsibility of the upper airway. Explorations were performed in 161 patients (132 males; 29 females) with a mean age of 46.81 (SD = 11.42) years, a BMI of 27.90 (SD = 4.19) kg/m2 and a mean AHI of 26.51 (SD = 21.23). Results showed no relationship between severity and MAD recommendation. Also, there was a weak positive relationship between the advancement required to obtain a response and the disease severity. Using the DISE-SAM protocol, the response and the range of mandibular protrusion were assessed, avoiding the inter-examiner bias of the jaw thrust maneuver. We suggest prescribing MAD as a single, alternative, or multiple treatment approaches following the SAM recommendations in a personalized design.

The unified Mittag-Leffler (ML) function is important factor in formulation of compact form of fractional integrals. In this paper estimations of integral operators, with the unified ML function as kernel are given. The Hadamard inequality in the form of fractional integrals is proved by considering refinement of convexities. These estimations provide various inequalities as refinements of recently published results.

Huntington disease (HD) is an autosomal dominantly inherited fatal neurodegenerative disease. It affects motor, cognitive and psychiatric functions, and ultimately leads to death. The pathology of the disease is due to an expansion of CAG repeats in exon 1 of the huntingtin gene on chromosome 4, which produces a mutant huntingtin protein (mhtt). HD patients manifest a typical phenotype of sporadic, rapid, involuntary control of limb movement, stiffness of limbs, impaired cognition and severe psychiatric disturbances. A variety of symptomatic treatments (which target excitotoxicity, the dopamine pathway, caspases, aggregation, mitochondrial dysfunction, transcriptional dysregulation, mHtt, nucleic acid, neurodegeneration, fetal neural transplants, etc.) are currently available, and new symptomatic and potentially disease-modifying therapies are being actively developed. Recent advances in novel therapeutic strategies, including targeting mutant huntingtin (mhtt) and the htt gene, promise another wave of disease-modifying trials in the near future. A better appreciation of heterogeneous clinical phenomenology and immediate tractable treatment goals coupled with advances in new therapeutics heralds a golden age of HD treatment that will positively impact the quality of life and longevity of HD patients and inform advances in other inherited and neurodegenerative neurological disorders. In the present review literature, our aims to address the latest research on promising therapeutics based on influencing the hypothesized pathological mechanisms associated with HD.

This paper describes a multi-channel in-situ monitoring system developed to better understand defect formation signatures in metal additive manufacturing. Three high-speed imaging modes coupled with an image computer capable of processing and storing these data streams allowed an examination of defect formations signatures and mechanisms. It was found that defects later detected in X-ray computed tomography (CT) scans were related to regions with anomalous heat signatures and powder bed morphology. Automated defect detection algorithms based on these defect signatures captured 80% of defects greater than 300 µm.

Intra-abdominal pressure (IAP) elevation during capnoperitoneum can cause adverse cardiovascular and respiratory effects. This study aimed to determine if a sequentially increased IAP affects cardiovascular and respiratory variables in anesthetized dogs and evaluate the effects of constant rate infusion of dexmedetomidine (Dex) on cardiovascular and respiratory variables with increased IAP. Five dogs were anesthetized, instrumented, and the Veress needle was equipped to adjust the IAP using a carbonic anhydrase insufflator. Stabilization was conducted for 1 h, and physiological variables were measured in IAPs of 0, 5, 10, 15, and 20 mmHg and after desufflation. After the washout period, the dogs underwent similar procedures along with constant rate infusion of dexmedetomidine. Cardiovascular effects of increased IAP up to 20 mmHg were not significant in healthy beagle dogs and those administered with dexmedetomidine. In the control group, the arterial pressure slightly increased, but not statistically significant, at an IAP of 20 mmHg compared with that at baseline (mean arterial blood pressure, p = 0.399; systolic arterial blood pressure, p = 0.293; diastolic arterial blood pressure, p = 0.141). When comparing the control and dexmedetomidine groups, overall significant effects of dexmedetomidine were noted on heart rate, cardiac output, and systemic vascular resistance during the experiment. Respiratory effects were not affected by abdominal insufflation when compared between different IAPs and between the two groups. Overall, an increased IAP of until 20 mmHg did not significantly affect cardiovascular and respiratory variables in both control and dexmedetomidine groups. This study suggests that dexmedetomidine infusion administration is applicable in laparoscopic procedures in healthy dogs.

With the digital transformation of the logistics industry, smart logistics algorithms have become a core technology to improve efficiency and reduce costs. This paper reviews the development history of traditional logistics technology and discusses the key role of technologies such as the Internet of Things, big data analysis, artificial intelligence, and automation in logistics technology innovation. It focuses on the application of intelligent logistics algorithms in path optimization, intelligent scheduling, data mining and prediction, and intelligent warehousing. To solve the problem of inconsistency between training and testing objectives, this paper proposes DRL4Route, a deep reinforcement learning-based path optimization framework, and designs the DRL4Route-GAE model. Validated through extensive offline experiments and online deployments, the model significantly outperforms existing optimal benchmark methods on real datasets, improving the location deviation squared metrics and the top-three location prediction accuracy metrics. These research results provide important support to further promote the intelligent development of the logistics industry.

To assess AR’s role in TNBC treatment, various existing and completed clinical trials targeting AR or co-targeting AR with other pertinent signaling molecules were analyzed. Cyclin-dependent kinase 4/6 (CDK4/6), cytochrome P450 17α-hydroxylase/17,20-lyase (CYP17 lyase), and the phosphatidylinositol 3kinase (PI3K)/protein kinase B (AKT) signaling pathway were some of the most prevalent biomarkers used in combination therapy with AR inhibitors in these trials. Studying how AR functions in tandem with these molecules can have increasing breakthroughs in the treatment options for TNBC. Previous studies have been largely unsuccessful in utilizing AR as the sole drug target for systemic targeted treatment in TNBC. However, there is a lack of other commonly used drug target biomarkers in the treatment of this disease, as well. Thus, analyzing the clinical benefit rate (CBR) within clinical trials that are using combination therapy can prove to be imperative to the progression of improving treatment options and prognoses.

The aim of this study was to analyze whether the respiratory variation in ECG standard lead II R-wave amplitude (ΔRDII) could be used to assess intravascular volume status following inferior vena cava (IVC) clamping. This clamping causes an acute decrease in cardiac output during liver transplantation (LT). We retrospectively compared ΔRDII and related variables before and after IVC clamping in 34 recipients. Receiver operating characteristic (ROC) curve and area under the curve (AUC) analyses were used to derive a cutoff value of ΔRDII for predicting pulse pressure variation (PPV). After IVC clamping, cardiac output significantly decreased while ΔRDII significantly increased (P = 0.002). The cutoff value of ΔRDII for predicting a PPV >13% was 16.9% (AUC: 0.685) with a sensitivity of 57.9% and specificity of 77.6% (95% confidence interval 0.561 – 0.793, P = 0.015). Frequency analysis of ECG also significantly increased in the respiratory frequency band (P = 0.016). Although significant changes in ΔRDII during vena cava clamping were found at norepinephrine doses < 0.1 μg/kg/min (P = 0.014), such changes were not significant at norepinephrine doses > 0.1 μg/kg/minP = 0.093). ΔRDII could be a noninvasive dynamic parameter in LT recipients presenting with hemodynamic fluctuation. Based on our data, we recommended cautious interpretation of ΔRDII may be requisite according to vasopressor administration status.

ELTD1 is expressed in endothelial and vascular smooth muscle cells and has a role in angiogenesis. It has been classified as an adhesion GPCR, but as yet, no ligand has been identified and its function remains unknown. To establish its role, ELTD1 was overexpressed in endothelial cells. Expression and consequently ligand independent activation of ELTD1 results in EndMT with a loss of cell-cell contact, formation of stress fibres and mature focal adhesions and an increased expression of smooth muscle actin. The effect was pro-angiogenic, increasing Matrigel network formation and endothelial sprouting. RNA-Seq analysis after the cells had undergone EndMT revealed large increases in chemokines and cytokines involved in regulating immune response. Gene set enrichment analysis of the data identified a number of pathways involved in myofibroblast biology suggesting that the endothelial cells had undergone a type II EMT. This type of EMT is involved in wound repair and is closely associated with inflammation implicating ELTD1 in these processes.

Cymbidium goeringii, locally known as the spring orchid in Korea, is one of the most important and popular horticultural species in the family Orchidaceae. C. goeringii cultivars were originated from plants with rare phenotypes in wild mountains where pine trees commonly grow. This study aimed to determine the cultivar-specific combined genotypes (CGs) of short sequence repeats (SSRs) by analyzing multiple samples per cultivar of C. goeringii. In this study, we collected more than 4,000 samples from 67 cultivars and determined the genotypes of 12 SSRs. Based on the most frequent combined genotypes (CG1s), the average observed allele number and combined matching probability were 11.8 per marker and 3.118×10-11, respectively. Frequencies of the CG1 in 50 cultivars (n ≥ 10) ranged from 40.9% to 100.0%, with an average of 70.1%. Assuming that individuals with the CG1 are genuine in the corresponding cultivars, approximately 30% of C. goeringii on the farms and markets may be not genuine. The dendrogram of the phylogenetic tree and principal coordinate analysis largely divided the cultivars into three groups according to their countries of origin; however, the genetic distances were not distant among the cultivars. In conclusion, this dataset of C. goeringii cultivar-specific SSR profiles could be used for ecogenetic studies and forensic authentication. This study suggests that genetic authentication should be introduced for the sale of expensive C. goeringii cultivars. We believe that this study will help establish a genetic method for the forensic authentication of C. goeringii cultivars.

Sediment cores were collected from a mudflow lobe (80 m water depth) offshore of the Mississippi River’s Southwest Pass in 2017 to better understand the sedimentology near the lobe entraining the SS Virginia shipwreck (sunk by a German U-Boat in 1942) and surrounding Mississippi River Delta Front. Core analyses included 210Pb/137Cs geochronology, granulometry, and X-radiography. Sediment accumulation rates (SAR) calculated from excess 210Pb activity in multicores are 0.22–0.29 cm/yr at seabed depths less than 20 cm and 0.29–0.51 cm/year at depths greater than 20 cm. 137Cs accumulation rates are ~0.15 to ~ 0.37 cm/year since 1954 and 1963 respectively. Sediment accumulation rates from 210Pb and 137Cs geochronology and indicators of relative sedimentation and bioturbation from X-radiographs suggest that rates of sediment accumulation near Virginia have declined since ca. the mid-20th century. This may be explained by the multi-decade downslope mass transport of the mudflow lobe in which the shipwreck is embedded, and decreases in sediment supply delivered offshore from the Mississippi River. Mass-transport calculations of the Virginia lobe derived from core properties and published lobe advection rates suggest downslope mass transport is far higher than sediment resupply from the Mississippi River, consistent with recent studies of delta retreat.

Hand, foot and mouth disease (HFMD) is a childhood disease caused by enterovirus A71 (EV-A71) and coxsackievirus A16 (CV-A16). We hypothesize that capsid loops are important epitopes for EV-A71 and CV-A16. Seven chimeric EV-A71 (ChiE71) involving VP1 BC, DE, EF, GH and HI loops, VP2 EF loop, and VP3 GH loop were substituted with corresponding CV-A16 loops. VP3 GH loop is the most conserved (91.3%) while VP1 BC loop has only 45.5% similarity. Only ChiE71-1-BC, ChiE71-1-EF, ChiE71-1-GH and ChiE71-3-GH were viable. EV-A71 and CV-A16 antiserum neutralized ChiE71-1-BC and ChiE71-1-EF. Mice immunized with inactivated ChiE71 elicited high IgG, IFN-γ, IL-2, IL-4 and IL-10. Neonatal mice receiving passive transfer of WT EV-A71, ChiE71-1-EF and ChiE71-1-BC immune sera had 100%, 80.0% and no survival, respectively, against lethal challenges with EV-A71, suggesting that the substituted CV-A16 loops disrupted EV-A71 immunogenicity. Passive transfer of CV-A16, ChiE71-1-EF and ChiE71-1-BC immune sera provided 40.0%, 20.0% and 42.9% survival, respectively, against CV-A16. One-day-old neonatal mice actively immunized with WT EV-A71, ChiE71-1-BC, ChiE71-1-EF and CV-A16 achieved 62.5%, 60.0%, 57.1% and no survival respectively, after the EV-A71 challenge. Active immunization using CV-A16 provided full protection while WT EV-A71, ChiE71-1-BC, ChiE71-1-EF immunization showed partial cross-protection in CV-A16 lethal challenge with survival rates of 50.0%, 20.0%, and 40%, respectively. Taken together, the EV-A71 VP1 BC loop is essential in immunogenicity of EV-A71 and substitution with CV-A16 VP1 BC loop was insufficient to confer protection against CV-A16. The EF loop maintains the cross-protective immune responses. Disruption of a capsid loop could affect virus immunogenicity, and future vaccine design should include conservation of the enterovirus capsid loops.

Amyotrophic Lateral Sclerosis (ALS) is a prototypical neurodegenerative disease characterized by progressive degeneration of motor neurons to severely effect the functionality to control voluntary muscle movement. Most of the non additive genetic aberrations responsible for ALS make its molecular classification very challenging along with limited sample size, curse of dimensionality, class imbalance and noise in the data. Deep learning methods have been successful in many other related areas but have low minority class accuracy and suffer from the lack of explainailbilty when used directly with RNA expression features for ALS molecular classification. In this paper we propose a deep learning based molecular ALS classification and interpretation framework. Our framework is based on training a convolution neural network (CNN) on images obtained from converting RNA expression values into pixels based on DeepInsight similarity technique. Then we employed Shapley Additive Explanations (SHAP) to extract pixels with higher relevance to ALS classifications. These pixels were mapped back to the genes which made them up. This enabled us to classify ALS samples with high accuracy for a minority class along with identifying genes that might be playing an important role in ALS molecular classifications. Taken together with RNA expression images classified with CNN, our preliminary analysis of the genes identified by SHAP interpretation demonstrate the value of utilising Machine Learning to perform molecular classification of ALS and uncover disease-associated genes.