In mesoscale eddies, chemical properties and biological composition are different from those in surrounding water, due to their unique physical processes. It is unclear how physical-biological coupling occurs in warm-core eddies, particularly since no study has examined the relationship between bacteria and viruses. The purpose of the present study was to examine the influence of anticyclonic warm eddy on the relationship between bacterial and viral abundances as well as viral activity (viral production) in different depths. In the core of warm eddy, bacterial abundance (0.48 to 2.82 ×105 cells mL−1) fluctuated less than that of the outside eddy (1.12 to 7.03×105 cells mL−1). In particular, there was four-folds higher of viral-bacterial abundance ratio (VBR) estimated within the eddy below DCM than the outside eddy. We suggest that prevailing physical forces with downwelling at the center of the anticyclonic warm eddy, viruses can also be transmitted into the deep ocean directly through adsorption on particulate organic matter during sinking. Overall, our findings provide valuable insights into the interaction between bacterial and viral communities and their ecological mechanism within the warm eddy.

Acoustic metasurface are artificial structures which could manipulate the wavefront in sub-wavelength dimensions and the previous proposed acoustic metasurface were mostly realized with single materials. An acoustic metasurface with composite structure is proposed for underwater acoustic stealth considering both wavefront manipulation and sound absorption. The unit cells of the metasurface are composed by metallic supporting lattice, interconnecting polymer materials and mass balancing columns. With the gradual modulations of equivalent physical properties along the horizontal direction of metasurface, the incident acoustic wave is reflected to other directions. Meanwhile, the polymer material inside the unit cells would dissipate the acoustic wave energy due to inherent damping properties. With the simultaneous modulations of reflected wave direction and scattering acoustic amplitude, significant improvement of underwater stealth effect is achieved. Compared with single-phase metasurface, the Far-Field Sound Pressure Level (FFSPL) of the multiphase metasurface decreased by 4.82 dB within the frequency range of 3kHz~30kHz. Under a hydrostatic pressure of 5MPa, the linearized mean stress for multiphase metasurface is only 1/3 of that of single-phase metasurface due to much thicker struts and much more uniform stress distribution. The proposed composite structure possesses potential applications due to acceptable thickness (80mm) and low equivalent density (1100 kg/m3).

Classifying network flow subsequences in an Industrial IoT gateway is an effective method for identifying Industrial IoT faults. This paper proposes a subsequence classification algorithm SSGBUL-IKNN based on unsupervised learning encoding to address the problem of low classification accuracy. Firstly, we built a network module based on unsupervised learning to encode the flow sequence of the Industrial IoT gateway. In the encoding module, a subsequence calibration algorithm controls the increasing error during the coding process. Then, the specific fault type is obtained through an improved KNN classification algorithm based on the indication distance source from the integrated coding sequences converted by multi-dimensional network flow sequences. The test result on three Industrial IoT datasets of a sewage treatment plant shows that the accuracy of SSGBUL-IKNN in this paper exceeds 92%, significantly higher than the algorithm DTW and TSF. It reaches the classification requirements of Industrial IoT fault diagnosis.

In coastal areas around the world, seagrass meadows play a crucial ecological and economic role. A large amount of seagrass beds dominates primary production and contributes to the high secondary productivity of this ecosystem. The microbial loop (consuming bacterial biomass by grazers and using seagrass-derived detritus by bacteria) may be an important mechanism for transferring seagrass-derived organic matter to the aquatic food chain. This study aims to improve our understanding of how bacterial growth and mortality (grazing and viral lysis rates) differ in seagrass and adjacent unvegetated meadow habitats. We found that viral lysis and grazing caused similar mortality rates of bacteria in a seagrass environment during the summer. It has been found, however, that bacterial production is controlled by the availability of resources (bottom-up control) and is cycled within the bacteria-virus-DOC loop in adjacent unvegetated waters. Our study region may be affected by this shift in organic matter fate and cycling.

There is no doubt that seagrass beds constitute one of the most productive ecosystems in shallow coastal waters. Despite this, picoplankton in seagrass ecosystems has received relatively little attention. The purpose of this study was to compare picoplankton growth and mortality rates between seagrass and unvegetated habitats using chamber incubations. We tested two main hypotheses: (i) incubation with seagrass would result in higher bacterial growth rates due to increased DOM release from seagrass photosynthesis, and (ii) Synechococcus spp. would be lower in the presence of seagrass due to competition for inorganic nutrients. Our results showed bacterial growth rates of 2.31 and 2.44 d–1 without and with seagrass, respectively. In seagrass chambers, bacterial growth was higher than that in non-seagrass chambers, suggesting that organic carbon coming from the seagrass community may support bacterial production. Furthermore, we observed a negative Synechococcus spp. growth rate (-0.9 d–1) in the seagrass treatment, likely reflecting nutrient competition with the seagrass. Small-scale chambers proved to be a useful tool for studying the factors controlling spatial and temporal patterns of picoplankton across different habitats. Furthermore, future studies should examine picoplankton growth over a wider range of spatial scales in seagrass beds and adjacent unvegetated sediment.

The quality of healthcare services is a very important indicator of social welfare in developed and emerging countries. Good quality levels are critical to ensuring patient safety, improving health outcomes, increasing patient satisfaction, optimizing resource utilization, and meeting regulatory requirements. The stable and sustainable operation of medical institutions urgently requires the establishment of a reliable and effective medical quality performance evaluation platform. However, the complexity of the evaluation process, involving numerous evaluators and the consideration of different subjective and objective criteria, poses significant challenges and essentially constitutes a group multi-criteria decision-making problem. This article uses the overall medical environment of the institution, medical service attitude, medical security, administrative service measures, etc. as measurement standards to deal with this challenge. It proposes a medical service quality measurement model suitable for both qualitative and quantitative analysis. In view of the heterogeneity of information, the two-tuple fuzzy language calculation method is introduced to enable evaluators to skillfully manage diverse information and effectively avoid potential information omission problems in the subjective evaluation integration process. The effectiveness and feasibility of the model were demonstrated by applying it to the operational framework of a medical institution in central Taiwan.

The NW-SE trending dextral strike-slip faults on the north side of the Tian Shan play an important role in accommodating the crustal shortening, which mainly includes the Karatau fault, Talas-Fergana fault, Dzhalair-Naiman fault, Aktas fault, Dzhungarian fault (also named Bolokenu-Aqikekuduk fault) and Chingiz fault. The classic viewpoint is that the strike-slip fault is the adjustment product caused by the difference of the crustal shortening from west to east. Another viewpoint attributes the dextral strike-slip fault to large-scale sinistral shearing. The Alakol Lake Fault is situated along the northern margin of the Dzhungarian Gate, stretching for roughly 150 km from Lake Ebinur to Lake Alakol. Our team utilized aerial photographs, Satellite Stereo-imagery, and field observation to map the distribution of the Alakol Lake fault. Our findings provided evidence supporting the assertion that the fault is a dextral strike-slip fault. In reference to its spatial distribution, Lake Alakol is situated in a pull-apart basin that lies between two major dextral strike-slip fault lines: the Chingiz and Dzhungarian faults. The Alakol Lake Fault serves as a connecting point for these two faults, resulting in the formation of a mega NW-SE dextral strike-slip fault zone. According to our analysis of the dating samples taken from the alluvial fan, as well as our measurement of the displacement of the riser and gully, it appears that the Alakol Lake fault has a dextral strike-slip rate of 0.8-1.5mm/yr. The strike-slip rate of the Alakol Lake fault is comparatively higher than that of the Chingiz fault in the northern region (~0.7 mm/yr), but slower than that of the Dzhungarian fault in the southern (3.2-5 mm/yr). The Chingiz-Alakol-Dzhungarian fault zone shows a gradual decrease in deformation towards the interior of the Kazakhstan platform. We contend that the rate of deformation observed is better explained by the crustal shortening adjustment model, rather than the large-scale sinistral shearing model.

In recent decades, with the ever-growing scale of video data, near-duplicate videos continue to emerge. Data quality issue caused by near-duplicate videos is becoming more and more prominent, which has affected the application of normal videos. Although current studies on near-duplicate video detection can be helpful to uncover data quality issues for videos, they still lack a process of automatic merging for the video data represented by high-dimensional features, which are difficult to automatically clean the near-duplicate videos to improve data quality for video datasets. At present, there are few studies on near-duplicate video data cleaning. The existing studies have the sensitive problems of video data orderliness and clustering initial center under a condition that prior distribution is unknown, which seriously affect the accuracy of near-duplicate video data cleaning. To address the above issues, an automatic near-duplicate video data cleaning method based on a consistent feature hash ring is proposed in this paper. First, a residual network with convolutional block attention modules, a long short-term memory deep network, and an attention model are integrated to construct an RCLA deep network with the multi-headed attention mechanism to extract spatiotemporal features of video data. Then, a consistent feature hash ring is constructed, which can effectively alleviate the sensitivity of video data orderliness while providing a condition of near-duplicate video merging. To reduce the sensitivity of the initial cluster centers to results of near-duplicate video cleansing, an optimized feature distance-means clustering algorithm is constructed by utilizing a mountain peak function on a consistent feature hash ring, which can implement automatic cleaning of near-duplicate video data. Finally, experiments are conducted based on a commonly used dataset named CC_WEB_VIDEO and a coal mining video dataset. Compared with some existing works, simulation results demonstrate that the performance of the proposed method.

In autonomous driving systems, high-speed and real-time image processing, along with object recognition, are crucial technologies. This paper builds upon the research achievements in in-dustrial item sorting systems and proposes an object recognition and sorting system for auton-omous driving. In industrial sorting lines, goods sorting robots often need to work at high speeds to efficiently sort large volumes of items. This poses a challenge to the robot's real-time vision and sorting capabilities, making it both practical and economically viable to implement a real-time and low-cost sorting system in a real-world industrial sorting line. Existing sorting systems have limitations such as high cost, high computing resource consumption, and high power consump-tion. These issues lead to the fact that existing sorting systems are typically used only in large industrial plants. In this paper, we design a high-speed, low-cost, low-resource-consumption FPGA (Field-Programmable Gate Array) based item sorting system that achieves similar perfor-mance to current mainstream sorting systems at a lower cost and consumption than existing sorting systems. The recognition part employs a morphological recognition method, which segments the image using a frame difference algorithm and then extracts the color and shape features of the items. To handle sorting, a six-degree-of-freedom robotic arm is introduced in the sorting segment. The improved cubic B-spline interpolation algorithm is employed to plan the motion trajectory and consequently control the robotic arm to execute the corresponding actions. Through a series of experiments, this system achieves an average recognition delay of 25.26ms, ensures smooth operation of the gripping motion trajectory, minimizes resource consumption, and reduces implementation costs.

The potential adverse effects of coronavirus disease 2019 (COVID-19) vaccinations raise public concerns. Data from Taiwan’s Vaccine Injury Compensation Program (VICP) can provide valuable insights. This study analyzed preliminary application data for COVID-19 vaccine compensation in Taiwan’s VICP, focusing on applicants receiving vaccines between March 2021 and June 2022. Among the 2941 adverse events, 113 cases (3.8%) were deemed causally associated with vaccination, 313 (10.6%) were indeterminate, and 2515 (85.5%) had no causal association. Nearly half (47.6%) of applicants were over 60 years old, and 76.6% had a history of preexisting chronic dis-eases. Among the 426 vaccine-associated or indeterminate cases, the most common causes were hematological diseases and thrombosis. There were 920 mortality cases reported, and 97.4% were unassociated with vaccination. Only five deaths were judged to be associated with the COVID-19 vaccination, all involving the adenovirus vector vaccine and thrombosis with thrombocytopenia syndrome. In conclusion, most compensation applications were not causally linked to vaccination. Compared to other countries, the number of applications in Taiwan’s VICP is relatively high. These findings may indicate a need to adjust the application requirements for compensation in Taiwan’s program.

A novel verifiable privacy preservation scheme for outsourcing medical image to cloud through ROI based crypto-watermarking is proposed in the paper. In the proposed scheme, data owner firstly carries out substitution of S-box for the region of interest (ROI) of medical image, and then separates the image into 4 most significant bits (MSBs) plane and 4 least significant bits (LSBs) plane images. Secondly, the hash value of ROI is embedded into the two separated bit plane images using reversible watermarking algorithm. Lastly, some selected hash values are transformed into the initial parameters of chaotic maps, and the two sharing secrets, which are produced through chaos based encryption algorithm, are finally outsourced to two different cloud servers. For authorized users, they can get shares from different cloud servers, and then can losslessly recover the original medical image through a series of decryption operations and extraction of watermarking. Furthermore, the users can verify whether the original image is completely reconstructed or not, they even can locate the tampered parts inside ROI if anyone of the sharing secrets is damaged. Some experiments analyses and comparisons are given to show the security and effectiveness of proposed scheme.

Amid escalating urbanization, devising rational commercial space layouts is a critical challenge. Leveraging machine learning, this study uses a Back-propagation (BP) neural network to optimize commercial spaces in Weinan City's central urban area. The results indicate an increased number of commercial facilities with a trend of multi-centered agglomeration and outward expansion. Based on these findings, we propose a strategic framework for rational commercial space development emphasizing aggregation centers, development axes, and spatial guidelines. This strategy provides valuable insights for urban planners in small and medium-sized cities in the Yellow River Basin and metropolitan areas, ultimately showcasing the power of machine learning in enhancing urban planning.

The physics of Hubble's law, motivated by the anomalous acceleration of Pioneer 10/11, suggests that the Hubble constant corresponds to a gravitational field of the Universe. The Hubble constant inferred from Pioneer 10/11 data is $\sim 69$ km/s/Mpc. The anomalous acceleration of Pioneer 10/11 can be interpreted as an observational evidence for Mach's principle. The redshift is an apparent value. Its intrinsic value has a limit resulting to $v

Promoting the sustainable development of resource-based cities is of great significance to the ecological protection and high-quality development of the Yellow River Basin. Combining the environmental status and economic development, we objectively evaluate the ecological safety level of resource-based cities in the Yellow River Basin, compare and analysis the main factors affecting the ecological safety of different resource-based cities, and formulate precise and differentiated ecological safety protection measures in river basins to achieve high-quality development. Taking the Yellow River Basin as an example, this paper analyses the ecological level of the Yellow River Basin based on the theory of sustainable development, calculates the ecological safety level of 30 resource-based cities in the Yellow River Basin from 2006 to 2020 by TOPSIS model, and makes convergence analysis by classification. Through the DID empirical test of sustainable development planning policy on ecological safety factors, distinguish the development characteristics of different resource-based cities. The results show that: (1) the ecological safety level of resource-based cities in the Yellow River Basin is generally developing well, and there are differences among different types of resource-based cities; (2) the kinetic energy of sustainable development of resource-based cities in the Yellow River Basin is mainly industrial transformation, and the power of science and technology is insufficient; (3) local governments pay limited attention to environmental protection, and the sustainable development planning of resource-based cities in 2013 mainly promotes the adjustment of industrial structure of resource-based cities.

This article illuminates the reception and transformation of Ippen一遍(1234-1289)’s religious tenets and practices by Enju Kato加藤円住 (1919-2021) and his temple Shōjōkō-ji清浄光寺. While Enju Kato asserts that his life has been dedicated to adhering and enacting Ippen's concept of "renunci-ation," he has reinterpreted this concept based on his personal experiences and comprehension. Second, Enju Kato and Shōjōkō-ji have inherited some of Ippen's religious practices yet adapted these to align with contemporary settings. This article presents a case study discussing the ac-ceptance and transformation of doctrines and practices of jishū時宗 in contemporary era, which has been overlooked by academia thus far.

Media thermal conductivity is important in various heat-transfer processes. Many conventional fluid conductors suffered low conductivity and environmental issues. Therefore, researchers developed efficient aqueous nanofluid conductors. Carbon nanotubes (CNTs) are widely studied to reach efficient, stable, low-cost and environmentally-friendly aqueous-nanofluids. This review provides a clear understanding of how CNTs improve thermal conductivity of aqueous nanofluids. A qualitative model is presented to explain literature mechanisms behind improvement. CNT type effects are discussed with other factors such as aspect ratio, Reynold number, dispersion quality, composition, temperature and additives. CNT functionalization is described. Relations to estimate nanofluid thermal conductivity are discussed. The model will help specialists to tailor CNT aqueous nanofluids as desired.

The diffusion coefficient--a measure of dissipation, and the entropy--a measure of fluctuation are found to be intimately correlated in many physical systems. Unlike the fluctuation dissipation theorem in linear response theory, the correlation is often strongly non-linear. To understand this complex dependence, we consider the classical Brownian diffusion in this work. Under certain rational assumption, i.e. in the bi-component fluid mixture, the mass of the Brownian particle $M$ is far greater than that of the bath molecule $m$, we can adopt the weakly couple limit. Only considering the first-order approximation of the mass ratio $m/M$, we obtain a linear motion equation in the reference frame of the observer as a Brownian particle. Based on this equivalent equation, we get the Hamiltonian at equilibrium. Finally, using canonical ensemble method, we define a new entropy that is similar to the Kolmogorov-Sinai entropy. Further, we present an analytic expression of the relationship between the diffusion coefficient $D$ and the entropy $S$ in the thermal equilibrium, that is to say, $D =\frac{\hbar}{eM} \exp{[S/(k_Bd)]}$, where $d$ is the dimension of the space, $k_B$ the Boltzmann constant, $\hbar $ the reduced Planck constant and $e$ the Euler number. This kind of scaling relation has been well-known and well-tested since the similar one for single component is firstly derived by Rosenfeld with the expansion of volume ratio.

Natural montane peatlands generally are not a significant source of nitrous oxide (N₂O) due to environment limitation including phosphorus (P) scarcity and temperature lowness. Phosphorus enrichment and warming caused by global change are altering this limitation, likely to increase the source function of N₂O. However, the combined effects of P addition and warming on N₂O fluxes and biotic/abiotic factor in peatlands are still uncertain. To address this, we investigated the long-term (12 yrs) effects of P addition (5 and 10 kg ha^-1 yr^-1) and its interaction with warming on N₂O fluxes in a peatland. The results showed that although long-term P addition did not significantly affect the source/sink function of N₂O in the peatland, it stimulated enzyme activities, promoted peat decomposition. However, warming amplified the effect of P addition to increase N₂O emissions by stimulating enzyme activities and changing soil stoichiometry, even turned the peatland into a significant source of N₂O with an emission of approximate 100 g m^-2 during the growing season. Our study suggests that P enrichment under the current background of global warming will enhance the possibility of strong N₂O emissions in montane peatlands, which may increase the risk to further aggravate global warming.

In this study, cement is used as the component that provides the stabilizing effect in order to evaluate the hardness and stability of loess soil. To assess the strength characteristics of loess soil reinforced with cement, samples were created with four different cement contents and three different curing times. The materials were put through a series of tests to determine their flexural strength, direct shear strength, indirect tensile strength, and unconfined compressive strength. An appropriate cement dosage was found, in addition to a durability index that could be used to quantify the effect of water absorption investigations on cement-stabilized loess. Both of these discoveries were made simultaneously. Analyses of investigations such as scanning electron microscopy (SEM) and energy dispersive X-ray fluorescence spectrometry (XRF) examinations were carried out so that the fundamental mechanics of the materials could be comprehended. According to the findings, the cohesion of cement-stabilized loess is significantly more sensitive to structure than the friction angle of the material, and the cohesion is responsible for the increase in shear strength after remolding. To get the desired level of strength, it is necessary to adjust the cement's proportions. In addition, as the curing period progresses, we see an increase in the cement-stabilized loess's resistance and stiffness. This is because of the interactions that take place between the structure and the mineral composition. It is believed that this event was caused by the cementation that occurs naturally. As a consequence of this reaction, the production of new cementitious materials takes place. The cation exchange that causes the hydration and pozzolanic reaction that leads to the creation of aggregates and interparticle flocculation is responsible for their production. These findings suggest that cement may be utilized as a simple and effective method of loess stabilization, which will ultimately result in improved performance of the loess.

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

Open source software such as OpenDSS has given a lot of help to distribution network researchers and educators. With high penetration of distributed renewable energy resources into distribution network, tradition distribution steady state analysis software such as OpenDSS is faced with difficulty in handling distributed generators. Three-phase distributed generators are often modeled in sequence frame while unbalanced distribution network are usually modeled in phase frame. So a load flow in sequence-phase coupled frame is proposed to handle models described in both frames. Voltage controlled DGs which are difficult to cope with in OpenDSS are handled in proposed program. The steady state analysis platform is programmed with open source Modelica language and the main aim of this paper is to introduce an open source platform for active distribution network steady analysis include load flow and short circuit analysis which can be easily adopted and improved by other educators and researchers.

The “Crisis of Reproducibility” has received considerable attention both within the scientific community and without. While factors associated with scientific culture and practical practice are most often invoked, I propose that the Crisis of Reproducibility is ultimately a failure of generalization with a fundamental scientific basis in the methods used for biomedical research. The Denominator Problem describes how limitations intrinsic to the two primary approaches of biomedical research, clinical studies and pre-clinical experimental biology, lead to an inability to effectively characterize the full extent of biological heterogeneity, which compromises the task of generalizing acquired knowledge. Drawing on the example of the unifying role of theory in the physical sciences, I propose that multi-scale mathematical and dynamic computational models, when mapped to the modular structure of biological systems, can serve a unifying role as formal representations of what is conserved and similar from one biological context to another. This ability to explicitly describe the generation of heterogeneity from similarity addresses the Denominator Problem and provides a scientific response to the Crisis of Reproducibility.

Eco-innovation denotes developing green practices using environmentally friendly innovative approaches or technologies. Although, eco-innovation has been broadly applied in different in-dustries, such as low-carbon production and manufacturing, how to implement such innovation in education for sustainable development (ESD) has rarely been studied. Therefore, this research considered a reflective and cooperative learning approach to science, technology, engineering, arts, and math (STEAM) education. A case study examined Wanluan Township of Pingtung County in southern Taiwan. Four departments’ students and teachers at Meiho University were involved in situated learning. Students of hospitality management played farm owners who en-gaged in organic agriculture to produce food and beverages. These agricultural products were farm-to-table, cooked and served for customers in a natural dining setting through the students’ teamwork. Students of tourism, sports & leisure management, and food science & nutrition played tourists in a self-guided travel context, who engaged in acts such as visiting buildings to understand heritage while observing that the houses were still in use a dwelling. This encouraged reflection on the importance of cultural preservation. According to the results from the role-play farm owners and tourists, eco-innovation can represent a sustainable marketing strategy for im-proving the local-community economy and can be implemented in a practical situation in STEAM. The goal of ESD for 2030 — societal transformation — is to foster students’ responsible behavior and attitudes in a personally authentic manner, thereby fostering sustainability learning and understanding.

This study explores the implementation of an interdisciplinary curriculum in product and media design education and its impact on knowledge innovation and competency development. The curriculum is based on scaffolding theory, incorporating design proposals, workshops, digital design, marketing tests, and marketing activities guided by teachers and mentors from a branded ceramic workshop. The research findings demonstrate that the interdisciplinary curriculum facilitates knowledge innovation and fosters the development of students' professional skills, creativity, and problem-solving skills. The study also highlights the importance of stable scaffolding, including artefact, peer, and teacher support, which significantly contributes to cultivating transformational competencies, as outlined in the 2030 OECD Learning Compass. Additionally, the collaboration with Shanshing Four Seasons Celadon Studio on a patented ceramic product, "Funny Monkey," is a tangible example of the journey towards a triple-helix knowledge economy. This research underscores the importance of interdisciplinary curricula in promoting knowledge innovation and integrating transformational competencies in education. Scaffolding theory provides practical guidance for student learning and teaching strategies, presenting a sustainable roadmap for developing interdisciplinary curricula and offering a concrete and transferable pedagogical prototype for educational innovation.

Inorganic polymeric materials react slowly at room temperature and as a result usually require high-temperature curing. This study used the Arrhenius equation to analyze the correlation between curing temperature and curing duration during high-temperature curing. The test results show that optimal values exist for each alkali equivalent of the activator (weight ratio of Na2O/glass powder), curing temperature, and curing duration. Extending the curing duration and increasing the curing temperature have positive effects when the alkali equivalent is lower than the optimal value. However, over-curing results in invisible cracking in the specimens. Furthermore, despite exhibiting high strength initially, the strength of specimens gradually diminishes after standing in air. To ensure the durability of glass-based geopolymer, the curing temperature should not exceed 70℃, and the curing duration should be less than one day.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.

3D printing is a non-traditional additive manufacturing process. It is different from the traditional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that traditional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, the structural strength and the parts assembly ca-pability. Therefore, this study compares the qualities of the warpage, weight, and surface rough-ness after milling and grinding processes under the same materials (316L stainless steel) between general rolled steel and 3D additive steel. Experimental results show that 3D printing parts are approximately 13% to 14% lighter than the general rolled steel. The surface roughness performance of 3D printing steel is better than general rolled steel under the same material after milling or grinding processing. The hardness of the 3D printing steel is better than that of the gen-eral rolled steel. The research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

Background Coronary artery disease (CAD) is a widely recognized cardiovascular disease that is considered the leading cause of death worldwide, affecting people on a global scale. Percutaneous coronary intervention (PCI), which involves procedures such as balloon angioplasty or stenting, plays an important role in opening blocked arteries and minimizing damage to the cardiac muscle. While the use of drug-eluting stents (DESs) has significantly reduced the occurrence of coronary restenosis, the problem of in-stent restenosis (ISR) continues to pose a significant clinical challenge. Gaining a deeper understanding of the clinical predictors associated with ISR is vital for early detection and appropriate treatment. Hence, this study aimed to evaluate the clinical predictors of ISR specifically in Taiwanese patients. Methods We conducted a single-center, retrospective case-control study, enrolling 517 CAD patients undergoing previous coronary stenting and stable angina with positive stress test or acute coronary syndrome (ACS) during follow-up between January 2019 and December 2022 at National Taiwan University Hospital. The patients were categorized into two groups: the ISR group, consisting of individuals who received drug-coated balloon (DCB) treatment (n=177), and the non-ISR group, comprising patients who did not receive DCB treatment (n=340). To gather relevant data, we meticulously reviewed the medical records and analyzed the findings from coronary angiography to assess the clinical characteristics of the patients. Results Patients with three-vessel disease (3VD) exhibited a higher prevalence of underlying diseases and were more likely to be taking aspirin and clopidogrel. Moreover, our analysis revealed that age (adjusted odds ratio [aOR] 1.02, 95% confidence interval [CI] 1.00 - 1.04, p = 0.037) and the presence of 3VD (adjusted odds ratio [aOR] 2.15, 95% confidence interval [CI] 1.03 - 4.46, p = 0.039) were significantly associated with an increased risk of coronary ISR. Conclusions Older age and 3VD were the independent predictors of coronary ISR in CAD patients receiving coronary stent implantation.

In recent years, the demand for coffee has increased tremendously. During the production process, green coffee beans are traditionally screened manually for defective beans before they are packed into coffee bean packages; however, this method is not only time-consuming but also increases the rate of human error due to fatigue. Therefore, this paper proposed a lightweight deep convolutional neural network (LDCNN) for the quality detection system of green coffee beans, which combined depthwise separable convolution (DSC), squeeze-and-excite block (SE block), skip block, and other frameworks. To avoid the influence of low parameters of the lightweight model caused by the model training process, rectified Adam (RA), lookahead (LA), and gradient centralization (GC) were included to improve efficiency; the model was also put into the embedded system. Finally, the local interpretable model-agnostic explanations (LIME) model was employed to explain the predictions of the model. The experimental results indicated that the accuracy rate of the model could reach up to 98.38% and the F1 score could be as high as 98.24% when detecting the quality of green coffee beans. Hence, it can obtain higher accuracy, lower computing time, and lower parameters. Moreover, the interpretable model verified that the lightweight model in this work is reliable, providing the basis for screening personnel to understand the judgment through its interpretability, thereby improving the classification and prediction of the model.

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

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

This study focuses on a sample of Chinese listed companies from 2019 to 2020 to explore the relationships among corporate social responsibility, financial constraints, and financial performance. In addition, we discuss five factors affecting financial constraints. We also analyze the types of enterprises that can improve their financial performance by implementing corporate social responsibility keeping in mind the factors that lead to a high degree of financial constraint. The results indicate that: 1. The degree of financial constraints has a negative and significant impact on financial performance; 2. There is a reverse relationship between the degree of financial constraints and the effectiveness of corporate social responsibility measures; 3. Enterprises with high financial constraints (due to lower financial slack and revenue growth rates) can significantly improve their financial performance through the implementation of effective corporate social responsibility programs. 4. Enterprises with high financial constraints, caused by financial slack and revenue growth rate, can significantly improve their financial performance by implementing corporate social responsibility programs.

When following a prescribed route, we need to decide at each intersection which way to proceed. The present work addressed several factors that might influence the difficulty of this decision making process. Participants repeatedly followed a route through a virtual maze with twelve or eighteen intersections, and with two or three choices per intersection. One group performed task S, which promoted decision making by the serial order strategy since all intersections looked alike. Another group performed task SA, which allowed the use of the serial order and the associative cue strategy since unique visual cues were presented at each intersection. We found that in both tasks, participants were more accurate in making decisions on routes with twelve rather than eighteen intersections, and more accurate by a similar amount on routes with two rather than three choices. Reaction time in task SA was reciprocal to accuracy; reaction time in task S was generally lower and route-independent. Accuracy in task SA was similar for participants who experienced smooth transport across intersections and those who experienced abrupt transport, while accuracy in task S was lower for participants who experienced smooth rather than abrupt transport across intersections. We conclude that the number of intersections and the number of choices were equivalent determinants of route following difficulty. We further conclude that optic flow during turns at intersections interfered with anticipatory decision making in task S; hence natural (smooth) transport across intersections did not enhance route following performance.

Preventing the occurrence of secondary caries serves as one of the significant issues in dental clinic, thus make it indispensable to improving the properties of conventional composite resin (CR) by developing a novel CR. In present study, two groups of experimental CRs loaded with different contents of fluoride-doped nano-zirconia fillers (25 wt% and 50 wt%) were fabricated. The surface topography, mechanical performance, fluoride release, antibacterial effect, aging property and cytotoxicity of the experimental CRs were evaluated subsequently. A uniform distribution of the F-zirconia fillers over the whole surface of resin matrix could be observed. The experimental CRs showed continuous fluoride release within 28 days, which was positively correlated with the content of F-zirconia fillers. Moreover, the amount of fluoride release increased in the acidic buffer. Addition of F-zirconia fillers could improve the color stability, wear resistance and microhardness of the experimental CRs, without reducing the flexure strength. Furtherly, the fluoride ions released continuously from the experimental CRs resulted in effective contact and antibacterial properties, while they showed no cytotoxicity. As a consequence, considerations can be made to employ this new kind of composite resin loaded with fluoride-doped nano-zirconia fillers to meet clinical requirements when the antimicrobial benefits are desired.

Objective: To compare the overall survival (OS) and surgical outcomes between open and minimally invasive surgery (MIS) in a large cohort of women with Type II endometrial cancer. Methods: Using the National Cancer Database, we identified a cohort of women who underwent hysterectomy for type II endometrial cancer (serous, clear cell, carcinosarcoma) between January 2010 and December 2014. Primary outcome was the comparison of OS between MIS and the open approach. Secondary outcomes included the length of hospital stay, readmission rate, 30- and 90-day mortality. Multivariable logistic regression and inverse propensity weighting analyses were performed. Results: A total of 12,905 patients with Type II, Stage I-III endometrial cancer who underwent hysterectomy were identified. Among these patients, 7,123 (55.2%) underwent MIS. The utilization of MIS increased from 39% to 64% over the four-year period. In propensity-score-weighted analysis, MIS was associated with superior OS (101.7 vs. 86.7 months, p=0.0003 by the log-rank test), with a hazard ratio of 0.9 (CI 0.857-0.954, p=0.0002). MIS was also associated with improved perioperative outcomes, including a shorter length of stay (1 vs. 4 days, p<0.001), lower 30-day readmission rate (2.5% vs. 5%), and lower 30- and 90-day postoperative mortality (0.5% vs. 1.3% and 1.5% vs. 3.6%, respectively; p<0.001). The time interval between surgery and initiation of chemotherapy was shorter in the MIS group (38 vs. 41 days, p<0.001).The increase in MIS adoption correlated with a decrease in 90-day postoperative mortality (2.8% to 2.2%, r=-0.89; p=0.003) and 12-month overall mortality (51% to 38%, r=-0.95, p=0.006). Conclusions: In an epidemiologic study, MIS is associated with improved overall survival and superior perioperative outcomes compared to open surgery in women with Type II endometrial cancer.

Macrophages exhibit impaired phagocytosis, adhesion, migration, and cytokine production in space, hindering their ability to elicit immune responses. Considering that the combined effect of spaceflight microgravity and radiation is multiscale and multifactorial in nature, it is expected that contradictory findings are common in the field. This theory paper reanalyzes research on the macrophage spaceflight response across multiple timescales from seconds to weeks, and spatial scales from the molecular, intracellular, extracellular, to the physiological. Key findings include time-dependence of both pro-inflammatory activation and integrin expression. Here, we introduce the time-dependent, intracellular localization of MRTF-A as a hypothetical confounder of macrophage activation. We discuss the mechanosensitive MRTF-A/SRF pathway dependence on the actin cytoskeleton/nucleoskeleton, microtubules, membrane mechanoreceptors, hypoxia, oxidative stress, and intracellular/extracellular crosstalk. By adopting a multiscale perspective, this paper provides the first mechanistic answer for a three-decade-old question regarding impaired cytokine secretion in microgravity—and strengthens the connection between the recent advances in mechanobiology, microgravity, and the spaceflight immune response. Finally, we hypothesize MRTF involvement and complications in treating spaceflight-induced cardiovascular, skeletal, and immune disease.

Improper disposal of waste plastic has caused serious ecological and environmental pollution problems. Transforming plastics into high value-added chemicals can not only achieve efficient recycling of waste plastics, but also an effective way to control white pollution. The catalyst selectively breaks the C-C bond of polyolefin plastic under heat treatment and converts it into liquid fuel, thus realizing sustainable recycling of plastics and has a good development prospect. This review provides a detailed overview of the current development of catalytic pyrolysis, catalytic hydrolysis, solvent decomposition and supercritical hydrothermal liquefaction for cracking plastics to make fuel oil. The reaction mechanism, influencing factors and promoting effects of catalysts in various degradation technologies are analyzed and summarized and the latest proposed tandem reaction for degrading plastics is briefly introduced. Finally, some optimization paths of waste plastic pyrolysis to fuel oil technology are proposed: synergies between mixed raw materials, in-depth exploration of catalysts, design and manufacture of reactors that match the pyrolysis technology. All these are important research directions for promoting the industrialization of plastic pyrolysis to fuel oil.

3D Zernike moments based on 3D Zernike polynomials have been successfully applied to the field of voxelized 3D shape retrieval and have attracted more attention in biomedical image processing. As the order of 3D Zernike moments increases, both computational efficiency and numerical accuracy decrease. Due to this phenomenon, a more efficient and stable method for computing high-order 3D Zernike moments was proposed in this study. The proposed recursive formula for computing 3D Zernike radial polynomials combines the recursive calculation of spherical harmonics to develop a voxel-based algorithm for the calculation of 3D Zernike moments. The algorithm was applied to the 3D shape Michelangelo's David with a size of 150×150×150 voxels. As compared to the method without additional acceleration, the proposed method uses a group action of order sixteen orthogonal group and saving unnecessary iterations, the factor of speed-up is 56.783±3.999 when the order of Zernike moments is between 10 and 450. The proposed method also obtained an accurate reconstructed shape with the error rate (normalized mean square error) of 0.00 (4.17×10^-3) when the reconstruction was computed for all moments up to order 450.

Atta capiguara is a grass-cutting ant species frequently found in Cerrado biome. However, little is known about the giant nest architecture of this ant. In this study, we investigated the architecture of three A. capiguara nests from the fragment of cerrado in Botucatu, São Paulo, Brazil. Casts were made of the nests by filling them with cement to permit better visualization of internal structures such as chambers and tunnels. After excavation, the depth and dimensions (length, width, and height) of the chambers were measured. The results showed the typical shape of Atta capiguara nests consisting of mounds of loose soil with unique features resembling a conic section. The fungus chambers were found outside the apparent main part of the nest and were spaced apart and distributed laterally at ground level. The waste chambers were located beneath the largest mound of loose soil. Both the fungus and waste chambers exhibited a sectoral distribution. Our study contributes to a better understanding of the so far unknown nest architecture of the grass-cutting ant A. capiguara.

Building information modeling (BIM) is the digital representation of physical and functional characteristics (such as geometry, spatial relationship, and geographic information) of a facility to support decisions during its life cycle. BIM has been extended beyond 3D geometrical representations in recent years, and now includes time as a fourth dimension and cost as a fifth dimension, as well as such other applications as virtual reality and augmented reality. The Internet of Things (IoT) has been increasingly applied in various products (smart homes, wearables) to enhance work productivity, living comfort, and entertainment. However, research addressing the integration of these two technologies (BIM and IoT) is still very limited, and has focused exclusively on the automatic transmission of sensor information to BIM models. This paper describes an attempt to represent and visualize sensor data in BIM with multiple perspectives in order to support complex decisions requiring interdisciplinary information. The study uses a university campus as an example and includes several scenarios, such as an auditorium with a dispersed audience and energy saving options for rooms with different functions (mechanical/electric equipment, classrooms, and laboratory). This paper also discusses the design of a common platform allowing communication among sensors with different protocols (Arduino, Raspberry Pi), the use of Dynamo to accept sensor data as input and automatically redraw visualized information in BIM, and how visualization may help in making energy-saving management decisions.

In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship radiated noise. After that, the characteristic parameters, namely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropy, are compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship radiated noise can be extracted efficiently with the method.

The key links of face recognition are digital image preprocessing, facial feature extraction and pattern recognition, this article aimed at the current problem of slow speed and low recognition accuracy of face recognition , from the above three key links, on the basic of analyzing the therories of Fractional Differential Masks Operator (FDMO), Principal Component Analysis (PCA) and Support Vector Machine (SVM), design a kind of FDMO+PVA+SVM coupling algorithm that applies to face recognition to improve the speed and accuracy of it. To realize FDMO+PCA+SVM coupling algorithm, first, we should apply FDMO to face image processing binary marginalization, the purpose is getting face contour; Then, we apply PCA to get the feature of face image which is disposed by binary marainalization. At last, we can apply One-Against All of the SVM classifier and LibSVM software package to realize face recognition. Beside, the article with nine different coupling algorithm design four groups of experimental reaults on the ORL face database verified by comparative analysic FDMO+PCA+SVM coupling algorithm in the superiority of face recognition accuracy and speed.

Amid the swift progression of the global automobile industry, the aspiration for lightweight vehicle design has surfaced as a crucial approach to boost fuel efficiency and curtail environmental impact. The objective of this study revolves around achieving holistic optimization of vehicle structure via detailed scrutiny of vehicle process characteristics, amalgamated with a Back Propagation neural network (BPNN) optimized by a genetic algorithm (GA) and a topology optimization (TO) method.The process initiates with an examination of the vehicle's technical characteristics, succeeded by an optimization protocol that couples GA with BPNN. This exhaustive optimization procedure derives the best-fit values of design parameters and identifies the globally optimal lightweight design approach. Subsequently, a comprehensive structural optimization is actualized by modifying the topological distribution of the structure.A simulation experiment of the conceptual car body beam skeleton is conducted as a conclusive step, and the anti-collision capacity of the car body beam skeleton is assessed by measuring deformation intrusion. The findings reveal that in the vehicle topology optimization, a comparative analysis of pre and post-optimization results indicates an improved topological density across diverse sections. The topological density of the vehicle's frontal structure escalates from 0.75 to 0.8. Following optimization, the stiffness assessment records a marginal increase (within the range of 0.02–0.05), implying that the lightweight design does not compromise the general rigidity of the structure.The optimized body structure manifests superior crashworthiness in the crash test: the deformation intrusion diminishes by 27% in front-end collisions. In side impacts, the deformation and intrusion at critical points are reduced by 13.15% to 10% respectively. The comprehensive method proposed herein proves to be an efficient strategy to actualize the lightweight design of vehicles.

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity is still elusive. Recently, genome-wide association studies (GWAS) have begun to unveil the genetic background of several psychiatric disorders, including MDD and insomnia. Identifying the shared genomic risk loci between comorbid psychiatric disorders could be a valuable strategy to understand their comorbidity. This study seeks to identify the shared genes and biological pathways between MDD and insomnia based on their shared genetic variants. First, we performed a meta-analysis based on the GWAS summary statistics of MDD and insomnia obtained from Psychiatric Genomics Consortium and UK Biobank, respectively. Next, we associated shared genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, a total of 719 shared genes were identified. Over half (51%) of them are protein-coding genes. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification, sensory perception, and immunologic signatures. We also identified druggable targets using a network approach. Together these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid MDD and insomnia symptoms.

As the natural resources are getting exhausted, the concept of sustainable development of region has received increasing attentions, especially for resource-dependent cities. In this paper an innovative method that emergy analysis and IPAT (Human Impact Population Affluence Technology) model were combined in order to analyze the quantitative relationship of economic growth and energy consumption and further to evaluate its overall sustainability level. Taiyuan, a traditional, resource-dependent city in China, is selected as the case study region. The main results show that total emergy of Taiyuan increased from 9.023× 1023 sej in 2007 to 9.116× 1023sej in 2014, with 38% reduction on non-renewable emergy and 125% growth on imported emergy. Regional emergy money ratio (RMB) was reduced by 48% from 5.31× 1013sej/$ in 2007 to 2.74× 1013sej/$ in 2014, indicating that the increasing speed of consuming resources and energy was faster than the increase of GDP, and that Taiyuan’s money purchasing power declined. The lower emergy sustainability index (ESI) indicates that Taiyuan was explored and produced large quantities of mineral resources, which puts more stress on the environment as a consequence, and that this is not sustainable in the long run. The IPAT analysis demonstrates that Taiyuan sticks to the efforts of energy conservation and environmental protection, in order to promote regional sustainable development, it is necessary to take an integrated effort. Policy insights suggest that resourceful regions should improve include energy and resource efficiency, optimizing energy and resourceful structure.

In foggy weather scenarios, the scattering and absorption of light by water droplets and particulate matter cause object features in images to become blurred or lost, presenting a significant challenge for target detection in autonomous driving vehicles. To tackle this problem, this study proposes a foggy weather detection method, YOLOv5s-Fog, based on the YOLOv5s framework. The model enhances the feature extraction and expression capabilities of YOLOv5s by introducing a novel target detection layer, SwinFocus. Additionally, this research incorporates decoupled head into the model and replaces the conventional non-maximum suppression method with Soft-NMS. Experimental results demonstrate that these improvements effectively enhance the detection performance for blurry objects and small targets in foggy weather conditions. Compared to the baseline model YOLOv5s, YOLOv5s-Fog achieves a 5.4% increase in mAP on the RTTS dataset, reaching 73.4%. This method provides technical support for rapid and accurate target detection in adverse weather conditions, such as foggy weather, for autonomous driving vehicles.

This paper introduces in general the conservation work of the Nara Palace Site in Japan carried out by Japanese conservation experts. Concerning conservation theory, this paper focused on the international conventions in which the 1994 Nara Document on Authenticity plays an important role in contributing to Japanese cultural heritage conservation achievements with the expansion of Cultural diversity and Heritage diversity, the Values and Authenticity conceptions which proposed a new orientation in terms of awareness and openness broader vision in identifying architectural heritage values. Regarding, based on the 1994 Nara Document on Authenticity, the 1964 Venice Charter, and the 1999 Bura Charter, we try to propose a new concept of the so-called “Architectural Heritage DNA” and its potential structure, providing a simple formula for the authentic values appraisal of the heritage conservation works. In addition, we also try to supplement the concept of Inheritance between Conservation and Development which is the lack of international conventions of cultural heritage conservation. The viewpoints expressed in this paper are based on the most common concepts of international conventions but interpreted in a new-understandable, practical, and highly applicable way possible to the current socio-political situation and in the future, as well.

As the most serious of the many worse new pathological changes caused by diabetes, there are many risk factors for the occurrence and development of DR. It mainly includes hyperglycemia, hypertension, hyperlipidemia and so on. Among them, hyperglycemia is the most critical cause, which plays a key role in the pathological changes of DR.High-sucrose diets(HSDs) lead to elevated blood glucose levels in vivo, which, through oxidative stress, inflammation, the production of AGEs and VEGF, causes plenty of pathological damages to the retina and ultimately bring about loss of vision. The existing therapies for DR primarily target the terminal stage of the disease, when irreversible visual impairment has appeared. Therefore, early prevention is particularly critical. Early prevention of DR-related vision loss requires adjustments to dietary habits, mainly by reducing sugar intake. This article primarily discusses the risk factors, pathophysiological processes, and molecular mechanisms associated with the development of DR caused by HSDs. It aims to raise awareness of the crucial role of diet in the occurrence and progression of DR, promote timely changes in dietary habits, prevent vision loss, and improve the quality of life. The aim is to make people aware of the importance of diet in the occurrence and progression of DR. According to the dietary modification strategies we give, patients can change their poor eating habits timely, avoid the retinopathy that can be avoided theoretically, and obtain a excellent outcome.

An adaptive operation strategy for on-demand control of DMFC system is proposed as an alternative method to enhance the voltage stability. Based on a single-cell DMFC stack, a newly simplified semi-empirical model is developed from the uniform-designed experimental results to describe the I-V relationship. Integrated with this model, the multi-objective optimization method is utilized to develop an adaptive operation strategy. Although the voltage instability is frequently encountered in unoptimized operations, the voltage deviation is successfully decreased to a required level by adaptive operations with operational adjustments. Moreover, the adaptive operations are also found to be able to extend the range of operating current density or to decrease the voltage deviation according to ones requirements. Numerical simulations are implemented to investigate the underlying mechanisms of the proposed adaptive operation strategy, and experimental adaptive operations are also performed on another DMFC system to validate the adaptive operation strategy. Preliminary experimental study shows a rapid response of DMFC system to the operational adjustment, which further validates the effectiveness and feasibility of the adaptive operation strategy in practical applications. The proposed strategy contributes to a guideline for the better control of output voltage from operating DMFC systems.

An easy to implement and cost-effective Fiber Bragg Grating (FBG) sensor interrogation technique based on a ring Erbium-Doped Fiber Laser (EDFL) topology is proposed and experimentally assessed. The FBG sensor is part of the EDFL cavity and must have a central wavelength located within the linear region of the EDF’s amplified spontaneous emission (ASE) spectrum which occurs between 1530 and 1540nm. In this manner, the wavelength-encoded response of the FBG under strain is converted to a linear variation of the laser output power, removing the need for spectrum analysis as well as any limitations from the use of external edge-filtering components. In addition, the laser linewidth is significantly reduced with respect to the FBG bandwidth thus improving the resolution of the system, whereas its sensitivity can be controlled through the pumping power. The performance of the system has been characterized by modeling and experiments for EDF's with different lengths, doping concentrations and pumping power levels. The influence of mode-hopping in the laser cavity on the resolution and accuracy of the system has also been investigated.

In this paper, a new axial-type magnetic gear with auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AFS-AMG, it has the higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of proposed AFS-AMG are elaborated. Then, the mapping relation between the radial-type magnetic gears (RMGs) and AMGs are elucidated. Compared to its counterpart in RMGs, AFS-AMGs achieve small size. Then, the geometrical parameters of AFS-AMGs are optimized to obtain the better electromagnetic performances, where the torque density per volume and per PM volume is adopted as the evaluation standard. Finally, three different AMG topologies are constructed in finite element analysis (FEA) software for comparison. It is proven that the AFS-AMG has the largest torque density per volume and per PM volume.

Although several protocols for genetic transformation of citrus have been published, it is highly desirable to further improve its efficiency. Here we report treatments of Agrobacterium cells and citrus explants prior to and during co-cultivation process to enhance transformation efficiency using a commercially used rootstock 'Carrizo' Citrange as a model plant. We pre-cultured Agrobacterium cells in a 1/10 MS, 0.5 g/L 2-(N-morpholino) ethanesulfonic acid (MES) and 100 µM acetosyringone liquid medium for 6 hours at 25 ℃ before used to infect citrus explants. We incubated epicotyl segments in an MS liquid medium containing 13.2 µM 6-BA, 4.5 µM 2,4-D, 0.5 µM NAA for 3 hours at 25℃ prior to Agrobacterium infection. In the co-cultivation medium, we added 30 µM paclobutrazol and 10 µM lipoic acid. Each of these three treatments significantly increased the efficiencies of transformation. When the three treatments were combined, we observed that the transformation efficiency was enhanced from 11.5% to 52.3%. The improvement of genetic transformation efficiency mediated by these three simple treatments may facilitate more efficient applications of transgenic and gene editing technologies for functional characterization of citrus genes and for genetic improvement of cultivated citrus varieties.

The last decade has witnessed rapid development of immersive virtual reality (IVR) and its application in various contexts. However, its application in supporting real-time virtual collaboration has been quite rare due to technical barriers and the lack of validated design principles. To address this research gap, this study designed and developed an IVR space to enable multi-user synchronous co-located collaboration. An evaluation study (N = 95) was conducted to explore its useful design considerations and the influencing factors for collaboration experience. The IVR space was enabled by the simultaneous localization and mapping (SLAM)-based inside-out tracking technique and was informed by four essential design considerations for promoting effective collaboration in IVR, namely, the role script, learning task, collaboration mechanism, and communication design. The study results revealed that students in general were satisfied with their collaboration experience in IVR, with social presence and collaboration competency as significant predictors of collective efficacy and social experience. Based on both quantitative and qualitative results, this study proposes four validated principles for designing effective IVR spaces to support synchronous co-located collaboration.

Landiolol is an ultra-short-acting, selective ß1- adrenergic receptor blocker that was originally approved by Japan for the treatment of intraoperative tachyarrhythmias. It has gained attention for its use in the management of tachyarrhythmias and perioperative tachycardia, especially atrial fibrillation for both cardiac and non-cardiac surgeries. It can be the ideal agent for heart rate control due to its high β1‐selectivity, the potent negative chronotropic effect, a limited negative inotropic potential, and an ultrashort elimination half‐life (around 4 min); moreover, it may have a potential therapeutic effect for sepsis and pediatric patients. Landiolol seems to be superior to other short‐acting and selective beta‐blockers such as esmolol. This review aims to provide a comprehensive overview of landiolol, a new ultra-short-acting ß1 selective antagonist, including its pharmacology, clinical applications, efficacy, safety profile, and future directions in research and clinical data.

Objective: To use the ancient and modern medical record cloud platform (V2.3.5) to organize and explore the medication patterns of the "Three Causes, Extremity, and One Disease Syndrome Formula" by Chen Wuxuan, and to summarize its therapeutic ideas. Method: Collect and organize the "San Yin Si Tian Fang" in the "San Yin Ji Yi Zheng Fang Lun", and use the modern medical record cloud platform (V2.3.5) to conduct medication frequency statistical analysis, cluster analysis, and complex network analysis. As a result, a total of 16 Chinese herbal medicines were collected in the "Three Causes, Extreme and One Disease Syndrome Formula", involving 75 traditional Chinese medicines. Statistical analysis showed that roasted licorice was the most commonly used, followed by Pinellia ternata, papaya, ginger, and Poria cocos; Medications mainly include warm drugs, sweet and pungent flavors, as well as drugs that promote lung and spleen meridians. Cluster analysis can divide the above-mentioned traditional Chinese medicine into two groups, with specific grouping as follows. Group 1: ginger, white peony, aconite, papaya, and achyranthes bidentata; Group 2: roasted licorice, poria cocos, dried ginger, pinellia ternata, and green peel. Conclusion: The characteristics of the 16 prescriptions are biased towards Xin Gan Wen, emphasizing the regulation of the spleen and stomach, which may be related to the common use of prescription by doctors in the Song Dynasty and the tendency towards warm and dry medication.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

The purpose of this study is to analyze how global research cooperation patterns in the secondary battery industry have changed over recent years and to identify the evolution in the focus of research. To this end, network analysis was performed using the nationality information of the authors of a 10-year multinational joint research paper related to lithium-ion batteries. Furthermore, keyword analysis and topic modeling were performed using the abstract data from the study. The results of this study confirm that some countries that are not well-known in the field, such as Australia, Spain, and France, showed high centrality, compared with the level of cooperation scale. Additionally, six research topics were identified. According to a comparison over the first half of the decade, no difference was observed in the appearance of keywords indicating high energy density and conductivity with lithium, a key mineral. Keyword distribution was high for topics like battery charging and discharging in the first half of the decade, and for next-generation battery materials, such as solid electrolytes, lithium metal anodes, and lithium-sulfur batteries in the second. These results provide insights into the establishment of R&D cooperation strategies by countries and pre-planning by companies in the battery industry.

Abstract: Molybdenum (Mo) thin films were sputtered from two kinds of Mo targets with different microstructures under the same sputtering process, and the effect of microstructure of Mo target on morphology, deposition rate and resistance of sputtered film were studied and discussed. The results show that morphological differences between Mo thin films sputtered by Mo targets with different microstructures are very small. The more uniform and finer the grain structures of Mo target, the better the uniformity on thickness and resistance of Mo sputtered film. Moreover, during sputtering process, when Mo target’s grain size is finer and the surface area of grain boundary is higher, the thickness reduction of the target is more homogeneous and the sputtering film has faster deposition velocity. The difference in microstructure of the Mo target has not obvious influence on the grain orientation of sputtering film.

The primary attraction of IaaS is providing elastic resources on demand. It becomes imperative that IaaS-users have an effective methodology for learning what resources they require, how many resources and for how long they need. However, the heterogeneity of resources, the diversity resource demands of different cloud applications and the variation of application-user behaviors pose IaaS-users big challenge. In this paper, we purpose a unified resource demand forecasting model suiting for different applications, various resources and diverse time-varying workload patterns. With the model, taking input from parameterized applications, resources and workload scenarios, the corresponding resources demands during any time interval can be deduced as output. The experiments configure concrete functions and parameters to help understanding the above model.

This paper investigates the evolution of microstructures and precipitations of an ultra-low iron alloy 625 subjected to long term aging treatment by scanning electron microscope (SEM) and X-ray diffraction(XRD). Use ASTM G28A acid Fe3(SO4)2 erosion to represent intergranular corrosion weightlessness and corrosive morphology. The result shows that alloy at 750C by aging treatment for 40h, precipitated γ'' phase in the grain boundary. In high density area of γ'' phase, occurs γ'' phase to δ phase degeneration transformation by aging treatment for 200h and the needle-like δ phase becomes more with time prolonged. And γ'' phase degenerated to δ phase completely until treated for 1000h. The sample which has aging treatment tends to have intergranular corrosion and mainly because alloy element spreading leads to dilution area and grain boundary precipitated phase, plus interlaced δ phase’s dissolving, which makes sample grain particle fall off and this results in apparent weightlessness. The weightlessness rate(WLR) is related with precipitated volume score. With aging sensitization time change, can be described by Johnson-Mehl-Avrami equation, i.e.: $WLR=44.32\left[1-\text{exp}\left(-\frac{t}{10.99}\right)\right]+44.62\left[1-\text{exp}\left(-\frac{t}{327.8}\right)\right]+1.267\left(mm/a\right)$

Agriculture is an industry that heavily relies on the environment. The increasing frequency of ex-treme disasters attributable to climate change has adversely affected agricultural land and dis-rupted the stability of the supply of agricultural products. Therefore, we implemented a research program focused on current strategies for adapting to agricultural meteorological disasters. The primary goal was to actively promote disaster prevention information and techniques through information platforms and applications and to provide refined forecasting and an early warning system to enhance preparedness for and recovery from agricultural disasters. This initiative can transform passive mitigation into dynamic action by disseminating crucial information to farmers. We integrated meteorological data and crop characteristics to develop disaster prevention strate-gies for the predisaster, during-disaster, and postdisaster stages to empower farmers to implement autonomous disaster prevention, ensuring their profitability and minimizing the impact of disas-ters. This paper presents an agricultural disaster prevention system involving cross-disciplinary collaboration to establish an early warning system for crop disasters. However, the effectiveness of the early warning system relies on the availability of complete meteorological and crop infor-mation, necessitating high-density agricultural meteorological stations, refined weather forecast services, historical crop damage data, and ongoing research and development on disaster preven-tion technology. In the system, a diversified social media interface is used to provide local farmers with weather forecast information. When impending disasters are identified, the platform acti-vates disaster prevention measures to reduce agricultural losses. This article paper introduces Taiwan’s agricultural disaster prevention system as a complete disaster prevention strategy.

Global warming may increase the potential evapotranspiration (Etp), thereby affecting the amount of clean water resources available in a region. In this study, the systematic biases in temperature outputs of 24 global climate models (GCMs) under 3 emission scenarios are corrected by using 8 bias correction methods. The trend of Etp in Yangzi River Delta in the 21st century is projected by using 4 Etp calculation formulas. The uncertainty of the projections is estimated and decomposed by using multi-way analysis of variance. The influence of uncertainty on the projected change signal is quantified by using the signal-to-noise ratio. The results show that, relative to the reference period (1971~2000), the annual mean daily Etp in Yangzi River Delta will increase by 0.14~0.17mm/d during the period 2021~2050 and by 0.21~0.41mm/d during the period 2061~2090, respectively. During 2021~2050, the uncertainty of Etp increase projections is dominantly contributed by the main effects of GCM (63%) and Etp calculation formula (24%). During 2061~2090, it is mainly contributed by the main effect of GCM (36%), followed by the main effects of emission scenario (34%) and Etp calculation formula (18%). The increase projections of Etp are generally reliable and robust during the two projection periods.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed: the unknown node is in the positioning unit or not. When the unknown node is on the side of the positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is not on the side of the positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

G protein-coupled receptor 15 (GPR15, also known as BOB) is an extensively studied orphan GPCR involving HIV infection, colonic inflammation and smoking-related diseases. Recently, GPR15 was deorphanized and its corresponding natural ligand demonstrated an ability of inhibiting cancer cell growth. However, no study reported the potential role of GPR15 in a pan-cancer manner. Using large-scale publicly available data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, we found that GPR15 expression is significantly lower in colon adenocarcinoma (COAD) than in normal tissues. And among 33 cancer types, GPR15 expression is significantly correlated with the prognoses of COAD, neck squamous carcinoma (HNSC), lung adenocarcinoma (LUAD) positively and stomach adenocarcinoma (STAD) negatively. This study also revealed that commonly upregulated gene set in the high GPR15 expression group (stratified via median) of COAD, HNSC, LUAD and STAD are enriched in immune systems, indicating that GPR15 might be considered as a potential target for cancer immunotherapy. Furthermore, we modelled the 3D structure of GPR15 and conducted the structure-based virtual screening. The top 8 hits compounds were screened and then subjected to molecular dynamics (MD) simulation for stability analysis. Our study provided novel insights into the role of GPR15 in a pan-cancer manner and discovered a potential hit compound for GPR15 antagonists.

The outbreak of novel coronavirus (COVID-19) infections in 2019 is in dire need of finding potential therapeutic agents. In this study, we used molecular docking to repurpose HIV protease inhibitors and nucleoside analogues for COVID-19, with evaluations based on docking scores calculated by AutoDock Vina and RosettaCommons. Our results suggest that Indinavir and Remdesivir possess the best docking scores, and comparison of the docking sites of the two drugs reveal a near perfect dock in the overlapping region of the protein pockets. After further investigation of the functional regions inferred from the proteins of SARS coronavirus, we discovered that Indinavir does not dock on any active sites of the protease, which may give rise to concern in regards to the efficacy of Indinavir. On the other hand, the docking site of Remdesivir is not compatible with any known functional regions, including template binding motifs, polymerization motifs and nucleoside triphosphate (NTP) binding motifs. However, when we tested the active form (CHEMBL2016761) of Remdesivir, the docking site revealed a perfect dock in the overlapping region of the NTP binding motif. This result suggests that Remdesivir could be a potential therapeutic agent. Clinical trials still must be done in order to confirm the curative effect of these drugs.

Abstract: Objectives: To establish the expression profile of N6-methyladenosine(m6A) modifications in the hippocampus of mice with diabetic cognitive impairment (DCI) and elucidate the potential regulatory mechanism. Methods: A DCI model was established by feeding a high-fat diet to C57BL/6J mice. m6A and RNA sequencing was conducted to profile the m6A-tagged transcripts in the hippocampus. Results: Methylated RNA immunoprecipitation with next-generation sequencing and RNA sequencing analyses yielded differentially m6A-modified and expressed genes in the hippocampus of DCI mice, which were enriched in pathways involving synaptic transmission and axonal guidance. Mechanistic analyses revealed a remarkable change in m6A modification levels through alteration of the mRNA expression of m6A methyltransferases (METTL3 and METTL14) and demethylase (FTO) in the hippocampus of DCI mice. Conclusions: We identified a co-mediated specific RNA regulatory strategy that broadens the epigenetic regulatory mechanism of RNA-induced neurodegenerative disorders associated with metabolic and endocrine diseases.

Piceatannol is a naturally occurring polyphenolic compound that is widely found in grapes, blueberries, mushrooms, passion fruit and other edible fruits and vegetables. It has a variety of biological activities and pharmacological effects, including anti-inflammatory, antioxidation, antiaging, antiviral, antitumor, anticancer, antiatherosclerosis, antiparasitic, immunoregulatory, and cardiovascular protection effects. The aim of this study was to investigate the antiherpesvirus effects of piceatannol. Pseudorabies virus (PRV) belongs to the family Herpesviridae. PRV has a wide host range and can cause cytopathic effects (CPEs) in PK-15 cells. Therefore, PRV was used as a model to study the antiherpesvirus effect of piceatannol. In this study, we evaluated the antiviral activity of piceatannol against PRV in vitro and in vivo. The results showed that piceatannol could reatrain PRV multiplication in PK-15 cells in a dose-dependent manner. The 50% inhibitory concentration (IC50) was 0.0307 mg/mL, the IC50 was 0.0307 mg/mL, and the selectivity index (SI, CC50/IC50) was 3.68. The addition of piceatannol at different stages of PRV infection inhibited the viral adsorption and intracellular replication phases of PRV. Piceatannol significantly reduced the expression levels of the IE180, EP0, UL29, UL44, US6 and UL27 genes of PRV within 48 h, significantly reduced the expression levels of the PRV gB and gD proteins, and reduced PRV-induced apoptosis. Molecular docking showed that piceatannol had good binding activity with the PRV gB and gD proteins. The results of animal experiments in vitro indicated that piceatannol could delay the onset of disease, improve the survival rate of the mice (14.3%), reduce the viral load in the brain and kidney of the mice, alleviate the pathological changes in the mouse tissues and organs, and increase the levels of TNF-α, IEN-γ and IL-4 in the serum of the mice. These data indicate that piceatannol has good anti-PRV activity in vitro and in vivo, indicating that it could be a novel antiherpesvirus infection agent in the future.

In the last two decades, the discovery of various pathways involved in renal cell carcinoma (RCC) have led to the development of biologically-driven targeted therapies. Hypoxia inducible factors (HIFs), angiogenic growth factors, von Hippel-Lindau (VHL) gene mutations and oncogenic miRNAs play essential roles in the pathogenesis and drug resistance of clear cell renal cell carcinoma. These insights have led to the development of VEGF inhibitors, mTOR inhibitors and immunotherapeutic agents which have significantly improved outcomes of patients with advanced RCC. HIF inhibitors will be a valuable asset in the growing therapeutic armamentarium of RCC. Various histone deacetylase (HDAC)inhibitors, including selenium and agents such as PT2385 and PT2977, are being explored in various clinical trials as potential HIF inhibitors to ameliorate the outcomes of RCC patients. In this article, we will review the current treatment options and highlight the potential role of selenium in the modulation of drug resistance biomarkers expressed in ccRCC tumors.

For offshore wind power generation, accessibility is one of the main factors that has great impact on operation and maintenance due to constraints on weather conditions for marine transportation. This paper presents a framework to explore the accessibility of an offshore site. At first, several maintenance types are defined and taken into account. Next, a data visualization procedure is introduced to provide an insight into the distribution of access periods over time. Then, a rigorous mathematical method based on finite state Markov chain is proposed to assess the accessibility of an offshore site from the maintenance perspective. A five-year weather data of a marine site is used to demonstrate the applicability and the outcomes of the proposed method. The main findings show that the proposed framework is effective in investigating the accessibility for different time scales and is able to catch the patterns of the distribution of the access periods. Moreover, based on the developed Markov chain, the average waiting time for a certain access period can be estimated. With more information on the maintenance of an offshore wind farm, the expected production loss due to time delay can be calculated.

Hong Kong is the biggest consumer of eggs in the world and ranks on the top with an average consumption of 24.52kg/capita/year. The egg consumption trend in Hong Kong has been increasing specifically; a drastic increase of about 100% has been observed from 2008 to 2020. One of the reasons behind this significant increase is the increase in the gross national income of Hong Kong in addition to the population growth rate. However, there was a slight decline in egg consumption trend in the year 2020 amid the COVID-19 pandemic. It has been estimated that there was a bulk of 17,100 tons of recoverable waste eggshells in 2019 (pre-COVID-19 situation), having a daily yield of 47 tons per day. Based on the linear regression, it may be expected that if the pre-COVID-19 trend of egg consumption remains sustained, there will be a big bulk of more than 45,000 tons per year and up to 125 tons per day of waste eggshells till 2050. In addition, a public survey was conducted across the city targeting individuals, families, and restaurants majorly on egg consumption and reuse. The survey outcomes revealed that Chinese eggs have an extensive market in Hong Kong, and people have a positive attitude towards eggshell recycling. Also, a massive population disposes of the waste eggshells while only a trace population reuses them. Therefore, Hong Kong has a very high potential to improve the circular economy by reusing waste eggshells on a commercial level in cementitious products.

This paper proposes a new non-radial biennial Luenberger energy and environmental performance index (EEPI) to measure the EEP change in various Chinese cities. The sources of EEP change, in terms of technical efficiency change and technological change, are examined by Luenberger EEPI. The contributions from specific undesirable outputs and energy inputs to the EEP change are identified by means of the non-radial efficiency measure. The proposed approach is applied to evaluate the EEP of the industrial sector in 283 cities in China over 2010-2014. Factors influencing the emission abatement potential are investigated by employing geographically weighted regression (GWR) model. We find that 1) changes in EEP can be attributed to technological progress but that technological progress slows down across the study period; 2) the soot emission performance experiences a downtrend among four specific sub-performances in line with the truth that severe haze happened frequently in China; 3) the best performers begin to move from the coastal to inland cities with the less resource consumption and higher ecological equality; 4) cities with the strongest positive effect in regards to pollution intensity on emission abatement potential are located in the areas around the Bohai Gulf, where air pollution is particularly severe.

Higher education informatization (HEI) is an interdisciplinary field that examines the use and integration of information and communication technologies (ICTs) in higher education. This paper provides a bibliometric and visual analysis of the research trends, patterns, and topics in this field. Using the Web of Science database, we selected and analyzed 199 SCI and SSCI papers on HEI published from 2000 to 2023 by VOSviewer and CiteSpace software. The results indicate that the publication volume of HEI research has grown significantly in recent years, with China and the US being the most productive and influential countries. The author network shows the collaboration and contribution of different researchers and institutions, while the journal network reveals the multidisciplinary nature and scope of the field. The keyword network and the burst keyword analysis identify the main research themes and the emerging hot topics in HEI, such as online learning, big data, and artificial intelligence. The co-citation network of sources illustrates the theoretical and methodological foundations and influences of the field. The paper concludes with some implications and suggestions for future HEI research.

In the last three decades the presence of phospholipids in the nucleus has been shown and thoroughly investigated. A great interest raised about nuclear inositol lipids mainly because of their role in signalling acting. Here we review the main issues of nuclear phospholipid localization and the role of nuclear inositol lipids and their related enzymes in cellular signaling both in physiological and pathological conditions.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system adjustments and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs. generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO₂ emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and the Rest of PJM region leading to scenario-varying changes in the plant-level release of several air pollutants. Due to air pollution chemistry and transport and socio-demographics, these changes in turn give rise to a reduction of 10 to 182 PM_2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Scenarios that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, vulnerable populations—in both PA and Rest of PJM—benefit most in scenarios that prioritize plant closures in PA near Environmental Justice Areas. These results demonstrate the importance of considering cross-regional linkages and socio-demographics in designing equitable retirement strategies.

Rapid urbanization has led to many ecological problems such as landscape fragmentation, decreased landscape connectivity, and decreased biodiversity. Building an ecological security pattern is an important way to ensure ecological security and maintain sustainable urban development. Harbin is an important large-scale city in northeastern China, and the urban central district of Harbin is used as the study area. Ecological sensitivity assessment, MSPA, gravity model, landscape connectivity assessment and MCR model were used to extract ecological source areas, ecological corridors and ecological nodes in the study area to construct and optimize the ecological security pattern. Research shows that: A total of 23 ecological source areas were identified, mainly located along the Songhua River in the central part of the study area and in the mountain forest areas within the A-cheng District in the southeastern part of the study area. 48 ecological corridors were extracted, mainly in Daowai District, A-cheng District and the eastern part of Xiangfang District. There are 8 important ecological corridors and 10 important connecting corridors. 61 ecological nodes of the first level and 65 ecological nodes of the second level were extracted. High, higher, medium, lower and low security areas were classified based on the minimum cumulative resistance surface, with the highest proportion of high ecological security areas accounting for 45.75% of the study area. 65 ecological breakpoints were extracted and restoration measures were proposed. Finally, The structure of the ecological security pattern optimization of "two axes, two belts and four areas" is proposed, and corresponding ecological management measures are put forward. The experimental system of this study can provide new ideas for the construction of ecological security patterns in other regions and provide scientific support for the ecological sustainable development of similar urban areas.

Viruses can induce the fusion of infected and neighboring cells, leading to the formation of syncytia. Cell-cell fusion is mediated by viral fusion proteins on the plasma membrane of infected cells that interact with cellular receptors on neighboring cells. Viruses use this mechanism to spread rapidly to adjacent cells or escape host immunity. For some viruses, syncytium formation is a hallmark of infection and a known pathogenicity factor. For others, the role of syncytium formation in viral dissemination and pathogenicity remains poorly understood. Human cytomegalovirus (HCMV) is an important cause of morbidity and mortality in transplant patients and the leading cause of congenital infections. Clinical HCMV isolates have broad cell tropism but differ in their ability to induce cell-cell fusions, and little is known about the molecular determinants. We developed a system to analyze HCMV glycoprotein B (gB) variants in a defined genetic background. HCMV strains TB40/E and TR were used as vectors to compare the fusogenicity of six gB variants from congenitally infected fetuses with those from three laboratory strains. Five of them conferred the ability to induce fusion of MRC-5 human embryonic lung fibroblasts to one or both backbone strains, as determined by a split GFP-luciferase reporter system. The same gB variants were not sufficient to induce syncytia in infected ARPE-19 epithelial cells, suggesting that additional factors are involved. The system described here allows a systematic comparison of the fusogenicity of viral envelope glycoproteins and may help to clarify whether fusion-promoting variants are associated with increased pathogenicity.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

This paper aims to address the exponential stability and stabilization problems for a class of delayed nonlinear Markov jump systems under randomly occurring Denial-of-Service (DoS) attack and packet loss. Firstly, the stochastic characteristics of DoS attack and packet loss are depicted by the attack success rate and packet loss rate. Secondly, a Period Observation Window (POW) method and a hybrid-input strategy are proposed to compensate for the impact of DoS attack and packet loss on the system. Thirdly, A Dynamic Event-triggered Mechanism (DETM) is introduced to save more network resources and ensure the security and reliability of systems. Then, by constructing a general common Lyapunov functional and combining with the DETM and other inequality analysis techniques, the less conservative stability and stabilization criteria for the underlying systems are derived. In the end, the effectiveness of our result is verified through a numerical example.

Motivated by the PEACOC project on metal recovery from solid wastes, an innovative magnetic density separation (MDS) process has been developed for granular material sorting. It has intrinsic advantages over the existing industrialized MDS by eliminating fluid turbulence and particle jamming problems. The new MDS applies an inclined planar magnet and a horizontal basin containing a static magnetic fluid as the separation medium. A particle sliding phenomenon is identified as a feature of the process which could help the separation. The MDS successfully sorted shredded PCBAs to concentrate valuable metals and sorted shredded wires to reduce metallic contaminants in the plastic fractions. A pilot scale facility is introduced to show the design to achieve continuous production and to reduce the consumption of ferrofluid.

Inflammasomes are multiprotein complexes that activate inflammatory responses by inducing pyroptosis and secretion of pro-inflammatory cytokines. Along with many previous studies on inflammatory responses and diseases induced by canonical inflammasomes, an increasing number of studies have demonstrated that non-canonical inflammasomes, such as mouse caspase-11 and human caspase-4 inflammasomes, are emerging key players in inflammatory responses and various diseases. Flavonoids are natural bioactive compounds found in plants, fruits, vegetables, and teas and have pharmacological properties in a wide range of human diseases. Many studies have successfully demonstrated that flavonoids play an anti-inflammatory role and ameliorate many inflammatory diseases by inhibiting canonical inflammasomes. Others have demonstrated the anti-inflammatory roles of flavonoids in inflammatory responses and various diseases, with a new mechanism by which flavonoids inhibit non-canonical inflammasomes. This review discusses recent studies that have investigated the anti-inflammatory roles and pharmacological properties of flavonoids in inflammatory responses and diseases induced by non-canonical inflammasomes and further provides insight into developing flavonoid-based therapeutics as potential nutraceuticals against human inflammatory diseases.

Fever control is essential in patients with severe traumatic brain injury (TBI). The efficacy of therapeutic hypothermia (TH) in severe TBI has been investigated over the last few decades; however, in contrast to experimental studies showing benefits, no evidence of efficacy has been demonstrated in clinical practice. In this review, the mechanisms and history of hypothermia were briefly outlined, while the results of major randomized controlled trials (RCTs) and meta-analyses investigating TH for adult TBI are introduced and discussed. The retrieved meta-analyses showed conflicting results, with a limited number of studies indicating benefits of TH. Some studies have shown benefits of long-term TH compared with short-term TH. Although TH is effective at lowering elevated intracranial pressure (ICP), reduced ICP does not lead to favorable outcomes. Low-quality RCTs overestimated the benefits of TH, while high-quality RCTs showed no difference or worse outcomes with TH. RCTs assessing standardized TH quality demonstrated the benefits of TH. As TBI has heterogeneous and complicated pathologies, applying a uniform treatment may not be ideal. A meta-analysis of young patients who underwent early cooling and hematoma removal showed better TH results. TH should not be abandoned, and its optimal should be advocated on an individual basis.

Nerve hydrodissection (HD), a technique used when treating nerve entrapments, involves using an anesthetic or solution such as saline or 5% dextrose solution to separate the nerve from the surrounding tissue, fascia, or adjacent structures. This technique aims to treat neuropathic pain, or pain caused by the nerve. Ultrasound-guided HD of peripheral nerves has gained significant attention in the medical profession and pain management fields in recent years. This is due to a number of high impact publications of randomized control trials demonstrating the efficacy and safety of this technique for the treatment of carpal tunnel syndrome. Even the 20th edition of Harrison’s Principles of Internal Medicine textbook lists injection of 5% dextrose as an alternative local treatment that does not have the side effects of corticosteroids. At present, there is no review of the current literature on this technique. This manuscript will summarize and discuss the following: 1) the different approaches to doing ultrasound-guided HD of nervous structures, 2) its usages in different clinical situations, 3) its clinical pearls, 4) the solution used, and 5) the postulated mechanisms of action.

Although effective in term of chance of future live birth, the current methods for fertility preservation such as oocytes, embryo or ovarian tissue cryopreservation cannot be offered to all cancer patients and in all clinical contexts. Expanding options for fertility preservation is crucial to address the need to encompass all situations. One emerging strategy is pharmacoprotection, which is non-invasive and has the potential to fill existing gaps in fertility preservation. Besides the identification of the most efficient therapeutic agent itself, the potential off-target effect re-mains one of the main limitation of this strategy for clinical application, particularly when healthy ovarian tissue is targeted. This review focuses on the advances in pharmacoprotective approaches and the challenge of targeting the ovaries to deliver these agents. The unique properties of gold nanoparticles (AuNPs) make them an attractive candidate for this purpose. We discuss how AuNPs meet many of the requirements for an ideal drug delivery system, as well as the existing limitations that have hindering the progression of AuNPs research into more clinical trials. Additionally, the review highlights microRNA (miRNA) therapy as a next-generation approach to address the issues of fertility preservation and discusses the obstacles that currently impede its clinical availability.

Greenwater (splashing of water on the deck) loading is a classical problem faced by the designer of ship-shaped vessels, which becomes even worst when the vessel operates at harsh weather conditions for an extended period. Installation of breakwaters on the deck can play a crucial role in minimizing this impact. However, research on the design and optimization of the breakwater is still at its infancy, and this study aims at shedding further light on this area by proposing and analyzing the effectiveness of three breakwater designs on a fixed box-shaped vessel. Commercial CFD software is used for this investigation. However, the design model (without breakwater) was validated at first against experimental results of green water splashing, before performing the actual simulations with proposed breakwater design. A vertical plate is used as the deck structure, and greenwater pressure at several locations on that plate is measured to compare the effectiveness of various breakwater designs. Overall, breakwaters with openings (perforations, grillages etc.) found to be more effective in minimizing the pressure generated by the greenwater. Nevertheless, there are significant rooms for improvement on breakwater designs, and some topics for further research are also suggested in this regard.

The development of computational acoustics allows simulation of sound generation and propagation in complex environment. In particular, meshfree methods are widely used to solve acoustics problems through arbitrarily distributed field points and approximation smoothness flexibility. As a Lagrangian meshfree method, smoothed particle hydrodynamics (SPH) method reduce the difficulty in solving problems with deformable boundaries, complex topologies, or multiphase medium. The traditional SPH method has been applied in acoustic simulation. This study presents the corrective smoothed particle method (CSPM), which is a combination of SPH kernel estimate and Taylor series expansion. The CSPM is introduced as a Lagrangian approach to improve accuracy in solving acoustic wave equations in the time domain. Moreover, a boundary treatment technique based on the hybrid meshfree and finite difference time domain (FDTD) method is proposed to represent different acoustic boundaries with particles. To model sound propagation in pipes with different boundaries, soft, rigid, and absorbing boundary conditions are built with this technique. Numerical results show that the CSPM algorithm is consistent and demonstrates convergence with exact solutions. Main computational parameters are discussed, and different boundary conditions are validated to be effective for benchmark problems in computational acoustics.

This paper describes the first results of an Image Recognition Based Location (IRBL) for mobile application focusing on the procedure to generate a Database of range images (RGB-D). In an indoor environment, to estimate the camera position and orientation, a prior spatial knowledge of the surrounding is needed. In order to achieve this objective a complete 3D survey of two different environment (Bangbae metro station of Seoul and E.T.R.I. building in Daejeon – Republic of Korea) was performed using LiDAR (Light Detection And Ranging) instrument and the obtained scans were processed in order to obtain a spatial model of the environments. From this, two databases of reference images were generated using a specific software realized by the Geomatics group of Politecnico di Torino (ScanToRGBDImage). This tool allow to generate synthetically different RGB-D images) centered in the each scan position in the environment. Later, the external parameters (X, Y, Z, ω, φ, κ) and the range information extracted from the DB images retrieved, are used as reference information for pose estimation of a set of acquired mobile pictures in the IRBL procedure. In this paper the survey operations, the approach for generating the RGB-D images and the IRB strategy are reported. Finally the analysis of the results and the validation test are described.

Health issues of children with intellectual disabilities (ID) have gained significant attention as a key focus of China health goals. This study aimed to compare the differences in displacement skills and problem behaviors among children with varying degrees and types of ID, while also exploring their relationship. The study included 90 participants who were children with ID and had completed TGMD-2 displacement skills and Strengths and Difficulties Questionnaire (SDQ) assessments. Covariance, partial correlation, and multiple linear regression analyses were conducted to examine the differences and correlations between these factors. The findings revealed that higher severity of intellectual disability was associated with lower scores in locomotor skills and increased manifestation of problem behaviors. Notably, there were significant variations in locomotor skills and problem behaviors among children with different types of intellectual disabilities. There is a positive correlation between locomotor skills and problem behaviors in children with intellectual disabilities, where locomotor skills can predict the occurrence of problem behaviors. In Conclusion, the research confirms that the development of locomotor skills can have a positive impact on the accompanying problem behaviors of children with developmental disabilities.

Educating children to be informed, responsible, socially adept citizens who care about others is an overarching purpose for schools. A rising variety of preventive and child development initiatives are being implemented in schools. Insufficient coordination with other school activities and neglect of implementation and assessment variables essential for a significant program impact these programs' current implications. They are not doomed to failure in the long term. The other challenges for scholars in school-based action research are identifying practical models to prevent problem characteristics, promoting positive child development, and supporting widespread development and sustainability of evidence-based preschool through educational practice. To conceptualize good youth development programs through Social and Emotional Learning (SEL) in schools, this research presents integrated social, emotional, and intellectual education (ISEIE). School interventions are necessary to implement the social and emotional skills on self-understanding, social knowledge, self-management, relationship management, responsibility, and decision-making. Schools are the best place to implement all these programs to create a better generation. To back up this viewpoint, this study looks at research from illustrative studies and research syntheses. In the end, this paper provides suggestions for implementing programs that combine social, emotional, and intellectual development.

Motivation: UCSC Xena platform provides huge amounts of processed cancer omics data from big public projects like TCGA or individual reserach groups for enabling unprecedented research opportunities. In 2019, we developed UCSCXenaTools, an R package for retrieval of UCSC Xena data. However, an easier dataset exploration and analysis tool is still lack, especially for researchers without programming experience. Results: We develop UCSCXenaShiny, an R Shiny package to quickly explore, download all datasets from UCSC Xena data hubs. In addiction, a module based analysis framework is constructed to analyze and visualize data. Availability: https://github.com/openbiox/UCSCXenaShiny or https://cran.r-project.org/package=UCSCXenaShiny.

Particulate matter (PM) is one of the problems faced in environmental science. It has health effects on man and animals in both developed and developing countries. Research and efforts have been on it several years back. Policy statements and efforts have been published. This review paper is an added information on air pollution. In it, efforts were made in discussing these: classification, effects, methodology, case studies and source apportionment. It is hoped that this paper would contribute to existing knowledge on PM.

In this nano era, nanomaterials and nanostructures are popular in developing novel functional materials. However, the combinations of nanoproducts with materials at micro and macro scale can open new routes for conceiving novel materials with an improved or even new functional performances. In this study, a brand-new hybrid, containing both nanofibers and particles having a microsize, was fabricated using a sequential electrohydrodynamic atomization (EHDA) process. Firstly, the microparticles loaded with drug (berberine hydrochloride, BH) molecules in the cellulose acetate (CA) were fabricated using a solution electrospraying process. Later, these microparticles were suspended into a co-dissolved solution containned BH and a hydrophilic polymer (polypyrrolidone, PVP), and were co-electrospun into the nanofiber/microparticle hybrids. The EHDA processes were clearly recorded, and the resultant products showed a typical hybrid topography, with microparticles distributed all over the nanofibers, which was demonstrated by SEM assessments. FTIR and XRD demonstrated that the components within the hybrids were presented in an amorphous state and have fine compatibility with each other. In vitro dissolution tests verified that the hybrids were able to provide the designed dula-step drug release profiles, a combination of the fast release step of BH from the hydrophilic PVP nanofibers through an erosion mechanism and the sustained release step of BH from the insoluble CA microparticles via a typical Fickian diffusion mechanism. The present protocols pave a new way for developing trans-scale functional materials.

The segmentation of abnormal regions is vital in smart manufacturing. However, the existing segmentation system for detecting sauce-packet leakage on intelligent sensors encounters an issue of imaging blurring caused by uneven illumination. This issue adversely affects segmentation performance, thereby impeding the rapid production of industrial assembly lines. To alleviate this issue, we propose the two-stage Illumination-aware Sauce-packet Leakage Segmentation (ISLS) method for intelligent sensors. The ISLS comprises two main stages: Illumination-aware region enhancement and leakage region segmentation. In the first stage, YOLO-Fastestv2 is employed to capture the Region of Interest (ROI), which reduces redundancy computations. Additionally, we propose an image enhancement to relieve the impact of uneven illumination, enhancing the texture details of ROI. In the second stage, we propose a novel feature extraction network. Specifically, we propose the Multi-scale Feature Fusion Module (MFFM) and the Sequential Self-Attention Mechanism (SSAM) to capture discriminative representations of leakage. The multi-level features are fused by MFFM with a small number of parameters, which capture leakage semantics at different scales. The SSAM realizes the enhancement of valid features and the suppression of invalid features by adaptive weighting of spatial and channel dimensions. Furthermore, we generated a self-built dataset of sauce-packets, including 606 images with various leakage areas. Comprehensive experiments demonstrate that our ISLS method shows better results than several state-of-the-art methods, with additional performance analyses deployed on intelligent sensors to affirm the effectiveness of our proposed method. Our code is available at https://github.com/LSJ5106/SauceDetect.

This paper investigates an Energy Neutral System using Micro Energy Harvesters for a Health Monitoring Wireless Sensor Node (HM-WSN). We have implemented HM-WSN consisting of a solar cell energy harvester, a Power Management Unit (PMU) and the ucontroller, sensor and transmitter acting as load. A battery extender and a switching logic circuit for sensor node is designed to evaluate the efficiency of the proposed system. The HM-WSN senses body temperature with improvement in lifetime of coincell. The HM-WSN is built using commercially available off the shelf (COTS components and consumes 47.2uW for data being updated every 134s. It can be operated for approximately 1.32 years only on a coincell. Furthermore, the HM-WSN can be operated with solar energy at 200lux, achieving 96.36 years with a combination of a coincell with an additional capacitor of 2.2mF. It attains 4.07 years to 16.87 years lifetime with the load capacitor varying from 1mF to 1.5mF at 350lux lighting condition. With the same ambient condition and a 2mF load capacitor, HM-WSN attains complete energy autonomy.

Familial Alzheimer’s disease (FAD) can be caused by mutations in PSEN1 that encodes presenilin-1, a component of the gamma-secretase complex that cleaves amyloid precursor protein. Alterations in calcium (Ca2+) homeostasis and glutamate signaling are implicated in the pathogenesis of FAD, however it has been difficult to assess in humans whether or not these phenotypes are the result of amyloid or tau pathology. This study aimed to assess early calcium and glutamate phenotypes of FAD by measuring the Ca2+ response of induced pluripotent stem cell (iPSC)-derived neurons bearing PSEN1 mutations to glutamate and the ionotropic glutamate receptor agonists NMDA, AMPA and kainate compared to isogenic control and healthy lines. The data shows that in early neurons, even in the absence of amyloid and tau phenotypes, FAD neurons exhibit increased Ca2+ responses to glutamate and AMPA, but not NMDA or kainate. Together this suggests that PSEN1 mutations alter Ca2+ and glutamate signaling as an early phenotype of FAD.

This paper investigates the impact of sediment deposition and inflow conditions on horizontal impact pressure and frequency analysis of bridge deck vibrations during flooding. Flooding-induced pressure and vibrations contribute to bridge collapse, and sediment deposition influences water flow and impact pressure. The study explores the relationship between sediment deposition height and impact pressure, revealing a significant increase as sediment approaches 50% of bridge deck clearance. Sediment amplifies impact pressure response to flow velocity changes. The dimensionless sediment deposition height has a greater influence on impact pressure compared to the inflow Froude number. Two distinct frequencies, dominant and secondary, are identified for impact pressure and water level fluctuations. Dominant frequencies positively correlate with sediment deposition height and Froude number, indicating an increasing trend. Secondary frequencies remain stable (0.31-0.58 Hz). These findings enhance understanding of flow dynamics and bridge-flow interaction in sediment-deposited channels, providing theoretical support for evaluating and managing disasters related to bridges in such environments. Overall, this research contributes to the field of bridge engineering and supports improved design and maintenance practices for bridges exposed to sediment-deposited channels.

Limited knowledge is available about the association between autistic spectrum disorder (ASD) and precocious puberty. Our study examined the association between the two medical conditions, and the effect modification by sex and neuropsychiatric comorbidities in a nationwide population. To compare the risk of precocious puberty between ASD and non-ASD cases, we conducted Cox regression analysis, using ASD as exposure and time-to-precocious puberty as outcome. We adjusted for sex, attention-deficit/hyperactivity disorder (ADHD), tics disorder, obsessive–compulsive disorder (OCD), anxiety disorder, intellectual disability, and epilepsy. We performed a moderation analysis to examine the potential moderating effects by sex or comorbidities. Patients with ASD were prone to have precocious puberty, with an adjusted hazard ratio (aHR) of 1.80 (95% CI: 1.61-2.01). For the effect modification, sex, specifically females, moderated the association between ASD and precocious puberty, with relative excess risk due to interaction (RERI) 7.35 (95% CI 4.90-9.80). No significant effect modification was found for any of the comorbidities within the scope of additive effect modification. We found that patients with ASD were prone to precocious puberty, regardless of sex or comorbid neuropsychiatric disorders. Girls with ASD are at particularly higher risk to develop precocious puberty.

The aim of this study was to examine the oxidation of human serum albumin (HSA) caused by oxidative stress after an exhaustive exercise such as ultra-marathon race. Thus, blood samples from 12 adult runners who underwent a 103 km mountain ultra-marathon race were collected pre- and 24, 48 and 72 h post race. HSA was partially purified using affinity chromatography and then was subjected to Western blot analysis for disulfide dimers determination, indicating oxidation. The results were correlated with those from a previous study in which the same samples were analyzed using different oxidative stress markers and a good correlation with protein carbonyls (PC) at all time points was observed. Moreover there was a significant correlation with static oxidation-reduction potential (sORP) at 24 h, and a negative correlation with capacity oxidation-reduction potential (cORP) at 24 and 48 h. In addition, an individual analysis of albumin dimers exhibited great inter-individual differences. This inter-individual variability in the oxidation of HSA may suggest different interventions (e.g. through diet) in order to confront the effects on athletes’ organism after a strenuous exercise. In conclusion, this study supported the importance of the assessment of albumin dimers as a predictive marker for exercise-induced oxidative stress.

Cloud computing refers to applications delivered as services over the Internet. Cloud systems employ policies that are inherently dynamic in nature and that depend on temporal conditions defined in terms of external events, such as the measurement of bandwidth, use of hosts, intrusion detection or specific time events. In this paper, we investigate an optimized resource management scheme named v-Mapper. The basic premise of v-Mapper is to exploit application-awareness concepts using software-defined networking (SDN) features. This paper makes three key contributions to the field: (1) We propose a virtual machine (VM) placement scheme that can effectively mitigate the VM placement issues for data-intensive applications; (2) We propose a validation scheme that will ensure that a service is entertained only if there are sufficient resources available for its execution and (3) We present a scheduling policy that aims to eliminate network load constraints. An evaluation was carried out with various benchmarks and demonstrated that v-Mapper shows improved performance over other state-of-the-art approaches in terms of average task completion time, service delay time and bandwidth utilization. Given the growing importance of supporting large-scale data processing and analysis in datacentres, the v-Mapper system has the potential to make a positive impact in improving datacentre performance in the future.

This study investigates the expression and prognostic value of TRIM6 in gliomas, the most prevalent primary brain and spinal cord tumors. Our results show that TRIM6 is predominantly overexpressed in glioma tissues and is associated with reduced overall survival, disease-specific survival, and progression-free interval. Furthermore, TRIM6 expression is correlated with WHO grade and primary treatment outcomes. Functional analysis indicates that interactions between cytokines and their receptors play a critical role in the prognosis of glioma patients. A protein-protein interaction network reveals 10 hub genes closely linked to cytokine-cytokine receptor interaction. In vitro experiments demonstrate that silencing TRIM6 impairs the proliferation, invasion, and migration of glioma cells, while overexpressing TRIM6 enhances these abilities. Additionally, TRIM6 expression is positively associated with the abundance of innate immune cells and negatively associated with the abundance of adaptive immune cells. In summary, TRIM6 is significantly upregulated in gliomas and linked to poor prognosis, making it a potential diagnostic and prognostic biomarker. TRIM6 plays a crucial role in promoting cell viability, clonogenic potential, migration, and invasion in glioma cells. It may regulate glioma progression by modulating cytokine-cytokine receptor interaction, leading to an inflammatory response and an imbalance in immunomodulation, thereby representing a potential therapeutic target.