Lately Silicon Carbide (SiC) and Galium Nitride (GaN) based high frequency power conversion has gained immense popularity which stems from relatively low switching energy, robustness to high temperature operation, wide-band gap and superior thermal limits. While this aspect inherently results in a high-density power stage design, the design of adjoining passive components, particularly magnetics, needs careful attention. This is especially true if the compatibility of core and winding options and their performance is limited with the use of higher switching frequency. In this regard, this paper presents a brief review of existent research conducted in materials, optimization and integration of magnetics for single and three phase applications, ranging from filters, resonant inductors to isolation transformers. Design knobs pertaining to medium voltage (MV) applications, low-voltage (LV) applications, e-mobility sector such as more electric aircrafts (MEAs) and electric vehicles (EVs) are discussed. Guidelines for magnetics design are summarized for each application with a projected roadmap on future trend for magnetics.

The rapid advancement in artificial intelligence (AI) and wide deployment of Internet of Video Things (IoVT) enable situation awareness (SAW). Robustness and security of the IoVT systems are essential to a sustainable urban environment. While blockchain technology has shown great potentials to enable trust-free and decentralized security mechanisms, directly embedding crypto-currency oriented blockchain schemes into resource-constrained Internet of Video Things (IoVT) networks at the edge is not feasible. Leveraging Electrical Network Frequency (ENF) signals extracted from multimedia recordings as region-of-recording proofs, this paper proposes EconLedger, an ENF-based consensus mechanism that enables secure and lightweight distributed ledgers for small scale IoVT edge networks. The proposed consensus mechanism relies on a novel Proof-of-ENF (PoENF) algorithm where a validator is qualified to generate a new block if and only if a proper ENF-containing multimedia signal proof is produced within the current round. Decentralized database (DDB) is adopted to guarantee efficiency and resilience of raw ENF proofs on the off-chain storage. A proof-of-concept prototype is developed and tested in a physical IoVT network environment. The experimental results validated the feasibility of the proposed EconLedger to provide a trust-free and partially decentralized security infrastructure for IoVT edge networks.

Industry 4.0 brings advanced technologies and automation, enabling greater productivity and efficiency. However, it also increases energy consumption and carbon emissions. Sustainable manufacturing in the era of Industry 4.0 is vital for addressing the environmental impact by minimizing resource consumption, optimizing energy efficiency, and adopting eco-friendly practices. CNC (Computer Numeric Control) 5-axis milling plays a significant role in the machining of precision molds and dies, aerospace, consumer electronics, etc. This research aims to explore the potential of the artificial intelligence (AI) technique in improving energy efficiency on CNC 5-axis milling process for sustainable manufacturing. The experiments were carried out using a CNC 5-axis milling machine with various machining parameters, toolpath planning, and dry cutting condition. Data on energy consumption of CNC 5-axis milling machine were collected, then the relationship between the machining parameters, toolpath planning, and energy consumption was analyzed and built. Furthermore, an AI-based optimization algorithm was developed that uses machine learning and optimization techniques to identify energy-efficient machining strategies. The developed algorithm was implemented within a simulation framework, the algorithm was rigorously assessed using machine learning analysis to effectively reduce energy consumption, all while ensuring the accuracy of machining result. Finally, verification experiments were carried out to evaluate the applicability and performance of the AI-based energy optimization approach on a CNC 5-axis milling machine. By integrating AI into the CNC machining process, manufacturers can achieve significant energy savings, leading to reduced carbon emissions and improved sustainability.

Due to the great threat of torpedo against surface warships, an efficient hydroacoustic countermeasure system must output realtime strategies that can accommodate varied antagonizing scenarios. Aiming at the decision-making problem in the anti-torpedo hydroacoustic countermeasure cases, this paper proposes an intelligent adversarial strategy based on the game theory. By discretizing the strategy space of both sides, a matrix game model is established with the payoff characterized by the capture probability of attacking torpedo. An improved simplex algorithm is then developed to get the mixed-strategy Nash equilibrium of the game model, with which preferred avoiding strategies can be obtained to minimize the risk of being captured by the attacking torpedo. Based on the probabilistic view of preferred adversarial strategy, the launching strategy of floating acoustic decoy can be achieved, and the evasion trajectory of warship can be confirmed simultaneously. Numerical simulation demonstrates that the proposed method can generate realtime intelligent antagonizing strategy, and consequently, can improve the survival rate of surface warships in the of anti-torpedo countermeasure scenarios.

Recently, oriented external electric fields (OEEFs) have earned much attention due to the possibility of tuning the properties of electronic systems. From a theoretical perspective, one can resort to electronic structure calculations to understand how the direction and strength of OEEFs affect the properties of electronic systems. However, for multi-reference (MR) systems, calculations employing the popular Kohn-Sham density functional theory with the traditional semilocal and hybrid exchange-correlation energy functionals can yield erroneous results. Owing to its decent compromise between accuracy and efficiency for MR systems at the nanoscale (i.e., MR nanosystems), in this study, thermally-assisted-occupation density functional theory (TAO-DFT) is adopted to explore the electronic properties of n-acenes (n = 2--10), containing n linearly fused benzene rings, in OEEFs, where the OEEFs of various electric field strengths are applied along the long axes of n-acenes. According to our TAO-DFT calculations, the ground states of n-acenes in OEEFs are singlets for all the cases examined. The effect of OEEFs is shown to be significant on the vertical ionization potentials and vertical electron affinities of ground-state n-acenes with odd-number fused benzene rings. Moreover, the MR character of ground-state n-acenes in OEEFs increases with the increase of the acene length and/or the electric field strength.

The endosomal sorting complex required for transport (ESCRT) is an essential molecular machinery in eukaryotic cells that facilitates the invagination of endosomal membranes, leading to the formation of multivesicular bodies (MVBs). It participates in various cellular processes, including lipid bilayer remodeling, cytoplasmic separation, autophagy, membrane fission and remodeling, plasma membrane repair, as well as the invasion, budding, and release of certain enveloped viruses. The ESCRT complex consists of five complexes, ESCRT-0 to ESCRT-III and VPS4, along with several accessory proteins. ESCRT-0 to ESCRT-II form soluble complexes that shuttle between the cytoplasm and membranes, mainly responsible for recruiting and transporting membrane proteins and viral particles, as well as recruiting ESCRT-III for membrane neck scission. ESCRT-III, a soluble monomer, directly participates in vesicle scission and release, while VPS4 hydrolyzes ATP to provide energy for ESCRT-III complex disassembly, enabling recycling. Studies have confirmed the hijacking of ESCRT complexes by enveloped viruses to facilitate their entry, replication, and budding. Recent research has focused on the interaction between various components of the ESCRT complex and different viruses. In this review, we discuss how different viruses hijack specific ESCRT regulatory proteins to impact the viral life cycle, aiming to explore commonalities in the interaction between viruses and the ESCRT system.

Seniors safety is a compelling need, which necessitates 24/7 real-time monitoring and timely dangerous action recognition. Being able to mirror characteristics of physical objects (PO) to corresponding logical objects (LO) and seamlessly monitor their footprints thus detect anomaly parameters, Digital Twins (DT) has been considered a practical way to provide virtual health services for seniors safety. Meanwhile, widely adopted Internet of Medical Things (IoMT) consisting of wearable sensors and non-contact optical cameras for self and remote health data monitoring also raises concerns on information security and privacy violation. Therefore, security of POs, LOs and reliable data sharing among healthcare professionals are challenging as constructing trust and privacy-preserving virtual health services. Thanks to characteristics of decentralization, traceability and unalterability, Blockchain is promising to enhance security and privacy properties in many areas like data analysis, finance and healthcare. This paper envisions a lightweight authentication framework (LAF) to enable secure and privacy-preserving virtual healthcare services. Leveraging Non-Fungible Token (NFT) technology to tokenize LOs and data streams on blockchain, anyone can certify the authenticity of a digital LO along with its synchronized data between PO without relying on a third-party agency. In addition, the NFT-based tokenization not only allows owners fully control their IoMT devices and data, but it also enables verifiable ownership and traceable transferability during data sharing process. Moreover, NFT only contains references to encrypted raw data that are saved on off-chain storage like local files or distributed databases, such a hybrid storage strategy ensures privacy-preservation for sensitive information. A proof-of-concept prototype is implemented and tests are conducted on a case study of seniors safety. The experimental evaluation shows the feasibility and effectiveness of the proposed LAF solution.

Purpose: Pitch plays an important role in auditory perception of music and language. This study provides a systematic review with meta-analysis to investigate whether individuals with autism spectrum disorder (ASD) have enhanced pitch processing ability and identify the potential factors associated with processing differences between ASD and neurotypicals. Method: We conducted a systematic search through six major electronic databases focusing on the studies that used nonspeech stimuli to provide a qualitative and quantitative assessment across existing studies on pitch perception in autism. We identified potential participant- and methodology-related moderators and conducted meta-regression analyses using mixed-effects models. Results: On the basis of 22 studies with a total of 464 participants with ASD, we obtained a small-to-medium positive effect size (0.26) in support of enhanced pitch perception in ASD.Moreover, the mean age and non-verbal IQ of participants were found to significantly moderate the between-studies heterogeneity. Conclusion: Our study provides the first meta-analysis on auditory pitch perception in ASD and demonstrates the existence of different developmental trajectories between individuals with ASD and neurotypicals. Non-verbal ability can be a significant contributor to the lower-level/ local processing bias in ASD. We highlight the need for further investigation of pitch perception in ASD under challenging listening conditions. Future neurophysiological and brain imaging research studies with a longitudinal design are also needed to better understand the nature of the atypical processing in ASD to obtain new insights into the underlying neural mechanisms and to help guide auditory-based interventions for improving language and social functioning.

For public safety and physical security, currently more than a billion closed-circuit television (CCTV) cameras are deployed around the world. Proliferation of artificial intelligence (AI) and machine learning (ML) technologies has gained significant applications including crowd surveillance. The state-of-the-art distance and area estimation algorithms either need multiple cameras or a reference scale as a ground truth. It is an open question to obtain an estimation using a single camera without a scale reference. In this paper, we propose a novel solution called E-SEC, which estimates interpersonal distance between a pair of dynamic human objects, area occupied by a dynamic crowd, and density using a single edge camera. The E-SEC framework comprises edge CCTV cameras responsible for capture a crowd on video frames leveraging a customized YOLOv3 model for human detection. E-SEC contributes an interpersonal distance estimation algorithm vital for monitoring the social distancing of a crowd, and an area estimation algorithm for dynamically determining an area occupied by a crowd with changing size and position. A unified output module generates the crowd size, interpersonal distances, social distancing violations, area, and density per every frame. Experimental results validate the accuracy and efficiency of E-SEC with a range of different video datasets.

While the Internet of Things (IoT) technology has been widely recognized as the essential part of Smart Cities, it also brings new challenges in terms of privacy and security. Access control (AC) is among the top security concerns, which is critical in resource and information protection over IoT devices. Traditional access control approaches, like Access Control Lists (ACL), Role-based Access Control (RBAC) and Attribute-based Access Control (ABAC), are not able to provide a scalable, manageable and efficient mechanism to meet the requirements of IoT systems. Another weakness in today's AC is the centralized authorization server, which can be the performance bottleneck or the single point of failure. Inspired by the smart contract on top of a blockchain protocol, this paper proposes BlendCAC, which is a decentralized, federated capability-based AC mechanism to enable an effective protection for devices, services and information in large scale IoT systems. A federated capability-based delegation model (FCDM) is introduced to support hierarchical and multi-hop delegation. The mechanism for delegate authorization and revocation is explored. A robust identity-based capability token management strategy is proposed, which takes advantage of the smart contract for registering, propagating and revocating of the access authorization. A proof-of-concept prototype has been implemented on both resources-constrained devices (i.e., Raspberry PI node) and more powerful computing devices (i.e., laptops), and tested on a local private blockchain network. The experimental results demonstrate the feasibility of the BlendCAC to offer a decentralized, scalable, lightweight and fine-grained AC solution for IoT systems.

The rapid development of three-dimensional (3D) acquisition technology based on 3D sensors provides a large volume of data, which is often represented in the form of point clouds. Point cloud representation can preserve the original geometric information along with associated attributes in a 3D space. Therefore, it has been widely adopted in many scene-understanding-related applications such as virtual reality (VR) and autonomous driving. However, the massive amount of point cloud data aggregated from distributed 3D sensors also poses challenges for secure data collection, management, storage, and sharing. Thanks to the characteristics of decentralization and security nature, Blockchain has a great potential to improve point cloud services and enhance security and privacy preservation. Inspired by the rationales behind Software Defined Network (SDN) technology, this paper envisions SAUSA, a blockchain-based authentication network that is capable of recording, tracking, and auditing the access, usage, and storage of 3D point cloud data sets in their life-cycle in a decentralized manner. SAUSA adopts an SDN-enabled point cloud service architecture which allows for efficient data processing and delivery to satisfy diverse Quality-of-Service (QoS) requirements. A blockchain-based authentication framework is proposed to ensure security and privacy preservation in point cloud data acquisition, storage, and analytics. Leveraging smart contracts for digitizing access control policies and point cloud data on the blockchain, data owners have full control of their 3D sensors and point clouds. In addition, anyone can verify the authenticity and integrity of point clouds in use without relying on a third party. Moreover, SAUSA integrates a decentralized storage platform to store encrypted point clouds while recording references of raw data on the distributed ledger. Such a hybrid on-chain and off-chain storage strategy not only improves robustness and availability but also ensures privacy preservation for sensitive information in point cloud applications. A proof-of-concept prototype is implemented and tested on a physical network. The experimental evaluation validates the feasibility and effectiveness of the proposed SAUSA solution.

We construct a novel family of summation-integral type hybrid operators in terms of shape parameter $\alpha\in \lbrack 0,1]$ in this paper. Basic estimates, rate of convergence, and order of approximation are also studied using the Korovkin theorem and the modulus of smoothness. We investigate the local approximation findings for these sequences of positive linear operators utilising Peetre's K-functional, Lipschitz class, and second-order modulus of smoothness.

Background: During pregnancy, major physiological changes occur in every system. Understanding the hemodynamic changes in different stages of pregnancy can help to identify abnormal states during pregnancy. Harmonic analysis could be a useful tool in monitoring the state of the ventricular-arterial system during pregnancy. The aim of this study was to investigate the specific statistical relationships between changes in harmonic indices during different stages of pregnancy. Methods: A Total of 380 women (190 pregnant women and 190 age-matched non-pregnant women), with ages ranging from 20 to 45, were enrolled in the study. The visit measured the subject’s hemodynamic parameters including heart rate, systolic blood pressure (SBP), diastolic blood pressure (DBP) and photoplethysmography (PPG). SBP and DBP were evaluated by an automatic blood pressure monitor. PPG signal were continuously recorded for 12-seconds using a PPG sensor. Spectrum analysis of the PPG signal was performed to evaluate the first five harmonic components (C1 – C5) and harmonic phases (P1 – P5). Result: A comparison between pregnant women and non-pregnant women showed that the non-pregnant women had lower DBP, C3, C5 and P5 (p<0.05). Waist Circumference, Heart rate, C2, C4 and P2 were higher in pregnant women. Logistic regression analysis was used to determine the associations between pregnancy and harmonics indices. C2, C4 and P3 were positively and P1 and P4 were negatively associated with pregnancy after controlling age, BMI, waist circumference, heart rate, SBP and DBP. Conclusion: The results of this study provide information on the changes in the harmonic frequency components during various stages of pregnancy. The harmonic components of the PPG signal have independent predictive value for changes in a woman's physiology during pregnancy. Since non-invasive PPG measurements can be performed frequently and easily, in the future, it is possible that the hemodynamic changes from some pregnancy-related disorders could be studied by harmonic analysis.

Due to the fact that abrasive media can deform flexibly in abrasive flow machining (AFM) making this method easily to polish the complex holes and the curved surface of the hard machining shapes. Although abrasive media dominate the polishing behavior in AFM process, the mechanism of the abrasive media are not easy to understand because of the high viscous gels, therefore, many finishing works need lots of time to design AFM process. Power laws of the abrasive gels is studied here to evaluate the non-Newtonian flow of abrasive gels in complex holes polishing firstly, at the mean time different abrasive gels are utilized to finish the complex holes to follow the results by non-Newtonian flow calculation. Moreover, traditional AFM has difficulty to achieve a uniform roughness of radial distribution in the complex holes polishing because of the non-uniform abrasive forces. So a helical passageway is proposed to create a multiple motion of abrasive medium and to obtain the even surface of the complex holes in AFM process.

Rapid advancements in the fifth generation (5G) communication technology and mobile edge computing (MEC) paradigm lead to the proliferation of unmanned aerial vehicles (UAV) in urban air mobility (UAM) networks, which provide intelligent services for diversified smart city scenarios. Meanwhile, the widely deployed internet of drones (IoD) in smart cities also brings up new concerns on performance, security, and privacy. The centralized framework adopted by conventional UAM networks is not adequate to handle high mobility and dynamicity. Moreover, it is necessary to ensure device authentication, data integrity, and privacy preservation in UAM networks. Thanks to characteristics of decentralization, traceability, and unalterability, Blockchain is recognized as a promising technology to enhance security and privacy for UAM networks. In this paper, we introduce LightMAN, a lightweight microchained fabric for data assurance and resilience-oriented UAM networks. LightMAN is tailored for small-scale permissioned UAV networks, in which a microchain acts as a lightweight distributed ledger for security guarantees. Thus, participants are enabled to authenticate drones and verify the genuineness of data that is sent to/from drones without relying on a third-party agency. In addition, a hybrid on-chain and off-chain storage strategy is adopted that not only improves performance (e.g,.latency and throughput) but also ensures privacy preservation for sensitive information in UAM networks. A proof-of-concept prototype is implemented and tested on a Micro Air Vehicle Link (MAVLink) simulator. The experimental evaluation validates the feasibility and effectiveness of the proposed LightMAN solution.

Blockchain technology has been recognized as a promising solution to enhance the security and privacy of Internet of Things (IoT) and Edge Computing scenarios. Taking advantage of the Proof-of-Work (PoW) consensus protocol, which solves a computation intensive hashing puzzle, Blockchain assures the security of the system by establishing a digital ledger. However, the computation intensive PoW favors members possessing more computing power. In the IoT paradigm, fairness in the highly heterogeneous network edge environments must consider devices with various constraints on computation power. Inspired by the advanced features of Digital Twins (DT), an emerging concept that mirrors the lifespan and operational characteristics of physical objects, we propose a novel Miner-Twins (MinT) architecture to enable a fair PoW consensus mechanism for blockchains in IoT environments. MinT adopts an edge-fog-cloud hierarchy. All physical miners of the blockchain are deployed as microservices on distributed edge devices, while fog/cloud servers maintain digital twins that periodically update miners’ running status. By timely monitoring miner’s footage that is mirrored by twins, a lightweight Singular Spectrum Analysis (SSA) based detection achieves to identify individual misbehaved miners that violate fair mining. Moreover, we also design a novel Proof-of-Behavior (PoB) consensus algorithm to detect byzantine miners that collude to compromise a fair mining network. A preliminary study is conducted on a proof-of-concept prototype implementation, and experimental evaluation shows the feasibility and effectiveness of proposed MinT scheme under a distributed byzantine network environment.

Thanks to rapid advances in the Internet of Things (IoT) and Edge-Fog-Cloud Computing technologies, Smart Public Safety (SPS) system has become feasible by integrating heterogeneous computing devices and different types of networks to collaboratively provide seamless public safety services. While SPS facilitates convenient exchanges of surveillance data streams among device owners and third-party applications, the existing monolithic service oriented architecture (SOA) architecture is unable to provide scalable and extensible services in a large-scale heterogeneous network environment. Moreover, traditional security solutions rely on centralized trusted third-party authority, which not only can be a performance bottleneck or the single point of failure, but it also incurs privacy concerns on improperly use of private information. Inspired by blockchain and microservices technologies, this paper proposed a BLockchain-ENabled Decentralized Smart Public Safety (BlendSPS) system. Leveraging hybrid blockchain fabrics, a microservices based security mechanism is implemented to enable decentralized security architecture, and it supports immutability, auditability and traceability for secured data sharing and operations among participants of the SPS system. An extensive experimental study verified the feasibility of the proposed Blend-SPS that possesses security and privacy proprieties with limited overhead on IoT based edge networks.

Over the past few years, the importance of video surveillance in securing the national critical infrastructure has significantly increased, whose applications include detecting failures and anomalies. Accompanied by video proliferation is the increasing number of attacks against surveillance systems. Among the attacks, false frame injection (FFI) attacks that replay video frames from a previous recording to mask the live feed has the highest impact. While many attempts have been made to detect FFI frames using features from the video feeds, video analysis is computationally too intensive to be deployed on-site for real-time false frame detection. In this paper, we investigate the feasibility of FFI attacks on compromised surveillance systems at the edge and propose an effective technique to detect the injected false video and audio frames by monitoring the surveillance feed using the embedded Electrical Network Frequency (ENF) signals. An ENF operates at a nominal frequency of 60 Hz/50 Hz based on its geographical location and maintains a stable value across the entire power grid interconnection with minor fluctuations. For surveillance system video/audio recordings connected to the power grid, the ENF signals are embedded. The time-varying nature of the ENF component is used as a forensic application for authenticating the surveillance feed. The paper highlights the ENF signal collection from a power grid creating a reference database and ENF extraction from the recordings using conventional short-time Fourier Transform and spectrum detection for robust ENF signal analysis in the presence of noise and interference caused in different harmonics. The experimental results demonstrate the effectiveness of ENF signal detection and/or abnormalities for FFI attacks.

This study integrated coastal-watershed models and combined a risk assessment method to develop a methodology to investigate the impact resulting from coastal disasters under climate change. The mid-western coast of Taiwan suffering from land subsidence was selected as the demonstrative area for the vulnerability analysis based on prediction of sea level rise (SLR), wave run-up, overtopping, and coastal flooding under the scenarios of 2020 to 2039. Database from tidal gauges and satellite images were used to analyze sea level rise using EEMD (Ensemble Empirical Mode Decomposition). Extreme wave condition and storm surge were estimated by numerical simulation using WWM (Wind Wave Model) and POM (Princeton Ocean Model). Coastal inundation was then simulated via WASH123D watershed model. The risk map of study areas based on the analyses of vulnerability and disaster were established using the AHP (Analytic Hierarchy Process) technique. Predictions of sea level rise, the maximum wave condition and storm surge under the scenarios of 2020 to 2039 are presented. The results indicate that the sea level at the mid-western coast of Taiwan will rise in an average of 5.8 cm, equivalent to a rising velocity of 2.8 mm/year. The analysis indicates that Wuqi, Lukang, Mailiao, and Taixi townships are susceptive, low resistant and low resilient, and reaches the high risk level. The assessment provides that important information for making adaption policy in the mid-western coast of Taiwan.

Adipose-derived stem cells (ADSCs) were suggested for treating degenerative osteoarthritis, suppressing inflammatory responses, and repairing damaged soft tissues. Moreover, the ADSCs have the potential to undergo self-renewal and differentiate into bone, tendon, cartilage, and ligament. Recently, investigation of the self-renewal and differentiation of the ADSCs becomes an attractive area. In this work, a pneumatic microdevice has been developed to study the gene expression of the ADSCs after the stimulation of multi-axial tensile strain. The ADSCs were cultured on the microdevice and experienced multi-axial tensile strain during a 3-day culture course. Self-renewal and differentiation abilities were investigated by mRNA expressions of NANOG, SOX2, OCT4, SOX9, PPAR-γ, and RUNX2. The result showed that the genes related self-renewal were significantly up-regulated after the tensile stimulation. Higher proliferation ratio of the ADSCs was also shown by cell viability assay. The microdevice provides a promising platform for cell-based study under mechanical tensile stimulation.

With the accelerating urbanization process, the population increasingly concentrates in urban areas. In view of the special situation in China and a series of problems in the process of rapid urbanization, there were no reasonable measures for optimizing the population pattern. This study explored the distribution pattern of the Chinese population and proposed an optimization plan for the population distribution using GIS analysis. The main findings were as follows. (1) From 2010 to 2015, the distribution of population density in China presented a pattern of high in the southeast and low in the northwest based on the county-level administrative regions. The population still showed a tendency to migrate to the southeast of the country based on the “Hu Huanyong Line”. (2) There was a great difference in the land use efficiency in terms of population and economic production in China. The economic concentration in China was higher than the population concentration. In the areas where population and economic production were aggregated, GDP per capita and land use efficiency were higher. (3) Based on the land use efficiency in terms of population and economic production, the optimized urbanization plan of “1+4+11” for China’s urbanization was put forward, namely, one national-level aggregated area of population and economic production, 4 regional-level aggregated areas of population and economic production, and 11 local regionally aggregated areas of population and economic production. This optimization plan for urbanization represents an attempt to explore the direction of China’s urbanization, and it can be used to optimize the spatial development pattern and provide scientific guidance for the new urbanization plan.

The proliferation of Unmanned Aerial Vehicle (UAV) networks is increasing, driven by their capacity to deliver automated services tailored to the varied demands of numerous smart city applications. Trust, security, and privacy remain paramount in the public domain. Traditional centralized network designs fall short of ensuring device authentication, data integrity, and privacy within UAV networks’ highly dynamic and adaptable environments. Decentralized reputation systems emerge as a promising solution to enhance the reliability and trustworthiness of data and communications within these networks while safeguarding UAV security. This paper presents an exhaustive survey of trust and reputation systems, exploring existing frameworks and proposed innovations alongside their inherent challenges. It highlights the crucial role of reputation systems in strengthening trust, security, and privacy throughout these networks and discusses various strategies to mitigate existing vulnerabilities. As a useful resource for researchers and practitioners seeking to advance the state of the art in UAV network security, we hope this survey will spark further community discussion and stimulate innovative ideas in this burgeoning field.

The booming wearable market and recent advances in material science has led to the rapid development of the various wearable sensors, actuators, and devices that can be worn, embedded in fabric or accessories, or tattoos directly onto the skin. Wearable actuators, a subcategory of wearable technology, have attracted enormous interest from researchers in various disciplines and many wearable actuators and devices have been developed in the past few decades to assist and improve people's everyday lives. In this paper, we review the actuation mechanisms, structures, applications, and limitations of recently developed wearable actuators including pneumatic and hydraulic actuators, shape memory alloys and polymers, thermal and hygroscopic materials, dielectric elastomers, ionic and conducting polymers, piezoelectric actuators, electromagnetic actuators, liquid crystal elastomers, etc. Examples of the recent applications such as wearable soft robots, haptic devices, and personal thermal regulation textiles are highlighted. Finally, we point out the current bottleneck and suggest the prospective future research directions for wearable actuators.

An improved synthesis of glucosyl esters was reported here, avoiding the use of expensive Ag reagent as well as the hydrolysis of instable glucosyl bromide. Notably, ß-configuration product was exclusively obtained in good yield.

Aim: Aging is companied by deteriorations of insulin resistance (IR) and insulin secretion. However, little is known about the roles of aging on different phases of insulin secretion (ISEC); i.e., the first- and second-phase of insulin secretion (FPIS, SPIS) and glucose effectiveness (GE). Methods: Totally 169 individuals (43 men and 126 women) with the similar fasting plasma glucose (FPG: 90 mg/dL) and BMI (men: 23 kg/m2, women 22 kg/m2) were enrolled. IR, FPIS, SPIS, and GE were estimated using our previously developed equations shown below. Pearson correlation analysis was conducted to assess the correlations between age and four diabetes factors (DFs: IR, FPIS, SPIS and GE). The equations that are used to calculate the DF in the present study were built and published by our group. Results: The age of the participants ranged from 18- to 78-year-old. Men had higher FPIS but lower HDL-C levels than women (2.067±0.159, 1.950±0.186 μU/min and 1.130±0.306, 1.348±0.357 mmol/dl, accordingly). The results of Pearson correlation revealed that age was negatively related to IR and GE in both genders (IR: r = -0.39, p < 0.001 for men, r = -0.24, p < 0.003 for women; GE: r = 0.66, p < 0.001 for men, r = 0.78, p < 0.001 for women). In the meanwhile, FPIS was also only found to be negatively correlated with age in female (r = -0.238, p = 0.003). But there was no different with SPIS and age in both of genders. Conclusions: We have found that in Chinese with normal FPG level (90 mg/dl) and body mass index (men: 23 kg/m2, women: 22: kg/m2), age is negatively related to IR and GE in both genders. At the same time, only FPIS was found to be negatively related to age in women. The tightness of their relationships, from the highest to the lowest are, GE, FPIS and IR accordingly. The importance of GE should be re-evaluated. These results should be interpreted with caution because of the small sample size.

Aiming at the problem of underactuated unmanned surface vehicles (USVs) performing fixed-point operations in the sea but without dynamic positioning control system. This paper introduces an original approach for positioning control, and the method is named as virtual anchor control method. This method is applicable in slow-varying current environments, and this approach does not need the prior knowledge of current information or vessel motion model parameters, thus offering convenient usability. This method is comprised by four steps. Firstly, a linear concise motion model with unknown disturbances is proposed. Then, the motion planning law is designed by imitating underlying principles of ship anchoring. Next, an adaptive disturbance observer is proposed for estimating uncertainties in the motion model. Last step, based on the observer, a sliding-mode method is used for heading control law designing, and thrust control law is also conducted by applying the Lyapunov method. Finally, numerical simulation experiments with significant disturbances and tidal current variations are conducted, which demonstrate that the proposed method has good control effect and robustness.

Small molecule kinase inhibitors (SMKIs) are one of the heightened concerns in the field of drug research and development. There are seventy-nine (up to July 2023) small molecule kinase inhibitors have been approved by FDA and hundreds kinase inhibitors candidates in clinical trials, which shed light on the treatment of some major diseases. As an important strategy of drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods, such as docking, molecular dynamic, pharmacophore have been applied to the design and optimization of small molecule kinase inhibitors. In the review, we provide an overview of recent advances in CADD and SMKIs; and the application of CADD for discovery of SMKIs.

Steam Generator Level Control System (SGLCS) is one of the key instrumentations and control subsystems to ensure the safe operation of nuclear power plants. It is highly recommended to perform reliability analysis for SGLCS for making better maintenance strategy. SGLCS is a digital control system with complex redundant configuration and failure\self-diagnosis\repair action, traditional fault tree is not applicable due to its static property, Markov model is not a good choice too because of heavy burden of creating state transition graph for even medium-size system. Boolean Logic Driven Markov Process (BDMP) can describe complex failure-repair state transition via ‘trigger link’ and three kinds of leaf nodes, as well as keep compact and easy-read struct like fault tree. So BDMP is adopted to analysis reliability of SGLCS. Graphical BDMP modeling environment KB3 and Monte Carlo simulator YAMS is used for BDMP modeling and quantitative analysis respectively, and unavailability of SGLCS is obtained. The contribution of three parts of SGLCS to the unavailability of the system is also evaluated, and it is found that the water supply flow control part contributes the most to the failure of SGLCS.

Nitric oxide (NO) is a key molecule in cardiovascular homeostasis and its abnormal delivery is highly associated with the occurrence and development of cardiovascular disease (CVD). The assessment and manipulation of NO delivery is crucial to the diagnosis and therapy of CVD, such as endothelial dysfunction, atherosclerotic progression, pulmonary hypertension, and cardiovascular manifestations of Coronavirus (COVID-19). However, due to the low concentration and fast reaction characteristics of NO in cardiovascular system, the clinical applications centered on the NO delivery are challenging. In this tutorial review, we first summarized the methods to estimate the in vivo NO delivery process based on the clinical images and mathematical modeling to assess the endothelial function and vulnerability of atherosclerotic plaque. Then, the emerging bioimaging technologies that have the potential to directly measure the arterial NO concentration were discussed, including the Raman spectroscopy and electrochemical sensor. Aside from the diagnostic methods, therapies aimed at controlling NO delivery to regulate CVD were reviewed, including the inhaled NO therapy to treat the pulmonary hypertension and COVID-19, stem cell therapy and NO-releasing platform to treat endothelial dysfunction and atherosclerosis.

Currently, data regarding optimal treatment modality, response, and outcome specifically for N3 head and neck cancer are lacking. This study aimed to compare the treatment outcomes between definitive concurrent chemoradiotherapy (CCRT) to the neck and upfront neck dissection followed by adjuvant CCRT. 93 N3 squamous cell carcinoma head and neck cancer patients were included. Primary tumor treatment was divided to definitive CCRT (CCRT group) or curative surgery followed by adjuvant CCRT (surgery group). Neck treatment was also classified into two treatment modalities: definitive CCRT to the neck (CCRT group) or curative neck dissection followed by adjuvant CCRT (neck dissection group). Overall, the 2-year overall survival (OS), local recurrence-free survival (LRFS), regional recurrence-free survival (RRFS), and distant metastasis-free survival (DMFS) were 51.8%, 47.3%, 45.6%, and 43.6%, respectively. In both oropharyngeal cancer and nonoropharyngeal cancer patients, in terms of OS, LRFS, RRFS or DMFS no difference was noted regarding primary tumor treatment (CCRT vs. surgery) or neck treatment (CCRT vs. neck dissection). In summary, N3 neck patients treated with definitive CCRT can achieve similar outcomes to those treated with upfront neck dissection followed by adjuvant CCRT. Cautions should be made to avoid overtreatment for this group of patients.

The effect of Pr6O11 on the microstructure and mechanical properties of high-strength steel weld metal was investigated by optical microscopy, scanning electron microscopy and mechanical testing. Three different contents of Pr6O11 were added to the flux-cored wires. The results demonstrate that the addition of 1% Pr6O11 can promote the refinement and spheroidization of inclusions, refine the grains, form acicular ferrites in the weld metal, and significantly improve the toughness. The addition of Pr6O11 promoted the formation of rare earth composite inclusions and acicular ferrites in the weld metal, refined the lath microstructure, inhibited the formation of martensite and bainite. The crack formation mode changed from the boundary cracking of the bainite clusters caused by the surface shear stress to the surface shear stress-induced decohesion of inclusion. Excessive addition of Pr6O11 will reduce the number of inclusion nucleation and deteriorate the mechanical properties. The wire No.2 with 1% Pr6O11 had the good comprehensive mechanical properties.

Antibiotic-loaded bone cements are widely used in orthopedic surgery. However, they present issues such as a short antibiotic release time and the antibiotic resistance. These challenges necessitate the development of novel antibacterial bone cements. Non-leaching bone cement containing antibacterial motifs represents a promising advancement in this direction. Antibacterial motifs are incorporated into the cement either covalently or non-covalently, and while they will not be released, they will still exhibit surface antibacterial activity. This review comprehensively examines the structure and antimicrobial activity of prevalent non-leaching antimicrobial bone cements. Additionally, it delves into the characteristics of current methods employed for detecting surface antimicrobial activity. Finally, the future research direction of non-leaching antibacterial bone cement is discussed, with a specific focus on innovative antibacterial motifs, the mechanisms underlying non-leaching antibacterial properties, and the potential synergies achievable by combining non-leaching antibacterial bone cement with traditional antibiotics.

For underwater vehicles navigating in Arctic Sea ice-covered waters, fatigue damage is a crucial issue. Many scholars have conducted low-temperature fatigue analysis on low-temperature ma-terials and substrate platforms for ships, and the results show that low-temperature is beneficial for improving the mechanical properties of materials. However, they mainly focus on low-temperature performance experiments and simulation analysis of standard components of materials, and there are very few fatigue life experimental studies on underwater vehicle me-chanical structures. This paper conducts experimental investigations on a scaled model of an underwater vehicle rudder mechanism in a polar environment laboratory. Using a comparative analysis method involving simulations and experiments, the low-temperature fatigue test data of the scaled underwater vehicle rudder mechanism are analyzed, and the quantified analysis be-tween fatigue and different low-temperature loading cycles, as well as the influence of icing on the fatigue life, is explored. It is indicated that the arctic environment can decrease the fatigue life of the underwater vehicle rudder mechanism by deteriorating its material properties. The paper builds the foundation for the fatigue life of an underwater vehicle rudder mechanism in arctic low-temperature environments.

Study design: Retrospective observational study. Objectives: To evaluate the change in adjacent segment disease (ASD) after hybrid dynamic stabilization with Dynesys-Transition-Optima (DTO). Methods: In 2012–2020, 115 lumbar spinal stenosis patients with spondylolisthesis re-fractory to nonsurgical management received hybrid dynamic stabilization with DTO system in a single medical center from a single neurosurgeon. After excluding those who did not receive L3–L4 dynamic stabilization and L4–L5 transforaminal lumbar interbody fusion fixation and those with incomplete postoperative data (n = 84), the 31 patients studied received follow-up vis-its at 6, 12 and 24 months postoperatively. Radiological assessment applied at the L2–L3, L3–L4 and L5–S1 segments separately included disc height, listhesis distance and angular change while in motion. Implant failure and screw loosening sign were both documented. Results: In the L3–L4 segment, the listhesis distance appeared 1 year after the operation; however, alterations in other segments showed at 6 months. At 2 years, the L3–L4 segment showed significantly less increase in listhesis distance and relatively less disc height reduction than other segments. In motion an-gular change, only the L3–L4 segment had a significant decrease at 2 years. Only the L3–L4 seg-ment maintained negative growth over 2 years in time-dependent assessment of motion angular change. Conclusions: In our study, disc height decreased, listhesis distance increased less and ASD changed later at the index level than the L2–L3 and L5–S1 levels. Angular change was re-duced at the index level while in motion. Although ASD was not significantly prevented, index level degeneration was both minor

Background and Objectives: Treatment for antineutrophil cytoplasmic antibody-associated vasculitis (AAV) must deal with immunosuppression as well as infections associated with compromised immune system, such as tuberculosis (TB). Our aim was to overcome the gap in the literature concerning the risk of incidental TB after diagnosis of AAV. Materials and Methods: This retrospective population-based cohort study was based on the data from the National Health Insurance Research Database in Taiwan. We used a novel algorithm to identify patients with newly diagnosed granulomatous polyangiitis (GPA) or microscopic polyangiitis (MPA) between January 1, 2000 and December 31, 2012. The primary outcome was risk of incidental TB. Cox proportional hazard models were used to evaluate the association between AAV and incidental TB. Results: A total of 2,257 patients with AAV and a propensity-score matched cohort of 9,028 patients were studied. Overall, patients with AAV were at a 1.48x higher risk of contracting incidental TB than were patients in the matched cohort (adjusted HR 1.48; 95% confidence interval [CI], 1.02-2.15). Note that the highest risk of contracting incidental TB was in the first two years following a diagnosis of AAV, with a nearly 1-fold increase in risk (adjusted HR, 1.91; 95% CI, 1.01-3.60). Female AAV patients were 3.24x more likely than females without AAV to develop TB (adjusted HR 3.24; 95%CI, 1.85-5.67). Conclusion: Patients with AAV face an elevated risk of contracting incidental TB, particularly within the first two years after AAV diagnosis. The risk of contracting TB is higher among female AAV patients than among females without AAV.

In Taiwan, peanuts are classified by hand. The kernel quality is judged based on the appearance of peanuts. The identification takes considerable time and labor. Fatigue can induce misrecogni-tion or grade cognition instability due. Peanut defects are generally divided into health, underde-velopment, insect bite, and rupture. This study employed two imaging methods push-boom FX10 and Snapshot. Deep learning was used to detect peanut defects. A push-broom instrument was used for testing. There were 1,560 peanuts, including 240 good and 240 bad ones. There were a total of 1,080 good peanuts and bad peanuts in the test set data, the band selection was used, and a CNN model was built. Based on the results from three methods, 3DCNN could classify with 97%accuracy. The Snapshot was used to achieve the real-time design of a lightweight CNN model. Finally, five bands were selected using PCA, and the screening could be accurate and efficient. The maximum overall accuracy was about 98.5%. Kappa was 97.3% with real-time recognition. This will be a major advantage in the future practical application and commercialization processes. This technique can reduce labor costs, achieve intelligent detection and intelligent grading, and bring breakthroughs to smart agriculture for other crops as well.

Streets are an essential element of urban safety governance and urban design, but they are designed with little regard for possible gender differences. This study proposes a safety perception evaluation method from the female perspective based on street view images (SVIs) and mobile phone data, taking the central city of Guangzhou as an example. The method relies on crowdsourced data and uses a machine learning model to predict the safety perception map. It combines the simulation of women's walking commuting paths to analyse the areas that need to be prioritised for improvement. Multiple linear regression was used to explain the relationship between safety perception and visual elements. The results showed the following: 1) There were differences in safety perceptions across genders. Women gave overall lower safety scores and more dispersed distribution of scores. 2) Approximately 11% of the streets in the study area showed weak perceived safety, and approximately 3% of these streets have high pedestrian flows and require priority improvements. 3) Safe visual elements in SVIs included the existence of roads, sidewalks, cars, railways, people, skyscrapers, and trees. Our findings can help urban designers determine how to evaluate urban safety and where to optimise key areas. Both have practical implications for urban planners seeking to create urban environments that promote greater safety.

The effect of rare earth Pr6O11 on the microstructure and mechanical properties of high-strength steel weld metal was investigated by optical microscopy, scanning electron microscopy and mechanical testing. Three different contents of Pr6O11 were added to the flux-cored wires. The results showed that the addition of 1% Pr6O11 can promote the refinement and spheroidization of inclusions, refine the grains, form acicular ferrites, and significantly improve the toughness of weld metal. The addition of Pr6O11 promoted the formation of rare earth composite inclusions and acicular ferrites in the weld metal, refined the lath microstructure, inhibited the formation of martensite and bainite. The crack formation mode changed from the boundary cracking of the bainite clusters caused by the surface shear stress to the surface shear stress-induced decohesion of inclusion. However, excessive addition of Pr6O11 will reduce the number of inclusion nucleation and deteriorate the mechanical properties. The wire No.2 with 1% Pr6O11 had the good comprehensive mechanical properties, and the corresponding values were 835MPa of tensile strength and 72 J of impact toughness. These findings suggest that the control of Pr6O11 can be an effective way to improve the impact toughness of weld metal.

With the unceasing advancement in wide-bandgap (WBG) semiconductor technology, the minimal reverse-recovery charge Qrr and other more powerful natures of WBG transistors enable totem-pole bridgeless PFC to become a dominant solution for energy storage systems (ESS). This paper focuses on design and implementation of a control structure for a totem-pole boost PFC with newfangled enhancement-mode Gallium Nitride (eGaN) FETs, not only to simplify the control implementation, but also to achieve high power quality and efficiency. The converter is designed to convert a 90-264-VAC input to a 385-VDC output for a 2.6-kW output power. Lastly, to validate the methodology, an experimental prototype is characterized and fabricated. The uttermost efficiency at 230 VAC attains 99.14%. The lowest total harmonic distortion in the current (ITHD) at high line condition (230 V) reaches 1.52% while the power factor gains 0.9985.

Lung cancer is almost the most common cause of cancer death in the world. Clinically, the conventional therapy to eradicate the cancer cells is chemotherapy but a better drug remains required. In this study, the effects of three bufadienolides, kalantuboside B, kalantuboside A and bryotoxin C, isolated from Kalanchoe tubiflora (Harvey) were evaluated and characterized in CL1-5 highly metastatic human lung cancer cells. Contrary to the apoptosis-promoting activity in other cancer cells, these three bufadienolides did not induce apoptosis in CL1-5 cancer cells. Instead, they activated an autophagy pathway, as indicated by the increase of autophagosomes formation. The induction of autophagy by these three bufadienolides was demonstrated to link to down-regulation of p-mTOR as well as up-regulation of LC3-II, ATG5, ATG7, Beclin-1. Moreover, among these three compounds, kalantuboside B in which a monosaccharide is attached at the bufadienolide aglycon, exhibited a better autophagy induction. Our findings revealed an alternative mechanism of drug action by bufadienolides in lung cancer cells and provided evidence for the possibility of treating highly metastatic human lung cancer through an autophagy pathway.

Dissolved organic matter (DOM) derived from organic fertilizers may increase soil phosphorus (P) availability. However, the frequently observed correlation between soil P availability and dissolved organic carbon (DOC) content has led to an excessive focus on DOC content at the expense of DOM properties. The present study investigated the influence of DOM characteristics on soil P availability by using a 6-year field experiment and microcosms of P sorption in paddy soil. Our results showed that partial replacement of chemical P fertilizer with manure or crop straw increased P fertilizer-use efficiency, even when decreasing chemical P input by 34 %, compared to normal chemical fertilization. The microcosm experiment demonstrated that DOM properties, rather than total DOC content, determine soil P sorption capacity, despite the significant correlation between DOC content and P availability observed in the field experiment. Manure-DOM exerted stronger inhibitory effects on P sorption than straw-DOM, and high molecular weight (HMW)-fractionated DOM exerted stronger inhibitory effects on P sorption than low-molecular-weight-fractionated DOM by 16-20%. The mechanism was rooted in the HMW DOM with unique characteristics (e.g., strong aromaticity, hydrophobicity, abundant humic-like components, carboxyl groups, and benzene ring structures) competing for soil P sorption sites (e.g., reduction in specific surface area and micropore volume), decreasing the soil surface charge (e.g., zeta potential), and thereby suppressing P sorption in paddy soil. Our study points out a promising avenue for regulating organic matter properties with organic fertilization to improve P use efficiency in agricultural soils.

Thanks to the rapid advancements in Connected and Automated Vehicles (CAVs) and vehicular communication, the concept of the Internet of Vehicles (IoV) combined with Artificial Intelligence (AI) and big data technologies promotes the vision of an Intelligent Transportation System (ITS). By enabling a comprehensive data exchange platform, ITS is critical in enhancing road safety, traffic efficiency, and the overall driving experience. However, the open and dynamic nature of IoV networks brings significant performance and security challenges to IoV data acquisition, storage, and usage. To comprehensively tackle these challenges, this paper proposes a Decentralized Digital Watermarking framework for smart Vehicular networks (D2WaVe). Specifically, D2WaVe consists of two core components: FIAE-GAN, a novel feature-integrated and attention-enhanced robust image watermarking model based on a Generative Adversarial Network (GAN), and BloVA, a Blockchain-based Video frames Authentication scheme. By leveraging an encoder-noise-decoder framework, trained FIAE-GAN watermarking models can achieve the invisibility and robustness of watermarks that can be embedded in video frames to verify the authenticity of video data. Then, BloVA ensures the integrity and auditability of IoV data in the storing and sharing stages. Experimental results based on a proof-of-concept prototype implementation validate the feasibility and effectiveness of our D2WaVe scheme for securing and auditing video data exchange in smart vehicular networks.

The movement of liquid droplets on the energy gradient surface has attracted extensive attention. Inspired by biological features in nature, such as the periodic spindle-shaped nodes in spider silks and conical-like barbs of cacti, the structure-property-function relationship of multifunctional gradient surfaces. In this study, a series of specific patterns are fabricated by 3D printing technology, followed by modification via the atmospheric pressure plasma treatment and liquid phase chemical deposition, resulting in enhancing the ability of water droplets of 5μL to travel 18.47mm on a horizontal plane and 22.75mm against gravity up to 20° tilting angle. Additionally, analysis techniques have been employed including contact angle analyzer, ESCA and laser confocal microscope to evaluate the sample performance. This work could further be applied to many applications related to microfluidic devices, drug delivery and water/fog collection.

The genus Lirianthe in the family Magnoliaceae includes approximately 25 species, each with exceptional landscaping and horticultural or medical worth. Many of these plants are considered rare and protected due to their endangered status. The limited knowledge of species within this genus and the absence of research on its chloroplast genome have greatly impeded studies on the relationship between its evolution and systematics. In this study, the chloroplast genomes of 8 species from the genus Lirianthe were sequenced and analyzed, their phylogenetic relationships with other genera of the family Magnoliaceae are also elucidated. The results showed that the chloroplast genome sizes of the 8 Lirianthe species ranged from 159,548 to 159,833 bp. The genomes consisted of a large single copy region, a small single copy region, and a pair of inverted repeat sequences. The GC content was very similar across species. Gene annotation revealed that the chloroplast genomes contained 85 protein-coding genes, 37 tRNA genes, and 8 rRNA genes, totaling 130 genes. Codon usage analysis indicated that codon usage was highly conserved among the 8 Lirianthe species. Repeat sequence analysis identified 42-49 microsatellite sequences, 16-18 tandem repeats, and 50 dispersed repeats, with microsatellite sequences being predominantly single nucleotide repeats. DNA polymorphism analysis revealed 10 highly variable regions located in the large single copy and small single copy regions, among which rpl32-trnL, petA-psbJ and trnH-psbA are recommended candidate DNA barcodes for the genus Lirianthe species. The inverted repeat boundary regions show little variation between species and are generally conserved. Phylogenetic tree analysis confirmed the monophyly of the genus Lirianthe and its closest relationship with the genera, Talauma and Dugandiodendron. Morphological studies found noticeable differences between Lirianthe species in aspects including leaf indumentum, stipule scars, floral orientation, tepal number, tepal texture, and fruit dehiscence. In summary, this study elucidated the chloroplast genome evolution within Lirianthe and laid a foundation for further systematic and taxonomic research of this genus.

Novel multifunctional fluorescent chemosensors composed of electrospun (ES) nanofibers with high sensitivity toward pH, mercury ions (Hg²⁺), and temperature were prepared from poly(N-Isopropylacrylamide-co-N-methylolacrylamide-co-rhodamine derivative) (poly(NIPAAm-co-NMA-co-RhBN2AM)) by employing electrospinning process. NIPAAm and NMA moieties provide hydrophilic and thermo-responsive properties (absorption of Hg²⁺ in aqueous solutions), and chemical cross-linking sites (stabilization of the fibrous structure in aqueous solutions), respectively. The fluorescent probe, RhBN2AM is highly sensitive toward pH and Hg²⁺. Synthesis of poly(NIPAAm-co-NMA-co-RhBN2AM) with different compositions were carried on via free-radical polymerization. ES nanofibers prepared from sensory copolymers with a 71.1:28.4:0.5 NIPAAm: NMA: RhBN2AM ratio (P3 ES nanofibers) exhibited significant color change from nonfluorescent to red fluorescence while sensing pH or Hg²⁺, and high reversibility of on/off switchable fluorescence emission when Hg²⁺ and ethylenediaminetetraacetic acid (EDTA) were sequentially added. The P3 ES nanofibrous membranes had a higher surface-to-volume ratio to enhance their performance than did the corresponding thin films. In addition, the fluorescence emission of P3 ES nanofibrous membranes exhibited second enhancement above the lower critical solution temperature. Thus, the ES nanofibrous membranes prepared from P3 with on/off switchable capacity and thermo-responsive characteristics can be used as multifunctional sensory devise for specific heavy transition metal (HTM) in aqueous solutions.

Resource and capacity constraints are common challenges for suppliers in digital transformation. This study examines the impact of government subsidies on supplier digital transformation from the perspectives of supply chain diffusion and the local government competition, with supply chain relationship data from A-share listed companies spanning 2010 to 2021. The findings indicate that: government subsidies promote suppliers to expand their diversified downstream customer base, which will boost supplier digital transformation. However, the spillover effect within the same region is higher than that across regions. The heterogeneity analysis results indicate that the effect of government subsidies becomes increasingly apparent as the opportunistic risk escalates; conversely, the impact of such subsidies is considerably constrained by heightened systemic risk. The higher the human capital of suppliers and the smaller the digital divide between suppliers and customers, the better the effect of suppliers receiving innovation diffusion. Further analysis reveals that local government subsidies to upstream suppliers reduce the proportion of downstream local customer purchases outside the jurisdiction, thereby hindering cross-regional spillover effects. This article enriches the research on the promotion mechanism of enterprise digital transformation and the efficiency loss of market segmentation, providing some reference for optimizing local government subsidy behavior.

Over the past decade, there has been a remarkable acceleration in the evolution of smart cities and intelligent spaces, driven by breakthroughs in technologies such as the Internet of Things (IoT), edge-fog-cloud computing, and machine learning (ML)/Artificial Intelligence (AI). As society begins to harness the full potential of these smart environments, the horizon brightens with the promise of an immersive, interconnected 3D world. The forthcoming paradigm shift in how we live, work, and interact owes much to groundbreaking innovations in augmented reality (AR), virtual reality (VR), extended reality (XR), Blockchain, and Digital Twins (DT). However, realizing the expansive digital vista in our daily lives is challenging. Current limitations include an incomplete integration of pivotal techniques, daunting bandwidth requirements, and the critical need for near-instantaneous data transmission, all impeding the digital VR Metaverse from fully manifesting as envisioned by its proponents. This paper seeks to delve deeply into the intricacies of the immersive, interconnected 3D realm, particularly in applications demanding high levels of intelligence. Specifically, this paper introduces Microverse, a task-oriented, edge-scale, pragmatic solution for smart cities. Unlike an all-encompassing Metaverses, each Microverse instance serves a specific task as a manageable digital twin of an individual network slice. Each Microverse enables on-site/near-site data processing, information fusion, and real-time decision-making within the edge-fog-cloud computing framework. The Microverse concept is verified using smart public safety surveillance (SPSS) for smart communities as a case study, demonstrating its feasibility in practical smart city applications. The aim is to stimulate discussions and inspire fresh ideas in our community, guiding us as we navigate the evolving digital landscape of smart cities to embrace the potential of the Metaverse.

Despite recent advancements, therapies remain ineffective against advanced oral squamous cell carcinoma (OSCC), resulting in unsatisfactory therapeutic outcomes. Cold atmospheric plasma (CAP) offers a promising approach in the treatment of malignant neoplasms. Yet, the exact mechanisms driving CAP-induced cancer cell death are not fully understood. This study revealed a significant reduction in the viability of OSCC cell lines, inactivation of AKT and ERK, and the downregulation of the miR-21, miR-31, miR-134, miR-146a and miR-211 expression followed the CAP treatment. Pretreatment with ZVAD, 3-MA, and Fer-1 synergistically reduced CAP-induced cell death, indicating a combined induction of variable death pathways by CAP. Activation of AKT and ERK, alongside combined treatments using death inhibitors and miRNA mimics, counteracted the cell mortality associated with CAP. CAP-induced downregulation of miR-21, miR-31, miR-187 and miR-211 expression was rescued by AKT and ERK activation. Additionally, CAP treatments notably inhibited the growth of SAS cell xenografts on nude mice. The reduced expression of oncogenic miRNAs in vivo aligned with in vitro findings. In conclusion, our study indicates that CAP jet treatment diminishes OSCC cell viability by abrogating survival signals and oncogenic miRNA expression.

Concussion, also known as mild traumatic brain injury (mTBI), commonly causes transient neurocognitive symptoms, but in some cases, it causes cognitive impairment, including working memory (WM) deficit, which can be long-lasting and impede a patient’s return to work. The predictors of long-term cognitive outcomes following mTBI remain unclear because abnormality is often absent in structural imaging findings. The purpose of the study was to determine whether machine learning-based models using functional magnetic resonance imaging (fMRI) biomarkers and demographic or neuropsychological measures at baseline could effectively predict 1-year cognitive outcomes of concussion. We conducted a prospective, observational study of patients with mTBI who were compared with demographically-matched healthy controls enrolled between September 2015 to August 2020. Baseline assessments were collected within the first week of injury, and follow-ups were conducted at 6 weeks, 3 months, 6 months, and 1 year. Potential demographic, neuropsychological, and fMRI features were selected according to the significance of correlation with the estimated changes in WM ability. The support vector machine classifier was trained using these potential features and estimated changes in WM between the predefined time periods. Patients demonstrated significant cognitive recovery at the third month, followed by worsened performance after 6 months, which persisted until 1 year after concussion. Approximately half of the patients experienced prolonged cognitive impairment at 1-year follow up. Satisfactory predictions were achieved for patients whose WM function did not recover at 3 months (accuracy=87.5%), 6 months (accuracy=83.3%), 1 year (accuracy=83.3%), and performed worse at 1-year follow-up compared to baseline assessment (accuracy=83.3%). This study demonstrated the feasibility of personalized prediction for long-term postconcussive WM outcomes based on baseline fMRI and demographic features, opening a new avenue for early rehabilitation intervention in selected individuals with possible poor long-term cognitive outcomes.

High-strength low-alloy steels (HSLAs) are widely used in the structural body components of many domestic motor vehicles owing to their better mechanical properties and greater resistance. The real production process of HSLA steelmaking can be regarded as a model that builds on the relationship between process parameters and product quality attributes. A surrogate modeling method is used, and the resulting production process model can be applied to predict the optimal manufacturing process parameters. We used different methods in this paper to build such a surrogate model, including linear regression, random forests, support vector regression, multilayer perception, and a simplified VGG model. We then applied three bio-inspired search algorithms, namely particle swarm optimization, the artificial bee colony algorithm, and the firefly algorithm, to search for the optimal controllable manufacturing process parameters. Through experiments on 9,000 test samples used for building the surrogate model, and 299 test samples for making the optimal process parameter selection, we found that the combination of a simplified VGG model and the firefly algorithm was the most successful at reaching a success rate of 100%—in other words, when the product quality attributes of all test samples satisfy the mechanical requirements of the end products.

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. 3D pharmacophore models are powerful computational tools in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning will be highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

The objective of this study aimed to develop biodegradable calcium alginate microspheres carrying doxorubicin (Dox) at the micrometer-scale for sustained-release and the capacity of pH regulatory for transarterial chemoembolization. Ultrasonic atomization and CaCl2 cross-linking technologies were used to prepare the microspheres. A 4 by 5 experiment was first designed to identify imperative parameters. The concentration of CaCl2 and the flow rate of the pump were found to be critical to generate microspheres with a constant volume median diameter (~ 39 m) across 5 groups with different alginate:NaHCO3 ratios using each corresponding flow rate. In each group, the encapsulation efficiency was positively correlated to the Dox-loaded efficiency. Fourier-transform infrared spectroscopy showed that NaHCO3 and Dox were step-by-step incorporated into the calcium alginate microspheres successfully. Microspheres containing alginate:NaHCO3 = 1 exhibited rough and porous surfaces, high Young’s modulus and hardness. In each group with the same alginate:NaHCO3 ratio, the swelling rates of microspheres were higher in PBS containing 10% FBS compared to those in PBS alone. Microspheres with relative high NaHCO3 concentrations in PBS containing 10% FBS maintained better physiological pH and higher accumulated Dox release ratios. In two distinct hepatocellular carcinoma-derived cell lines, treatments with microspheres carrying Dox demonstrated that the cell viabilities decreased in groups with relative high NaHCO3 ratios in time- and dose-dependent manners. Our results suggested that biodegradable alginate microspheres containing relative high NaHCO3 concentrations improved the cytotoxicity effects in vitro.

In kidney, epithelial barrier has diverse functions in body fluid and electrolyte homeostasis, and urine production. Maintaining epithelial integrity fundamentally builds up physiological functionality of the renal epithelial barrier (REB). Specially, the REB) states regularly in osmotic dynamics. The osmotic dynamics gives rise of osmotic pressure that is a physical force. Overloading of osmotic pressure can crack epithelial integrity and damage REB. How REB endures the osmotic pressure force yet remains enigmatic. LMO7 (LIM domain only 7) is a protein associated with cell-cell junctional complex and cortical F-actin. LMO7 upregulation was observed in cells cultured in hypertonic condition. In kidney, LMO7 predominantly distributes in epithelial cells in renal tubules. Hypertonic stimulation leads to assembly of LMO7 and F-actin in cortical stress fibers in renal epithelial cells. Hypertonic-isotonic alternation as pressure force pushing plasma membrane inward/outward was set as osmotic disturbance and was applied to test FAK signaling and LMO7 functioning in maintaining junctional integrity. Along with junctional integrity, LMO7 depleted cells resulted in loss of junctional integrity in the epithelial sheet cultured hypertonic medium or hypertonic-isotonic alternation. On the other hand, FAK inhibited by PF-573228 leads to failure in robust cortical F-actin assembly and association of LMO7 with cortical F-actin in epithelial cells responding upon hypertonic stress. Epithelial integrity in context of osmotic stress, LMO7 and FAK signaling both involves in assembling robust cortical F-actin and maintaining junctional integrity. The LMO7 elaborately manages FAK activation in renal epithelial cells, which was evidently demonstrated in NRK-52E cells who have excessive FAK activation and lost epithelial integrity when cells with LMO7 depletion exposed to hypertonic environment. Our data suggests that LOM7 manages FAK activation and is responsible for maintaining REB under osmotic disturbance.

Magnesium and its alloys are not normally used as bio-resorbable temporary implants due to their high and uncontrolled degradation rate in physiological liquid environment. The improvement of corrosion resistance to simulated body fluids (SBF) of a Magnesium alloy (AZ31) coated with poly-β-hydroxybutyrate (PHB) was investigated. Scanning electron microscopy, Fourier transform infrared spectrometer, and contact angle measurements were used to characterize surface morphology, material composition and wettability, respectively. pH modification of the SBF corroding medium, mass of Mg2+ ions released, and weight loss of the samples exposed to the SBF solution, and electrochemical experiment were used to describe the corrosion process and its kinetics. Materials biocompatibility was described by evaluating the effect of corrosion by products collected in the SBF equilibrating solution on hemolysis ratio, cytotoxicity, Nitric Oxide (NO), and total antioxidant capacity (T-AOC). The results showed that the PHB coating can diffusively control the degradation rate of Magnesium alloy improving its biocompatibility: hemolysis rate of materials was lower than 5%, while in vitro Human Umbilical Vein Endothelial Cells（HUVECs) compatibility experiments showed that PHB coated Mg alloy promoted cell proliferation and had no effect on the NO content, the T-AOC was enhanced compared with the normal group and bare AZ31 alloy. PHB coated AZ31 Magnesium alloy extraction fluids have a less toxic behavior due to the lower concentration of corrosion by-products deriving from the diffusion control exerted by the PHB coating films both from metal surface to the solution and vice versa. These findings provide more reference value for the selection of such system as tunable bioresorbable prosthetic materials

Metaverse represents a multifaceted digital universe integrating diverse technologies to create immersive, interconnected virtual environments. Key components foundational to its structure include the infrastructure layer for hardware and network support, the human interface layer utilizing virtual reality (VR) and augmented reality (AR) devices, and a decentralized layer leveraging blockchain for secure digital asset management. Further components encompass spatial computing for realistic 3D environments, the creator economy for content generation and monetization, and discovery mechanisms for navigation within Metaverse. VR, AR, blockchain, AI, the fifth-generation (5G) networks, and the Internet of Things (IoT) are central to Metaverse functionality, enabling real-time interactions and data integration. Real-Time Metaverse aims to replicate instantaneous real-world interactions, requiring advanced technological infrastructure for seamless data exchange. Critical challenges include ensuring low latency, high bandwidth, scalability, and robust security measures. Metaverse’s potential spans various domains, promising to revolutionize social interactions, entertainment, workplaces, and education through dynamic, immersive experiences. Ongoing advancements in high-performance computing, cloud services, and AI-driven technologies are essential for addressing existing barriers and achieving a cohesive, secure, and inclusive Metaverse ecosystem. Future research must focus on enhancing user experience, accessibility, and standardized interoperability to fully realize the transformative capabilities of a Metaverse.

This study evaluates the incidence and characteristics of adverse events (AEs) following the second COVID-19 booster dose, leveraging Taiwan's distinctive approach of extending booster vaccinations to all citizens, unlike the targeted high-risk group strategies in other countries. Utilizing data from Taipei Veterans General Hospital's Vaccine Adverse Event Reporting System (VAERS) from October 27, 2022, to January 19, 2023, the research examines AEs in 441 out of 1711 second booster recipients, considering factors like age, vaccine brands, and booster combinations. The findings reveal incidence rates (IR) of 25.6% (95% CI: 21.1-30.8) after the first booster and 24.9% (95% CI: 20.5-30.0) after the second, mostly non-serious, with those having AEs post-first booster 5 times more likely to report them again (Incidence rat rato, 5.02, P&lt;0.001). Significantly, switching from the mRNA1273 vaccine to another brand reduced AE risk by 18%. The study underscores that AEs are more repetitive than cumulative with additional booster doses, advocating for personalized vaccination strategies based on individual medical histories and previous vaccine reactions. These insights are valuable for healthcare providers in discussing potential AEs with patients, thereby improving vaccine compliance and public trust, and for policymakers in planning future booster vaccination strategies.

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.

B4GALNT2 is a vital candidate gene that affects the growth traits litter size in and growth traits of sheep, but whether it has the same function in goats remains to be further investigated. In this study, we utilized 348 Nanjiang Yellow goats as experimental subjects, conducted a whole exon, and the conserved the non-coding region SNP scanning of the B4GALNT2 gene. Our results revealed the presence of a synonymous mutation, rs672215506, within the exon of the B4GALNT2 gene in the Nanjiang Yellow goat population. This mutation was found to be associated with reduced mRNA stability of the B4GALNT2 gene. The results of SNPs detection of conserved non-coding region of B4GALNT2 gene showed that there were five potential regulatory SNPs in the Nanjiang Yellow goat population, except for rs66095343, the ~500 bp fragments of four SNPs (rs649127714, rs649573228, rs652899012 and rs639183528) could significantly increase luciferase activity both in goat skeletal muscle cells and 293T cells . Genetic diversity indexes indicated low or intermediate levels for all six SNPs analyzed, each conforming to Hardy-Weinberg equilibrium regarding genotypic frequencies. Association analysis indicated that rs660965343, rs649127714 and rs649573228 were significantly correlated with growth traits in the later stage of growth and development of Nanjiang Yellow goat. The haplotype combinations of H2H3 and H2H2 had higher body weight and greater body size; moreover, H2H2 haplotype combinations were significantly correlated with the litter size of Nanjiang Yellow goat. The results of our study demonstrate the potential utility of the B4GALNT2 gene as a functional genetic marker in breeding programs for Nanjiang Yellow goats.

With the continuous update of gene editing technology, great progress has been made in livestock breeding, researchers have produced gene edited pigs, cattle, sheep and other improved livestock. Gene editing technology is a genetic means to knock in, knock out, delete, inhibit, activate or replace specific bases of DNA or RNA sequences at the genome level to achieve accurate modification, and can edit genes at a fixed point without the need for DNA templates. In recent years, although regular clusters of interspaced short palindromic repeats (CRISPR)/Cas9 system mediated gene editing technology has been widely used in animal genetic breeding research, but so far, the system's precise insertion efficiency of foreign genes is not high enough, and there are certain off-target effects, and it is not enough to be used in genome editing of large livestock such as cashmere goats. In this paper, the development status, challenges, application prospects and look into the distance of CRISPR/ Cas9-mediated precisiongene editing technology in livestock breeding were reviewed, in order to provide theoretical reference for livestock gene function analysis, genetic improvement and livestock breeding with local economic characteristics.

Colonoscopy, essential for diagnosing and treating colorectal cancer, relies on effective bowel preparation to inspect the colonic mucosa fully. Traditional education methods include printed instructions and verbal explanations, but these may not ensure clear patient understanding. Poor bowel preparation can obscure mucosal visibility, delaying cancer diagnosis and treatment. Using the outpatient’s Android mobile device, the mobile health care model is provided as a nursing guide to assist in bowel preparation for colonoscopy. This single-blinded, randomized trial en-rolled patients for colonoscopy at a Northern Taiwan gastroenterology center. Eligible patients were physically and mentally healthy and could communicate in Chinese. The study tested the ColonClean app during bowel preparation. After the procedure, endoscopists rated the prepara-tion quality using the Aronchick Scale. Data analysis with SPSS software (version 25.0) evaluated if the app significantly improved bowel preparation compared to those who did not use it. Forty patients were recruited for both the control (conventional method) and experimental (conven-tional method plus ColonClean app) groups. In the experimental group, endoscopists assessed bowel preparation quality; all achieved at least "Fair," with 75% receiving "Excellent" or "Good" ratings. The ColonClean App enhanced bowel preparation quality more effectively than tradi-tional nursing guidance.

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

Mercury (Hg) is a toxic element impacting on biological systems and ecosystems. Because the toxicity of Hg species is highly dependent on concentration levels and chemical forms, sensitive identification of chemical forms for Hg, i.e., Hg speciation, is of major significance in providing meaningful information about the source of Hg exposure. In this study, a microfluidic-based device made of high clarity poly(methyl methacrylate) (PMMA) was fabricated. Then titanium dioxide nanoparticles (nano-TiO2) were attached to the treated channel interior with the aid of poly(diallyldimethylammonium chloride) (PDADMAC). After coupling the nano-TiO2-coated microfluidic-based photocatalyst-assisted reduction device (the nano-TiO2-coated microfluid-ic-based PCARD) with high-performance liquid chromatography (HPLC) and inductively coupled plasma-mass spectrometry (ICP-MS), a selective and sensitive hyphenated system for Hg specia-tion was established. Validation procedures demonstrated that the method could be satisfactorily applied to the determination of mercuric ion (Hg2+) and methylmercury ion (CH3Hg+) in both human urine and water samples. Remarkably, the zeta potential measured clearly indicated the PDADMAC-capped nano-TiO2 with predominance of positive charges indeed provided steady force for firm attachment to the negatively charged device channel. The cause for the durability of the nano-TiO2-coated microfluidic-based PCARD was clarified thus.

The unique structure of G4.0 PAMAM dendrimers allows the drug to be enclosed in internal spaces or immobilized on the surface. In the conducted research, the conditions for the formation of the active G4.0 PAMAM complex with doxorubicin (DOX) were optimized. The physicochemical properties of the system were monitored using DLS, CD, and fluorescence spectroscopy. The QCM-D method was chosen to determine the preferential conditions for the complex formation. The highest binding efficiency of the drug to the cationic dendrimer was observed under basic conditions when the DOX molecule was deprotonated. The decrease in the zeta potential of the complex confirms that DOX immobilizes through electrostatic interaction with the carrier's surface amine groups. The binding constants were determined from the fluorescence quenching of the DOX molecule in the presence of G4.0 PAMAM. The two-fold way of binding doxorubicin in the structure of dendrimers was visible in the ITC isotherm. Fluorescence spectra and release curves identified reversible binding of DOX to the nanocarrier. Among the selected cancer cells, the most promising anticancer activity of G4.0-DOX was observed in A375 malignant melanoma cells. Moreover, the preferred intracellular location of the complexes concerning the free drug was found, which is important from a therapeutic point of view.

Insulin-like Growth Factor 2 mRNA binding Protein 1 (IGF2BP1) is a promising candidate gene for influencing economic traits in livestock and poultry. The second intronic region of IGF2BP1 is closely related to growth traits, although the exact mechanism remains unclear. The preliminary resequencing results of goats in our laboratory demonstrated that the IGF2BP1 gene region was subject to strong selection, then we selected multiple single nucleotide polymorphisms (SNPs) to identify. Seven SNPs were located in the conserved region of the second intron, and their functions and relationship with growth traits require further clarification. This study selected 348 Nanjiang Yellow goats as experimental subjects, and chose Time of Flight Mass Spectrometer (MALDI-TOF) as the main method. Our results showed that six SNPs were significantly correlated with the growth traits of the Nanjiang yellow goat by association analysis. Among them, the rs652062749(A>G) was identified as the primary locus affecting the later stage of growth traits of Nanjiang yellow goat. Moreover, there was a strong linkage among three SNPs, and the rs638185407 (T>A) mutant type was observed to increase the luciferase activity in H293T cells extremely significantly. The TTAACT, TTCCCC, and ATCACT combination genotypes were dominant combination genotypes, which provided theoretical references for further genetic co-breeding. The results of our study demonstrate the potential role of the IGF2BP1 gene as a functional genetic marker in the breeding programs of Nanjiang Yellow goats.

Antibacterial bone cements (ABCs), such as antibiotic-loaded bone cements (ALBCs), have been widely utilized in clinical treatments. Currently, bone cements loaded with vancomycin, gentamicin, tobramycin, or clindamycin are approved by the US Food and Drug Administration. However, traditional ALBCs exhibit drawbacks like burst release and bacterial resistance. Therefore, there is a demand for the development of antibacterial bone cements containing novel agents. In this review, we summarize the latest advancements in ABCs. More importantly, we provide an overview and outlook on novel antibacterial agent-loaded bone cements, including metallic antibacterial agents, pH-switchable antibacterial agents, cationic polymers, N-halamines, non-leaching acrylic monomers, antimicrobial peptides, etc. Offering novel perspectives for designing ABCs and treating bone infections.