The aim of this study was to assess the best timing to perform arthrocentesis in the management of temporomandibular disorders with regards to conservative treatment. A systematic search based on PRISMA guidelines, including a computer search with specific keywords, reference list search, and manual search was done. Relevant articles were selected after 3 search rounds for final review based on 6 predefined inclusion criteria, followed by a round of critical appraisal. Eleven publications, including 5 randomized controlled trials and 6 prospective clinical studies informed this review. The studies were divided into 3 groups based on the timing of arthrocentesis: 1). Arthrocentesis as the initial treatment, 2). Early arthrocentesis, and 3). Late arthrocentesis. Meta-analyses compared the efficacy of improvement in mouth opening and pain reduction in the 3 groups. The results were statistically significant and favoured early arthrocentesis, followed by late arthrocentesis in terms of both improvements in mouth opening and pain reduction. All 3 groups showed improvement in mouth opening and pain reduction. We conclude that early arthrocentesis may be able to produce the best clinical results, while arthrocentesis before attempting conservative treatment may produce less favourable outcomes.

Background: Platelets are increasingly recognised for their multifaceted roles in inflammation beyond their traditional involvement in haemostasis. This review consolidates knowledge on platelets as critical players in inflammatory responses. Methods: This study did an extensive search of electronic databases and identified studies on platelets in inflammation, focusing on molecular mechanisms, cell interactions, and clinical implications, emphasising recent publications. Results: Platelets contribute to inflammation via surface receptors, release of mediators, and participation in neutrophil extracellular trap formation. They are implicated in diseases like atherosclerosis, rheumatoid arthritis, and sepsis, highlighting their interaction with immune cells as pivotal in the onset and resolution of inflammation. Conclusion: Platelets are central to regulating inflammation, offering new therapeutic targets for inflammatory diseases. Future research should explore specific molecular pathways of platelets in inflammation for therapeutic intervention.

This review article delves into the multifaceted nature of primary ovarian insufficiency (POI), a condition marked by diminished ovarian function before age 40, underscoring the complexity of its aetiology encompassing genetic, autoimmune, infectious, and environmental factors. A significant focus is placed on the potential role of single-gene mutations, such as those in FMR1, BMP15, and GDF9, in the pathogenesis of POI, highlighting the intricate interplay between genetics and ovarian health. The article also explores innovative therapeutic avenues, including the activation of dormant follicles in vitro, offering hope for fertility restoration in affected individuals. Despite the prevalence of traditional treatments, such as Chinese medicine and hormone therapy, in China, these approaches often need to meet therapeutic needs, underscoring the urgency for advanced research and tailored treatment strategies. The discovery of a pituitary tumour-associated POI case further complicates the diagnostic landscape, suggesting a broader diagnostic lens and more in-depth research to unravel the complex underpinnings of POI and enhance patient care.

The management of vision-threatening retinal diseases remains challenging due to the lack of an effective drug delivery system. Encapsulated cell therapy (ECT) offers a promising approach for the continuous delivery of therapeutic agents without the need for immunosuppressants. In this context, an injectable and terminable collagen-alginate composite (CAC) ECT gel, designed with a Tet-on pro-caspase-8 system, was developed as a safe intraocular drug delivery platform for the sustained release of glial cell line-derived neurotrophic factor (GDNF) to treat retinal degenerative diseases (RDDs). This study examined the potential clinical application of the CAC ECT gel, focusing on its safety, performance, and termination through doxycycline (Dox) administration in the eyes of healthy New Zealand White rabbits, as well as its therapeutic efficacy in rabbits with sodium iodate (SI)-induced retinal degeneration. The findings indicated that CAC ECT gel can be safely implanted without harming the retina or lens, displaying resistance to degradation, facilitating cell attachment, and secreting bioactive GDNF. Furthermore, the GDNF levels could be modulated by the number of implants. Moreover, Dox administration was effective in terminating gel function without causing retinal damage. Notably, rabbits with retinal degeneration treated with the gels exhibited significant functional recovery in both a-wave and b-wave amplitudes and showed remarkable efficacy in reducing photoreceptor apoptosis. Given its biocompatibility, mechanical stability, controlled drug release, terminability, and therapeutic effectiveness, our CAC ECT gel presents a promising therapeutic strategy for various retinal diseases in a clinical setting, eliminating the need for immunosuppressants.

In order to correct attenuated millimeter-wavelength (Ka-band) radar data and address the problem of instability, an attenuation correction methodology (attenuation correction with variation trend constraint; VTC) was developed. Using synchronous observation conditions and multi-band radars, the VTC method adopts the variation trends of reflectivity in X-band radar data captured with wavelet transform as a constraint to adjust reflectivity factors of millimeter-wavelength radar. The correction was evaluated by comparing reflectivities obtained by millimeter-wavelength cloud radar and X-band weather radar. Experiments showed that attenuation was a major contributory factor in the different reflectivities of the two radars when relatively intense echoes exist, and the attenuation correction developed in this study significantly improved data quality for millimeter-wavelength radar. Reflectivity differences between the two radars were reduced and reflectivity correlations were enhanced. Errors caused by attenuation were eliminated, while variation details in the reflectivity factors were retained. The VTC method is superior to the bin-by-bin method in terms of correction amplitude and can be used for attenuation correction of shorter wavelength radar assisted by longer wavelength radar data.

Atopic dermatitis (AD) is a chronic inflammatory condition which significantly affects quality of life in both patients and their caregivers. Calcineurin inhibitors (CNI) are a class of immunosuppressive drugs predominantly inhibiting T cell mediated immune processes. CNI form complex by binding with immunophilins and in turn inhibit calcineurin and suppress downstream inflammatory pathway. Tacrolimus and pimecrolimus are topical CNI approved for the treatment of mild to severe AD in both children and adults. Application site reactions are frequently seen. They have been issued with black box warning towards increased risk of malignancies but supportive evidence is lacking. Cyclosporine, though highly effective, is used off-label for AD management. It is used for controlling acute flares of AD due to its very rapid onset of action. Nephrotoxicity and hypertension are its serious complications. CNI have not been reported with teratogenicity and may be used conditionally during pregnancy and lactation.

Objective: The long-term care insurance (LTCI) system was introduced in 2000 to provide financial support for long-term care services to older adults. What is known on this topic report focuses on a comparative analysis of how the LTCI system has affected older people in Japan. Methods: We obtained data from the literature about the LTCI system, compared and analysed the collected articles, and concluded. Results: The LTCI system has improved access to long-term care services, with more older adults receiving care than before the system’s implementation. This service has improved the quality of life for many elderly individuals who require assistance with daily activities. Furthermore, the LTCI system has alleviated the financial burden of long-term care services since the insurance covers a large portion of the costs. It has made older adults maintain their independence and dignity, as they can afford the necessary care without relying solely on their savings or burdening their families. Conclusions: Japan’s LTCI system has positively impacted older adults by improving access to long-term care services and alleviating financial burdens. However, challenges such as increasing demand and variations in service quality need to be addressed to ensure the system effectively supports older people in Japan.

In recent years, wireless networks have undoubtedly become a convenient way to connect to the Internet and provide connection to everyone in any corner of the world. In fact, in this era, people are connected to the internet almost everyday and wireless networks give us this privilege in a seamless manner. A wireless network normally consists of access points and nodes where the access points are responsible to amplify the wireless signals, while the nodes are the gadgets that are receiving these signals. However, with such great convenience provided, many challenges are also faced by the users and stakeholders. With no physical connection to devices, wireless networks are evidently more vulnerable to invisible cyber attacks. In this research paper, it the security issues that cause issues in the wireless networks are discussed. Furthermore, an analytical review of privacy challenges found in these networks is performed; these challenges are segregated into security issues and privacy issues. The paper will then present the methods used in conducting a survey and gathering the research results along with further discussion on the results obtained through this study. Finally, a suitable solution is proposed to prevent and overcome the intrusions faced in terms of security and privacy in wireless network scenarios through detection and response mechanism for mitigation of the problems.

The emergence of SARS-CoV-2 mutations pose significant challenges to diagnostic tests as these mutations can reduce the sensitivity of commonly used RT-PCR assays. Therefore, there is a need to design diagnostic assays with multiple targets to enhance sensitivity. In this study, we identified a novel diagnostic target, nsp10 gene, using nanopore sequencing. Firstly, we determined the analytical sensitivity and specificity of our COVID-19-nsp10 assay. The COVID-19-nsp10 assay had the limit of detection of 74 copies/mL (95% confidence interval: 48-299 copies/mL) and did not show cross-reactivity with other respiratory viruses. Next, we determined the diagnostic performance of the COVID-19-nsp10 assay using 261 respiratory specimens, including 147 SARS-CoV-2-positive specimens belonging to ancestral strain and Alpha, Beta, Gamma, Delta, Mu, Eta, Kappa, Theta and Omicron lineages. Using the LightMix E-gene RT-PCR assay as the reference method, the diagnostic sensitivity and specificity of the COVID-19-nsp10 assay were 100%. The median Cp values for the LightMix E-gene RT-PCR and our COVID-19-nsp10 RT-PCR were 22.48 (range: 12.95-36.60) and 25.94 (range 16.37-36.87), respectively. The Cp values of the COVID-19-nsp10 RT-PCR assay correlated well with those of the LightMix E-gene RT-PCR assay (Spearman’s ρ = 0.968; P<0.0001). In conclusion, nsp10 is a suitable target for SARS-CoV-2 RT-PCR assay.

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

In this COVID-19 pandemic, the use and dependency on Internet has grown exponentially. The number of people doing online activities such as e-learning, remote working, online shopping and others have increased. This has also led to increased vulnerability to cyber crimes. Cyber security attacks have become a serious problem. The common types of cyber security attacks are phishing, malware, ransomware, social engineering, identity theft and denial-of-service. The attackers target the victims in order to get their credential information or financial benefits. Those people who are doing online activities are vulnerable to cyber threats. This is because the network is not safe. The attackers are able to code according to the weaknesses of the Internet. Once the attackers hack into the devices, they have the root access and can do whatever they want to do with the device. In this research paper, the concept of cyber security attack and detailed research about real attacks are discussed. This is followed by detailed review about the recent cyber security attacks with a critical analysis. Moreover, the research paper will be proposing the latest research contribution of cyber security during COVID-19 and the implementation scenario which will give the examples about how the companies maintain privacy as well as the limitations. Then, the paper will be discussing the reasons that people are vulnerable to cyber security and the unique solution to the problems stated. Finally, this paper will conclude with an in-depth analysis and future direction for cyber security research.

Tao and Ming (name) or Tao and Yan (language or speech) is an inseparable pair of important concepts in traditional Chinese language philosophy. In LaoTze’s opinion, Tao could not be spoken out, and language or speech could not reach Tao’s essence. Yan and Tao are separated from each other, and they are paradoxical. All the confusion derives from Yan regardless of how delicate they are. Tao can be expressed in words, but it will never be expressed through common languages. In this article, Tao is regarded as a human being’s thoughts or intentions and is even considered to be the origin of the real world. Language can express people’s thought, although it has some limitations. There exist some contradictions between the real word and the world expressed in words. To enable people to better understand the existence of the real world from multiple perspectives at the language or linguistic level without being constrained by words, this article studies LaoTze’s linguistic philosophy reflected in his opinion on the relationship between Tao and Yan and makes a comparative analysis of modern Western language philosophers’ stand on language (or speech) and existence.

To understand the health impacts of “hikikomori” lifestyle and to establish its first comprehensive health profile, a cross-sectional study was designed to measure how well the cases of hikikomori youths of Hong Kong were living, in terms of social, mental and physical aspects. This study involved 104 eligible participants at age 19.02 year-old who had completed the set of questionnaires and a series of anthropometric and physical health measurements. Despite SF36 score of 84.0 indicated good physical functioning in general, participants were lived sedentarily with high incidence of hypertension at 15.4% and prehypertension at 31.7%. Occurrence of hypertension in cases living as hikikomori >6 months was 3-times higher than those newly onset cases. The blood pressure levels were correlated with age and all obesity index parameters measured including waist circumference and body mass index. Half of the hypertensive cases involved the elevation of systolic blood pressure, which suggested higher odds of cardiovascular complications. Participants were mentally stable living with moderate levels of perceived stress and state anxiety, but borderline clinical depression. In conclusion, the hikikomori lifestyle could be a risk behavior that may harm the younger generation physically by promoting obesity and hypertension and probably other chronic illnesses.

MicroRNAs (miRNAs), particularly miR-16 and miR-21, play a crucial role in mul-tiple myeloma (MM) pathogenesis by regulating gene expression. This study evalu-ated the prognostic significance of circulating miR-16 and miR-21 expression levels in 48 patients with MM at diagnosis treated with lenalidomide/dexamethasone (LD) compared with 15 healthy individuals (HI). All patients were treated with LD, 13 at first line and 35 at relapse, of whom 21 were tested twice at diagnosis and before LD initiation. The results revealed significantly lower levels of miR-16 and miR-21 in patients than in HIs, both at diagnosis and relapse, with decreased miR-16 levels at diagnosis, indicating improved overall survival (OS) (p value 0.024). Furthermore, miR-16 and miR-21 levels were associated with disease markers, while both corre-lated with the depth of response and mir-16 with sustained response to LD treatment. The ratios of both miR-16 and miR-21 expression levels (prior to LD treat-ment/diagnosis) below 2 predicted a shorter time to response (P = 0.027) and a longer time to next treatment (P = 0.042), respectively. These findings suggested a prognostic value for serum miR-16 and miR-21 levels in MM, as their expression levels corre-lated with disease variables and treatment outcomes.

Temporomandibular disorders (TMD) is a group of orofacial pain conditions which is the most common non-dental pain complaint in the maxillofacial region. Due to the complexity of the etiology and often cyclical nature of the disease, the diagnosis and management of TMD remain a challenge where consensus is still lacking in many aspects. While clinical examination is considered the most important process in the diagnosis of TMD, imaging may serve as a valuable adjunct in selected cases. Depending on the type of TMD, many treatment modalities have been proposed, ranging from conservative options to open surgical procedures. In this review, the authors discuss the present thinking in the etiology and classification of TMD, followed by the diagnostic approach and the current trend and controversies in management.

Archaea are an essential class of gut microorganisms in humans and animals. Despite the substantial progress in gut microbiome research in the last decade, most studies have focused on bacteria, and little is known about archaea in mammals. In this study, we investigated the composition, diversity, and functional potential of gut archaeal communities in pigs by re-analyzing a published metagenomic dataset including a total of 276 fecal samples from three countries: China (n=76), Denmark (n=100), and France (n=100). For alpha diversity (Shannon Index) of the archaeal communities, Chinese pigs were less diverse than Danish and French pigs (P<0.001). Consistently, Chinese pigs also possessed different archaeal community structures from the other two groups based on the Bray-Curtis distance matrix. Methanobrevibacter was the most dominant archaeal genus in Chinese pigs (44.94%) and French pigs (15.41%), while Candidatus Methanomethylophilus was the most predominant in Danish pigs (15.71%). At the species level, the relative abundance of Candidatus Methanomethylophilus alvus, Natrialbaceae archaeon XQ INN 246, and Methanobrevibacter gottschalkii were greatest in Danish, French, and Chinese pigs with a relative abundance of 14.32%, 11.67%, and 16.28%, respectively. In terms of metabolic potential, the top three pathways in the archaeal communities included the MetaCyc pathway related to the biosynthesis of L-valine, L-isoleucine, and isobutanol. Interestingly, the pathway related to hydrogen consumption (METHANOGENESIS-PWY) was only observed in archaeal reads, while the pathways participating in hydrogen production (FERMENTATION-PWY and PWY4LZ-257) were only detected in bacterial reads. Archaeal communities also possessed CAZyme gene families, with the top five being: AA3, GH43, GT2, AA6, and CE9. In terms of antibiotic resistance genes (ARGs), the class of multidrug resistance was the most abundant ARG, accounting for 87.41% of archaeal ARG hits. Our study reveals the diverse composition and metabolic functions of archaea in pigs, suggesting that archaea might play important roles in swine nutrition and metabolism.

Information encryption and anti-counterfeiting play an important role in many aspects of daily life, such as in minimizing economic losses, protecting secure communication and public security, and so on. Owing to the high information capacity and ease of operation, luminescent materials for advanced information encryption and anti-counterfeiting are essential to meet the increasing demand on encryption security. Herein, we summarize two emerging luminescent materials for information encryption and anti-counterfeiting, the AIE materials and room-temperature phosphorescent materials. At last, we discuss the opportunities and anticipations of these two information encryption and anti-counterfeiting materials.

Li-rich layered oxide cathode materials have become one of the most promising cathode materials for high-energy-density lithium-ion batteries owning to its high theoretical specific capacity, low cost, high operating voltage and environmental friendliness. Yet they suffer from severe capacity and voltage attenuation during prolong cycling, which blocks their commercial application. To clarify these causes, we synthesize 0.5Li2MnO3·0.5LiNi0.8Co0.1Mn0.1O2 (LL-811) with high-nickel-content cathode material by a solid-sate complexation method, and it manifests a lot slower capacity and voltage attenuation during prolong cycling compared to LL-111 and LL-523 cathode materials. The capacity retention at 1C after 100 cycles reaches to 87.5% and the voltage attenuation after 100 cycles is only 0.460 V. Combining X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscopy (TEM), it indicates that increasing the nickel content not only stabilizes the structure but also alleviates the attenuation of capacity and voltage. Therefore, it provides a new idea for designing of Li-rich layered oxide cathode materials that suppress voltage and capacity attenuation.

In this study, a field experiment was conducted to evaluate the growth and yield responses of Sri Lankan lowland rice (Oryza sativa L.) with the application of beneficial Arbuscular mycorrhizal fungi (AMF) inoculum, and inter-cropping with highly mycorrhizal dependent vetiver grass (Chrysopogon zizanioides L.) under two different soil nutrient management systems (NMSs): conventional/chemical (CNMS) and organic (ONMS). The experiment was designed as a split plot with three blocks. Each CNMS and ONMS experiment included untreated control (T0), and three treatments—AMF inoculation (T1), vetiver intercropping (T2), and the combination of AMF and vetiver (T3). According to the results, colonization of rice roots with AMF was not affected significantly by the treatments and ranged from 0‒15.8%. The effect was very low or absent in the early stage and then higher in the later stages of the rice plant. Furthermore, plant growth was not significantly different between the two NMSs, although grain yield was significantly higher (P &lt; 0.05), with the order T1 (0.45 kg/m2) &gt;T2 (0.42 kg/m2) &gt;T3 (0.41 kg/m2) in CNMS and T2 (0.44 kg/m2) &gt;T1 (0.41 kg/m2) &gt;T3 (0.40 kg/m2), in ONMS than for the respective controls (T0), thus suggesting beneficial utilization of AMF and vetiver in the lowland rice farming system.

3,4-Dihydroquinolin-2(1H)-ones represent a class of valuable bioactive compounds with six-membered nitrogen-containing heterocyclic structures. The development of simple, mild and efficient synthetic methods has been widely concerned by synthetic chemists. In this review, we have summarized a series of different synthetic strategies for the synthesis of dihydroquinoline-2(1H)-ones via catalytic annulation of α,β-unsaturated N-arylamides in the past decade, including covering electrophilic cyclization, radical initiated cyclization and photochemical cyclization reactions. Besides, the substrate scope and mechanistic details are also discussed. This paper will provide a useful reference for the development of diverse synthesis methodologies of 3,4-dihydroquinolin-2(1H)-ones.

During an interdisciplinary study of the mire “Pod Małym Śnieżnikiem”, a very old specimen of the Norway spruce (Picea abies L.) was encountered. The aim of the present work was to perform a detailed examination of this tree, to compare it to other spruce trees on the mire, and to provide support for establishing protection for this tree stand. Tree-ring cores were sampled at 1.3 m above ground using Pressler borer, in two field campaigns: in June and July 2023, the latter campaign aiming to find the oldest trees. A total of 46 trees were sampled, yielding 84 measuring radii. Tree ring widths were measured down to 0.01 mm under a stereomicroscope. The oldest sampled tree yielded a total of 370 tree rings in the two radii, representing the period 1653–2022. The average tree ring width for TM15 equals 0.33 mm/year, and shows low values (on average 0.19 mm/year) for the period 1742–1943, i.e., during the Little Ice Age cooling. TM15 does not stand out from other trees from the population with respect to height or trunk diameter. A comparison of the age of this tree to the oldest spruce trees in Poland indicates that it is one of the longest living specimens of this species. Considering the natural character of the stand, the remaining flora and the peat-forming processes taking place within the mire “Pod Małym Śnieżnikiem”, we argue that the mire should become protected by the law as soon as possible in order to preserve this valuable high-mountain habitat.

This qualitative research explores the adoption of blockchain technology in supply chain management, aiming to understand the drivers, barriers, and implications associated with its integration. Through in-depth interviews and thematic analysis, insights are gathered from key stakeholders in the supply chain ecosystem. The findings reveal a complex landscape, with stakeholders recognizing blockchain's potential to enhance transparency, efficiency, and trust while acknowledging challenges related to technical complexities, regulatory uncertainties, and organizational barriers. Despite these challenges, participants express optimism about blockchain's transformative potential, citing opportunities for improved traceability, supply chain resilience, and sustainability. Collaboration, governance, and ecosystem development emerge as critical factors for driving blockchain adoption within supply chains, alongside the need for continuous education and capacity-building initiatives. Overall, the study underscores the importance of addressing challenges and fostering a culture of innovation and collaboration to unlock the full potential of blockchain-enabled supply chains.

Sentinel-1 (S1) extra-wide (EW) swath data in cross-polarization (horizontal-vertical, HV or vertical-horizontal, VH) are strongly affected by the scalloping effect and thermal noise, particularly over areas with weak backscattered signals, such as sea surfaces. Although noise vectors in both the azimuth and range directions are provided in the standard S1 EW data for subtraction, the residual thermal noise still significantly affects sea ice detection by the EW data. In this paper, we improve the denoising method developed in previous studies to remove the additive noise for the S1 EW data in cross-polarization. Furthermore, we propose a new method for eliminating the residual noise (i.e. multiplicative noise) at the sub-swath boundaries of the EW data, which cannot be well processed by simply subtracting the reconstructed 2-D noise field. The proposed method of removing both the additive and multiplicative noise was applied to EW HV-polarized images processed using different Instrument Processing Facility (IPF) versions. The results suggest that the proposed algorithm significantly improves the quality of EW HV-polarized images under various sea ice conditions and sea states in marginal ice zone (MIZ) of the Arctic. This is of great support for the utilization of cross-polarization SAR images in wide swaths for intensive sea ice monitoring in polar regions.

This study explores the potential to reach a circular economy for post-consumer recycled polyethylene terephthalate (rPET) packaging and bottles by using it as a distributed recycling for additive manufacturing (DRAM) feedstock. Specifically, rPET is processed using only an open source toolchain with fused particle fabrication (FPF) or fused granular fabrication (FGF) processing. In this study, first the impact of granulation, sifting and heating (and their combination) is quantified on the shape and size distribution of the rPET flakes. Then feeding studies were performed to see if they could be printed through an external feeder or needed to be direct printed with a hopper using two Gigabot X machines, one with extended part cooling and one without. Print settings were optimized based on thermal characterization and for the latter which was shown to print rPET directly from shredded water bottles mechanical testing is performed. The results showed that geometry was important for extended feeding tubes and direct printed using a hopper. Further there is a wide disparity in the physical properties of rPET from water bottles depending on source and the history of the material. Future work is needed to enable water bottles to be used as a widespread DRAM feedstock.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

High dimensional statistical analysis for the yield of large-scale circuits is quite difficult due to expensive simulations, especially for the memory circuits with high sigma requirement (e.g., SRAM). In this paper, we developed an efficient sparse additive model to substitute simulations. To fit high sigma region accurately, the modeling center is moved to near failure boundary searched by scaling the shape of sampling function. To solve the model efficiently, the process variables are grouped by standard cells so that the model can be solved by our developed blockwise greedy algorithm. The experiments on the 28nm memory circuits validate that our method achieves high accuracy and efficiency compared with other state-of-art works.

Surface soil moisture (SSM) is a significant factor affecting crop growth. This paper presents a method for retrieving SSM over wheat-covered areas using synergy dual-polarization C-band Sentinel-1 synthetic aperture radar and Sentinel-2 optical data. Firstly, a modified water cloud model (WCM) was proposed to remove the influence of vegetation from the backscattering coefficient of the radar data. The vegetation fraction was then introduced in this WCM, and the vegetation water content (VWC) was calculated using multiple linear regression model. Subsequently, the support vector regression technique was used to retrieve the SSM. This approach was validated using in-situ measurements of the wheat field in Hebi, in the north of Henan Province. The key findings of this study are as follows: (1) Based on vegetation indices obtained from Sentinel-2; the proposed VWC estimation model can effectively eliminate the influence of vegetation; (2) compared with vertical transmit and horizontal receive polarization, vertical transmit and vertical receive polarization is better for detecting changes in SSM at different growth stages of wheat; and, (3) the validation results indicated that the proposed approach, based on Sentinel-1 and Sentinel-2 data, successfully retrieved SSM in the study area.

Psoriasis is a chronic, multisystem, inflammatory disease. The typical clinical cutaneous manifestation of psoriasis is scaly erythema or plaque, limited or widely distributed. However, psoriasis is far beyond the skin involvement and provides many challenges, including associated comorbidities. In this review, we classify psoriasis as cutaneous and systemic psoriasis, according to the clinical diversity and associated comorbid diseases, and recommend classification criteria for psoriasis. The key objective of this novel classification is to raise awareness of the complexity of this multifaceted disease and help to better understand and manage this complex disease comprehensively.

A low-cost bio-mass-derived carbon substrate has been employed to synthesize MoS₂@carbon composites through a hydrothermal method. Carbon fibers derived from natural cotton provide a three-dimensional and open framework for the uniform growth of MoS₂ nanosheets, thus constructing hierarchically coaxial architecture. The unique structure could synergistically benefit fast Li-ion and electron transport from the conductive carbon scaffold and porous MoS₂ nanostructures. As a result, the MoS₂@carbon composites, when served as anodes for Li-ion batteries, exhibit a high reversible specific capacity of 820 mAh g^-1, high-rate capability (457 mAh g^-1 at 2 A g^-1), and excellent cycling stability. The superior electrochemical performance makes the MoS₂@carbon composites to be low-cost and promising anode materials for Li-ion batteries.

This paper proposed an optimal tracking control scheme through adaptive dynamic programming(ADP) for a class of partially unknown discrete-time nonlinear systems based on radial basis function neural network(RBF-NN). In order to acquire the unknown system dynamics, we use two RBF-NNs, the one is used to construct the identifier, and the another is used to directly approximate the steady-state control input, where a novel adaptive law is proposed to update neural network weights. While the optimal feedback control and the cost function are derived via feedforward neural networks approximating, it is proposed to regulate the tracking error, the critic network and the actor network are then trained online to obtain the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation being built under the ADP framework. Simulations verify the effectiveness of the optimal tracking control technique using the neural networks.

At present paper, we aim to study the long-time behavior of a stochastic semi-linear degenerate parabolic equation on bounded or unbounded domain and driven by a nonlinear noise and defined. Since the theory of pathwise random dynamical systems can not be applied directly to the equation with nonlinear noise, first, we establish the existence of weak pullback mean random attractors for the equation by applying the theory of mean-square random dynamical systems; then, we prove the existence of (pathwise) pullback random attractors for the Wong-Zakai approximate system of the equation. In addition, we establish the upper semicontinuity of pullback random attractors for the Wong-Zakai approximate system of the equation under consideration driven by a linear multiplicative noise.

The fluorinated organic compounds have superior physicochemical properties than general organic compounds due to the strong C-F single bond, and widely used in medicine, biology, pesticides, and materials science. In order to gain a deeper understanding of the physicochemical properties of fluorinated organic compounds, fluorinated aromatic compounds have been investigated by various spectroscopic techniques. 2-Fluorobenzonitrile and 3-fluorobenzonitrile are important fine chemical intermediates, and their excited state S1 and cationic ground state D0 vibrational features remain unknown. In this paper, we used two-color resonance two photon ionization (2-color REMPI) and mass analyzed threshold ionization (MATI) spectroscopy to study S1 and D0 states vibrational features of 2-fluorobenzonitrile and 3-fluorobenzonitrile. The precise excitation energy (band origin) and adiabatic ionization energy were determined to be 36028 2 cm-1 and 78650 5 cm-1 for 2-fluorobenzonitrile; and 35989 2 cm-1 and 78873 5 cm-1 for 3-fluorobenzonitrile, respectively. The density functional theory (DFT) at the levels of RB3LYP/aug-cc-pvtz, TD-B3LYP/aug-cc-pvtz, and UB3LYP/aug-cc-pvtz were used to calculate the stable structures and vibrational frequencies for the ground states S0, excited state S1, and cationic ground state D0, respectively. Franck-Condon spectral simulations for transitions of S1 S0 and D0 S1 were performed based on above DFT calculations. The theoretical and experimental results are in good agreement. The observed vibrational features in S1 and D0 states are assigned according to the simulated spectra and the comparison with structurally similar molecules. Several experimental findings and molecular features were discussed in detail.

Research on the development of new lightweight Al-Li alloys using selective laser melting pro-cess has great potential for industrial applications. This paper reports on the development of novel aluminum-lithium alloys using selective laser melting technology. Al-Cu-Li-Mg-Ag-Sc-Zr pre-alloyed powders with lithium contents of 1 wt.%, 2 wt.% and 3 wt.%, respectively, were prepared by inert gas atomization. After SLM process optimization, the microstructure and me-chanical properties of the as-formed specimens were investigated. The densification of the three newly developed alloys are 99.51 %, 98.96 % and 92.01 %, respectively. They all have good form-ability, with the lithium loss rate about 15 %. The as-formed alloy with 1% Li content presents good comprehensive properties with a yield strength of 412.6 ± 16.0 MPa, an ultimate tensile strength of 461.1 ± 11.7 MPa, and an elongation of 13.6 ± 1.1%. The three alloys exhibit a layered molten pool stacking morphology and have a typical heterostructure. The columnar crystals and equiaxed fine grains are alternately arranged, and most of the precipitated phases are enriched at the grain boundaries. The change of Li content mainly affects the precipitation of Cu-containing phase. When the Li content is 1 wt.%, there are θ phase, T1 phase and TB phase. When Li increased to 2 wt.%, T1 and T2 phases precipitated together. When Li reaches 3 wt.%, δ' phase precipitates with T2 phase. This study provides useful guidance for the future SLM form-ing of new crack-free and high-strength Al-Li alloys.

In the evolving landscape of Portfolio Management (PM), the fusion of advanced machine 1 learning techniques with traditional financial methodologies has opened new avenues for innovation. 2 Our study introduces a cutting-edge model combining Deep Reinforcement Learning (DRL) with 3 a Non-stationary Transformer architecture. This model is specifically designed to decode complex 4 patterns in financial time series data, enhancing portfolio management strategies with deeper insights 5 and robustness. It effectively tackles the challenges of data heterogeneity and market uncertainty, 6 key obstacles in PM. Our approach integrates key macroeconomic indicators and targeted news 7 sentiment analysis into its framework, capturing a comprehensive picture of market dynamics. This 8 amalgamation of varied data types addresses the multifaceted nature of financial markets, enhancing 9 the model’s ability to navigate through the complexities of asset management. Rigorous testing 10 demonstrates the model’s efficacy, highlighting the benefits of blending diverse data sources and 11 sophisticated algorithmic approaches in mastering the nuances of PM.12

Introduction: People with schizophrenia have poor cardiometabolic health, with elevated 10-year cardiovascular disease risk (CVD-R) scores and poor quality of life (QOL). There is lack of understanding of these issues in early psychosis. Aims: To quantify CVD-R in people with early psychosis and profile their obesity prevalence, lifestyle behaviours and QOL. Secondary aim was to explore associations between lifestyle behaviours/treatment characteristics and CVD-R/QOL. Method:Baseline data from 81 RCT participants were used to profile cardiometabolic health risks (QRISK®3, BMI and waist circumference). Participants self-reported lifestyle behaviours and QOL. Relationships between modifiable treatment/lifestyle factors and QOL/CVD-R were explored using bivariate analyses. Results: Participants’ relative risk for CVD over 10 years was 1.93 times higher than healthy counterparts; 39% also had an obese BMI and physical QOL was poor. No significant associations were observed between CVD-R or QOL with treatment characteristics and lifestyle factors. Discussion: Despite positive lifestyle behaviours, participants had elevated CVD-R scores and poor physical health related QOL. Quantifying CVD-R with QRISK®3 may highlight the need for health promotion interventions. Implications for practice: Mental health professionals should be alert to elevated cardiometabolic health risks in early psychosis, particularly as these can occur in the context of relatively healthy lifestyle behaviours.

We examine the global legal entity identifier (LEI) system for the identification of participants in financial markets. Semi-structured interviews with data professionals reveal the many ways in which the LEI can improve both business process efficiency and counterparty and credit risk management. Larger social benefits, including monitoring of systemic financial risk, are achievable if it becomes the accepted universal standard for legal entity identification. Our interviews also review the substantial co-ordination and investment barriers to LEI adoption. To address these, a clear regulatory-led road map is needed for its future development with widespread application in regulatory reporting.

Management of chronic inflammation and wounds has always been a key issue in the pharmaceutical and healthcare sector. Curcumin (CCM) is an active ingredient extracted from turmeric rhizomes that has antioxidant, anti-inflammatory, and antibacterial activities, thus showing significant effectiveness toward wound healing. However, its shortcomings such as poor water solubility, poor chemical stability and fast metabolic rate limit its bioavailability and long-term use. In this context, hydrogels appear to be a versatile matrix for carrying and stabilizing drugs due to the biomimetic structure, soft porous microarchitecture, and pleasant biomechanical properties. The drug loading/releasing efficiencies can also be controlled by use of highly crystalline and porous metal organic frameworks (MOFs). Here, a flexible hydrogel composed of sodium alginate (SA) matrix and CCM-loaded MOFs was constructed for long-term drug release and antibacterial activity. The morphology and physicochemical properties of composite hydrogels were analyzed by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), ultraviolet visible spectroscopy (UV-Vis), Raman spectroscopy and mechanical property tests. The results showed that the composite hydrogel was highly twistable and bendable to mechanically comply with human skin. The as-prepared hydrogel could capture efficient CCM for slow drug release as well as effective killing of bacteria. Therefore, such composite hydrogel is expected to provide a new management system for chronic wound dressings.

Wheat, a component of the staple diet globally, is a common food allergen in children. The symptoms of wheat allergy (WA) range from skin rash to shortness of breath, significantly impairing quality of life. Following initial clinical suspicion, individuals may undergo wheat allergen-specific skin prick test (SPT), blood test for serum immunoglobulin E (sIgE) levels or oral food challenge. Conventional management of WA lies in wheat avoidance, yet accidental consumption may be inevitable owing to the ubiquity of wheat in various food products. This article aims to provide an overview of the immunologic pathway of WA, followed by its novel diagnostic methods, namely alcohol-soluble SPT extracts, component-resolved diagnosis and basophil activation test (BAT). The mechanisms underlying wheat allergen-specific oral immunotherapy (OIT) as well as a summary of the efficacy, tolerability and safety of related clinical trials will then be discussed.

Poly-ether-ether ketone (PEEK) is a great potential thermoplastic in industry and medical treatment and health. In this work, the PEEK/GO and PEEK/MoS2 composites were prepared by a novel hot isostatic pressing method. The addition of GO alters the tribological behaviours mechanism, fatigue wear mechanism is predominant to PEEK/GO composites. However, the combination of abrasive and adhesive wear mechanisms is observed for PEEK/MoS2 composites and PEEK. The reason is the hardness and tensile strength of composites are increased with the appropriate addition of GO. The response time to stable friction state of PEEK/GO and PEEK/MoS2 composites reduces in compared with PEEK, which conduce to shorten running-in time, reduce energy consumption and improve the tribological performances of composites. The addition of GO and MoS2 can effectively decrease the friction coefficient and wear rate, and the optimal content of GO and MoS2 was 0.7 wt.% and 15 wt.%, respectively. The results indicate that PEEK/GO and PEEK/MoS2 are impressive composites that possess super tribological properties.

Nanoparticle carriers can selectively deliver the drug cargo to tumor cells, thus having the ability to pre-vent early drug release, reduce non-specific cell binding, and prolong in vivo drug retention. We con-structed paclitaxel (PTX)-loaded lipid-shell mesoporous silica nanoparticles (LMSNs) for targeted an-ti-cancer drug delivery. The physical properties of PTX-LMSNs were analyzed by scanning electron mi-croscopy (SEM) and transmission electron microscopy (TEM). The drug loading (DL%) and entrapment efficiency (EE%) of PTX-LMSNs were measured by high performance liquid chromatography (HPLC). In vitro drug release test, in vivo imaging, tissue distribution and pharmacokinetics of PTX-LMSNs were also evaluated. The SEM examination showed that MSNs were sphere, whereas TEM showed that they were rich in fine pores. The uniform core-shell structure of PTX-LMSNs was also verified by TEM. The DL capacity of PTX-LMSN was as high as 21.75%, and PTX was released from the nanoparticles in vitro in a pH-dependent manner. The cumulative amount of free PTX increased at lower pH, which is conducive to selective drug release from LMSNs in the acidic tumor tissues. In vivo imaging showed prolonged reten-tion of PTX-LMSNs, which is beneficial to their therapeutic efficacy. In addition, PTX-LMSNs were primarily concentrated in the liver. Pharmacokinetic experiments showed that the half-life of PTX-LMSNs was 23.21% longer and 79.24% higher than that of Taxol. Together, LMSNs are a highly promising antineoplastic drug carrier system.

Excessive production, consumption and indiscriminate disposal of plastic waste cause an increasing plastic pollution with detrimental impacts on environment and human health. This study aimed to assess the level of knowledge, attitude, and practices (KAP) towards plastic pollution among Malaysians and evaluate the variation of plastic pollution related KAP among various socio-demographics. An online survey was conducted, and 294 valid responses was obtained. Descriptive statistics, KAP scoring and cross tabulation of responses were estimated. One-way analysis of variance, paired t-test and binary logistic regressions were carried out. Results showed that respondents had poor knowledge (mean 7.41 ± 1.80) and practice score (3.81 ± 1.39) across all socio-demographics. Compared to younger (18-30 years) respondents, older ones (>46 years) had higher knowledge (odds ratio, OR 4.304; p<0.01). However, middle aged (31-45 years) respondents reported significantly (p<0.01) higher attitude (OR 4.019) and practice (OR 4.056; p <0.05). Respondents with environmental related university education had showed higher odds about plastic pollution related knowledge (OR 10.343; p<0.01). Suggestions are made to undertake interventions such as environmental awareness creation, incorporating plastic pollution topics in formal and informal education, and providing recycling facilities nearby the localities for encouraging good practices towards minimizing plastic uses and pollution.

Lithium rich layered oxides (LRLO) are a wide class of innovative active materials for positive electrodes in lithium-ion (LIB) and lithium-metal secondary batteries (LMB). LRLOs are over-stoichiometric layered oxides rich in lithium and manganese, with general formula Li1+xTM1-xO2, where TM is a blend of transition metals comprising Mn (main constituent), Ni, Co, Fe and others. Due to the very variable composition and the extended defectivity their structural identity is still debated among researchers being likely an unresolved hybrid between a monoclinic (mC24) and a hexagonal lattice (hR12). Once casted in composite positive electrode films and assembled in LIBs or LMBs, LRLOs can delivery reversible specific capacities above 220-240 mAhg-1, thus beyond any other available intercalation cathode material for LIBs, with mean working potential above 3.3-3.4 V vs Li for hundreds of cycles in liquid aprotic commercial electrodes. In this review we critically outline the recent advancements in the fundamental understanding of the physico-chemical properties of LRLO as well as the most exciting innovations in their battery performance. We focus in particular on the elusive structural identity of these phases, on the complexity of the reaction mechanism in batteries as well as on practical strategies to minimize or remove cobalt from the lattice while preserving the outstanding performance upon cycling.

Pore structure characterization and fractal analysis have great significance for understanding and evaluating tight limestone reservoirs. In this work, the pore structure of tight limestone is characterized combined with low-temperature nitrogen adsorption (LTNA) and low-field nuclear magnetic resonance (NMR), and the fractal dimension of tight limestone pore structure is discussed based on LTNA and NMR data. The results indicate that the pores of tight limestone have H3 and H4 types, the pore size distribution (PSD) of H3 type is a wave distribution ranging from 2 to 10 nm, and the PSD of H4 type is a unimodal distribution ranging from 2 to 10 nm. The transverse relaxation time (T2) spectrum of tight limestone shows single peak (DF), double peak (SF) and three peak (TF), and the T2 spectrums for micropores, mesopores and macropores range from 0.1 to 10 ms, from 10 to 100 ms, and greater than 100 ms, respectively. The LTNA fractal dimension of tight limestone (DL) ranges between 2.4446 and 2.7688, with an average of 2.5729, and the NMR fractal dimensions of micropores (DNMR1), mesopores (DNMR2) and macropores (DNMR3) are distributed between 0.3744 to 1.1293, 2.4263 to 2.9395 and 2.6582 to 2.9989, respectively. Moreover, there is no correlation between fractal dimension and permeability and porosity, a negative correlation between DL and average pore radius, a positive correlation between DL and specific surface area, and a positive correlation between DNMR2 and DNMR3 and micropore content, while DNMR2 and DNMR3 are negatively correlated with the content of mesopores and macropores.

Blockchain technology has gotten much interest recently from academics, industry, and governments worldwide. It is regarded as a technical innovation that can disrupt various application fields affecting many aspects of our lives. Cryptocurrencies are a public blockchain application's success story that sparked extensive research and development. Scalability, energy consumption, and security, on the other hand, remain significant challenges. With low throughput, high transaction delay, and high energy consumption, most cryptocurrencies are experiencing low-efficiency difficulties. The scalability issue with public Blockchains is preventing organizations and sectors from receiving effective solutions. As a result, it is critical to bridge the gap and develop new frameworks that connect Blockchain with those goals. This paper examines the evolution of blockchain architecture and consensus protocols, provides a retrospective analysis, discusses the rationale for the various architectures and protocols' change, and captures the assumptions supporting their development and contributions to collaborative application development. However, existing research on consensus algorithms is insufficient. The features of the algorithms are discussed insufficiently in those papers, and some prominent blockchain consensus methods are not examined in terms of their scopes. The study’s findings are delivered in tabular formats, allowing for a clear representation of these algorithms. We discovered in our investigation that scalability is a result of many parameters such; transaction throughput, number of nodes, storage, block size, high communication, latency, cost. Furthermore, Due to its off-chain data storage and smaller block size, PoF is much more scalable than PoS and PoW, and Because PoA is a hybrid of PoW and PoC, it does not necessitate a large number of computational resources. As a result, it has a higher throughput than PoW. PoPF entails ranking all participating nodes and appointing n accountants to compete for adding new blocks. This article addresses the need by analyzing a wide range of consensus algorithms using a complete taxonomy of attributes and delving into the consequences of several still-present flaws in consensus algorithms.

This research investigates the challenges and opportunities associated with supply chain transparency and traceability in the renewable energy sector. Using a qualitative methodology, the study involved semi-structured interviews with key stakeholders, including industry experts, supply chain managers, regulatory officials, and NGO representatives. The findings reveal that the complexity and global span of renewable energy supply chains pose significant hurdles for ensuring transparency and traceability. Variability in the maturity of traceability systems across companies further complicates the landscape, with some companies benefiting from advanced systems while others struggle with cost and technical barriers. Technological advancements, especially blockchain, offer promising solutions but require standardization and scalability to be effective. Regulatory frameworks play a crucial role, yet inconsistencies across jurisdictions create compliance challenges, underscoring the need for harmonized standards. Collaboration and partnerships are essential, providing platforms for sharing best practices and developing common standards. Enhanced transparency can lead to operational efficiencies, improved consumer trust, and stronger market positioning. Integrating sustainability into supply chain practices is fundamental, aligning with the increasing emphasis on ESG criteria among investors and stakeholders. Education and capacity-building, particularly for suppliers in developing countries, are vital for promoting transparency. Leadership and corporate culture are critical in driving these efforts, with strong commitment from the top necessary to implement effective practices. This study contributes valuable insights for stakeholders in the renewable energy sector, offering a foundation for future research and policy development aimed at advancing sustainable and ethical supply chain practices. The findings highlight the need for a holistic approach that integrates transparency and traceability into broader sustainability and business strategies.

Objective: The purpose of this study was to investigate the effect of aerobic exercise on myocardial injury induced by I/ R in rats by regulating SIRT3/SOD2/NF-κB signaling pathway, and to provide theoretical guidance for clinical treatment of myocardial I/R injury.Methods:SPF Male Sprague-Dawley(SD) rats were randomly assigned to 4 groups: Sham operation group(n=10), I/R group(n=10), Aerobic exercise group(n=10)and Aerobic exercise+κ-receptor antagonist group(Pro DTC group，n=10). The left anterior descending coronary artery(LAD) of rats was ligated and re-canalized to establish I/R rat model. Hematoxylin-eosin(HE) staining was performed to examine histological morphology in myocardial tissues of each group. The biological analysis was performed to measure cTnI、CK-MB、BNP levels in blood samples of each group. The expression levels of SOD2, TLR4, and p65 in myocardial tissues were measured by immunohistochemical assay. The influence of aerobic exercise on Beclin-1 、LC3II/I、SIRT3, TLR4, and phosphorylated p65 was measured by Western blotting.Results: The result of histological morphology examination revealed that Aerobic exercise group exhibited integrated cardiac myofilament, less inflammatory cell infiltration, as much as significantly decreased cellular edema. Measurement of cTnI、CK-MB、BNP revealed that oxycodone post-treatment reduces the injury of myocardial tissues(P<0.05). Immunohistochemical staining results revealed that aerobic exercise clearly decreased the expression of TLR4 and p65, and increased the expression of SOD2(P<0.05). Besides, Western blotting revealed that aerobic exercise down-regulated the expression of Beclin-1 、LC3II/I、TLR4 and phosphorylated p65, up-regulated the expression of SIRT3(P<0.05).Conclusions: Aerobic exercise significantly improved myocardial I/R injury. The mechanisms may be associated with activating κ-receptor to regulate SIRT3/SOD2/NF-κB pathway.

Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern between the suppliers and demanders. In this paper, a negotiation pricing model that is based on the multiobjective genetic algorithm is developed for innovation service pricing. Regarding the service pricing process as a multiobjective problem, the objective functions, which include the service price, service efficiency, and service quality, for suppliers and demanders are constructed. As the solution of a multiobjective problem is typically a series of alternatives, another negotiation process is necessary for determining the final decision. A learning strategy is adopted during the negotiation process to simulate reality. Finally, the model is implemented for an innovation service transaction, the objective of which is to identify the optimal price plan. The results demonstrate that the model can provide quantitative decision support for the pricing of an innovation service and ultimately yield a win-win result for both the supplier and demander of the innovation service. Furthermore, the influence of the parameters during the negotiation process is analyzed in detail. The effects of the learning strategy on accelerating the negotiation process, as well as the chosen of reasonable parameters are given.

Proton exchange membrane water electrolyzers (PEMWEs) for water electrolysis have received tremendous attention due to their immediate response, high proton conductivity, low ohmic losses and gas crossover rate. However, design high activity, economical and long-term durable electrocatalysts in an acidic environment is still the bottleneck to realize the large-scale commercialization of PEMWEs. Iridium-based materials represent one of the most promising classes of oxygen evolution reaction (OER) catalysts due to their intrinsic stability in acid media over ruthenium-based counterparts. However, only a few innovative approaches have been developed to synthesizing iridium-based catalysts (IBCs) in the past decade, mainly due to achieving high activity may deteriorate the stability of IBCs. Accordingly, various engineering strategies of optimizing IBCs have been proposed to address this issue, including doping engineering, morphology engineering, crystal phase engineering and support engineering. Herein, a critical overview focusing on various synthesis and modulation strategies of IBCs is presented, based on an in-depth understanding of the relationship between electronic structures, charge redistribution and activity as well as stability of the electrocatalysts. In addition, the unprecedented achievements in PEMWEs are summarized. The reaction mechanisms and future perspectives are critically discussed to inspire more rational design of IBCs toward practical applications.

Fifty-two kinds of N’-phenylhydrazides were successfully designed and synthesized. Their anti-fungal activity in vitro against five strains of C. alb. was evaluated. All prepared compounds owned varying degrees of activity and their MIC80, TAI, and TSI values were calculated. The in-hibitory activities of 27/52 compounds against fluconazole-resistant fungi C. alb. 4395 and C. alb. 5272 were much higher than those of fluconazole. The MIC80 values of 14/52 compounds against fluconazole-resistant fungus C. alb. 5122 were less than 4 μg/mL, so it was the most sensitive fungus (TSIB = 12.0). A11 showed the highest inhibitory activity against C. alb. SC5314, 4395, and 5272. The antifungal activities of B14 and D5 against four strains of fluconazole-resistant fungi were higher than those of fluconazole. The TAI values of A11 (2.71), B14 (2.13), and D5 (2.25) are the highest. Further exploring the antifungal mechanism revealed that the fungus treated with compound A11 produced free radicals and reactive oxygen species, and their mycelium mor-phology was damaged. In conclusion, the hydrazide scaffold showed potential in the develop-ment of antifungal lead compounds. Among them, A11, B14, and D5 demonstrated particularly promising antifungal activity and hold potential as novel antifungal agents.

The Dst index is the geomagnetic storm index used to measure the energy level of geomagnetic storms, and the prediction of this index is of great significance for the geomagnetic storm study and the solar activity. In contrast to traditional numerical modelling techniques, machine learning, which has emerged in decades ago based on rapidly developing computer hardware and software and artificial intelligence methods, has been unprecedentedly developed in geophysics, especially solar-terrestrial space physics. This study chooses two machine learning models, the LSTM (Long-Short Time Memory, LSTM) and EMD-LSTM model (Empirical Mode Decomposition, EMD), to model and predict the Dst index. By building the Dst index data series from 2018-2023, two models were built to fit and predict the data. Firstly, we evaluated the influences of the learning rate and the amount of training data on the prediction accuracy of the LSTM model, and finally, 10-3 was thought as the optimal learning rate; secondly, the two models were used to predict the Dst index in the solar active and quiet periods, respectively, and the RMSE (Root Mean Square Error) of the LSTM model in the active period is 7.34 nT, the CC (correlation coefficient) is 0.96, those of the quiet period are 2.64nT and 0.97; the RMSE and r of EMD-LSTM model are 8.87nT and 0.93 in active time and 3.29nT and 0.95 in the quiet time. Finally, the prediction accuracy of the LSTM model in short time period is slightly better than the EMD-LSTM model. However, there will be a problem of prediction lag, which the EMD-LSTM model can then solve, and can better predict the geomagnetic storm.

Barnyardgrass (Echinochloa spp.) is a prevalent type of weed in rice fields worldwide. Despite the growing knowledge concerning allelopathic interference with barnyardgrass, little is understood regarding the competitive mechanisms between allelopathic rice and herbicide-resistant barnyardgrass at the plant physiological level. In this context, a hydroponic system was employed to investigate the root morphological traits and different phytohormones levels of two rice cultivars, i.e., the allelopathic rice cultivar “PI312777” (PI) and the non-allelopathic rice cultivar “Lemont” (LE), when co-planted with quinclorac-resistant and -susceptible barnyardgrass, respectively. The results showed that the shoot and root biomass were greater in the allelopathic rice cultivar. Moreover, the treatments at the two time points induced an increase in shoot and root biomass of PI when subjected to barnyardgrass stress. In terms of root morphology, PI exhibited significantly higher fine-root length in diameters &lt;0.5 mm, a greater number of root tips, and longer root tips compared to LE. In addition, the levels of different plant hormones, including auxin (IAA), abscisic acid (ABA), jasmonic acid (JA), and salicylic acid (SA), known for their diverse adaptation strategies to biotic stress, were analysed. The response to quinclorac-resistant barnyardgrass stress was consistent in terms of the content of well-known stress-related hormones, namely SA and JA. The accumulation of SA and JA was observed in both rice cultivars under the stress of quinclorac-resistant barnyardgrass, with higher contents of these hormones in PI than that in LE. The most significant change was observed in IAA and ABA contents in rice, which decreased significantly from 7 days to 14 days under co-culture stress. Additionally, PI contained higher levels of IAA and ABA than LE in the presence of barnyardgrass stress. This research may aid in the development of strategies for reducing the environmental impact of herbicides through the prudent selection of non-chemical herbicide control tactics.

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

Social media giants like Facebook are struggling to keep up with fake news, in the light of the fact that disinformation diffuses at lightning speed. For example, the COVID-19 (i.e. Coronavirus) pandemic is testing the citizens' ability to distinguish real news from falsifying facts (i.e. disinformation). Cyber-criminals take advantage of the inability to cope with fake news diffusion on social media platforms. Fake news, crafted as a means to manipulate readers to perform various malicious IT activities. However, no previous study has investigated the strategies used to create fake news on social media. Therefore, we have analysed five data-sets that contain online news articles (i.e. both fake and legitimate news) to investigate strategies of crafting fake news on social media platforms. Our study findings revealed a threat model understanding strategies of crafting fake news which may highly likely diffuse on social media platforms.

The detection of temporary color steel buildings and the analysis of their spatiotemporal patterns and characteristics are of great importance in many developing cities, because areas densely distributed with color steel buildings are usually problematic regions with high population density, sustainable development and risk level, which are challenging for local governments. Using the high-resolution satellite images of the Anning District, Lanzhou City, China as the case study, this paper first extracts the information of the color steel buildings for two different periods. Then the spatiotemporal distributional characteristics of the color steel buildings are analyzed, both at small scale (temporary buildings) and large scale (planthouses, warehouses, etc.). Finally, this paper utilizes kernel density estimation, Delaunay triangulation and Voronoi diagrams to examine the spatial distribution, aggregation and proximity characteristics of the color steel buildings. Our experiments show that the temporal and spatial differences of urban development, the phased characteristics and urban space are represented by various types of color steel buildings. Thus, there are some robust coupling relationship between color steel buildings, urban spatial form and urban development.

To explore the forage quality of wild oat populations under different growth environments, the basic nutrient composition and forage quality of five wild oat populations in Israel were compared. Ash, crude protein, and soluble sugar content of oats were significantly (P<0.05) related to some forage quality and possible environment of population origin. Among them, the environmental factors of origin had significant effects on the indicators of ash, crude protein, and soluble sugars of oat straw, but less on the contents of crude fat, total phosphorus, and total potassium. Meanwhile, the annual rainfall and the number of days of rainfall in the country of origin greatly influenced the cellulose content. Finally, we investigated the similarity of feeding values of different populations using PCA analysis. The results showed that, in conclusion, the higher variability of wild oat populations may be a new possibility brought by feeding oats.

Penile squamous cell carcinoma (SCC) is a rare disease. Treatment options for advanced penile cancer are often limited and prognosis remains poor. We reported a 52-year-old male recurrent and metastatic penile SCC patient with high PD-L1 expression(90%) and TMB(14.4 muts/Mb). He had undergone penectomy, bilateral inguinal lymph node dissection and excision of the abdominal wall mass during two surgeries. Despite cisplatin-based concurrent chemoradiotherapy and sequential chemotherapy with docetaxel plus cisplatin were then carried out, the carcinoma still had progressed. The patient then obtained progression free survival exceeding 32 months with continuous sintilimab, although new onset of ICI-induced diabetes after 24 cycles of sintilimab and required sustained insulin treatment. He didn’t have positive type 1 diabetes associated autoantibodies, but had susceptible HLA genotype DR3-DQ2 haplotype. This is the first patient with radiation and multichemorefractory penile SCC obtained remarkable anti-tumor effect of partial regression exceeding 32 months during continuous sintilimab.

A Co–doped porous carbon was successfully fabricated by a facile carbonizing procedure using coal hydrogasification semi-coke (SC) as the carbon and cobalt nitrate as the magnetic precursors, respectively. The microwave absorption (MA) performances were regulated by adjusting the mass ratio of the precursors. The dielectric loss from the carbon framework, the magnetic loss from nano–sized Co particles coupled with multiple scattering from the residual pores synergistically contribute to the favorable MA capabilities. When the initial mass ratio of cobalt nitrate and SC was 1:1, the Co/C composite showed the lowest reflection loss of -33.45 dB at the thickness of 4.0 mm. The effective absorbing bandwidth (EAB) could achieve 3.5 GHz at 2 mm in thickness. This work not only exploits a new avenue for the structural design and facile fabrication of dielectric and magnetic loss combinations, but also opens up another way for the high value–added utilization of SC.

Some biologically active compounds isolated from sea cucumbers stimulate the body’s immune response through activating immune cells. Immune function is closed related to the integrity intestinal barrier and balanced gut microbiota. However, it is unknown whether daily administration of holothurian wall hydrolysates (HWH) ameliorated intestinal dysbiosis and barrier injury induced by immunodeficiency. This study aimed to investigate the immunomodulatory effect and the underlying mechanism of HWH in cyclophosphamide (CTX)-induced immunocompromised mice. BALB/c mice received CTX (80 mg/kg, intraperitoneally) once a day for 3 days to induce immunodeficiency, and then oral administration of HWH (80 or 240 mg/kg), levamisole hydrochloride (LH, 40 mg/kg, positive control) respectively once a day for 7 days. We utilized 16S rRNA sequencing for microbial composition alterations, histopathological analysis for splenic and colonic morphology, Western blotting for expressions of tight junction proteins (TJs), and quantitative real-time (qRT-PCR) for measurements of pro-inflammatory cytokines. HWH attenuated the immune organ damage induced by CTX, increased the secretions of interleukin (IL)-6, IL-1β and tumor necrosis factor (TNF)-α, and promoted the recovery of goblet cells and the productions of TJs (claudin-1, occludin, and ZO-1) in the colon of the immunocompromised mice. Moreover, HWH promoted the growth of beneficial microorganisms such as Lactobacillus, Lachnospiraceae, Christensenellaceae, and Bifidobacterium, while suppressed the populations of Ruminococcus, Staphylococcus, and Streptococcus. These results demonstrate that HWH elicits intestinal mucosal immunity, repairs the damage to intestinal mucosal integrity, and normalizes the imbalanced intestinal microbial profiles in immunocompromised mice. It may be helpful to identify the biological activities of HWH, and supports the potential as new prebiotics, immunomodulatory agents, and medical additive for intestinal repair.

This study explores the barriers and opportunities faced by women in supply chain leadership, a field traditionally dominated by men. Through in-depth interviews and thematic analysis, it uncovers the pervasive cultural and societal biases that undermine women's perceived competence and suitability for leadership roles. These biases, often rooted in deep-seated stereotypes, influence hiring and promotion decisions, creating significant obstacles for women. Structural and organizational barriers, such as the lack of formal diversity policies, flexible working arrangements, and adequate mentorship, further hinder women's career progression. The dual burden of professional and domestic responsibilities also disproportionately affects women, limiting their availability for work-related travel and extended hours, which are often required in supply chain roles. Despite these challenges, the study identifies several pathways to promote gender diversity in supply chain leadership. Organizational commitment to diversity and inclusion, flexible working policies, and comprehensive mentorship programs are crucial in supporting women's advancement. Education and professional development opportunities are essential in equipping women with the necessary skills for leadership roles. Additionally, fostering an inclusive corporate culture that values diverse perspectives and addresses discrimination is vital for creating a supportive environment. Broader societal and policy-level changes, such as government and industry initiatives promoting gender diversity, are also necessary. The integration of emerging areas like sustainability, entrepreneurship, emotional intelligence, marketing, and supplier relationship management offers new opportunities for women to contribute to the industry's evolution. By addressing these barriers and leveraging the identified opportunities, it is possible to create a more inclusive and equitable supply chain industry, benefiting both the industry and society.

Previous research has shown that the effectiveness of selecting filter set from a large set of commercial broadband filters by vector analyzing method based on maximum linear independence (MLI). However, the traditional MLI is suboptimal due to predefining the first filter of the selected filter set being the maximum ℓ2 norm among all those of the filters. An exhaustive imaging simulation is conducted to investigate the features of the most competent filter set. In the simulation, every filter in a subset of all the filters is selected serving as the first filter in turn. From the results of the simulation, we found there are remarkable characteristics for the most competent filter set. Besides smaller condition number, the geometric features of the best-performed filter set comprise the distinct peak of the transmittance of the first filter, the generally uniform distributing of the peaks of the transmittance curve of the filters, the substantial overlapping of the transmittance curves with those of the adjacent filer sets. Therefore, the best-performed filter sets can be decided intuitively by simple vector analyzing and just a few experimental verifications. This work would be useful for optimizing spectral sensitivity of broadband multispectral imaging sensors or SFA sensors.

In recent years, nocturnal ozone enhancement(NOE) events have become a hot research topic in the field of atmospheric environment. By using statistically-based data analysis, we made a comparative investigation about nocturnal ozone concentrations and NOE events in 2022 and 2023, and further explored the effects of NOE events on O3 and PM2.5 at the night of the same day and the next day. The results showed that from 2022 to 2023 in Dongying, the annual average nocturnal ozone concentrations increased from 51 μg/m3 to 59 μg/m3, and the frequency of NOE events was higher in spring, summer and autumn, and lower in winter. NOE events not only had an obvious promoting effect on nocturnal O3 and Ox, and the daily maximum 8 h average concentration of O3 (MDA8-O3) of the same day (more apparent in summer and autumn), and nocturnal PM2.5 and PM2.5-bounded NO3- and SO42- (more apparent in winter), but also had a distinct influence on O3, Ox and MDA8-O3 of the next day (more apparent in summer). The results could strengthen the understanding of the phenomena of NOE events, and provide a scientific basis for the collaborative control of PM2.5 and ozone in urban areas in the Yellow River Delta, China.

Hepatocellular carcinoma (HCC) is the fifth most common type of cancer, and is the third leading cause of cancer-related deaths each year. It involves a multi-step progression and is strongly associated with chronic inflammation induced by the intake of environmental toxins and/or viral infections (i.e., hepatitis B and C viruses). Although several genetic dysregulations are considered to be involved in disease progression, the detailed regulatory mechanisms are not well defined. Homeobox (Hox) genes that encode transcription factors with homeodomains control cell growth, differentiation, and morphogenesis in embryonic development. Recently, more aberrant expressions of Hox genes were found in a wide variety of human cancer, including HCC. In this review, we summarize the currently available evidence related to the role of Hox genes in the development of HCC. The objective is to determine the roles of this conserved transcription factor family and its potential use as a therapeutic target in future investigations.

The scalar meson f0(980) has been a long-standing puzzle in light hadron physics. The mass and width of the f0(980) in normal decay processes are estimated to be M=990±20 MeV/c2 and Γ=40−100 MeV, respectively. Theoretically, the internal structure of the f0(980) is proposed to be a conventional quark-antiquark meson, tetraquarks state, KK¯ molecule, or quark-antiquark gluon hybrid. So far, explanations about the nature of f0(980) have been controversial for a long time. Recently, anomalously narrow width f0(980) were observed by the BESIII experiment in five independent isospin-violating decay channels. Based on the experimental data, we performed a simultaneous fit to ππ invariant mass distributions, and the mass and width in isospin-violating decays are determined to be M=990.0±0.4 MeV/c2 and Γ=11.4±1.1 MeV, respectively. In addition, we use the parameterized Flatté formula to simultaneously fit the same ππ invariant mass distributions, the two coupling constants of gfππ and gfKK¯ are measured to be gfππ=0.46±0.03 and gfKK¯=1.24±0.32, respectively. According to the joint confidence regions of gfππ and gfKK¯, we conclude that the experimental data tend to support the KK¯ molecule model and the quark-antiquark (qq¯) model, but tend not to support the tetraquarks (q2q¯2) model and the quark-antiquark gluon (qq¯g) hybrid model.

In this paper, we focus on developing a novel method to extract sea ice cover (i.e., discrimination/classification of sea ice and open water) using Sentinel-1 (S1) cross-polarization (vertical-horizontal, VH or horizontal-vertical, HV) data in extra wide (EW) swath mode based on the machine learning algorithm support vector machine (SVM). The classification basis includes the S1 radar backscatter coefficients and texture features that are calculated from S1 data using the gray level co-occurrence matrix (GLCM). Different from previous methods where appropriate samples are manually selected to train the SVM to classify sea ice and open water, we proposed a method of unsupervised generation of the training samples based on two GLCM texture features, i.e. entropy and homogeneity, that have contrasting characteristics on sea ice and open water. We eliminate the most uncertainty of selecting training samples in machine learning and achieve automatic classification of sea ice and open water by using S1 EW data. The comparison shows good agreement between the SAR-derived sea ice cover using the proposed method and a visual inspection, of which the accuracy reaches approximately 90% - 95% based on a few cases. Besides this, compared with the analyzed sea ice cover data Ice Mapping System (IMS) based on 728 S1 EW images, the accuracy of extracted sea ice cover by using S1 data is more than 80%.

Ethnopharmacological relevance: Novel coronavirus disease (COVID-19) outbroke in Wuhan has imposed a huge influence onto the society in term of the public heath and economy. However, so far, no effective drugs or vaccines have been developed. Whereas, the Traditional Chinese Medicine (TCM) has been considered as a promising supplementary treatment for the disease owing to its clinically proven performance on many diseases even like severe acute respiratory syndrome (SARS). Meanwhile, many side-effect (SE) reports suggest the SE of the TCM prescriptions cannot be ignored in curing the COVID-19, especially because COVID-19 always simultaneously leads to dramatic degradation of the patients’ physical condition. How to evaluate the TCM regarding to their latent SE is a urgent challenge. Aim of the study: In this study, we use an ontology-based side-effect prediction framework (OSPF) developed in our previous work and Artificial Neural Network (ANN)-based deep learning to evaluate the TCM prescriptions that are officially recommended in China for novel coronavirus (COVID-19). Materials and methods: Firstly, we adopted the OSPF developed in our previous work, where an ontology-based model separate all the ingredients in a TCM prescription into two categories: hot and cold. Then, we established a database by converting each TCM prescription into a vector containing the ingredient dosage and the according hot/cold attribution as well as the safe/unsafe label. And, we trained the ANN model using this database, after which a safety indicator (SI), as the complementary percentage of side-effect (SE) possibility, is then given for each TCM prescription. According to the proposed SI from high to low, we re-organize the recommended prescription list. Secondly, by using this method, we also evaluate the safety indicators of some other famous TCM prescriptions that are not in the recommended list but are used traditionally to cure flu-like diseases for extending the potential treatments. Results: Based on the SI generated in the ANN model, FTS, PMSP, and SF are the safest ones in recommended list, which all own a more-than-0.8 SI. Whereas, JHQG, LHQW, SFJD, XBJ, and SHL are the prescriptions that are most likely unsafe, where the indicators are all below 0.2. In the extra list, the indicators of XC, XQRS, CC, and CHBX are all above 0.8, and at the meantime, XZXS, SJ, QW, and KBD’s indicators are all below 0.2. Conclusions: In total, there are seven TCM prescriptions which own the indicators more than 0.8, suggesting these prescriptions should be considered firstly in curing COVID-19, if suitable. We believe this work will provide a reasonable suggestion for the society to choose proper TCM as the supplementary treatment for COVID-19. Besides, this work also introduces a pilot and enlightening method for creating a more reasonable recommendation list of TCM to other diseases.

Insect herbivores have a wide range of life cycles and feeding habits, making them extremely diverse. With their host plants, they form close relationships and suppress their defense mecha-nisms. Molecular elicitors are the key bio-elements in detection and recognition of attacking enemies in tissue consumption. Insect oral secretion, frass, and fluid of egg deposition contain bio-logical active molecules called herbivore-associated elicitors (HAEs) are recognized by pattern recognition receptors (PRRs). However, in insect herbivores, little is known about the molecular basis of signal transduction and regulation of plant resistance. Many plants distinguish insect feeding from wounding by HAEs presenting in their oral secretions (OS) and induce local and systemic responses against arthropod feeding. PRRs perceive HAEs in the oral secretion of cater-pillars in a species-specific manner to elicit exclusive defense responses. HAEs-PRRs interactions induce plant resistance by reprogramming plant metabolism and transcriptional machinery. Quantitative, timely, and coordinated plant response initiate early signalling events including Ca+2, reactive oxygen species (ROS) and mitogen-activated protein kinases (MAPKs). We have discussed how early signalling cascades converge into the accumulation of phytohormones that regulate down-stream special metabolites against herbivores. In this review, we have drawn a hypothetical model of PPRs-HAEs mediated induced responses in plants and discussed how PRRs-HAEs interactions based on molecular mechanism that elicit short- and long-term induced defenses in plants. The identification of plant target insect herbivore PRRs-HAEs interactions will help to explore the fundamental molecular mechanisms of host manipulation and may generate prospects to develop novel pest resistance strategies.

Industrial nameplates serve as a means of conveying critical information and parameters. In this work, we propose a novel approach for rectifying industrial nameplate pictures utilizing a probabilistic Hough transform. Our method effectively corrects for distortions and clipping, and features a collection of challenging nameplate pictures for analysis. To determine the corners of the nameplate, we employ a progressive probability Hough transform, which not only enhances detection accuracy but also possesses the ability to handle complex industrial scenarios. The results of our approach are clear and readable nameplate text, as demonstrated through experiments that show improved accuracy in model identification compared to other methods.

Ocean surface currents and winds are tightly coupled essential climate variables, and, given their short time scales, observing them at the same time and resolution is of great interest. DopplerScatt is an airborne Ka-band scatterometer that has been developed under NASA's Instrument Incubator Program (IIP) to provide a proof of concept of the feasability of measuring these variables using pencil-beam scanning Doppler scatterometry. In the first half of this paper, we present the Doppler scatterometer measurement and processing principles, paying particular attention to deriving a complete measurement error budget. Although Doppler radars have been used for the estimation of surface currents, pencil-beam Doppler Scatterometry offers challenges and opportunities that require separate treatment. The calibration of the Doppler measurement to remove platform and instrument biases has been a traditional challenge for Doppler systems, and we introduce several new techniques to mitigate these errors when conical scanning is used. The use of Ka-band for airborne Doppler scatterometry measurements is also new, and, in the second half of the paper, we examine the phenomenology of the mapping from radar cross section and radial velocity measurements to winds and surface currents. To this end, we present new Ka-band Geophysical Model Functions (GMF's) for winds and surface currents obtained from multiple airborne campaigns. We find that the wind Ka-band GMF exhibits similar dependence to wind speed as that for Ku-band scatterometers, such as QuikSCAT, albeit with much greater upwind-crosswind modulation. The surface current GMF at Ka-band is significantly different from that at C-band, and, above 4.5 m/s has a weak dependence on wind speed, although still dependent on wind direction. We examine the effects of Bragg-wave modulation by long waves through a Modululation Transfer Function (MTF), and show that the observed surface current dependence on winds is consistent with past Ka-band MTF observations. Finally, we provide a preliminary validation of our geophysical retrievals, which will be expanded in subsequent publications. Our results indicate that Ka-band Doppler scatterometry could be a feasible method for wide-swath simultaneous measurements of winds and currents from space.

We analyze a time-delayed SIQR model that considers the transportation-related infections and entry-exit screening. This model aims to determine the measures for preventing and controlling major emergent infectious diseases and the associated costs. We calculate the basic reproduction number (R0), apply the linearization method, and construct an appropriate Lyapunov function to determine the stability of the disease-free equilibrium in the local and global. We collect COVID-19 infection data from two regions in the United States in 2020 for data fitting, obtain a set of optimal parameter values, and show that the model is suitable for simulating the outbreak and spread of emerging infectious diseases. We find that transportation-related infections increase the basic reproduction number, enhancing the impact on disease spread. Entry-exit screening effectively suppress the spread of disease by reducing the basic reproduction number. Furthermore, we investigate the influence of the incubation period on disease and find that a shorter incubation period results in a shorter duration but a larger scale of infection, and the peaks are reduced. We conduct a sensitivity analysis of the R0 and propose three measures to prevent the spread of new infectious diseases based on the most sensitive parameters: wearing masks, implementing urban closures, and administering medication to sick but not yet hospitalized patients promptly. In the case of COVID-19, we use Pontryagin’s minimum principle to get time-varying control measures to control the spread of the outbreak. Optimal control effectively controls the development and deterioration of the disease. Finally, several control measures are compared through cost-effectiveness analysis, and the results show that wearing masks is the most cost-effective measure. Our study provides some practical guidance for controlling the spread of major emerging infectious diseases.

This qualitative study explores consumer perceptions of ethical supply chains and their implications for brand loyalty in contemporary markets. Ethical supply chain practices, encompassing sustainability, transparency, and social responsibility, are increasingly pivotal in shaping consumer attitudes and behaviors. A semi-structured interview approach was utilized to gather insights from a diverse sample of consumers, revealing nuanced perspectives on how ethical considerations influence brand preferences and loyalty. Findings indicate that consumers value brands that demonstrate genuine commitment to ethicality, viewing transparency and accountability in supply chain operations as essential for building trust and credibility. Emotional responses such as admiration and respect were commonly associated with brands perceived as ethical, highlighting the emotional resonance of ethical supply chain practices in consumer decision-making processes. Challenges such as greenwashing and perceived discrepancies between brand promises and actions underscore the importance of authentic communication in aligning consumer perceptions with brand behaviors. The COVID-19 pandemic further emphasized the role of ethical supply chains in ensuring business resilience and consumer trust during global disruptions. Brands that exhibited ethical leadership during the crisis reinforced their reputational capital and strengthened relationships with ethically conscious consumers. This study contributes to understanding the strategic imperative for businesses to integrate and communicate ethical supply chain practices effectively, thereby fostering sustainable competitive advantages and enhancing long-term brand loyalty. Future research directions include exploring evolving consumer expectations, emerging ethical challenges, and innovative strategies for embedding ethicality into supply chain management.This qualitative study explores consumer perceptions of ethical supply chains and their implications for brand loyalty in contemporary markets. Ethical supply chain practices, encompassing sustainability, transparency, and social responsibility, are increasingly pivotal in shaping consumer attitudes and behaviors. A semi-structured interview approach was utilized to gather insights from a diverse sample of consumers, revealing nuanced perspectives on how ethical considerations influence brand preferences and loyalty. Findings indicate that consumers value brands that demonstrate genuine commitment to ethicality, viewing transparency and accountability in supply chain operations as essential for building trust and credibility. Emotional responses such as admiration and respect were commonly associated with brands perceived as ethical, highlighting the emotional resonance of ethical supply chain practices in consumer decision-making processes. Challenges such as greenwashing and perceived discrepancies between brand promises and actions underscore the importance of authentic communication in aligning consumer perceptions with brand behaviors. The COVID-19 pandemic further emphasized the role of ethical supply chains in ensuring business resilience and consumer trust during global disruptions. Brands that exhibited ethical leadership during the crisis reinforced their reputational capital and strengthened relationships with ethically conscious consumers. This study contributes to understanding the strategic imperative for businesses to integrate and communicate ethical supply chain practices effectively, thereby fostering sustainable competitive advantages and enhancing long-term brand loyalty. Future research directions include exploring evolving consumer expectations, emerging ethical challenges, and innovative strategies for embedding ethicality into supply chain management.

By reviewing the research of development economics in recent years, five key terms of ‘innovation, coordination, green, openness and sharing’ are extracted, corresponding to the five dimensions of the New Development Concept advocated by China. Based on this, an evaluation index system of the development quality of China's fishery industry is constructed. The spatio-temporal characteristics of China's fishery industry development quality were analyzed by using the provincial panel data from 2007 to 2017. The results show that: i) China's fishery industry overall development quality continues to grow, while the variation of provincial quality is also increasing, and the contribution of innovation quality and sharing quality is increasing, becoming an important sub-dimension leading the overall development quality.ii) there is a significant spatial dependence among provincial quality, and the significance is further strengthening. The Hangzhou Bay area and Bohai Bay area have gradually become a dual-core area where the high-quality development of China's fishery industry agglomeration, and the radiation from the dual-core area to the peripheral areas may still be in the process of enhancement. The spatial and temporal distribution of China’s fishery industry development quality keeps the trend of ‘from northeast to southwest’, which is almost parallel to Hu Huanyong line. The gravity center of its distribution is close to the gravity center of Chinese population and economy, and the development quality experienced a process from relatively concentrated to dispersed and then returned to concentrated, and the development speed in the later period was higher than that in the earlier period. iii) Capital accumulation level is the dominant positive influencing factors, while government support level is the dominant negative influencing factors respectively, and both have significant spatial differentiation among provinces.

Supply chain transparency and traceability have become increasingly important in today's globalized and interconnected business environment. This qualitative research explores the challenges and perspectives of industry practitioners regarding supply chain transparency and traceability. Drawing on semi-structured interviews with a diverse group of supply chain professionals, the study identifies key themes including difficulties in achieving visibility beyond immediate suppliers, data fragmentation and inconsistency, barriers to technology adoption, regulatory compliance, cultural and organizational factors, impacts on supplier relationships, and the influence of the COVID-19 pandemic and sustainability goals. The findings highlight the complex nature of these challenges and the need for collaborative, multi-stakeholder approaches to address them effectively. Despite the challenges, the study also reveals the potential benefits of transparency and traceability for enhancing supply chain resilience, sustainability, and stakeholder trust. Moving forward, companies must leverage technological innovations, establish clear communication channels with suppliers, navigate regulatory complexities, and foster a culture of transparency and accountability within their organizations. Future research should focus on practical strategies for implementing transparency and traceability initiatives, as well as evaluating their impact on supply chain performance and sustainability outcomes.

The abstract of the study on the challenges and opportunities of supply chain digitalization encapsulates the primary findings and their implications from the perspectives of industry leaders. This qualitative research investigated how senior executives across diverse sectors perceive and manage the transition to digital supply chains. Interviews with twenty industry leaders revealed key challenges such as data integration, cybersecurity, organizational resistance, and financial constraints. Data integration issues were particularly pronounced, as participants struggled with unifying disparate data sources from legacy and modern systems, creating barriers to achieving cohesive digital frameworks. Cybersecurity emerged as a critical concern due to the increased vulnerability of digital supply chains to cyber threats, necessitating robust and proactive security measures. Organizational resistance, driven by employee apprehensions about job displacement and technological unfamiliarity, highlighted the need for effective change management practices, including clear communication and training. Financial constraints, especially for small and medium-sized enterprises (SMEs), underscored the difficulty of justifying the substantial investments required for advanced digital technologies. Despite these challenges, the study identified significant opportunities associated with digitalization, including enhanced operational efficiency, improved visibility, predictive analytics, and better customer satisfaction. Digital tools were found to streamline processes, reduce manual intervention, and provide real-time insights into supply chain performance, thus facilitating more informed decision-making and swift responses to disruptions. The accelerated adoption of digital technologies during the COVID-19 pandemic demonstrated their essential role in enhancing supply chain resilience and agility. Additionally, the integration of sustainability goals through digitalization supported resource optimization and waste reduction, aligning with broader corporate social responsibility objectives. The findings suggest that while the path to digital transformation is complex, the benefits of improved efficiency, decision-making, customer satisfaction, and sustainability present compelling incentives for organizations to invest in and embrace digital supply chain solutions.

Earth observation satellites can capture images of specific areas in Earth's orbit based on user requirements. Despite the high demand for satellite imagery, satellites remain a scarce resource. When there are many observation tasks that are large and dense, they may interfere with each other due to satellite mobility. To address this issue, a multi-satellite scheduling algorithm based on a task merging mechanism has been proposed. This paper proposes a two-stage approach to the problem: task merging phase and merging task scheduling phase. The task merging phase introduces two methods based on Mean Shift and Complete Graph to generate the merging task set. In the merging task scheduling phase, a multi-satellite scheduling algorithm based on merging tasks is employed to solve the problem. Finally, certain measurement experiments suggest the effectiveness of the algorithm.

In this research, 117,718 ionospheric perturbations, with a space size (t) of 20–300 s but no limit on amplitude (A) have been automatically searched globally by a software from ion density data measured by the DEMETER satellite for more than 6 years. The influence of the solar activity on the ionosphere has been firstly examined and the results have presented that the solar activities can globally enhance ionospheric irregularities but rarely induce plasma variations more than 100%. A statistical work has been performed on ion PERs to check their dependence on local time and it is shown that there are 24.8% perturbations appeared in daytime (10:30 LT) and 75.2% ones in nighttime (22:30 LT). Ionospheric fluctuations with an absolute amplitude A < 10% tend to be background variations and the percentages of positive perturbations with small A < 20% are 64% in daytime and 26.8% in nighttime, respectively, but this number is revers for mid-large amplitude PERs. There is a demarcation point in space size t = 120 s and occurrence probabilities of day PERs are always higher than that of nighttime ones before this point while this trend is contrary after this point. Distributions of PER according to various amplitudes or space scales have been characterized by typical seasonal variations either in daytime or in nighttime. The EIA only exists in dayside equinox and winter occupying two lowlatitude crests with lower Np. The huge WSA appears in all periods except for dayside summer full of PERs with enhanced amplitude, especially in winter night. The WN-like structure can be obviously figured out in all seasons showing absolutely space large-scales. In the meanwhile, several magnetic anomalous zones of planetary scale non-dipole fields, such as the SAMA, Northern Africa anomaly, and so on, have been also successfully detected by extreme negative ion perturbations in this time.

We investigated and quantified soil organic carbon (SOC) stock at the mangrove forest (Magyi, That Bot Khan and Wette) of Shwe Thaung Yan coastal region in Myanmar and estimated the SOC stock changes in Magyi mangrove forest over six years using repeated field measurements. The study sites were characterized by different mangrove vegetation, soil types, and sediment deposition from different water sources. Results showed that the mangrove preservation and restoration efforts had a significant effect on soil C storage, with soil carbon stocks in 2021 (1954.43 ± 33.24 ton/ha) being 2.7 times higher than the estimated carbon stock in 2015 (732.26 ± 6.99 ton/ha). The results also revealed slight differences in SOC between Magyi and the Tha-Bot-Khan and Wette areas, as the mangrove plants in the latter areas have an additional source of nutrients from Pho-Thoung-Gyi, a deep-sea bay near the forest. Our research findings are beneficial in understanding the role of Myanmar’s mangrove ecosystems in carbon sequestration and climate change mitigation efforts.

This study explores the role of stakeholder engagement in enhancing supply chain sustainability within the renewable energy sector. Through a qualitative research approach, including in-depth interviews with key stakeholders such as government agencies, industry associations, renewable energy companies, community groups, and environmental organizations, the research reveals the complexity and significance of effective stakeholder engagement. Stakeholders highlighted diverse motivations, including environmental, social, economic, and regulatory concerns, driving their participation. The study underscores the importance of tailored engagement strategies that recognize stakeholder heterogeneity and address specific needs and expectations. Collaborative approaches, such as public-private partnerships and multi-stakeholder initiatives, were identified as crucial for pooling resources, sharing knowledge, and addressing common challenges. However, challenges related to power imbalances, conflicting interests, and communication barriers were also noted. Government policies and regulatory frameworks were found to play a pivotal role in shaping stakeholder engagement practices and sustainability outcomes. Regulatory uncertainty and inconsistency were cited as significant concerns that could undermine sustainability initiatives. Community engagement emerged as a critical factor, with local communities often directly impacted by renewable energy projects. Meaningful engagement, including consultation and benefit-sharing mechanisms, is essential for building trust and securing social acceptance. Emotional intelligence and marketing strategies were recognized as important tools for effective stakeholder engagement, emphasizing the role of empathy, active listening, and clear communication. The findings of this study highlight the need for a holistic and integrated approach to stakeholder engagement and supply chain sustainability in the renewable energy sector. By addressing diverse stakeholder needs, fostering collaboration, and aligning policies with sustainability goals, stakeholders can work together to accelerate the transition towards a more sustainable energy future.

This study probes the probabilistic features of major fire hazards in enclosed spaces to establish their importance to the occurrence of fires onboard ro-ro passenger ships and in turn to raise effective operational countermeasures. Distinct from the previous studies, the present research employs Bayesian Network (BN) analysis to determine the probabilities of fire hazards more effectively. The findings of the research include five critical basic events (BE) identified namely, vehicle engine fire (fuel system fault), vehicle electric fire (electrical equipment defect or short circuit), used car electrical fire, reefer units electrical fire (electrical appliances defects or short circuit), and cargo spontaneous combustion. Additionally, the risk of fire for lithium - ion battery powered vehicles is also highlighted in the process of BN analysis, which prompts the authors to propose preventive measures for mitigating the possibility of fire occurrence on this type of electric vehicles. It is hoped that these measures can be essential justifications for establishing relevant rules regarding carrying LIB vehicles in enclosed spaces on international level.

This paper presents a novel sensor for the detection and characterization of regions of air turbulence that would be of use to improve UAV stability in bad weather. It consists of a combined Schlieren imager and a Radar Acoustic Sounding System (RASS) to produce dual modality “images” of air movement within the measurement volume. The ultrasound modulated Schlieren imager consists of a strobed point light source, parabolic mirror, light-block and camera which are controlled by two laptops. It provides a fine scale projection of the acoustic pulse modulated air turbulence through the measurement volume. The narrow beam 40 kHz/ 17 GHz RASS produces spectra based on Bragg enhanced Doppler radar reflections from the acoustic pulse as it travels. Tests using artificially generated air vortices showed some disruption of the Schlieren image and of the RASS spectrogram. This should allow the higher resolution Schlieren images to identify the turbulence mechanisms that are disrupting the RASS spectra.

Since matter, energy and information are the three major components of the world, is there an interaction between information and matter? In the present work, the coevolution of human language and brain is taken as a case of interaction between information and brain. Some evidence that may show interactions between human language and brain revealed by previous researches is summarized in this paper, such as the language areas in the cerebral cortex of the modern human brain, the evolution of human language and brain in human history, and the genetic basis for the evolution of language. Based on the evidence, a dynamic model is developed to investigate the possible mechanism of coevolution of human language and brain. In the model, human language development and brain development reinforce each other: the developmental level of language can be promoted by advances in brain function due to language-related gene mutations, in turn, whether such mutations are selected positively can be influenced by the current developmental level of language. The coevolution of human language and brain can be taken as a case of interaction between information and matter.

Catalytic upgrading of bio-based platform molecules is one of promising approaches for biomass valorization. However, most solid catalysts are thermally and/or chemically unstable and difficult to prepare. In this study, a stable organic phosphonate-hafnium solid catalyst (PPOA-Hf) was synthesized, and acid-base bifunctional sites were found to play a cooperative role in the cascade transfer hydrogenation and cyclization of ethyl levulinate (EL) to γ-valerolactone (GVL). Under relatively mild reaction conditions of 160 ºC for 6 h, EL was completely converted to GVL in a good yield of 85%. The apparent activation energy was calculated to be 53 kJ/mol, which was lower than other solid catalysts for the same reaction. In addition, the PPOA-Hf solid catalyst did not significantly decrease its activity after five recycles, and no evident leaching of Hf was observed, indicating its high stability and potential practical application.

We report on the role of synergistic polarization of Ba0.9Sr0.1TiO3 (BST) nanoparticles in sulfur cathodes to enhance the redox kinetics of polysulfides for high-capacity Li-S batteries. Ferroelectric nanoparticles are known to significantly improve the electrochemical performance of Li-S batteries due to their inherent self-polarization and high adsorption capacity towards polysulfides. X-ray diffraction spectra confirmed the tetragonal symmetry (c/a=1.0073), while Raman spectroscopic analysis validated the presence of tetragonal orientation Raman modes in BST-modified composites. Scanning electron microscope (SEM) images showed a homogeneous distribution of BST in the sulfur cathode system, with grain sizes ranging from 1 to 1.5 μm. Notably, the BST-coupled S50BST30CB10PVDF10 composite cathode achieved a capacity of approximately 820 mAh/g at 100 mA/g, maintaining stability over 100 cycles, demonstrating improved electrochemical performance. Two distinct plateaus between 2.3 V to 2.0 V and 2.0 V to 1.5 V further underscore the superior performance of BST ferroelectric nanoparticles in enhancing the redox kinetics of Li-S batteries. By leveraging the favourable affinity of polar substances towards polysulfides, we aimed to create a more stable reactive environment within the cathodic site, effectively trapping polysulfide intermediates through the synergistic polarization of BST nanoparticles. The synergistic polarization induced by the asymmetric crystal structure of ferroelectrics is anticipated to generate internal electric fields, enhancing chemisorption with heteropolar reactive. The observed high cyclic stability further validates the efficacy of these composite cathodes in mitigating the polysulfide shuttle effect, offering promising prospects for advancing Li-S battery technology.

Blockchain technology (BCT) has the potential for sustainable development, enhancing business efficiency, reducing costs, and strengthening data security. Despite its potential, adoption among small and medium-sized enterprises (SMEs) is low due to the need for significant changes in technology infrastructure and the challenge of interoperability. A cross-sectional survey was done with 226 Hong Kong SMEs. The PLS-SEM results highlighted favorable transformation conditions as the most critical factor for SMEs considering the adoption of BCT. These conditions address both internal and external readiness for adopting the disruptive strategy. Other contributing factors to BCT adoption include trust in BCT developers, perceived usefulness and ease of use, government support, and perceived security. The research results contributed to the literature on disruptive technology acceptance, adoption, transformation conditions, technology readiness, and SMEs’ technology adoption. Government-supported policies and initiatives can promote BCT adoption, including educational programs, case studies, and resources for readiness. Financial support and regulatory frameworks can further encourage adoption. BCT developers can demonstrate the value of their systems, effectively communicate potential ROI and cost savings, and provide user-friendly interfaces to increase SMEs’ intention to adopt BCT.

Mate crime is a specific subset of hate crime in which the perpetrator is known to the victim. To date, there is very little research into the perception and experience of mate crime in autism. The aim of the current study was to examine perceptions of friendship and mate crime in autistic adults, using semi-structured interviews. Five adults were interviewed about their experiences of social interactions, friendships and mate crime. Participants described distancing themselves from the ‘disability’ label whilst growing up to avoid condescension and being perceived as vulnerable, whilst learning to camouflage their social difficulties. Feelings of anxiety were associated with socialising, and participants valued relationships that did not place too many overwhelming demands on their time or energy. Finally, all participants had prior experiences of bullying. They understood the concept of mate crime but were unsure as to whether they would be able to identify it in their own lives if it occurred. However they could identify potential support networks in close friends and family. Results highlight the importance of further research into positive and negative aspects of social relationships in autistic adults, and the need to provide support to those who are socially vulnerable.

Taking a certain type of test centrifuge as the research object, the finite element model of the test centrifuge is established, the vibration characteristics and aerodynamic performance of the test centrifuge are analyzed, and the structural optimization design of the test centrifuge is carried out. In this paper, the load is applied according to the actual working condition of a certain type of test centrifuge. The vibration of the mounting seat of the test centrifuge is analyzed and the structure of the mounting seat is optimized. After optimization, the vibration of the mounting seat is 77.38 % lower than that of the original mounting seat. Then, the aerodynamic analysis of the test centrifuge is carried out. The analysis results show that the test centrifuge moves more smoothly under the whole package shell and the steady flow shell, and the resistance decreases and the shaft load decreases. Finally, the steady flow shell of the test centrifuge is optimized. The analysis shows that the increase of the width of the steady flow shell can reduce the resistance coefficient, which is helpful to the stability of the test centrifuge during operation and reduces the unbalanced response of the system caused by air resistance.

Translation is spatiotemporally regulated and ER-associated mRNAs are generally in efficient translation. It is unclear whether the ER-associated mRNAs are deadenylated or degraded on the ER surface in situ or in the cytosol. Here, we showed that ER possessed active deadenylases, particularly the poly(A)-specific ribonuclease (PARN), in common cell lines and mouse tissues. Consistently, purified recombinant PARN exhibited a strong ability to insert into the Langmuir monolayer and liposome. ER-anchored PARN was found to be able to reshape the poly(A) length profile of the ER-associated RNAs by suppressing long poly(A) tails without significantly influencing the cytosolic RNAs. The shortening of long poly(A) tails did not affect global translation efficiency, suggesting that the non-specific action of PARN towards long poly(A) tails was beyond the scope of translation regulation on the ER surface. Transcriptome sequencing analysis indicated that the ER-anchored PARN trigged the degradation of a small subset of ER-enriched transcripts. The ER-anchored PARN modulated the translation of its targets by redistributing ribosomes to heavy polysomes, suggesting that PARN may play a role in dynamic ribosome reallocation. During DNA damage response, MK2 phosphorylated PARN-Ser557 to modulate PARN translocation from the ER to cytosol. By promoting the decay of ER-associated MDM2 transcripts with low ribosome occupancy, the ER-anchored PARN modulated DNA damage response and thereby cell viability. These findings revealed that a highly regulated communication between mRNA degradation rate and translation efficiency is present on the ER surface in situ and that PARN may contribute to this communication by modulating the dynamic ribosome reallocation between transcripts with low and high ribosome occupancies.

Three new species of the Sequester group of Pteromalus (Habrocytus) (Hymenoptera: Pteromalidae: Pteromalinae), Pteromalus (Habrocytus) boleensis Yan et Li sp. nov., Pteromalus (Habrocytus) longepedicelus Yan et Li sp. nov., and Pteromalus (Habrocytus) robustus Yan et Li sp. nov. are described and illustrated based on adult morphology and molecular data from Xinjiang, China. The DNA barcodes (ITS2) of Pteromalus (Habrocytus) boleensis sp. nov. and Pteromalus (Habrocytus) robustus sp. nov. have been generated and compared with all existing sequences of the Sequester species group. The results of morphological taxonomy and molecular identification are consistent. A key to all known species of the Sequester group in the world is provided.

Background: In recent years, computational aesthetics and neuroaesthetics have provided novel insights into understanding beauty. Building upon the findings of traditional aesthetics, this study aims to combine these two research methods to explore an interdisciplinary approach to studying aesthetics; Method: Abstract artworks were used as experimental materials. Based on traditional aesthetics and in combination, features of composition, tone, and texture were selected. Computational aesthetic methods were then employed to correspond these features to physical quantities: blank space, gray histogram, GLCM, LBP, and Gabor filters. An EEG experiment was carried out, in which participants conducted aesthetic evaluations of the experimental materials in different contexts (genuine, fake), and their EEG data was recorded to analyze the impact of various feature classes in the aesthetic evaluation process. Finally, a SVM was utilized to model the feature data, EEG data, context data, and subjective aesthetic evaluation data; Result: Behavioral data revealed that higher aesthetic ratings in the genuine context. EEG data indicated that genuine contexts elicited more negative deflections in the prefrontal lobes between 200-1000ms. Class II compositions demonstrated more positive deflections in the parietal lobes at 50-120ms, while Class I tones evoked more positive amplitudes in the occipital lobes at 200-300ms. Gabor features showed significant variations in the parieto-occipital area at an early stage. Class II LBP elicited a prefrontal negative wave with a larger amplitude. The results of the SVM models indicated that the model incorporating aesthetic subject and context data (ACC=0.76866) outperforms the model using only parameters of the aesthetic object (ACC=0.68657); Conclusion: A positive context tends to provide participants with a more positive aesthetic experience, but abstract artworks may not respond to this positivity. During aesthetic evaluation, the ERP data activated by different features show a trend from global to local. The SVM model based on multimodal data fusion effectively predicts aesthetics, further demonstrating the feasibility of the combined research approach of computational aesthetics and neuroaesthetics.

Background: Symmetry is a special kind of balance. This study aims to systematically explore and apply the role of balanced composition in aesthetic judgments by focusing on balanced composition features and employing research methods from computational aesthetics and Neuroaesthetics. Methods: First, experimental materials were classified by quantifying balanced composition using several indices, including symmetry, center of gravity, and negative space. An EEG experiment was conducted with 18 participants, who were asked to respond dichotomously to the same stimuli under different judgment tasks (balance and aesthetics), with both behavioral and EEG data being recorded and analyzed. Subsequently, participants' data were combined with balanced composition indices to construct and analyze various SVM classification models. Results: Participants largely used balanced composition as a criterion for aesthetic evaluation. ERP data indicated that from 300-500ms post-stimulus, brain activation was more significant in the aesthetic task, with unbeautiful and imbalanced stimuli eliciting larger frontal negative waves and occipital positive waves. From 600-1000ms, beautiful stimuli caused smaller negative waves in the PZ channel. The results of the SVM models indicated that the model incorporating aesthetic subject data (ACC=0.9989) outperforms the model using only balanced composition parameters of the aesthetic object (ACC=0.7074). Conclusions: Balanced composition is a crucial indicator in aesthetics, with similar early processing stages in both balance and aesthetic judgments. Multimodal data models validated the advantage of including human factors in aesthetic evaluation systems. This interdisciplinary approach not only enhances our understanding of the cognitive and emotional processes involved in aesthetic judgments but also enables the construction of more reasonable machine learning models to simulate and predict human aesthetic preferences.

In some parts of Nigeria, many girls do not attend school, and among those sent to school, many still drop out early. This and other socio-cultural factors affect girls psychologically. There is no doubt that girls need consistent love and tutoring to guide them through the turbulent teen years and beyond. They need a mentor who acts as a friend and a role model. The Mobile-based Mentoring Platform seeks to leverage on mobile technology's affordances to focus on the needs of the girl-child, such as improvement in academic achievement, guidance in career choice, development of self-concept, and esteem. The girl-mentees comments revealed that using the platform provided them frequent access to mentors and access to learning opportunities. The challenges they faced include epileptic internet network, intrusions by parents, and others. Therefore, this paper examined the challenges and benefits of mentoring girls via a mentoring platform.

The detection of waste plastics in the marine and terrestrial environment using satellite Earth Observation data offers the possibility of large-scale mapping, and reducing on-the-ground manual investigation. In addition, costs are kept to a minimum by utilizing free-to-access Copernicus data. A Machine Learning based classifier was developed to run on Sentinel-1 and -2 data. In support of the training and validation, a dataset was created with terrestrial and aquatic cases by manually digitizing varying landcover classes alongside plastics under the sub-categories of greenhouses, plastic, tyres and waste sites. The trained classifier, including an Artificial Neural Network and post-processing decision tree, was verified using five locations encompassing these different forms of plastic. Although exact matchups are challenging to digitize, the performance has generated high accuracy statistics, and the resulting land cover classifications have been used to map the occurrence of plastic waste in aquatic and terrestrial environments.

This article aims to understand the role of tacit knowledge in call center organizations with the objective of understanding how call center representatives use tacit knowledge in their job roles and functions. Extant literature has focused on explicit knowledge but the research on tacit knowledge is still underdeveloped. The complexities and difficulties of the call center job role and the usage and transfer of knowledge is reviewed. Also, it takes into considerations past literature on tacit knowledge, how these respondents employ tacit knowledge in efficiently handling customers, responding to their queries, and engaging this form of knowledge in problem solving. The article concludes with discussion and implications for call center organizations and responders.

We report an all-optical radio-frequency (RF) spectrum analyzer with a bandwidth greater than 5 terahertz (THz), based on a 50-cm long spiral waveguide in a CMOS-compatible high-index doped silica platform. By carefully mapping out the dispersion profile of the waveguides for different thicknesses, we identify the optimal design to achieve near zero dispersion in the C-band. To demonstrate the capability of the RF spectrum analyzer, we measure the optical output of a femtosecond fiber laser with an ultrafast optical RF spectrum in the terahertz regime.

In a global context, the story of the Jesuit compound in Shanghai, since its establishment by French Jesuits in 1847, reflected not only conflicts between rival powers in Europe but also the fight for their interests in the Eastern world. The Pope, who was stuck without legal status in the Vatican after 1861, was also seeking the chance to save the authority of the Church in the face of questions regarding the extent of his temporal power and the status of Rome in the context of Italian unification. As in the Reformation, a break-through in the east seemed to offer a solution for losses in Europe. However, the Jesuits to the East in the late 19th century were not only troops working and fighting on behalf of the Pope; their identities under the French Protectorate added complexity to an already complicated story involving not just the Church, but the course of world history.The female Catholic orders at the east bank of Zi-ka-wei compound became a unique window to approach the complexity.

Antimicrobial resistance (AMR) has been a serious threat to human health, and combination therapy is proved to be an economic and effective strategy to fight the resistance. However, the abuse of drug combinations would conversely accelerate the spread of AMR. In our previous work, it had been concluded that the mutant selection indexes (SIs) of one agent against a specific bacterial strain are closely related to the proportions of two agents in a drug combination. To discover probable correlations, predictors and laws for further proposing feasible principles and schemes guiding the AMR-preventing practice, here three aspects were further explored. First, the power function (y=ax^b, a > 0) correlation between the SI (y) of one agent and the ratio value (x) of two agents in a drug combination was further established based on the mathematical and statistical analyses for those experimental data, and two rules a₁ × MIC₁ = a₂ × MIC₂ and b₁ + b₂ = -1 were discovered from both equations of y=a₁x^b1 and y=a₂x^b2 respectively for two agents in drug combinations. Simultaneously, it was found that one agent with larger MPC alone for drug combinations show greater potency for narrowing itself MSW and preventing the resistance. Second, a new concept as mutation-preventing selection index (MPSI) was proposed and used for evaluating the mutation-preventing potency difference of two agents in drug combinations, and the positive correlation between the MPSI and the mutant prevention concentration (MPC) or minimal inhibitory concentration (MIC) was subsequently established. Inspired by this, the significantly positive correlation, contrary to previous reports, between the MIC and the corresponding MPC of antimicrobial agents against pathogenic bacteria was established using one hundred and eighty-one of data pairs reported. These results together of above three aspects indicate that the MPCs in alone and combination are very important indexes for drug combinations to predict the mutation-preventing effects and the trajectories of collateral sensitivity, and while the MPC of an agent can be roughly calculated from its corresponding MIC. Subsequently, the former conclusion was further verified and improved by the antibiotic exposure to forty-three groups designed as different drug concentrations and various proportions. The results further proposed that the C/MPC for the agent with larger proportion in drug combinations can be considered as a predictor and is the key to judge whether the resistance and the collateral sensitivity occur to two agents. Based on these above correlations, laws, and their verification experiments, some principles were proposed, and a diagram of the mutation-preventing effects and the resistant trajectories for drug combinations with different concentrations and ratios of two agents was presented. Simultaneously, the reciprocal of MPC alone (1/MPC), proposed as the stress factors of two agents in drug combinations, together with their SI in combination, is the key to predict the mutation-preventing potency and control the trajectories of collateral sensitivity. Finally, a preliminary scheme for antimicrobial combinations preventing the AMR was further proposed for subsequent improvement research and clinic popularization, based on the above analyses and discussion. Moreover, some similar conclusions were speculated for triple or multiple drug combinations.

BiVO4 powder was synthesized by a simple hydrothermal method. The nanobelts with well dispersed and uniform morphology were synthesized by controlling the temperature. The structure of BiVO4 powder was studied by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The diameter of the nanobelts was about 50 nm. The structure and composition of the nanobelts were studied by X-ray diffraction (XRD), photoluminescence (PL) and X-ray photoelectron spectroscopy (XPS). The absorption intensity of BiVO4 powder in UV-Vis region was compared by UV–vis diffuse reflectance spectroscopy. As a photocatalyst, BiVO4 nanobelts have good photocatalytic ability under visible light irradiation, which is very useful for the treatment of environmental wastewater. The synthesized nanobelts photocatalyst can be reused without destroying its structure. The reusability and chemical stability of photocatalysts are of great significance for practical application.

This study investigates the microstructures and deformation mechanism of hetero-structured pure titanium under different high strain rates (500 s-1，1000 s-1，2000 s-1). The influence of strain rate on the deformation mechanism is examined. As the strain rate increases, the dominance of dislocation slip decreases while deformation twinning becomes more prominent. Notably, at a strain rate of 2000s-1, nanoscale twin lamellae are activated within grain with a size of 500nm, which is a rarely observed phenomenon in pure Ti. Additionally, martensitic phase transformation is also identified. These findings can greatly enhance our understanding of the mechanical responses of Ti and broaden the potential applications of Ti in dynamic deformation scenarios.

Low-dimensional carbon-based (LDC) materials have attracted extensive research attentions in electrocatalysis because of their unique advantages such as structural diversity, low cost, and chemical tolerance. They have been widely used in a broad range of electrochemical reactions to relief environmental pollution and energy crisis. Typical examples include hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), carbon dioxide reduction reaction (CO₂RR), and nitrogen reduction reaction (NRR). Traditional “trial and error” strategies seriously slowed down the rational design of electrocatalysts for these important applications. Recent studies show that the combination of density functional theory (DFT) calculations and experimental research is capable of accurately predicting the structures of electrocatalysts, thus could reveal the catalytic mechanisms. Herein, current well-recognized collaboration methods of theory and practice are reviewed. The history of modern DFT, commonly used calculation methods, and basic functionals are briefly summarized. Special attention is paid to descriptors that are widely accepted as a bridge links the structure and activity, and the breakthroughs for high-volume accurate prediction of electrocatalysts. Importantly, correlating multiple descriptors are used to systematically describe the complicated interfacial electrocatalytic processes of LDC catalysts. In addition, machine learning and high-throughput simulations are crucial in assisting the discovery of new multiple descriptors and reaction mechanisms. This review will guide the further development of LDC electrocatalysts for extended applications from the aspect of DFT computations.

Anthracnose is one of primary diseases in tea plants that affects tea yield and quality. The geographical distribution, occurrence regularity, and agronomic measures of tea plants with anthracnose have been researched for decades. However, the pathogenic cause of anthracnose in tea plants is diverse in different regions of the world. Identifying the specific pathogenic fungi causing tea anthracnose is an essential control measure to mitigate this disease. In this study, 88 Diaporthales and 45 Colletotrichum isolates were obtained from 3 different types of diseased tea leaves. Based on multilocus phylogenetic and morphological analysis, 3 known species, including Discula theae-sinensis, Diaporthe ueckerae, Diaporthe lithocarpus, and 3 indistinguishable species of Diaporthales were identified. In adddition, 8 known species of Colletotrichum, C. fructicola, C. camelliae, C. aenigma, C. siamense, C. henanense, C. karstii, C. tropicicola, C. gigasporum, were identified. This study is the first to report C. tropicicola and C. gigasporum in tea plant in China. Discula theae-sinensis was the most common species in this study and caused disease lesions around wounded areas of tea leaves. The dual trials in vitro indicated Discula theae-sinensis and Colletotrichum were slight inhibition. Co-inoculating Discula theae-sinensis and C. fructicola was superior to single inoculation at low concentration.

This paper presents an extensive performance analysis of open-ended waveguide elements for direct radiating arrays with high scan angle (± 50º/60º). The evaluated designs are based on square and hexagonal apertures loaded with ridges. Both square and triangular lattices are considered in the framework of Ka-band downlink design requirements for future LEO mega-constellations. The parameter space defined by the monomodal condition has been explored to find an optimum value for each structure. The analyses are validated with both infinite and finite full-wave models in terms of active reflection coefficient, scan loss and cross-polar discrimination.