Control as a Service (CaaS) is an emerging paradigm where low-level control of a device is moved from a local controller to the Cloud, and provided to the device as an on-demand service. Among its many benefits, CaaS gives the device access to advanced control algorithms which may not be executable on a local controller due to computational limitations. As a step toward 3D printer CaaS, this paper demonstrates the control of a 3D printer by streaming low-level stepper motor commands (as opposed to high-level G-codes) directly from the Cloud to the printer. The printer is located at the University of Michigan, Ann Arbor, while its stepper motor commands are calculated using an advanced motion control algorithm running on Google Cloud computers in South Carolina and Australia. The stepper motor commands are sent over the Internet using the user datagram protocol (UDP) and buffered to mitigate transmission delays; checks are included to ensure accuracy and completeness of the transmitted data. All but one part printed using the cloud-based controller in both locations were hitch free (i.e., no pauses due to excessive transmission delays). Moreover, using the cloud-based controller, the parts printed up to 54% faster than using a standard local controller, without loss of accuracy.

This paper looks at key elements of global culture that are driving a new paradigm shift in museums causing them to question their raison d'être, their design and physical space, recognizing the need to accommodate visitor interaction and participation, and to reprioritize institutional outcomes and goals reexamining their priorities. As heritage sharing in online spaces reaches across national, political, and social boundaries on platforms and networks, this has been driven by museum engagement with Internet life during the pandemic. Museum relationships and interactions with communities both local and global, continue to challenge core values and precepts, leading to radical changes in how museums define their roles and responsibilities. In this new cultural landscape, museums are responding to human digital identity in a tidal wave of human interactions on the Internet, from social media to online sharing of images and videos. This is revealing shared perspectives on cultural conflict as being tied to freedom of expression of one’s heritage embedded in digital identity.

Museums increasingly recognize the need to address advances in digital culture which impact the expectations and needs of their audiences. Museum collections of real objects need to be presented both on their own premises and digitally online, especially as social media becomes more and more influential in people’s everyday lives. We investigate these challenges magnified by advances in digital and computational media and culture looking particularly at recent and relevant reports on changes in the ways museums interact with the public. We find that the Covid-19 pandemic has accelerated many of the changes driving museum transformation. We believe that museums must be more prepared than ever to adapt to unabated technological advances set in the midst of cultural and social revolution, now intrinsic to the digital landscape in which museums are inevitably connected and participating across the global digital ecosystem where they inevitably find themselves entrenched.

We developed an ovarian cancer-targeted drug delivery system based on a follicle-stimulating hormone receptor (FSHR) peptide. The lipophilic chemotherapeutic drug SN38 and the photosensitizer IR820 were loaded into the phospholipid bilayer of liposomes. Near-infrared laser irradiation stimulated the generation of reactive oxygen species, causing short-term reactive molecular species and spatial-temporal restricted photodamage to the biological targets. The reactive molecular species and spatial-temporal restricted photodamage enhanced the release and uptake of chemotherapy drugs and increased the sensitivity to chemotherapy drugs in ovarian cancer cells. FSH liposomes loaded with SN38 and IR820 (SN38/IR820-Lipo@FSH) were prepared using thin-film hydration-sonication. FSH peptide binding was analyzed using 1H NMR spectrum and Maldi-Tof. The average size and zeta potential of SN38/IR820-Lipo@FSH were 105.1 ± 1.15 nm (PDI: 0.204 ± 0.03) and −27.8 ± 0.42 mV, respectively. SN38/IR820-Lipo@FSH exhibited good drug-loading properties and the in vitro release was slow. FSH significantly increased the uptake of liposomes, inhibited cell proliferation, and induced apoptosis in A2780 cells. Moreover, SN38/IR820-Lipo@FSH exhibited good tumor-targeting ability and anti-ovarian cancer activity in vivo. The SN38/IR820-Lipo@FSH exhibited specific targeting to A2780 ovarian cancer cells. The combination of chemotherapy and photodynamic treatment based on an FSH peptide-targeted delivery system may be an effective approach to treating ovarian cancer.

Due to the linear property around an acetylenic carbon, the introduction of such an atom to a small cycle would result in high ring strain. Currently, the smallest isolated rings are five-membered, including metallacycloalkynes and metallapentalynes. Both types contain at least one unusual small bond angle around the acetylenic carbon, thus exhibiting abnormal reactivities. This feature article gives a comprehensive overview on these two kind complexes. The synthesis and reactivities are extensively described, the source of stability is presented, and the future prospect is discussed. The article aims to provide a better development for the chemical diversity of five-membered metallacycloalkynes and metallapentalynes.

The two-dimensional, laterally-averaged mechanistic eutrophication model CE-QUAL-W2 version 3.72 was used to predict chlorophyll-a concentrations across two different time periods in the Neuse River Estuary, North Carolina. Chlorophyll calibration was performed for two time periods simultaneously by performing by a full-factorial experiment that tested seven algal kinetic growth parameters over three levels for a single algal group. A cluster of up to six computers each running between two and ten instances of the program was used to complete and manage the data for 2187 runs for each time period. A set of six criteria were used to determine which runs performed acceptably, yielding a group of 27 cases that met all of the criteria. Calibration performance of the set of cases outperformed a previously calibrated model using three algal groups that met only four of the six selection criteria. Calibration performed this way allowed for a more rational specification of model calibration performance and provided uncertainty estimates of model predictions, albeit at the cost of a considerable increase in computational requirements that necessitated the use of a computer cluster.

In the paper, we explore the notion of global digital citizenship, particularly with respect to museums and cultural heritage organizations. In this perspectives study, we explore current examples of how museums can adapt to the tenets of global digital citizenship necessary to navigate and participate in increasingly interconnected digital worlds and culture, and to collectively address global challenges.

China's implementation of public-private partnerships projects has been quite effective, involving infrastructure and other livelihood projects, a total of 19 industries, and an investment of nearly 1.5 trillion yuan. The characteristics of PPP projects such as long construction period and large investment amount determine the risks of PPP projects are also great, and the PPP projects of comprehensive environmental governance are also the same. The government and social capital use the PPP model to cooperate, and use the principal component analysis method to assess the risks of the entire life cycle of the comprehensive environmental governance PPP project. Therefore, it plays an important role in ensuring the smooth implementation of projects and reducing the losses caused by risks. According to the risk factors of the whole life cycle of the comprehensive environmental governance PPP project, an indicator system of 5 first-level indicators, 18 second-level indicators, and 43 third-level indicators has been established. Principal component analysis is used to analyze the influence weight of risk factors at each stage. The analysis shows that among the four stages, environmental pollution risk, project approval delay risk, completion risk, interest rate and financial fluctuation risk, and franchise life risk are the most influential risks in the implementation of PPP projects. Therefore, suggestions are made through the risk factors of each stage in the comprehensive environmental governance PPP project. For example, strengthen the response to the external environment risks of the comprehensive environmental governance PPP project, standardize the bidding and procurement of the comprehensive environmental governance PPP project, and strengthen the subsequent management of the transfer of the comprehensive environmental governance PPP project. In this way, the ability to resist risks of comprehensive environmental governance PPP projects is improved; the smooth implementation of the project is guaranteed, and the long-term development of comprehensive environmental governance PPP projects is promoted.

This study examines the DCMA concerning the future risk of the water security status. We considered three risk factors: population growth, economic growth, and natural water supply demand differences. In the risk analysis part, we consulted with experts from several sectors including academia, Non-Governmental Organization (NGOs), and industry, to predict that the probability of future water stresses in high, medium, and low scenarios are 0.73, 0.24, and 0.03, respectively. In the decision analysis part, we adopted two Multiple Criteria Decision Analysis (MCDA) approaches that include Multiple Attribute Value Theory (MAVT) and Analytic Hierarchy Process (AHP) methods to evaluate the best alternative decision to alleviate future water stresses in the DCMA. The sensitivity analysis demonstrates the best option closely connects to the weighting scheme of the criteria considered in the framework. This study provides a valuable risk and decision analysis framework to analyze the water security status associated with the future water supply and demand gap decrease caused by three risk factors: population growth, climate change, and natural water supply.

To expand the application area of the reference group and enrich exercise theoretical research, based on Stimulus-Organism-Response (S–O-R) framework, this study examines the factors that motivate for adherence to exercise from the external. Taking reference group and strategy and cultural fit as the main stimulus, and personal investment and life satisfaction as mediating variables, this study try to explore the influence of external stimulus on residents’ exercise behavior. In order to enrich the sample size, two surveys of 734 Chinese residents in two cities (Xiamen vs. Fuzhou) were conducted using factor analyses, regression analysis, and T-test analysis. The results indicated that the reference group and strategic and cultural fit as external stimulus have impact on residents’personal investment, life satisfaction and exercise adherence, personal investment and life satisfaction as the organism has impact on residents’ exercise adherence. Personal investment and life satisfaction play a chain mediating role between the reference group and exercise adherence, strategy and cultural fit, and exercise adherence. Moreover, the T-test determined the differences between Xiamen and Fuzhou residents’ exercise adherence and life satisfaction. Residents’ surroundings affect their exercise behavior and life satisfaction. These findings have implications for policymaking aimed at promoting national exercise, which could gradually improve residents’ physical fitness, particularly in light of the current coronavirus emergency.

Nutrients are the driving force of plant and herbivore interactions. Different elements and fertilization levels in soil, or artificially fertilized substrates can have a direct impact on plant defense responses. Meanwhile, nutrient levels mediated by root associated microbes can indirectly affect plant-herbivore interactions. Nutrient uptake promoted by beneficial mycorrhizal fungi or rhizobacteria interacting with roots can stimulate plant tolerance to herbivore attack, as evidenced by herbivore performance, plant nutrient status, plant biomass allocation and compensatory growth. In return, herbivory affects nutrient fluxes between plants and their associated beneficial microbes. Furthermore, aboveground and belowground herbivory can affect the nutrient exchange between plants and soil microbial communities, mainly for carbon-and nitrogen-based resources supporting herbivores´ life cycles. These ecological interactions are governed by jasmonic acid (JA) and key enzymes on the molecular level. This review summarizes the current scientific literature on the role of nutrients in plant-herbivore interactions. This will support efforts to optimize plant defense strategy via managing nutrient variance.

Hypersonic aircraft focuses more on the integration of aircraft and engine than ordinary aircraft owing to high performance requirements, and the nozzle design is reflected in the required large area ratio of nozzle inlet and outlet and the compactness of the overall size of the aircraft. In this study, the height constraint is directly introduced into the maximum thrust nozzle design method. A new method for designing nozzles under the height constraints that consults the maximum thrust theory is proposed. Initially, the condition that the nozzle reaches the maximum thrust under the height constraint is deduced mathematically. Then, a nozzle design method satisfying the height constraint is computed using the method of characteristics (MOC). Subsequently, the influence of the design parameters on the design method is studied parametrically. Results show that Mach number scale and asymmetrical factors can affect ramp length and flap length of the nozzle, respectively. These factors great influence the axial thrust performance and lift under a specific height constraint. Compared with the traditional truncation design method, the thrust coefficient and lift increased by 11.93% and 138.45% respectively.

Lymphoma diagnoses in the U.S. are substantial, with an estimated 89,380 new cases in 2023, necessitating innovative treatment approaches. Phase 1 clinical trials play a pivotal role in this context. We developed a binary predictive model to assess trial adherence to expected average durations, analyzing 1,089 completed Phase 1 lymphoma trials from clinicaltrials.gov. Using machine learning, the Random Forest model demonstrated high efficacy with an accuracy of 0.7248 and ROC-AUC of 0.7701 for lymphoma trials. Importantly, this model maintained an accuracy of 0.7405 when applied to lung cancer trials, showcasing its versatility. A key insight is the correlation between higher predicted probabilities and extended trial durations, offering nuanced insights beyond binary predictions. Our research contributes to enhanced clinical research planning and potential improvements in patient outcomes in oncology.

We explored the dynamics of the two interacting information systems. We show that for the Markovian marginal systems the driving force for information dynamics is determined by both the information landscape and information flux. While the information landscape can be used to construct the driving force to describe the equilibrium time reversible information system dynamics, the information flux can be used to describe the nonequilibrium time-irreversible behaviours of the information system dynamics. The information flux explicitly breaks the detailed balance and is a direct measure of the degree of the nonequilibriumness or time irreversibility. We further demonstrate that the mutual information rate between the two subsystems can be decomposed into the equilibrium time-reversible and nonequilibrium time-irreversible parts respectively. This decomposition of the mutual information rate (MIR) corresponds to the information landscape-flux decomposition explicitly when the two subsystems behave as Markov chains. Finally, we uncover the intimate relationship between the nonequilibrium thermodynamics in terms of the entropy production rates and the time-irreversible part of the mutual information rate. We found that this relationship and MIR decomposition still hold for the more general stationary and ergodic cases. We demonstrate the above features with two examples of the bivariate Markov chains.

Geopolitical situations, such as the Ukraine–Russia war, the Israel–Hamas war, and pandemics, can disrupt supply chains, such as the rerouting of oil tankers via South Africa to avoid the impact of the Israel–Hamas conflict. These events will probably occur again, but they are black swan events and difficult to predict. How can firms manage these events to minimise disruption to their supply chains? This paper proposes that a blockchain architecture has the potential to build resilience in supply chains and give them the flexibility to withstand the challenges of black swan events. The decentralisation ability of blockchain technology enables separation of the discrete elements of a sustainable supply chain so contagion does not impact the overall sustainable supply chain. To achieve flexibility in a sustainable supply chain ecosystem requires governance, leadership, and management. Also, artificial intelligence (AI), in conjunction with blockchain, is a technology that can enhance the flexibility and resilience of the supply chain. Thus, AI can act as a controller, co-ordinator, and an integrator in sustainable supply chain systems.

. In this paper, we introduce a series of definitions of generalized affine functions for vector-valued functions. We prove that our generalized affine functions have some similar properties with generalized convex functions. We present examples to show that our generalized affinenesses are different from one another, and also provide an example to show that our definition of presubaffinelikeness is non-trivial; presubaffinelikeness is the weakest generalized affineness introduced in this article. We work with optimization problems that are defined and taking values in linear topological spaces. We devote to the study of constraint qualifications, and derive some optimality conditions as well as a strong duality theorem. Our optimization problems have inequality constraints, equality constrains and abstract constraints; our inequality constraints are generalized convex functions and equality constraints are generalized affine functions.

In this paper, we prove that the sub convexlikeness introduced by V. Jeyakumar [1], and the subconvexlikeness defined in V. Jeyakumar [2] are equivalent in loccallly convex topological spaces. And then, we work with set-valued vector optimization problems and obtain some vector saddle-point theorems and vector Lagrangian theorems.

General wisdom thinks that the central of blackholes are singular and featured by mass, charge and spin exclusively; the microstate reflected in the Bekenstein-Hawking entropy can be accounted for only in some quantum gravity. We challenge this wisdom with two exact solution families to the sourceful Einstein equation which describe dust ball with oscillatory inner structure and variety of mass profiles. We attribute the matter content's oscillation across the central point of the system to the forward scattering domination in high energy collisions induced by inter-gravitating acceleration and provide their Penrose-Carter diagram representation and quantum description briefly. Our solution family provides a very simple semi-classic picture for the micorstate definition of black holes.

In this paper, mineralogical and elemental geochemical characteristics of massive sulfide samples collected from Jade hydrothermal field, located in the Izena depression in the central graben of Okinawa Trough, were analyzed by means of optical microscopy, scanning electron microscopy and electron probe. The results show that the sulfide in Jade hydrothermal area can be divided into Zn-Cu-Pb rich massive sulfide and Zn-Fe rich massive sulfide. The former is composed of sphalerite, galena, anglesite, chalcopyrite and pyrite, and its formation stage can be divided into pyrite stage, sphalerite-chalcopyrite stage, anglesite stage and colloidal pyrite stage. The latter is mainly composed of sphalerite, pyrite, marcasite and a small amount of galena, which can be divided into galena stage, pyrite stage, sphalerite stage, pyrite and marcasite stage. Cu and Zn in pyrite may exist in the form of microinclusions, while Ag and Pb may exist in pyrite in the form of fine galena inclusions containing Ag. Fe and Cu may enter sphalerite in the form of ion replacement. Zn may enter chalcopyrite in the form of ion replacement, and As and Pb may be inclusions in chalcopyrite as As-bearing galena inclusions. Consistent with the previous understanding, the metal elements in the hydrothermal liquid system in Jade hydrothermal field mostly migrate with the hydrothermal fluid as sulfur complexes, and when the hydrothermal fluid mixes with seawater, the physical and chemical conditions of the fluid change, resulting in sulfide mineral precipitation. However, the chemical structure of chalcopyrite is still controversial, which restricts the understanding of the substitution mechanism of trace elements during chalcopyrite precipitation.

In this paper we study the class of mixed-index time fractional differential equations in which different components of the problem have different time fractional derivatives on the left hand side. We prove a theorem on the solution of the linear system of equations, which collapses to the well-known Mittag-Leffler solution in the case the indices are the same, and also generalises the solution of the so-called linear sequential class of time fractional problems. We also investigate the asymptotic stability properties of this class of problems using Laplace transforms and show how Laplace transforms can be used to write solutions as linear combinations of generalisedMittag-Leffler functions in some cases. Finally we illustrate our results with some numerical simulations.

Ligand-based virtual screening (LBVS) is a promising approach for rapid and low-cost screening of potentially bioactive molecules in the early stage of drug discovery. Compared with traditional similarity-based machine learning methods, deep learning frameworks for LBVS can more effectively extract high-order molecule structure representations from molecular fingerprints or structures. However, the 3D conformation of a molecule largely influences its bioactivity and physical properties, and has rarely been considered in previous deep learning-based LBVS methods. Moreover, the relative bioactivity benchmark dataset is still lacking. To address these issues, we introduce a novel end-to-end deep learning architecture trained from molecular conformers for LBVS. We first extracted molecule conformers from multiple public molecular bioactivity data and consolidated them into a large-scale bioactivity benchmark dataset, which totally includes millions of endpoints and molecules corresponding to 954 targets. Then, we devised a deep learning-based LBVS called EquiVS to learn molecule representations from conformers for bioactivity prediction. Specifically, graph convolutional network (GCN) and equivariant graph neural network (EGNN) are sequentially stacked to learn high-order molecule-level and conformer-level representations, followed by attention-based deep multiple-instance learning (MIL) to aggregate these representations and then predict the potential bioactivity for the query molecule on a given target. We conducted various experiments to validate the data quality of our benchmark dataset, and confirmed EquiVS achieved better performance compared with 10 traditional machine learning or deep learning-based LBVS methods. Further ablation studies demonstrate the significant contribution of molecular conformation for bioactivity prediction, as well as the reasonability and non-redundancy of deep learning architecture in EquiVS. Finally, a model interpretation case study on CDK2 shows the potential of EquiVS in optimal conformer discovery. The overall study shows that our proposed benchmark dataset and EquiVS method have promising prospects in virtual screening applications.

Fire is a serious security threat that can lead to casualties, property damage, and environmental damage. However, despite the availability of object detection algorithms, challenges persist in detecting fires and smoke. These challenges include slow convergence speed, poor performance in detecting small targets, and high computational cost limiting deployments. In this paper, Fire smoke and human detection based on ConvNeXt and Mixed encoder (FCM-DETR), an end-to-end object detection algorithm based on Deformable DETR, is proposed. Firstly, we introduce ConvNeXt to take the place of Resnet, which greatly reduces the amount of computation and improves the ability to extract irregular flame features. Secondly, to effectively process multi-scale features, the original encoder is decoupled into two modules. Then Mixed encoder, an innovative encoder structure, is proposed, resulting in excellent performance of multi-scale fire and smoke features fusion. What can’t be overlooked is that the encoder block is compatible with any DETR-based models. Finally, the convergence speed is accelerated and the mean of average precision is improved by applying a novel loss function called Powerful IoU v2. The experimental results indicate that our model achieves the best detection accuracy compared to other models, with mAP reaching 66.7%, mAPs and Accuracyfire achieving impressive 50.2% and 98.05%, respectively.

Manipulation of the intestinal microbiome is an emerging area of research, especially in hind-gut fermenters such as the horse. The aim of this study was to determine whether fecal pH can provide a simple and cost-effective tool to document changes in the intestinal metabolome and microbiome following supplementation of feed with an enzyme rich malt extract (ERME). Fecal pH was determined weekly in triplicate using a commercial soil pH meter in 72 Thoroughbred racehorses in training before and during supplementation with ERME (300mls per day divided into two feeds) alongside their regular feeding schedule. No control group was included. Fecal pH increased over the 4 weeks of treatment from 6.20 (6.15-6.24) to 6.40 (6.38-6.44; P<0.0001). Changes were not observed at one-week intervals but were apparent after 2 weeks There was a significant increase in the proportion of horses with a ‘normal’ pH at the end of the study (55%) compared to the start of the study (11%; p<0.001). These data support the further validation of the use of fecal pH in large scale microbiome/metabolome studies in the horse, although comparisons with these outcomes are now warranted.

Nanopowders are continuously under investigation as they open new perspectives in numerous fields. There are two main challenges to stimulate their development: sufficient low-cost high throughput synthesis methods leading to a production with well-defined and reproducible properties, and for ceramics, conservation of their nanostructure after sintering. In this context, this paper presents the synthesis of a pure nanosized powder of ZnO (dv₅₀ ~ 60 nm, easily redispersable) by using a continuous Segmented Flow Tubular Reactor (SFTR), which has previously shown its versatility and its robustness, ensuring a high powder quality and reproducibility over time. A higher scale of production can be achieved based on a “scale-out” concept by replicating the tubular reactors. The sinterability of ZnO nanopowders synthesized by the SFTR was studied, by natural sintering at 900 °C and 1100 °C, and Spark Plasma Sintering (SPS) at 900 °C. The performances of the synthesized nanopowder were compared to a commercial ZnO nanopowder of high quality. The samples obtained from the synthesized nanopowder could not be densified at low temperature by traditional sintering, whereas SPS led to a fully dense material after only 5 minutes at 900 °C, while limiting the grain growth and thus leading to a nanostructured material.

Estimating Visual Quality of Street Space (VQoSS) is pivotal for urban design, environmental sustainability, civic engagement, etc. Recent advancements, notably in deep learning, have enabled large-scale analysis. However, traditional deep learning approaches are hampered by extensive data annotation requirements and limited adaptability across diverse VQoSS tasks. Multimodal Large Language Models (MLLMs) have recently demonstrated proficiency in various computer vision tasks, positioning them as promising tools for automated VQoSS assessment. In this paper, we pioneer the application of MLLMs to VQoSS change estimation, with our empirical findings affirming their effectiveness. In addition, we introduce Street Quality GPT (SQ-GPT), a model that distills knowledge from the current most powerful but inaccessible (not free) GPT-4, requiring no human efforts. SQ-GPT approaches GPT-4’s performance and is viable for large-scale VQoSS change estimation. In a case study of Nanjin, we showcase the practicality of SQ-GPT and knowledge distillation pipeline. Our work promises to be a valuable asset for future urban studies research.

High-quality rice (Oryza sativa L.) is increasingly widely planted in China with the improvement of people's living standards and the achievement of rice breeding efforts in recent years. However, the agronomic and physiological performances of high-quality indica rice (HQIR) under different nitrogen(N) application conditions in southern China are little known. Two-year consecutive field experiments were conducted with two HQIR and two ordinary-quality indica rice (OQIR) varieties under moderate and high N application rates, with yield and yield components, biomass, N up-take, and their related traits investigated. We found that grain yields of HQIR were slightly de-creased, but grain yields of OQIR were significantly increased by 6.60%-8.88% under high N rate compared with moderate N rate in both years. Thereby, OQIR produced 8.34%-11.87% and 22.00%-22.50% higher grain yield than HQIR under moderate and high N rates, respectively. The different responses of grain yield to N application rates were mainly due to decreased grain set-ting rate in HQIR and increased spikelets m-2 in OQIR under high N rate. Furthermore, high N rate significantly reduced pre-anthesis AE and improved grain-leaf area ratio, while did not in-crease post-anthesis DM compared with moderate N rate in HQIR, which might result in carbon metabolic deterioration and imbalance of source-sink relationship and subsequently lower supply of carbohydrate to panicle. Our results suggest that a moderate N rate (165 kg N ha-1) is beneficial for HQIR varieties to balance the maximum grain yield and high quality in southern China

The impacts of inflation on international finance are generally reflected in the decline of buying power, risks of investment and deposit loss from currency devaluation. For the purpose of optimized allocation and management of asset values, i.e., annual income or research grants, a framework of a three-level model for static financial management is presented to maximize banking interests, bonuses, and the remaining balance after spending necessary expenditures. Meanwhile, in retrospect to higher-level financial inflation, strategies of dynamic investment, i.e., posing regular tests of flipping coins, exploiting variations of the currency exchange rate, as well as applying the theory of broad money, are presented to increase the appreciation rate of net assets in and post the era of COVID-19. Quantitative evaluations in case studies verify the feasibility of improving the financial situation, indicating broader applications for budgeting and investing when US inflation rate is below 3.0%. Besides, combining approaches of static and dynamic strategies, the expected annual growth rate of individual zero-risk asset investment is predicted as within the range of 8.30~9.62% according to budgeted appreciation on net assets in 12 months, which is capable of overcoming negative impacts from higher level annual inflation, i.e., those as highest as 8.01% in the Year 2022.

Cacao (Theobroma cacao L.) is an important woody species for production in Ecuador. Woody species have the potential to incorporate soil organic carbon (SOC) into the soil. The province of Manabí is known for its cocoa plantations and several cocoa species, which generates interest in their analysis. This study aimed to determine the concentration and accumulation of SOC in three cocoa species (EET95, EET103 and EET116) 15 years old, both under the tree and in the rows, at different depths 0-5, 5-10, 10-20 and 20-30 (cm). The results showed that soil SOC concentration was higher in the row for EET116 (2.51%) and significantly different under the tree for EET103 (1.57%) at 0-5 cm. No significant differences were found in the other sections. In the whole profile analyzed (0-30 cm), the EET116 species accumulated 41 t ha-1 and 54 t ha-1 under the tree and in the row, respectively. The species EET103 in the row presented 47 t ha-1 with no significant differences. Species EET95 and EET103 had the lowest values, but without significant differences between sampling locations, with 36 t ha-1, 37 t ha-1, and 47 t ha-1 under the tree and in the windrow, respectively. In conclusion, the species EET116 accumulated more organic carbon due to several factors, possibly a higher decomposing biomass, not only from the tree but also from other trees in the area, which contributes to the incorporation of organic matter throughout the soil profile.

For traffic management under sudden disaster in high-density areas, the first and foremost step is to prevent traffic congestion in the disaster-affected area by traffic flow control, as to provide enough and flexible traffic capacity for emergency evacuation and emergency rescue. Catastrophe border identification is the foundation and the key to traffic congestion prediction under sudden disaster. This paper uses a mathematical model to study the regional traffic flow in the high-density area under sudden fire disaster based on the Cusp Catastrophe Theory (CCT). The catastrophe border is identified by fitting the CCT-based regional traffic flow model to explore the stable traffic flow changing to the instable state, as to provide a theoretical basis for traffic flow manage and control in disaster-affected areas, and to prevent the traffic flow being caught into disorder and congestion. Based on VISSIM simulator data by building simulation scenarios with and without sudden fire disaster in a Sudoku traffic network, the catastrophe border is identified as 439pcu/lane/h, 529pcu/lane/h, 377pcu/lane/h at 5s, 10s, 15s data collection interval respectively. The corresponding relative precision, which compares to the method of Capacity Assessment Approach (CAA), is 89.1%, 92.7% and 76.5% respectively. It means that 10s data collection interval would be the suitable data collection interval in catastrophe border identification and regional traffic flow control in high-density area under sudden fire disaster.

High temperature titanium alloys are widely used in aerospace hot parts, however, the thermal barrier temperature of 600 oC limits its service temperature. In this paper, a two-step hot-dip plating method is proposed to prepare the composite coating containing Ce on the surface of titanium alloy, which can make the oxidation resistance temperature of titanium alloy reach 800 oC The microstructure, phase composition and element distribution of Ce-containing Ti-Al-Si hot-dip coating, Ce-containing Ti-Al-Si pre-oxidation coating and Ce-containing Ti-Al-Si high-temperature oxidation coating were studied by X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS), respectively. The results show that the Ti-Al-Si hot-dip coating containing Ce is mainly composed of (Ti,Ce)(Al,Si)3 alloy phase layer, and the Ti-Al-Si pre-oxidation coating containing Ce is mainly composed of Ti-Al binary system phase layer and dense Al2O3 layer rich in CeO2. Ce in the high temperature oxidation coating of Ti-Al-Si containing Ce is mainly distributed in Ti3Al, TiAl, TiAl3+Ti5Si3 mixed phase layer and Al2O3. The addition of Ce can promote the formation of continuous Al2O3 layer, improve the uniformity of composite coating, prevent the spread of cracks, and improve the high temperature oxidation resistance of Ti-Al-Si coating.

Artificial Intelligence (AI) is a breakthrough technology that has been widely applied in many fields and its use in pharmacy is also gaining increasing attentions. Recently, ChatGPT, a newly developed virtual assistant and large language model, is showing strong ability in writing, which makes it a potential tool for review writing. Here in our study, we employ the public available ChatGPT and try to instruct it to generate a mini review on the topic of “lipid-based drug delivery systems” by conversation. Our results showed that ChatGPT can give reasonable outline for this topic and give seemingly sentences with concluding wording, which can give useful information to the readers. However, the accuracy and consistence of the review are not fully guaranteed and there is lack of reliable citations. Therefore, it is concluded that ChatGPT can only give general knowledge on the selected topic, but not capable of giving in-depth discussion. The generated review article can be a useful but occasionally unprecise electronic encyclopedia instead of rigorous scientific literature, which can give benefit for pharmaceutical education and interchange to some extent.

This study examined the tourism spatial distribution of nine cities in the Fujian province and assessed the impacts of COVID-19. The modified gravity model found that it was widely dispersed, with uneven and relatively independent tourism development in different cities. The social network analysis showed that tourism connections across cities were significantly reduced after the pandemic. The impacts of brand awareness and transport accessibility on spatial networks were positive in pre-pandemic but became negative during the pandemic. In contrast, tourist volume had negative impacts on spatial networks in pre-pandemic but had positive ones during the pandemic. Tourism resources and market performance had significantly positive impacts in the post-pandemic era. These findings provide advice on tourism recovery and destination management in coping with future critical events. It also contributes to the theoretical gravity framework in tourism and the research scope of the social networks analysis at the city level.

Changing mobility patterns combined with changes in the climate present challenges and opportunities for global health, requiring effective, relevant and humane policy responses. This study used data from a systematic literature review that examined the intersection between climate change, migration and health. The aim of the present study was to synthesize policy recommendations in the peer-reviewed literature, regarding this type of environmental migration with respect to health, to strengthen the evidence-base. Systematic searches were conducted in four academic databases (PubMed, Ovid Medline, Global Health and Scopus) and Google Scholar for empirical studies published between 1990 – 2020 that used any study design to investigate migration and health in the context of climate change. Studies underwent a two-stage protocol-based screening process and eligible studies were appraised for quality using a standardized mixed-methods tool. From the initial 2,425 hits, 68 articles were appraised for quality and included in the synthesis. Among the policy recommendations, six themes were discernible: (1) avoid the universal promotion of migration as an adaptive response to climate risk; (2) preserve cultural and social ties of mobile populations; (3) enable the participation of migrants in decision-making in sites of relocation and resettlement; (4) strengthen health systems and reduce barriers for migrant access to health care; (5) support and promote optimization of social determinants of migrant health; (6) integrate health into loss and damage assessments related to climate change. The results call for transformative policies that support the health and wellbeing of people engaging in, or affected by mobility responses, including those whose migration decisions and experiences are influenced by climate change, and to establish and develop inclusive migrant healthcare.

Yaw misalignment can make a wake steer, which is an effective method to increase the power of wind farms, but it also increases the fatigue load of the turbines. In this paper, the method of combining yaw misalignment and pitch control (CYMP) is proposed to investigate the potential to mitigate wake interference, the wind velocity distribution and turbulence distribution in the wake, as well as the power and load changes of the wind turbine are studied, focusing on power in-crement and fatigue damage reduction. Although some studies have found that the method of CYMP are beneficial to increase power generation and reduce fatigue loads, there are no papers that have made a detailed analysis of the effects of wake turbulence, wind speed distribution, power, especially fatigue damage under this control. Simulation tool FAST.Farm is used to model and analyze wind farms, obtain the variation details of wake and provide simulation data for calculating power and fatigue load. The pitch control brings bias to the CYMP optimization results was neglected, the case studies show that the method of CYMP can reduce the fatigue load by 10.29% and increase the total power by 1.7% compared with only wake steering. The Model Predictive Control collaborative method based on CYMP is proposed, which can increase power by more than 2% and reduce thrust by more than 4% under 10m/s turbulent wind.

Although the positive relationship between religion and environmental behavior is well-argued, empirical research about the relationship between religion and public pro-environmental behavior is relatively lacking. This paper aims to explore the group differences in the influence of religion on public pro-environmental behavior and the mediating role of environmental risk perception in religion and public pro-environmental behavior. Using the Chinese General Social Survey data in 2013 for empirical analysis, this study’s results show that there are group differences in the impact of religion on public pro-environmental behavior. Women with religious beliefs are more willing to engage in public pro-environmental behavior than those without religious beliefs. Religious believers over the age of 45 are more willing to participate in public pro-environmental behavior than those without religious beliefs. Political participants with religious beliefs are more willing to practice public pro-environmental behavior than those without religious beliefs. In addition, we found that environmental risk perception can act as partial mediation in religious and public pro-environmental behavior. In other words, religious beliefs are deeply embedded in local political and social culture. In order to correctly understand the relationship between religion and public pro-environmental behavior, it is necessary to consider religion in a specific cultural background.

The average working person can spend between 35-60 hours a week in the workplace, making it an influential place for mental well-being while also being a place for socio-economic contribution. Workplace incivility can diminish positive mental health outcomes and negatively impact work engagement through increased social anxiety. To investigate this, 118 working adults aged between 19 to 67 years old in Singapore were recruited for a survey comprising of demographics questions, the Workplace Incivility Scale, Brief DSM-5 Social Anxiety Disorder Severity Scale, Utrecht Work Engagement Scale-9 over the period of November 2022 to April 2023. Correlational, regression and mediation analysis showed workplace incivility scale scores to significantly pre-dict social anxiety after controlling for covariates, supporting our hypothesis that employees exposed to work-place incivility would have higher levels of social anxiety that mediated work engagement after controlling for age and gender. The findings here show workplace incivility to be a possible intervention target for social anx-iety to reduce negative impacts on work engagement in order to improve employee experience and retention for organizations.

The model internal year-to-year variability (hereafter, internal variability) is a significant source of uncertainty when estimating anthropogenic aerosol effective radiative forcing (ERF). In this study, we investigate the impact of internal variability using large ensemble simulations (600 years in total) with the same climate model under prescribed anthropogenic aerosol forcings. A comparison of the magnitudes (i.e., standard deviation, Std) of these influences confirms that internal variability has negligible impacts on the instantaneous radiative forcing (RF) diagnosed by double radiation calls but has considerable impacts on estimating ERF through rapid adjustments (ADJ). Approximately half of the model grids exhibit strong internal variability influence on ERF (Std > 5 W m−2). These strong internal variabilities lead to a 50% probability that 30-year linear change can reach 2 W m−2, and 10-year linear change can reach 4 W m−2. A 50-year simulation can provide a relatively stable annual mean map of ERF (ERF = ADJ + RF), but it fails for ADJ. The statistically significant areas in the annual mean maps of both ERF and ADJ from a 10-year simulation exhibit instability with evident chaotic features. These analyses contribute to the setup of comparative experiments and a more comprehensive understanding of the modeled anthropogenic aerosol ERF.

The Marchenko method is a data-driven way which makes it possible to calculate Green's functions from virtual points in the subsurface by the reflection data at the surface, only requiring a macro velocity model. This method requires collocated sources and receivers. However, in practice, subsampling of sources or receivers will cause gaps and distortions in the obtained focusing functions and Green's functions. To solve this problem, this paper proposes to integrate sparse inversion into the iterative Marchenko scheme. Specifically, we add sparsity constraints to the Marchenko equations and apply sparse inversion during the iterative process. Our work not only reduces the strict requirements on acquisition geometries, but also avoids the complexity and instability of direct inversion for Marchenko equations. This new method is applied to a two-dimensional numerical example with irregular sampled data. The result shows that it can effectively fill gaps of the obtained focusing functions and Green's functions in the Marchenko method.

These years have witnessed growing research on applying rheology in grinding and flotation treatment of finely disseminated ores. The slurry rheology has long been identified as the comprehensive effect of inter-particle interactions, including their aggregation (coagulation and flocculation) and dispersion states in slurry, which are more impactive under the fine-particle effect. In this regard, rheology has the potential to play a significant role in interpreting the flowing and deforming phenomenon of inter-particle aggregates, particle-bubble aggregates, and flotation froth. Though much attention has been paid to the rheological effect in industrial suspension, this has not been the case for mineral grinding and flotation for fine particles. The influential mechanism of rheology on the sub-processes of mineral processing has not been systemically concluded and revealed thoroughly, without which the underpinning mechanism for enhancing the processing efficiency has been difficult to discover. This paper reviews the current application and importance of rheology in the fine mineral processing, and the potential research direction in the field is proposed.

Crash prediction of the sharp horizontal curve segment (SHCS) of a freeway is an important tool in analyzing safety of SHCSs and in building a crash prediction model (CPM). The design and crash report data of 88 SHCSs from different institutions were surveyed and three negative binomial (NB) regression models and three generalized negative binomial (GNB) regression models were built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The study demonstrates the effective use of the GNB model in analyzing the interactive influence of explanatory variables and in predicting freeway basic segments. Traffic volume, highway horizontal radius, and curve length have been formulated as explanatory variables. Subsequently, we performed statistical analysis to determine the model parameters and conducted sensitivity analysis. Among the six models, the result of model 6, which considered interactive influence, is much better than those of the other models by fitting rules. We also compared the actual results from crashes of 88 SHCSs with those predicted by models 1, 3, and 6. Results demonstrate that model 6 is much more reasonable than models 1 and 3.

At present, in the field of aviation industry, titanium alloy is mainly used to manufacture parts such as compressor disc, blade and casing of aircraft engine. When working, titanium alloy parts produce high temperature due to high-speed running friction, which makes the high temperature oxidation resistance and friction resistance of titanium alloy greatly reduced. When their working environment contains salt, titanium alloys are subjected to thermal corrosion, which limits their wider practical applications. This paper introduce the aluminide coating and its preparation methods. The characteristics and functional mechanism of three functional coatings for service environment, such as high temperature resistant alumina-based coating, thermal corrosion resistant alumina-based coating and wear-resistant alumina-based coating are summarized. Finally, the development direction of composite coatings of titanium and titanium alloys for complex service environment is prospected.

Chicken infectious anemia (CIA) poses a significant threat to the chicken industry in China. De-spite its non-specific symptoms, the disease is often overlooked. This study aimed to conduct a comprehensive analysis of the etiology and pathology of CIA in Guangxi Province, China. Three strains of the chicken infectious anemia virus (CIAV) were isolated from liver samples of diseased 20-week-old chickens. The complete genomes of these strains were sequenced, and experiments on specific pathogen-free (SPF) chicks revealed that the GX21121 strain exhibited high virulence. Histopathological examination of the deceased chicks showed liver cell necrosis, fibrous-serous exudation, inflammatory cell infiltration, hemorrhage in liver tissues, as well as congestion in lung and renal tissues. Phylogenetic analysis of the genome revealed that the three strains had a close genetic relationship to the Heilongjiang wild-type (GenBank KY486144). The genetic evolu-tion of their VP1 genes indicated that all three CIAV isolates belonged to genotype IIIc. In sum-mary, this study demonstrated the genomic diversity of three CIAV strains in adult layer hens. The isolation and characterization of the GX21121 strain as a highly virulent isolate provide val-uable information for further investigations into the etiology, molecular epidemiology, and viral evolution of CIAV.

Water quality retrieval for small urban waterbodies by remote sensing get used to be difficult due to coarse spatial resolution of the remote sensing imagery. The recently launched Sentinel-2 produces imagery with a spatial resolution of 10 m. It provides an opportunity to solve the problem of retrieving water quality for small waterbodies. Additionally, many water management issues also require fine resolution of imagery, e.g. illegal discharge to an urban waterbody. Since illegal discharges are an important issue for urban water management, chemical oxygen demand (COD), total phosphorous (TP), and total nitrogen (TN) were chosen as the target parameters for water quality retrieval in this study. COD, TP and TN, however, are non-optically active parameters. There were limited studies in the past to retrieve these parameters in comparison with optically active parameters, e.g. Chlorophyll-A etc. This study compared three machine learning models, namely Random Forest (RF), Support Vector Regression (SVR), and Neural Networks (NN), to investigate the opportunity to retrieve the above non-optically active parameters. Results showed that R² of TP, TN, and COD by NN, RF and SVR were 0.94, 0.88, and 0.86, respectively. The performances of water quality retrieval for these non-optically active parameters were significantly improved by the optimized machine learning models. These models hence solved the problem to use remote sensing data to retrieve these non-optically active water quality parameters and provided a new monitoring strategy for small waterbodies. Water quality mapping obtained by Sentinel-2 imagery provided a full spatial coverage of the water quality characterization for the entire water surface. Compared with water samples collecting and testing, it greatly reduced labor cost, reagents cost, and waste treatment cost. It also may help identify illegal discharges to urban waterbodies. The method developed in this research provides a new practical and efficient water quality monitoring strategy in managing water with consideration of environmental sustainability.

Plastic materials have revolutionized modern life, particularly in the domain of food packaging, owing to their versatility, lightweight nature, and ease of processing. However, the environmental ramifications of non-degradable plastics have raised concerns. Polylactic acid (PLA), derived from renewable sources, presents a sustainable alternative due to its biodegradability and exceptional barrier, mechanical, and safety properties. Nevertheless, the high UV transmittance of PLA limits its use for photosensitive food and pharmaceutical packaging, where UV radiation can lead to nutritional loss and spoilage. Various methods have been explored to enhance the UV-blocking capabilities of PLA, including the integration of inorganic nanoparticles and surface coatings. Despite advancements, these approaches often compromise the inherent transparency of PLA. Incorporating large conjugated groups can maintain transparency but introduces additional challenges. This paper reviews modification methods to enhance PLA's UV-barrier properties and anticipates its expanded utility in food and drug packaging, promoting UV resistance and diversifying PLA's applications.

We found an important fact that the beam footprint line of Ping will intersect with the real water depth when the initial incidence angle is about 45°, and sound velocity error hardly has an effect on it. This is contrary to our previous experience that the soundings of the central beam of multi-beam bathymetric system (MBS) is the most accurate. Firstly, the influence of sound velocity errors on central beam and seafloor topography distortion was analyzed. Secondly, the process of proving this fact was given, and the topography correction method was proposed by compensating the sound velocity profile area (SVP area). Finally, we showed in the first simulation of four type errors in SVPs that this fact is verified. The topography correction method used in the second simulation to correct the topography distortion of the first simulation is also verified.

Hydrological connectivity plays a major role in solving water resource and eco-environmental problems. However, this phenomenon has not been afforded the attention it deserves. Detailed analysis of connectivity in river systems could provide considerable insight into structural and functional attributes of riverine landscapes. The current study used graph theory approach and associated connectivity indicators to explore the characteristics and evolution of river systems and hydrological connectivity in a large catchment (Poyang Lake, China). The results revealed that the structure of the river system tended to be complex during 1990-2020, characterized by a dynamic evolution of tributaries in certain northern areas. Both river density and complexity exhibited an increasing trend by up to 15%, with the change rate after 2000 approximately twice as high as that of the preceding period. Overall, human activities across the catchment are more likely to play a key role in leading to significant changes in the quantity, morphometric, and structure characteristics of the river system. Additionally, the functional connectivity analysis indicated that the index of connectivity (IC) in the downstream catchment is stronger than that of the upstream vegetation areas, suggesting a strong contribution to the runoff-sediment transport (r=0.6-0.7). This study highlights the spatial and temporal evolution of both the structural and functional connectivity in the large Poyang Lake catchment. The findings of this work will bene-fit future water resource management and applications by providing a strategy for protecting the surface hydrology and mass transport of large river basins under climate and land-use changes.

As a widely used plastic, the aging and degradation of polyethylene (PE) are inevitable problems, whether the goal is to prolong the life of PE products or address the issue of white pollution. Molecular simulation is a vital scientific tool in elucidating the mechanisms and processes of chemical reactions. To obtain the distribution and evolution process of PE's thermal oxidation products, this work employs the self-consistent charge density functional tight binding (SCC-DFTB) method to perform molecular simulations of the thermal oxidation of PE with different crystallinity and branched structures. We discovered that crystallinity does not affect the thermal oxidation mechanism of PE, but higher crystallinity makes PE more susceptible to cross-linking and carbon chain growth, reducing the degree of PE carbon chain breakage. The branched structure of PE results in differences in pore size between the carbon chains, with larger pores leading to a concentrated distribution of O2 and free radicals subsequently formed. The breakdown of PE is slowed down when free radicals are localized in low-density regions of the carbon chain. The specifics and mechanism of PE's thermal oxidation are clearly revealed in this paper, which is essential for understanding the process in-depth and for the development of anti-aging PE products.

Drug-target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited, failing to delve into the structural nuances of interactions. With increasingly accurate and accessible structure prediction of targets, we developed a novel deep learning model, named S2DTA, to accurately predict DTA by fusing sequence and structural knowledge of drugs, targets, and pockets using heterogeneous models based on graph and semantic networks. Experimental findings underscored that complex feature representations imparted negligible enhancements to the model’s performance. However, the integration of heterogeneous models demonstrably bolstered predictive accuracy. In comparison to three state-of-the-art methodologies, the supremacy of S2DTA became strikingly apparent. It showcased a noteworthy 25.2% reduction in Mean Absolute Error (MAE) and an impressive 20.1% decrease in Root Mean Square Error (RMSE). Furthermore, S2DTA exhibited substantial advancements in other pivotal metrics, including Pearson Correlation Coefficient (PCC), Spearman, Concordance Index (CI), and R2. These metrics experienced remarkable increments of at least 19.6%, 17.5%, 8.1%, and a remarkable 49.4%, respectively. Finally, we conducted interpretability analysis on the effectiveness of S2DTA by bidirectional self-attention mechanism, fully proving that S2DTA is a valuable and accurate tool for predicting DTA. For further exploration, the source data and code repository can be accessed at https://github.com/dldxzx/S2DTA.

Privacy and information insurance have consistently been a priority for the European Union lawmaker. This paper presents whether the NIS prevails in its underlying endeavors to remain the congruity among residents and companies. It distinguishes current difficulties that specific business structures may experience while conforming to the Regulation. The exploration traces certain reasons which could impede the opportune reception of the new lawful ideas inside the system of the organizations. The exploration incorporates what is unique about the NIS; how it overlaps with existing frameworks; and how security requirements in the GDPR influence the NIS Directive. This paper furnishes different point of views of experts with the aim of setting up an entire examination

Due to the lack of theoretical research on the amount of spatio-temporal information in the high-speed photography technologies, obtaining an optimized system with a best amount of spatio-temporal information remains a challenge, resulting in insufficient effective information and observation accuracy for ultrafast events. The paper presents an ultrafast raster imaging (URI) system with a large amount of spatio-temporal information based on the all-optical raster principle in single-shot. Specifically, we derive the optimal equation of spatial resolution and the expression for the maximum amount of spatio-temporal information that can achieve excellent performance for an URI system. It serves as a general guideline for getting a large amount of information design in the URI system. Compared to the existing URI systems, the advanced URI system exhibits an improvement of nearly 1 order of magnitude in the amount of spatio-temporal information, and more than twofold in spatial resolution. It shows a great potential for capturing intricate and non-repetitive ultrafast events on the femtosecond time scale.

This study aimed to identify miRNA editing sites during adipose tissue development in Ningxiang pigs and analyze their characteristics and functions. Based on the small RNA-seq data from subcutaneous adipose tissue samples of Ningxiang pigs at four stages (30, 90, 150 and 210 days), we constructed a developmental atlas of the miRNA editome in adipose tissue of Ningxiang pigs. The characteristics and functions of this editome were further explored through bioinformatics analysis. The findings revealed that a total of 505 miRNA editing sites were identified with C-to-U editing types being the most prevalent, followed by U-to-C, A-to-G and G-to-U. Importantly, these four types of miRNA editing exhibited a base preference. The number of editing sites showed obvious differences among age groups, with the highest occurrence of miRNA editing events observed at 90 days of age and the lowest at 150 days of age. In the miRNA seed region, a total of 9 miRNA editing sites were identified with significant differences in editing levels (P < 0.05), and located in ssc-miR-23a, ssc-miR-27a, ssc-miR-30b-5p, ssc-miR-15a, ssc-miR-497, ssc-miR-15b, and ssc-miR-425-5p, respectively. Target gene prediction and enrichment analysis revealed that the editing of miR-497 may potentially regulate fat deposition by inhibiting adipose synthesis via influencing target binding. These results provide new insights into the regulatory mechanism of pig fat deposition.

Mineral identification is an important part of geological analysis. Traditional identification methods rely on either the experiences of the appraisers or the various measuring instruments and the methods are either easily influenced by the experiences or need too much work. To solve the above problems, there have been studies using image recognition and intelligent algorithms to identify minerals. But the current studies can not identify many minerals, and the accuracy is low. To increase the number of identified mineral categories and the accuracy, we proposed the method that uses both the mineral images and the Mohs hardness in the deep neural networks to identify the minerals. The experimental results showed that the method can reach 94.0% Top-1 accuracy and 99.9% Top-5 accuracy for 28 common minerals. The model that combines image and Mohs hardness together can identify more minerals and increase the accuracy using less training data.

To obtain a cost-effective and high-performance composite material of polybutylene adipate-terephthalate (PBAT), for this study we selected microcrystalline cellulose, which is inexpensive and easily available, as the reinforcing medium. Hexadecyl trimethoxysilane (HDTMS) containing a long carbon chain was chosen to silanize the microcrystalline cellulose (MCC) to obtain silanized cellulose (SG). Three types of SGs with different degrees of silanization were obtained by controlling the reaction ratio. Characterization of these three types of SGs was conducted using FTIR, TEM, and water absorption analysis. Subsequently, PBAT/SG composites were prepared through a sol-gel method, and the effects of these three types of SGs on the thermal stability, compatibility, mechanical properties, and dynamic thermomechanical properties of PBAT were evaluated. Furthermore, the mechanism behind enhancing the mechanical properties of the composite was analyzed. The results demonstrated successful synthesis of SG. As the reaction ratio between HDTMS and MCC increased, the nanoparticle size increased, while the water absorption decreased significantly. After SG was added to the PBAT composites, the yield stress increased while maintaining good thermal stability. Both the SEM and DMA results indicated good compatibility of the PBAT/SG composites. Analysis of the mechanical properties revealed that the tensile strength initially increased and then decreased with increasing blending ratio for all three composites tested; among them, the PBAT/SG2 composites exhibit superior performance, with a maximum tensile strength reaching 22 MPa at an 85/15 blending ratio—nearly 30% higher than that of pure PBAT alone. The addition of SG significantly improved the strength of the PBAT, and we speculated as to the underlying mechanism involved. This study provides a new idea for the industrial-scale development of degradable polyesters with low cost and good mechanical properties.

In this work, an novel flow-electric field coupling configuration for enhanced Zn-Cd cementation was designed and utilized. A series of tests were conducted to explore the optimization of Zn-Cd cementation process and its mechanism.Firstly, the various characterisations of the cadmium sponge at different locations in the device were compared and it was concluded that the purity of the cadmium sponge was optimal from the anode surface. The generation and stripping of cadmium sponge was revealed for the first time by cross-sectional electron microscopy. The four stages of the apparent reaction in the system were analysed in relation to the pH, cadmium concentration and cadmium sponge flaking at each flow rate. It was proved that the separation of cadmium sponge mainly occurred in the third phase. Secondly, by comparing the morphology and specific surface area of cadmium sheep at different flow rates, the optimum flow field velocity was identified as 30 ml/s. Six flow field configurations were compared and preferred. The results demonstrate that the LCAH modulation results in a more sparse structure of the cadmium sponge, which is more easily exfoliated from the zinc anode surface by fluid impact. This was considered to be the most beneficial flow field configuration for improving the cadmium cementation rate and reducing the cost of the reaction. Further, the reaction steps of the system were analysed. The diffusion process under different flow field configurations was confirmed by calculations to follow first order kinetics. The diffusion coefficient of LACH proved to be the highest in the comparative tests and this result was also supported by the apparent experimental results.

Many types of banana (Musa spp.)—one of the most economically important horticultural crops—exist, and their ploidy (diploid, triploid, and tetraploid, usually) and genome types (containing A or/and B genome in most cases) differ. At present, observation and genome type detection are commonly used to identify banana germplasm resources. However, the former is tedious, while the latter cannot distinguish categories below genome types. It is therefore urgent that a simple and effective method for identifying banana germplasm resources is established. We sequenced and analyzed the ribosomal DNA internal transcribed spacer (ITS) sequences of 62 banana germplasm and found that the sequencing peaks, especially the 20 bp region near the 420 bp position (referred to as the “420 bp region”), exhibited relatively recognizable and repeatable polymorphism characteristics. Using the “420 bp region” as a marker, we were able to quickly distinguish bananas belonging to different genome type groups (comprising the AA, AB, AAA, ABB, AAB, ABBB, AAAB, and AAAA groups) or different subgroups in the same genome type group (for example, the Cavendish, Gros Michel, Red, Lakatan, and Ibota Bota subgroups in the AAA group; and the Pisang Raja, Plantain, Pome and Silk subgroups in the AAB group). Moreover, it appeared that Sanger sequencing of ITS could be used for identifying banana hybrid offspring. These results demonstrated that the banana ITS region contains rich genetic information that is useful for genotyping. In general, ITS sequencing simplifies the classification of banana germplasm resources and has potential application in several areas of Musa improvement.

Following the occurrence of a typhoon, quick damage assessment related to residents can facilitate quick dispatch of house repair and disaster insurance works. Employing a deep learning method, this study used aerial photos of the Chiba prefecture obtained following the Typhoon Faxai in 2019 to automatically detect and evaluate the roof damage. This study comprised three parts: training deep learning model, detecting the roof damage using trained model, and classifying the level of roof damage. The detection object comprised roof outline, blue tarps, and roof completely destroyed. The roofs were divided into three categories: roof without damage, roof with blue tarps and roof completely destroyed. the F value obtained using the proposed method was higher than those obtained using other methods. In addition, it can be further divided into 5 levels from level 0 to 4. Finally, the spatial distribution of the roof damage was analyzed using ArcGIS tools. The proposed method is expected to provide certain reference for the real-time detection of the roof damage after the occurrence of a typhoon.

Petri nets are a graphical notation for describing a class of discrete event dynamic systems whose behaviours are charaterised by concurrency, synchronisation, mutual exclusion and conflict. They have been used over the years for the modelling of various distributed systems applications. With the advent of pervasive systems and the Internet of Things, the Calculus of Context-aware Ambients (CCA) emerged as a suitable formal notation for analysing the behaviours of these systems. In this paper, we are interested in comparing the expressive power of Petri nets to that of CCA. That is, can the class of systems represented by Petri nets be modelled in CCA? To answer this question, an algorithm is proposed that maps any Petri net onto a CCA process. We show that a Petri net and its corresponding CCA process behave the same way through experiments. It follows that CCA is at least as expressive as Petri nets, i.e. any system that can be specified in Petri nets can also be specified in CCA. Moreover, tools developed for CCA can also be used to analyse Petri nets.

Aiming to investigate the impact of strategic knowledge disclosure on the continuous realization of digital innovation in enterprises, this study examines data from 168 listed companies across three high-tech industries in China from 2012 to 2021. By examining investor trust, consumer trust, worker trust, and rival trust as mediating variables within the market trust dimension, this research explores the impact mechanism of strategic knowledge disclosure on the sustainability of input and output in digital innovation. The findings reveal that strategic knowledge disclosure significantly promotes both input and output sustainability in digital innovation. Specifically, investor trust positively mediates the relationship between strategic knowledge disclosure and the sustainability of digital innovation input. Similarly, consumer trust and worker trust positively mediate the association between strategic knowledge disclosure and both input and output sustainability in digital innovation. However, it is important to note that rival trust negatively mediates the link between strategic knowledge disclosure and both input and output sustainability in digital innovation. The research findings possess significant theoretical value and provide valuable guidance for promoting the sustainable development of digital innovation in enterprises.

As one of the common techniques for measuring coseismic deformations, optical image correlation techniques are capable of overcoming the drawbacks of inadequate coherence and phase blurring which can occur in radar interferometry, as well as the problem of low spatial resolution in radar pixel offset tracking. However, the scales of the correlation window in optical image correlation techniques typically influence the results, the conventional SAR POT method faces a fundamental trade-off between the accuracy of matching and the preservation of details in the matching window size. This study regards co-seismic deformation as a two-dimensional vector, and develops a new post-processing workflow called VACI-OIC to reduce the dependence of shift estimation on the size of the matching window. This paper takes the coseismic deformations in both the east-west and north-south directions into account at the same time, treating them as vectors, while also considering the similarity of displacement between adjacent points on the surface. Herein, the angular continuity index of the coseismic deformation vector was proposed as a more reasonable constraint condition to fuse the deformation field results obtained by optical image correlation across different matching window. Taking the earthquake of 2021 in Maduo, China, as the study area, the deformation with the highest spatial resolution in the violent surface rupture area was determined (which could not be provided by SAR data). Compared to the results of single-scale optical correlation, the presented results were more uniform (i.e., more consistent with published results). At the same time, the proposed index also detected the strip fracture zone of the earthquake with impressive clarity.

Epilepsy is characterized by repeated spontaneous reactions caused by hyper-excitability and neurons firing in high synchronization in the central nervous system. It seriously affects the quality of life of epileptic patients and nearly 30% of individuals are refractory to treatment of antiepileptic drugs. Therefore, there is an urgent need to develop new medicines to manage and control the refractory epilepsy. Cannabinoid ligands including selective cannabinoid receptor subtype (CB1 or CB2 receptor) ligands and non-selective cannabinoid (synthetic and endogenous) ligands may serve as the novel candidates for this need. Cannabinoid systems appear to regulating seizure activity in the brain through the activation of CB1 and CB2 cannabinoid receptors (CB1R and CB2R). An abundant series of cannabinoid analogues have been tested in various animal models, including a rat pilocarpine model of acquired epilepsy, in vitro hippocampal neuronal culture models of acquired epilepsy and status epilepticus, a pentylenetetrazole model of myoclonic seizures in mice and a penicillin-induced model of epileptiform activity in the rats. The accumulating lines of evidence show that cannabinoid ligands exhibit significant benefits to control seizure activity in different epileptic models. For this reason, we summarize the relationship between brain CB2 receptors and seizures, and emphasize the potential mechanisms of their therapeutic effects involving affecting neurons, astrocytes, and microglia cells. The unique features of CB2Rs, such as lower expression levels under physiological conditions and high inducibility under epileptic conditions, make it an important target for future research on drug-resistant epilepsy.

Hand and arm gesture recognition using radio frequency (RF) sensing modality proves valuable in man-machine interface and smart environment. In this paper, we use time series analysis method for accurately measuring the similarity of the micro-Doppler (MD) signatures between the training and test data, thus providing improved gesture classification. We characterize the MD signatures by the maximum instantaneous Doppler frequencies depicted in the spectrograms. In particular, we apply the dynamic time warping (DTW) method and compare its performance with that of the long short-term memory (LSTM) network. Both methods take into account the values as well as the temporal evolution and trends of time series data. It is shown that the DTW method achieves high gesture classification rates and is robust to time misalignment.

List-only entity linking is the task of mapping ambiguous mentions in texts to target entities in a group of entity lists. Different from traditional entity linking task, which leverages rich semantic relatedness in knowledge bases to improve linking accuracy, list-only entity linking can merely take advantage of co-occurrences information in entity lists. State-of-the-art work utilizes co-occurrences information to enrich entity descriptions, which are further used to calculate local compatibility between mentions and entities to determine results. Nonetheless, entity coherence is also deemed to play an important part in entity linking, which is yet currently neglected. In this work, in addition to local compatibility, we take into account global coherence among entities. Specifically, we propose to harness co-occurrences in entity lists for mining both explicit and implicit entity relations. The relations are then integrated into an entity graph, on which Personalized PageRank is incorporated to compute entity coherence. The final results are derived by combining local mention-entity similarity and global entity coherence. The experimental studies validate the superiority of our method. Our proposal not only improves the performance of list-only entity linking, but also opens up the bridge between list-only entity linking and conventional entity linking solutions.

The analysis of high-temperature physicochemical properties of theK₃AlF₆-Na₃AlF₆-AlF₃ molten salt system is crucial for practical production of electrolytic aluminum. In this paper, the physicochemical properties of the K₃AlF₆-Na₃AlF₆-AlF₃ molten salt electrolyte system at 1173 K and standard atmospheric pressure were simulated using molecular dynamics calculations. The effects of Zr、B、C、W、Ti、Hf、Nb、and Ta on the radial distribution function, coordination number, viscosity and conductivity of the electrolyte system are discussed in detail. The simulation results show that the coordination number between Al-F and the conductivity is decreasing as the content of B²- increases. And the coordination number between Al-F and the viscosity is decreasing as the content of Zr⁴⁺ increases. With the addition of impurity elements such as C, W, Ti, Hf, Nb, and Ta, the data show that C has no significant effect on this electrolyte system, while the presence of W will decrease the coordination number between Al-F in the system. The presence of Ti, Hf, Nb, and Ta may intensify the decomposition reaction between one of the Al-F ligands, which increases the coordination number between Al-F and the number of ions in the electrolyte. This work provides theoretical support for the subsequent study of inert anodes containing Zr, B, Ti, Hf, Nb, and Ta.

Wearable touch sensors, which can convert force or pressure signals into quantitative electronic signals, have emerged as an essential smart sensing devices and played an important role in various cutting-edge fields, including wearable health monitoring, soft robots, electronic skin, artificial prosthetics, AR/VR, and the Internet of Things. Flexible touch sensors have made significant advancements, while construction of novel touch sensors via mimicking the unique properties of biological materials and biogenetic structures always remains a hot research topic and significant technological pathway. This review provides a comprehensive summary of the research status of wearable touch sensors constructed by imitating the material and structural characteristics in nature, and also summarizes the scientific challenges and development tendency of this aspect. Firstly, the research status for constructing flexible touch sensors based on biomimetic materials is summarized, including hydrogel materials, self-healing materials, and other bioinspired or biomimetic materials with extraordinary properties. Then, design and fabrication of flexible touch sensors based on bionic structures for performance enhancement are fully discussed. These bionic structures include special structures in plants, special structures insects/animal, and special structures in human body. Moreover, a summary of the current issues and future prospects for developing wearable sensors based on bioinspired materials and structures is discussed.

This research focussed on utilisation of salmon protein and lipid to manipulate pasta glycaemic index and protein digestibility. Salmon fish (Oncorhynchus tschawytscha) powder (SFP) supplemented pasta flour at the from 5% to 20% (w/w). Inclusion of SFP lead to a significant reduction in starch digestibility and hence the potential glycaemic values of pasta (experimental pasta being up to 143% lower than control values). SFP addition to pasta increased the release of phenolic compounds from pasta during both a gastric digestion (179%) and pancreatic digestion ( 133%) in comparison to the control sample. At the same time, the antioxidant activity of the digested pasta was increased by up to 263% (gastric) and 190% (pancreatic) in comparison to durum wheat pasta alone. Interestingly, although protein levels increased with incorporation of SFP, the digestibility values of the protein decreased from 86.41% for the control pasta to 81.95% for 20% SFP pasta. This may indicate that there are interactions between phenolic and protein in the pasta samples which affect overall protein digestibility levels.

Here, we present a series of novel block copolymers (BCP) from bio-derived monomers, poly(lactic acid)-block-poly(2,5-furandimethylene succinate) (PLA-b-PFS), in which the furan groups from PFS block can be crosslinked with bis(maleimido) triethylene glycol (M2) through a Diels-Alder reaction. This dynamic crosslinking reaction leads to a network structure for enhancing the mechanical properties compared to their linear BCP analogous. Decreasing the crosslinking density leads to a decrease of glass transition temperature of BCPs and a transition from glassy to rubbery-like behavior at room temperature. This allows a wide tunablity of both elastic moduli and yields of the materials. For the lowest crosslinking density. the material exhibits an over 50% self-healing efficiency at room temperature after five days, attributed to the low Tg (15.2 C) from the introduction of PFS block, allowing sufficient chain mobility for structure re-organization. Moreover, with the appropriate selection of crosslinking density (PLA-b-PFS/M2 (6/1)), it also shows an excellent shape memory property with a high recovery rate of 96.3% and a fixity rate of 97.3%. The permanent shape can be rewriteable due to the reversibility of Diels-Alder reaction. With these advanced functionalities and ease in large-scale fabrication, the PLA-b-PFS/M2 shows great promises for self-healing coatings or films with shape memory properties in a wide variety of applications such as packaging materials

The deployment of a manufacturing execution system (MES) holds promising potential in facilitating the accumulation of a substantial amount of inspection data. Low quality levels in discrete manufacturing environments are the result of multi-factor coupling and failure to find quality issues in a timely manner within manufacturing settings may trigger the propagation of defects downstream. Currently, most of the inspection quality methods are direct measurement followed by manual judgment. The integration of deep learning methods provides a feasible way to identify defects in a timely manner, thus improving the acceptance rate of factories. This paper focuses on the design of a data-driven quality prediction and control model around discrete manufacturing characteristics, and use fuzzy theory to evaluate the quality level of production stages. Building Multivariate Long and short-term memory learning hidden quality representations to extract predictions from multi-level inspection data in manufacturing systems. Finally, by validating the data of actual produced water dispensers according to three evaluation indexes, RMSE, MAE, MAPE, the results show that Multivariate Long and short-term memory has better prediction performance.

Connected and Autonomous Vehicle (CAV) combines technologies of autonomous vehicle (AV) and connected vehicles (CV) to develop quicker, more reliable and safer traffic. Artificial Intelligence (AI) based CAV solutions play significant roles in sustainable city. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on driver; increased connectivity increases the exposures of vehicles vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles vulnerabilities to negatively impact the performance and operations of CAV. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAV, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAV is elaborated from both viewpoints of intra-vehicle system and inter-vehicle system. We pointed out that securing the perception and operations of CAV would be the top requirement to enable CAV to be applied safely and reliably in practice. Also, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAV.

The exploitation of bio-based foams implies an increase in the use of renewable biological resources to reduce the rapid consumption of petroleum-derived resources. Both tannins and furfuryl alcohol are derived from forestry resources and are therefore considered as attractive precursors for the preparation of tannin-furanic foams. In addition, toughening modification of tannin-furanic foams using polyvinyl alcohol (PVOH) resulted in a more flexible network-like structure, which imparts excellent flexibility to the foams with acquirement of relative properties that are even close to those of polyurethane foams, which are the most used polymers for fabrication of insoles for athletes. In addition, the addition of PVOH did not affect the thermal insulation of the foams, resilience and elongation at break, while reducing the brittleness of the samples and improving the mechanical properties. Also the observation of the morphology of the foam indicated that the compatibility between PVOH and tannin-furanic resin is good, and the cured foam does not show fragmentation or collapse, while the bubble pore structure is uniform. The developed flexible foam derived from biomass resources endowed the foam good thermal insulation properties and high mechanical properties, and the samples exhibited suitable physical parameters to be used as flexible insoles for athletes.

Urban vitality is an important reflection of a city's development potential and urban quality. This study uses exploratory spatio-temporal big data such as social media check-ins to portray the spatio-temporal evolution of urban vitality at the subdistrict scale in Changsha, a city in central China, from 2013-2021, and finds that urban vitality in Changsha exhibits central agglomeration and outward circling expansion over time; and then use Geodetector and spatial regression analyses are used to explain the interactive effects and spatio-temporal heterogeneity of the spa-tial elements of subdistrict form, subdistrict function and subdistrict economy on urban vi-tality. The results show the following: (1) The subdistrict form and subdistrict function dimen-sions have a significant effect on urban vitality, and the effect of the economic dimension of the subdistrict is not significant. (2) The interaction effect of the density of entertainment and leisure facilities and the density of business office facilities in subdistrict function is the dominant factor in the change of urban vitality. (3) Under the spatio-temporal effect, land use diversity and park facility density have the strongest positive effect on urban vitality; road density and shopping facility density have the weakest effect. The study aims to provide a reference for the optimization and allocation of spatial elements of subdistricts in sustainable urban development and urban renewal, to achieve the purpose of urban vitality creation and enhancement.

Based on the analysis of the spatial distribution of uranium grade in 348 boreholes of a uranium deposit in Xinjiang, the enrichment and spatial variation of uranium ore in two stopes of the deposit are discussed by using multifractal theory. The distribution characteristics of uranium ore of the two stopes are studied by multifractal parameters: the scaling exponent of mass , the scaling exponent of each sub-set and its corresponding fractal dimension , the fractal dimension D0 and information dimension D1. The differences of uranium distribution in two stopes can be well quantified by multifractal spectrum and multifractal parameters( , , ).10m×10m is defined as a fence unit, and the window sizes are respectively set, the singularity exponent of the two stopes are calculated by this element concentration-area(C-A) method. The results show that the multifractal theory and model can organically combine spatial structure information, scale change information and anisotropy information to obtain low-grade and weak mineral resources information, and can effectively distinguish complex and superimposed anomalies. This will provide a basis for local concentration and spatial variation rules of uranium distribution and the design of the parameters of leaching uranium mining well site.

The study's motivation is to gauge the nexus between economic policy uncertainty and financial innovation for the period 2004M1 to 2018M12 in BRIC nations. For establishing a long-run cointegration study applied Autoregressive Distributed Lagged (ARDL) and asymmetry effects of economic policy uncertainty investigated following nonlinear framework known as NARDL. Furthermore, directional causality is established by performing a non-granger causality test. Cointegration test results of Fpss, Wpss, and tBDM confirmed the long-run association between EPU and financial innovation. On the other hand, the Wald test results proved asymmetry effects furring from EPU to financial innovation both in the long-run and short-run. Referring to asymmetry effects that positive and negative shocks in financial innovation, the study revealed that negative linkage between shocks in EPU and financial innovation in the long-run but short-run effects are insignificant. Furthermore, financial innovation measured by R&D investment exhibits positive linked with shocks in EPU, implying that uncertainty induces innovation in the economy. Refers to directional causality estimation, the study revealed evidence supporting the feedback hypothesis between EPU and financial innovation in all sample countries.

SETD7 is a member of the SET domain-containing lysine methyltransferase family and is a crucial component in the development and spread of a number of human cancers. However, the specific function of the SETD7 gene in ovarian cancer (OC) is still unclear. The purpose of this research was to elucidate the expression and role of SETD7 in OC. In comparison to normal controls, OC tissues (83%, 73/88) and cell lines exhibited higher protein levels of SETD7 (p < 0.001). High SETD7 protein levels were substantially correlated with M category (p = 0.019) and FIGO stage (p = 0.021). Furthermore, the high mRNA levels of SETD7 were correlated to poor progression-free survival (PFS) in all patients and serous patients with OC (p < 0.05). Importantly, the biological function experiments showed that SETD7 behaved as an oncogene in OC by dramatically facilitating the proliferation and migration of A2780 and SKOV3 cells. Additionally, SETD7 might promote cell migration via accelerating the EMT process in A2780 and SKOV3 cells. Our findings reveal that SETD7 may be a valuable molecular marker for identifying and anticipating the development of OC.

In this study, we investigate the magnetization behavior of coaxial nanowires fabricated through the sol-gel electrospinning method. Our analysis uncovers a significant reduction in coercivity for CoFe2O4 nanowires when BaTiO3 is used as the shell material, effectively transforming them from hard to soft magnetic. This intriguing behavior is attributed to the magnetization reversal effect at the interface between ferromagnetic and paramagnetic regions, and it is also observed in NiFe2O4 and Fe2O3 nanowires. Surprisingly, introducing a GdBa2Cu3O7 shell induces a similar effect. Additionally, we employ magnetic impedance measurements on the coaxial nanowires, unveiling their potential for magnetic field sensing applications.

In the pursuit of China’s dual carbon goals, identifying spatio-temporal changes in industrial carbon emission efficiency and their influencing factors in cities at different stages of development is the key to effective formulation of countermeasures to promote the low-carbon transformation of Chinese national industry and achieve high-quality economic development. In this study, we used balanced panel data of 270 Chinese cities from 2005 to 2020 as a research object: (1) to show spatio-temporal evolution patterns in urban industrial carbon emission efficiency; (2) to analyze the aggregation characteristics of industrial carbon emission efficiency in Chinese cities using Global Moran's I statistics; and (3) to use the hierarchical regression model for panel data to assess the non-linear impact of the digital economy on the industrial carbon emission efficiency of cities. The results show the following: (1) the industrial carbon emission efficiency of Chinese cities exhibited an upward trend from 2005 to 2020, with a spatial distribution pattern of high in the south and low in the north; (2) China's urban industrial carbon emission efficiency is characterized by significant spatial autocorrelation, with increasing and stabilizing correlation, and a relatively fixed pattern of spatial agglomeration; (3) there is a significant inverted-U-shaped relationship between the digital economy and the industrial carbon emission efficiency of cities. The digital economy increases carbon emissions and inhibits industrial carbon-emission efficiency in the early stages of development, but inhibits carbon emissions and promotes industrial carbon emission efficiency in mature developmental stages. Therefore, cities at all levels should reduce pollution and carbon emissions from high-energy-consuming and high-polluting enterprises, gradually reduce carbon-intensive industries, and accelerate the digital transformation and upgrading of enterprises. Western, central and eastern regions especially should seek to promote the sharing of innovation resources, strengthen exchanges and interactions relating to scientific and technological innovation, and jointly explore coordinated development routes for the digital economy.

The heritage of ancient buildings is an important part of the world's history and culture, which has an extremely rich historical-cultural value and artistic research value. Beijing has a large number of palace ancient buildings, and because of the age of their construction, many of them have problems of varying degrees of peeling and mold on the inner surfaces of the envelope. To solve the problems of the damp and moldy interior of palace buildings, a mathematical model of indoor heat and moisture transfer was established based on a wooden palace ancient building in Beijing. Through the indoor mold distribution validation model, the effects of outdoor humidity, soil moisture, wall humidity, and other factors on the indoor heat and moisture transfer of ancient buildings were simulated and analyzed by using the control variables method. The results showed that the molds were distributed at the indoor corners and floors, and the simulation of indoor humidity match the measured humidity. Thus, the simulation results were consistent with the actual situation. The variable trend of the relative humidity of the indoor environment with the outdoor humidity is inconsistent from plane to plane, i.e. it increases or remains constant with the increase of the outdoor humidity. The indoor ambient relative humidity increased with increasing the wall humidity. And the indoor average temperature is 23.3 ℃ and indoor relative humidity ranged between 90.9 % to 92.44 %. Soil moisture and wall humidity were the main factors affecting the indoor environmental relative humidity.

The promotion of plant growth and suppression of plant disease using beneficial microorganisms is considered an alternative to the application of chemical fertilizers or pesticides in the field. In this study, a coconut-scented antagonistic Trichoderma strain LZ42, previously isolated from Genoderma lucidum-cultivated soil, was investigated for biostimulatory and biocontrol functions in tomato seedlings. Morphological and phylogenetic analyses suggested that strain LZ42 is closely related to T. atroviride. Tomato plants showed increased aerial and root dry weights in greenhouse trials after treatment with T. atroviride LZ42 formulated in talc, indicating the biostimulatory function of this fungus. T. atroviride LZ42 effectively suppressed Fusarium wilt disease in tomato seedlings, with an 82.69% control efficiency, which is similar to that of fungicide treatment. The volatile organic compounds (VOCs) emitted by T. atroviride LZ42 were found to affect the primary root growth direction and promote the root growth of tomato seedlings in root Y-tube olfactometer assays. The fungal VOCs from T. atroviride LZ42 were observed to significantly inhibit F. oxysporum in a sandwiched Petri dish assay. SPME-GC-MS analysis revealed several VOCs emitted by T. atroviride LZ42; the dominant compound was tentatively identified as 6-pentyl-2H-pyran-2-one (6-PP). 6-PP exhibited a stronger ability to influence the direction of the primary roots of tomato seedlings but not the length of the primary roots. The inhibitory effect of 6-PP on F. oxysporum was the highest among the tested pure VOCs, showing a 50% effective concentration (EC50) of 5.76 μL mL-1 headspace. In conclusion, T. atroviride LZ42, which emits VOCs with multiple functions, is a promising agent for the biostimulation of vegetable plants and integrated management of Fusarium wilt disease.

Uridine diphosphate (UDP)-glycosyltransferases (UGTs) are major phase II detoxification enzymes involved in glycosylation of lipophilic endobiotics and xenobiotics, including phytoalexins. Nicotine, one of the most abundant secondary plant metabolites, is highly toxic to herbivorous insects. Plant-herbivore competition has been the major impetus for evolution of large superfamilies of UGTs and other detoxification enzymes. However, UGT functions in Myzus persicae adaptation have remained unknown. In this study, UGT inhibitors (sulfinpyrazone and 5-nitrouracil) significantly increased nicotine toxicity in M. persicae nicotianae, suggesting UGTs may be involved in nicotine tolerance. One hundred one UGT transcripts identified from the M. persicae genome/transcriptome were renamed according to UGT Nomenclature Committee guidelines and clustered into 11 families: UGT329, UGT330, UGT339, UGT341-UGT345, and UGT348-UGT350. UGT344 contained the most UGTs (fifty-seven). Ten UGTs (UGT330A3, UGT339A2, UGT341A6, UGT342B3, UGT343C3, UGT344D5, UGT344D8, UGT348A3, UGT349A3 and UGT350A3) were overexpressed in M. persicae nicotianae compared with M. persicae sensu stricto. UGT330A3/UGT344D5/UGT348A3/UGT349A3 knockdown significantly increased M. persicae nicotianae nicotine sensitivity, suggesting UGT upregulation in this subspecies may be associated with nicotine tolerance and thus host adaptation. This study reveals possible UGTs relevant to nicotine adaptation in tobacco-consuming M. persicae nicotianae and might facilitate further validation of the roles of these UGTs in nicotine tolerance.

Europium (Eu)-doped fluorapatite (FA) nanorods has a similar biocompatibility with hydroxyapatite (HA) in terms, attracted much attention as cell imaging biomaterials due to their luminescent property. Here, we will discuss the new feature of europium doped fluorapatite (Eu-FA) nanorods as anticancer drug carrier. Eu-FA nanorods was prepared using a hydrothermal method. The morphology, crystal structure, fluorescence and composition are investigated. The specific crystal structure, enabling an effective loading of drug molecules. Doxorubicin (DOX), used as an anticancer model drug, was shown to be effectively loaded onto the surface of the nanorods. The DOX release was fairly pH-dependent, occurring more rapidly at pH 5.5 than pH 7.4 was observed. The intracellular penetration of the DOX-loaded Eu-FA nanorods (Eu-FA/DOX) can be imaged in situ due to the self-fluorescence property. Treatment of melanoma A375 cells with Eu-FA/DOX elicited a more effective apoptosis rate than direct DOX treatment. Overall, Eu-FA show great promise for tracking and treating tumor, may potentially useful as a multifunctional carrier system to effectively load and sustainably deliver drugs.

This study examines the potential of UiO-66 and g-C3N4-based composite catalysts for environmental purification and pesticide degradation. By integrating zirconium-based metal-organic framework UiO-66 with graphitic carbon nitride (g-C3N4), a composite with a Z-type heterojunction structure is created, enhancing photocatalytic pesticide degradation and phosphorus recovery. The optimal composite, UiO-66/g-C3N4(UG6:4), shows high efficiency in degrading organophosphorus pesticides like DDVP under visible light. This catalyst's high surface area and porous nature efficiently adsorb and break down persistent soil pollutants, including DDT and DDVP. Featuring robust stability and effective photocatalytic activity, the UiO-66/g-C3N4 composite holds promise for soil remediation and dealing with organic pollutants. Future research will aim to further refine this material’s structure and properties, ensuring its practical application in environmental cleanup.

Brugada syndrome (BrS) is an inherited disease characterized by right precordial ST-segment elevation on electrocardiograms (ECGs), and a high risk of life-threatening ventricular arrhyth-mia and sudden cardiac death. In BrS patients, except for SCN5A, mutations in other responsible genes are poorly elucidated. We identified a new missense mutation, c.1189C>T (p.R397C), in the KCNH2 gene in asymptomatic male proband with diagnosed BrS. We performed patch-clamp analysis on I(Kr) reconstituted with this KCNH2 mutation in Chinese hamster ovary cells and compared the phenotype with the wild type. We found that the R397C mutation increased the I(Kr) density. In silico modeling demonstrated that this missense mutation potentially leads to the shortening of action potential in the heart.

Lunar grabens are the largest tensional linear structures on the Moon. In this paper, 17 grabens were selected to investigate the dips and displacement-length ratios (γ) of graben-bounding faults. Several topographic profiles were generated from selected grabens to measure their rim elevation, width and depth through SLDEM2015 (+LOLA) data. The differences in rim elevation (∆h) and width (∆W) between two topographic profiles on each graben were calculated, yielding 146 sets of data. We plotted ∆h versus ∆W for each and calculated the dip angle (α) of graben-bounding faults. A dip of 39.9° was obtained using the standard linear regression method. In order to improve accuracy, large error data was removed based on error analysis. The results 49.4° and 52.5° were derived by the standard linear regression and mean methods, respectively. Based on the depth and length of grabens, the γ value of the graben-bounding normal fault is also studied in this paper. The γ value is 3.6×10-3 for lunar normal faults according to the study of grabens and the Rupes Recta normal fault. After obtaining the values of α and γ, the increase in lunar radius caused by the formation of grabens was estimated. We suggest that the lunar radius has increased by around 130 m owing to the formation of grabens. This study could aid in the understanding of normal fault growth and provide important constraints on the thermal evolution of the Moon.

In this study, the generality and prediction accuracy of a generalised series model for large eddy simulation of premixed and non-premixed turbulent combustion is explored. The model is based on Taylor series expansion of the chemical source term in scalar space and implemented into OpenFOAM. The mathematical model does not depend on the combustion regimes, and has the correct limiting behaviour. The numerical error sources are outlined and analysed. The model is first applied to a piloted methane/air non-premixed jet flame (Sandia Flame D). The statistical (time-averaged and RMS) results agree well with experimental measurements, particularly with regard to the mixture fraction, velocity, temperature, and concentrations of major species CH4, CO2, H2O, and O2. The concentrations of intermediates CO and H2 are over-predicted, due to the limitations of the reduced reaction mechanism employed. Then, a Bunsen piloted flame is simulated. Most of the statistical properties of both reactive species and progress variable are well reproduced. The only major discrepancy evident is in the temperature, which is attributed to the experimental uncertainties of temperature fields in the pilot stream. These findings have demonstrated the model`s generality for both premixed and non-premixed combustion simulation, as well as the accuracy of prediction of reactive species distribution.

This study aimed to evaluate the effects of a palygorskite-based antibacterial agent (PAA) as an alternative to antibiotics on growth performance, blood parameters, rumen fermentation, and rumen microbiota in sheep. A total of 120 sheep were randomly divided into five groups of six replicates with four sheep each. Sheep were fed a basal diet, an antibiotic diet supplemented with 500 g/t chlortetracycline (CTC), and a basal diet supplemented with 500, 1,000, and 2,000 g/t PAA for 80 d, respectively. Supplementation with 2,000 g/t PAA and 500 g/t CTC increased the average daily gain (ADG) of sheep compared with the control group (P < 0.05). Diets supplemented with 2,000 g/t PAA and 500 g/t CTC reduced (P < 0.05) the feed: gain (F/G ratio) in the overall periods. Dietary Supplementation with 1,000 g/t PAA significantly increased albumin and total protein (P < 0.05). A significant positive correlation was found between growth hormone concentration and PAA supplementation (P < 0.05). In addition, compared to the control group, the CTC group had higher growth hormone concentration and lower lipopolysaccharide concentration (P < 0.05). No dif-ference was observed between the five groups in terms of rumen fermentation characteristics (P > 0.05). At the phylum level, the relative abundance of Proteobacteria was lower in the PAA 2000 and CTC 500 groups than that in the control and PAA 500 groups (P < 0.05). At the genus level, a sig-nificant decrease (P < 0.05) in the relative abundance of RuminococcaceaeUCG-010 was observed in the PAA 1000, PAA 2000, and CTC 500 groups compared with that in the control group. In addition, the relative abundance of Prevotella1 (P < 0.05) was higher in the PAA 2000 group than that in the control group. These findings indicate that dietary supplementation with PAA has ameliorative effects on growth performance, blood parameters, and rumen microbiota, with an optimal dosage of 2,000 g/t for sheep.

Hippophae is a tree species with ecological, economic and social benefits. In this study, we assembled and annotated chloroplast genomes of sympatric Hippophae gyantsensis and H. rhamnoides subsp. yunnanensis. Their full-length are 155260 and 156415 bp, respectively. Each of them has 131 genes, comprising 85 protein-coding genes, 8 ribosomal RNA genes and 38 transfer RNA genes. After comparing the chloroplast genomes, we found 1302 base difference loci, and 63.29% are located in the intergenic region or intron sequences and 36.71% are located in the coding sequences. The SSC region has the highest mutation rate, followed by the LSC region; the IR regions have the lowest mutation rate. Among the protein-coding genes, three had a ratio of nonsynonymous to synonymous substitutions (Ka/Ks) >1 (but P values were non-significant) and 66 had Ka/Ks <1 (46 were significant). In general, the chloroplast protein-coding genes may be subject to purification selection. Among H. gyantsensis and H. rhamnoides subsp. yunnanensis chloroplast protein-coding genes, there are 20 and 16 optimal codons, respectively. Most of the optimal codons were ending with A or U, which indicates significant AT preference. It is an important reference for studies on the general characteristics and evolution of the Hippophae chloroplast genome.

In order to investigate the relationship between government policy, the service and design of rural crowdsourcing spaces, the self-efficacy of returning youth, and the innovation performance of businesses, this study focuses on gathering data by distributing questionnaires to returning youth in rural crowdsourcing spaces and developing a structural model. The results demonstrate how important government policies are in encouraging youth entrepreneurship in their local communities. It has the potential to enhance both the development of rural crowdsourcing spaces and the self-efficacy of young entrepreneurs, thereby enhancing the innovative capabilities of local entrepreneurial businesses. Therefore, in order to encourage economic development in rural areas, the government should improve pertinent support measures.

Flexible capacity applications demands to large energy storage density and high breakdown electric field strength of flexible films. Here, P(VDF-HFP) with ultra-thin Al2O3 nanosheets composite films were designed and fabricated through an electrospinning process followed by hot-pressing in sandwich structured. The results show that the insulating ultra-thin Al2O3 nanosheets and the sandwich structure can enhance the composites' breakdown field (by 24.8%) and energy density (by 30.6%) remarkedly to P(VDF-HFP) polymer matrix. An energy density of 23.5 J/cm3 at the ultrahigh breakdown field of 740kV/mm can be therefore realized. Insulating test and phase-field simulation results reveal that ultra-thin nanosheets insulating buffer layers can reduce the leakage current in composites, thus it effects the electric field spatial distribution to enhance breakdown strength. Our research provides a feasible method to increase the breakdown strength of ferroelectric polymers, which is comparable to those of non-ferroelectric polymers.

Chinese investors are easily affected by hot topics on the media and Internet and likely take irrational behavior. They tend to consume rationally and invest emotionally. This research aims to analyze the Baidu index’s effect on share price of solar power industry in China. Three main models are established to identify the correlation between Baidu index and stock price of solar industry. The media index and searching index of Baidu are chosen as an independent variable to measure the influence from media and Internet, and stock price as the dependent variable. To improve and complete the analysis, Hexun index is taken into consideration as mediator variable. This study applied Multiple Linear Regression Model and VAR (Vector auto-regression) Model. The research mainly uses the tools of SPSS, Eviews and Excel to conduct data analysis. The test is based on the theories of Granger Causality, unit root test, F-test, and t-test. The research proves the relationship between the close price of stock and Baidu index, and it also created a model for further forecasting.

This study aimed to overcome the difficulty of conducting the horizontal-well cavity leaching test in the field and to investigate the long-term stability of the horizontal-well salt-cavity natural gas storage. The simulation test design is combined with the similarity theory to study the cavity expansion characteristics and the influence law of cavity leaching parameters. Through the design of a rubber hose connection, an integrated closed test system for multi-stage horizontal-well cavity leaching and brine drainage was built. The test system also realises the repeatable backward movement of the injection well during the test. A similarity simulation of the test design was carried out, and the test platform was constructed to carry out multi-stage horizontal-well leaching tests with a nitrogen cushion. In the horizontal-well leaching tests with a nitrogen cushion, the influence laws of the well spacing, flow rate and liquid level position on cavity expansion were investigated. Based on the morphological characteristics of the horizontal-well cavity, a numerical model of the horizontal-well salt cavity was developed, which reflects the real cavity morphology leached in the test. The long-term stability of the horizontal-well salt-cavity natural gas storage under different internal pressures was investigated through numerical simulation.

In this paper, single and repetitive frequency UIS characteristics of 1200 V asymmetric (AT)and double trench silicon carbide (DT-SiC) metal–oxide-semiconductor field-effect transistors (MOSFETs) under different working conditions are investigated by experiment and simulation. For asymmetric trench SiC MOSFETs, the failure mode is all thermal runaway under working conditions. However, the failure mode of double trench SiC MOSFETs mostly is gate oxide rupture, which indicates an instable avalanche robustness under UIS stress. The variations of measured parameters are recorded to evaluate typical electrical features of device failure. Furthermore, TCAD simulation is used to reveal the electro-thermal stress inside the device during avalanche. Additionally, failed devices are decapsulated to verify the location of failure point from the perspective of the semiconductor die. Finally, a new type of stepped-oxide vertical power DT MOSFET with P-type shielding and current spread layers is proposed for improvement of gate dielectric reliability.

(1) Background: Since the pandemic, adolescent girls have increasingly faced mental health challenges. We examined prevalence trends and associated risk factors for depression among adolescent girls. 2) Methods: Data for girls aged 12 to 17 years (N=4346) from the 2021 cross-sectional National Survey on Drug Use and Health were analyzed. Factors associated with depression were examined using multiple regression analysis. (3) Results: Rates of severe depression were significantly higher (p&lt;.001) in older girls (adjusted odds ratio [AOR]: 1.63, 1.61, those who did not have authoritative parents (AOR: 3.40), and those with negative school experiences (AOR: 4.03). Black and Asian/Native Hawaiian or other Pacific Islanders were less likely to report severe depression than white girls. As previously reported, non-White girls were significantly less likely to receive treatment for depression (p&lt;.05). Parents’ characteristics and school experiences had no effect on the likelihood of receiving mental health treatment. (4) Conclusion: Depression has become increasingly common among American adolescent girls, who are now three times as likely as adolescent boys to have had recent experiences with depression. Our results show that family structure, parenting style, and negative school experiences significantly contribute to the rate of depression and that treatment disparities exist with regard to race and ethnicity.

Chlorophyll-a (Chla) is a crucial pigment in phytoplankton, playing a vital role in determining phytoplankton biomass and water nutrient status. However, in optically complex water bodies, Chla concentration is no longer the primary factor influencing remote sensing spectral reflectance signals, leading to significant errors in traditional Chla concentration estimation methods. With advancements in in-situ measurements, synchronized satellite data, and computer technology, machine learning algorithms have become popular in Chla concentration retrieval. Nevertheless, when using machine learning methods to estimate Chla concentration, abrupt changes in Chla values can disrupt the spatiotemporal smoothness of the retrieval results. Therefore, this study proposes a two-stage approach to enhance the accuracy of Chla concentration estimation in optically complex water bodies. In the first stage, a one-dimensional convolutional neural network (1DCNN) is employed for precise Chla retrieval, and in the second stage, the regression layer of the 1DCNN is replaced with Support Vector Regression (SVR). The research findings are as follows: (1) In the first stage, the performance metrics (R², RMSE, RMLSE, Bias, MAE) of the 1DCNN outperform state-of-the-art algorithms (OCI, SVR, RFR) on the test dataset. (2) After the second stage, the performance further improves, with the metrics achieving values of 0.892, 11.243, 0.052, 1.056, and 1.444, respectively. (3) In mid-to-high latitude regions, the inversion performance of 1DCNN\SVR is superior to other algorithms, exhibiting richer details and higher noise tolerance in nearshore areas. (4) 1DCNN\SVR demonstrates high inversion capabilities in water bodies with medium to high nutrient levels.

For W-band long-range mm-wave wireless transmission systems, nonlinearity issues resulting from photoelectric devices, optical fiber, and wireless power amplifiers can be handled by deep learning equalization algorithms. Besides, the PS technique is considered an effective measure to further increase the capacity of the modulation-constraint channel. However, since the proba-bilistic distribution of m-QAM varies with the amplitude, there have been difficulties in learning valuable information from the minority class. This limits the gain of nonlinear equalization. To overcome the imbalanced machine learning problem, we propose a novel two-lane DNN (TLD) equalizer with the random over-sampling (ROS) technique in this paper. The combination of PS at the transmitter and ROS at the receiver improves the overall performance of the W-band wireless transmission system, and our 4.6-km ROF delivery experiment verifies its effectiveness for the W-band mm-wave PS-16QAM system. Based on our proposed equalization scheme, we realize single-channel 10-Gbaud W-band PS-16QAM wireless transmission over 100 m optical fiber link and 4.6-km wireless air-free distance. The results show that compared with the typical TLD without ROS, the TLD-ROS can improve the receiver sensitivity by 1dB. Furthermore, a reduction of 45.6% in complexity is realized, and training samples can be reduced by 15.5%. Considering the actual wireless physical layer with its requirements, there is much to be gained from the joint use of deep learning and balanced data pre-processing techniques.

Manipulation of radiation pattern control is challenging, especially at low frequencies. In this paper, we demonstrate that acoustic metamaterials as an effective array of quadrupoles can remarkably improve the directionality of acoustic radiation at low frequencies, compared with previous metamaterials as monopole and dipole structures. The directivity of the acoustic radiation can be adjusted by changing the characteristic parameter and the symmetry of the structure, which provide a flexible method of adjustable radiation di-rections. The directionality can be further improved by constructing linear array of structure. Our work opens an approach of acoustic radiation control via quadrupolar metamaterials.

Solar assisted hybrid cooling systems are promising for the energy saving of refrigeration systems. In most cases, the solar thermal gain is only able to power the heat-driven process of facilities in part of the working period. Therefore, the reduction of compressor power strongly depends upon the duration of heat-driven processes, which has not been addressed properly. Motivated by such knowledge gap, the thermodynamic understanding of solar assisted hybrid cooling systems is deepened through considering the duration in heat-driven processes. Three absorption-compression integrated cooling cycles were taken as examples. It is found that optimal parameters, e.g., inter-stage pressure and temperature, corresponding to various performance indicators trend to be identical, as the duration of heat-driven processes is taken into account. Furthermore, the optimal parameter for different working conditions was obtained. It is displayed that the dimensionless optimal intermediate temperature of layout with the cascade condensation process varies slightly, e.g., 4%, for different conditions. Moreover, the fall of compressor power in entire working periods is nearly independent upon the intermediate temperature. The paper is favorable for the efficient design and operation of solar assisted hybrid cooling systems.

An increasingly large quantity of primary mineral resource is being converted into manufactured products and destined for solid waste disposal. This material can be reclassified as “anthropogenic mineral reserves” and be a potential source of metals for a range of manufacturing uses. China is implementing a range of policy interventions which can lead to such a classification that will raise the profile of recycling programs as a means of metal supply. China is not only a major producer of consumer products and importer of secondary metals, but also has a major urban infrastructure footprint. Here we consider three product groups, 30 products, and imports, and map the recycling potential of anthropogenic mineral and 23 types of the capsulated materials by targeting their evolution from 2010 to 2050. Total weight of anthropogenic mineral on average in China reached 39 Mt in 2010, but it will double in 2022 and quadruple in 2045. Stocks of precious metals and rare earths will increase faster than most base materials. The total economic potential in yearly-generated anthropogenic mineral is anticipated to grow markedly from 100 billion US$ in 2020 to 400 billion US$ in 2050. Anthropogenic mineral of around 20 materials will be able to meet projected consumption of three product groups by 2050, due to high availability of recycled content and gradual saturation of consumption. Durability of material usage and the concomitant stock of the anthropogenic mineral remain major challenges in determining the viability of this supply in the second half of the coming century.

In this study, we evaluated the effects of Cyclosporine A (CsA) on Lipopolysaccharide (LPS)-induced cytokine production in the genital tract of female rabbits. Twelve sexually mature and healthy female rabbits were randomly divided into four groups (n = 3 each). The rabbits in the LPS group were given an intrauterine infusion of Escherichia coli LPS (4 mg/kg body weight (BW)). Rabbits in the CsA group were given CsA (20 mg/kg BW). Rabbits in the LPS + CsA group were given LPS (4 mg/kg BW) and CsA (20 mg/kg BW). The control group received only LPS and CsA carrier. The gene expression and protein levels of pro- and anti-inflammatory cytokines were observed using qRT-PCR and immuno-histochemical (IHC) assay, respectively. Our study showed that IL-1β, IL-6, IL-8, TNF-α, IFN-γ, IL-4, IL-10, IL-13, and TGF-β were expressed in female genital organs. The LPS challenge increased the mRNA expression of IL-6 and TNF-α in the uterine body and IL-1β in the uterotubal junction compared to the control group. CsA increased the basal mRNA expression of anti-inflammatory cytokines (i.e., IL-4 in the uterine body, uterotubal junction, and oviductal ampulla; IL-10 in the cervix, oviductal isthmus, and ampulla; and TGF-β in the uterotubal junction and oviductal ampulla) and pro-inflammatory cytokines (i.e., IL-6 and IL-8 in the cervix; IL-1β in the oviductal isthmus; TNF-α in the oviductal ampulla; and IFN-γ in the uterine body compared to the control group). In addition, CsA inhibited the mRNA expression of pro-inflammatory cytokines, such as IL-6 in the uterine body, uterotubal junction, and oviductal isthmus; TNF-α in the uterine body; and IFN-γ in the uterotubal junction and oviductal isthmus induced by the LPS challenge. The IHC assay showed the LPS-induced increase in protein production of IL-6 in the uterine body and oviductal isthmus. CsA increased the protein production of IL-10 in the cervix, uterine body, oviductal ampulla, and isthmus. Moreover, CsA decreased the protein production of IL-6 in the uterine body and oviductal isthmus induced by LPS.

The recent COVID-19 pandemic has caused tremendous damage to social economy and people’s health. Some major issues fighting COVID-19 include early and accurate diagnosis and the shortage of ventilator machines for critical patients. In this work, we propose a closed-loop solution to deal with COVID-19: portable biosensing and wearable photoacoustic imaging for early and accurate diagnosis of infection and magnetically neuromodulation or minimally invasive electrical stimulation to replace the traditional ventilation. Proposed technique can guarantee ubiquitous and onsite detection, and electrical hypoglossal stimulator can be more effective in helping severe patients as well as reducing complications caused by ventilators.

Prime period sequences can serve as the fundamental tool to construct arbitrary composite period sequences. This is a review study of prime period perfect Gaussian integer sequence (PGIS). When cyclic group {1,2,…,N−1} can be partitioned into k cosets, where N=kf+1 is an odd prime number, the construction of a degree-(k+1) PGIS can be derived from either matching the flat magnitude spectrum criterion or making the sequence with ideal periodic autocorrelation function (PACF). This is a systematic approach of prime period N=kf+1 PGIS construction, and is applied to construct PGISs with degrees 1, 2, 3 and 5. However, for degrees larger than 3, matching either the flat magnitude spectrum or achieving the ideal PACF encounters a great challenge of solving a system of nonlinear constraint equations. To deal with this problem, the correlation and convolution operations can be applied upon PGIS of lower degrees to generate new PGIS with degree-4 and other higher degrees, e.g., 6, 7, 10, 11, 12, 14, 20 and 21 in this paper. In this convolution based scheme, both degree and pattern of a PGIS vary and can be indeterminant, which is rather nonsystematic compared with the systematic approach. The combination of systematic and nonsystematic schemes contributes the great efficiency for constructing abundant PGISs with various degrees and patterns for the associated applications.

China's vast geographical and climatic diversity presents distinct challenges to its aviation industry, especially in understanding Density Altitude (DA). The study reveals a concentration of airports in the eastern and central regions due to socio-economic factors, while the west, shaped by the Tibetan Plateau, faces infrastructural constraints owing to geographical barriers and limited economic activity. Notable DA variations, particularly negative values in the northeast and discrepancies between DA and elevation in the south, underscore operational complexities. The prominent influence of humidity on DA, especially in the southern coast, prompts a reevaluation of conventional aviation practices. To address these challenges, there's a pressing need for specialized training, region-centric flight planning, comprehensive risk assessment, and increased awareness about humidity's impact on DA. As China's aviation sector expands, harnessing these insights is crucial for sustained operational excellence.