Brain vascular health appears to be of critical importance for protection against the development of amyotrophic lateral sclerosis (ALS) as well as the slowing of disease progression. ALS patients often demonstrate cardiovascular risk factors and commonly suffer from cerebrovascular disease, with evidence of pathological alterations in the small cerebral vessels. Impaired vascular brain health has detrimental effects on motor neurons as lowered vascular endothelial growth factor levels compromise endothelial cell formation, promoting blood-brain barrier leakage and inflammation. Increased turnover of neurovascular unit cells precedes their senescence, which, together with pericyte alterations, further fosters the failure of toxic metabolite removal. We here provide a comprehensive overview of the pathogenesis of impaired brain vascular health in ALS and how novel magnetic resonance imaging techniques can aid its detection. In particular, we discuss vascular patterns of blood supply to the motor cortex with the number of branches from the anterior and middle cerebral arteries acting as a novel marker of resistance and resilience against downstream effects of vascular risk and events in ALS. We outline how certain interventions adapted to patient needs and capabilities have the potential to mechanistically target the brain microvasculature towards favorable motor cortex blood supply patterns. Through this strategy, we aim to guide novel approaches to ALS management and a better understanding of ALS pathophysiology.

Globally, inequalities in educational provision are prevalent between genders, various geographical regions, and among different socio-economic backgrounds. Consequently, this study set-out to assess the level of disparity among the Federal Regional States of Ethiopia using Gini-coefficient and Lorenz curve from the statistical data of MoE. Moreover, data were collected from 656 respondents found in the sample regions. The result of the Gini-coefficient indicated that disparity in educational provision has been reduced over the past couple of decades both at primary (0.145 to 0.032) and secondary levels (0.277 to 0.126). Emerging regions are by far lagging behind the central and established regions. The sources of variation were mainly the demand-side variables, especially the economic and contextual related issues like drought and conflicts. Therefore, educational policies designed at the central level are advised to consider the strategies to bridge the existing inequalities through equitable provision of the education system to its citizen.

This study emphasizes the necessity of introducing a blockchain-based joint logistics system to strengthen the competency of medical supply chain management (SCM) and tries to develop a healthcare supply chain management (HSCM) competency measurement item through an analytic hierarchy process. The variables needed for using blockchain-based joint logistics are the performance expectations, effort expectations, promotion conditions, and social impact of the UTAUT model, and the HSCM competency results in increased reliability and transparency, enhanced SCM, and enhanced scalability. Word cloud results, analyzing the most important considerations to realize work efficiency among medical industry-related agencies, mentioned numerous words, including sudden situations, delivery, technology trust, information sharing, effectiveness, urgency, etc. This might imply the need to establish a system that can respond immediately to emergency situations during holidays. It could also suggest the importance of real-time information sharing to increase the efficiency of inventory management. Therefore, there is a need of a business model that can increase the visibility of real-time medical SCM through big data analysis. By analyzing the importance of securing reliability based on the blockchain technology in the establishment of a supply chain network for HSCM competency, we reveal that joint logistics can be achieved and synergistic effects can be created by implementing the integrated database to secure HSCM competency. Strengthening partnerships, such as joint logistics, will eventually lead to HSCM competency. In particular, HSCM should seek ways to upgrade its competitive capabilities through big data analysis based on the establishment of a joint logistics system.

Food additives are used for a variety of technological or processing reasons, including to add or restore colour in a food. In European Union (EU) the safety of food additives was in history assessed by the Scientific Committee on Food, while the role of risk accessor is not in hands of the European Food Safety Authority (EFSA). Only additives for which the proposed uses is considered safe are on the EU list of authorized additives. Very recently – in May 2020, a scientific opinion was published by the EFSA, concluding that TiO2 can no longer be considered as a safe food additive, and the European Commission is expected to remove it from list of authorized food additives in near future. Our aim was to investigate the trends in the use of TiO2 in the food supply. A case study was conducted in Slovenia, using two nationally representative cross-sectional datasets of branded foods. Original sample contained 49,919 pre-packed food items, while analyses was done on N=12.644 foods (6.012 and 6.632 in 2017 and 2020, respectively) from 15 food subcategories, where TiO2 was found as food additive. Overall, we observed significantly decrease in use of TiO2 (3.6% vs. 1.8%; p<0.01) in the course of these three years. The most TiO2-containing foods were in the Chewing gum category (36.3%) in 2017, and Chocolate and sweets (45.9%) in 2020. Meanwhile in 2017 the largest within-category share of TiO2-containing foods was Chewing gum category, namely 70.3%, and those products presented over 85% of the market-share. In 2020 only 24.6% chewing gums contained TiO2, and those were accounting only 3% of the market share. In con-clusion, we showed overall decrease of TiO2 use and considerable improvements in certain food categories (particularly in chewing gums) despite the fact, that this additive has not yet been of-ficially removed from the list of authorized additives. Specific food categories (i.e. Chocolate and sweets) were identified, where product-reformulation is needed, and where official controls by authorities will be most relevant.

Additive manufacturing (AM) processes, including stereolithography (SL), can fabricate complex ceramic parts layer by layer using computer-aided design (CAD) models. A ceramic slurry with high solid loading is usually used in SL to fabricate the desired shape, which is further sintered to produce the final part. The traditional SL system utilizes a tank filled with printable material, known as a vat, which for ceramic slurry contributes several limitations and operational difficulties, and further renders it non-recyclable mainly due to its high viscosity and the fragility of the green state. In this study, we utilized a continuous film supply (CFS) printer integrated with a tape casting system using in-house-designed ceramic slurry to print standard prototype specimens. Various printing parameters, including viscosity, layer thickness control, and slurry recycling efficiency, were studied. In addition, post-processing optimizations of the prototype, characterizations, and the microhardness of sintered samples were studied to determine their properties and compare them with traditional methods. The effectiveness of slurry reusability was demonstrated by printing with original and recycled slurry to produce consistent densification of final parts. Post-processing was optimized to achieve a relative sinter density of 99.02% and microhardness of 12.59 GPa. This method provides new opportunities to realize dense complex ceramic features with final properties comparable to those produced by subtractive machining and traditional SL. Furthermore, slurry recycling helps to reduce the overall cost and material consumption.

With the development of big data analysis, blockchain and other technologies, the supply chain of enterprises is transforming to lean and intelligent. As an important link in the enterprise supply chain, the intelligent transformation of procurement plays an important role in the improvement of the supply chain efficiency, therefore, the construction of a common method supporting the intelligent upgrade of the enterprise procurement business has become a key concern for enterprise managers. Based on the balanced scorecard theory and the supply chain maturity model, this study combines the actual situation of procurement management in Chinese energy enterprises and constructs a procurement benchmarking system that balances the development direction of the industry and the actual needs of enterprises. Meanwhile, based on the grounded theory, three major themes of the intelligent procurement system (digital business module, procurement synergy mechanism and procurement ecosystem) are extracted to provide a methodological reference for the construction of intelligent procurement systems of energy enterprises. The study concludes with a case study of China National Energy Group Materials Company to demonstrate the application of the intelligent procurement system built in this paper, with a view to providing methodological reference for the intelligent procurement management in energy enterprises.

Biofuels and biochemicals play significant roles in the transition towards a fossil-free society. However, large-scale biorefineries are not yet cost-competitive with their fossil-fuel counterparts, and it is important to identify biorefinery concepts with high economic performance. For evaluating early-stage biorefinery concepts, one needs to consider not only the technical performance and process costs but also the economic performance of the full supply chain and the impacts on feedstock and product markets. This article presents and demonstrates a conceptual interdisciplinary framework that can constitute the basis for evaluations of the full supply-chain performance of biorefinery concepts. This framework considers the competition for biomass across sectors, assumes exogenous end-use product demand, and incorporates various geographical and technical constraints. The framework is demonstrated empirically through a case study of a sawmill-integrated biorefinery producing liquefied biomethane from forestry and forest industry residues. The case study results illustrate that acknowledging biomass market effects in the supply chain evaluation implies changes in both biomass prices and the allocation of biomass across sectors. The proposed framework should facilitate the identification of biorefinery concepts with a high economic performance which are robust to feedstock price changes caused by the increase in biomass demand.

At present time world is facing from the coronavirus disease known as Covid-19. The first case of the coronavirus was reported in the December, 2019 in the Wuhan city of China which is known as the major transportation hub of China. After the spread of Covid-19 many countries have shut down their sea ports and airports. They have banned the import and export activities. Also, China is the major distributor of the raw materials which affect the manufacturing activities across the globe due to lockdowns. India is the developing country due to the Covid-19 spread the cases reported in the India government has lockdown the country for 41 days which affected the manufacturing activities and majorly it affects the supply chains and economy of the country. In the present paper we have discussed the effect of Covid-19 on Indian economy and on supply chains in India. There are total of 18 critical barriers are found out which affected the supply chains in the India. It is expected that this study will helpful the researchers to develop the conceptual models to overcome from this issue.

This study was conducted generally by aiming assessment of the hydraulic performance of water distribution systems of Addis Ababa Science and Technology University (AASTU). In line with the main objective, this study addressed, (1) pinpointing problems of existing water supply versus demand deficit (2) evaluating the hydraulic performance of water distribution system using water GEMS and (3) recommended alternative methods for improving water demand scenarios. The University’s water supply distribution network layout was a looped system and the flow of water derived by both gravity and pressurized system. The gravity flow served for the academic and administrative staffs whereas the pressurized system of the network fed the students dormitories, cafeteria’s etc. The study revealed the existence of unmet minimum pressure requirement around the student dormitories which accounts 25.64% below the country’s building code standard during the peak hour consumption. The result of the water demand projection showed an increment of 2.5 liter per capita demand (LPCD) in every five years. Hence, first, the university’s water demand was projected and then hydraulic parameters such as; pressure, head loss and velocity were modeled for both the existing and the improved water supply distribution. The finding of the study was recommended to the university’s water supply project and institutional development offices for its future modification and rehabilitation works.

Abstract: Many countries around the world suffer from the lack of a sea port directly linked to the rest of the world. Such countries are called "landlocked countries". This leads to Weak competitiveness of their products in the global market, as well as to the high cost of the imports. Africa has the largest share of these countries, with 16 of the 43 landlocked countries around the world. The aim of this paper is to propose a general framework for criteria that can be used to choose between ports in transit countries that can be used for import or export. These criteria are related to the assessment of the sea ports in terms of infrastructure and tariffs. It is also related to transport infrastructure from the transit country to the landlocked country and the level of safety. The study identified nine criteria that could be used to compare between ports in transit countries. Using Full Consistency Method (FUCOM) to evaluate those criteria showed that the number of navigation lines is the most important criteria followed by the port service level.

Digital technologies have changed the way supply chain operations are structured. In this article, we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks. A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0, with a specific focus on the mitigation of cyber risks. An analytical framework is presented, based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies. This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning (AI/ML) and real-time intelligence for predictive cyber risk analytics. The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge. This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when AI/ML technologies are migrated to the periphery of IoT networks.

Improving the efficiency of the supply process in prefabricated components is challenging and requires accounting for a variety of risks involved in the management of the suppliers. The purpose of this study is to present a method to account for the systematic trade-offs between several supplier alternatives. A novel framework is presented for the whole assessment of supplier alternatives by taking advantage of the information extracted from customized building information modeling (BIM) and a database required for assessment of impacts. A data library related to assessment criteria for supply alternatives is built to facilitate the storage and sharing of information. Analytic hierarchy process (AHP) is used to select the optimal supplier that is able to provide the most satisfaction for the determined criteria. The proposed framework was also illustrated by the implementation in a mega project. The study implication is that BIM-enabled supplier selection can indeed lead to more benefits and higher values for all stakeholders.

The Smart Park (well-known as Taman Pintar) as a major educational tourism destination in Jogjakarta offers a variety of tourism attractions that are very interesting for tourists. The main purpose of tourists visiting Smart Park is to get an educational tourism experience. A subjective experience raises a specific challenge for Smart Park toward the status of competitive destination. The purpose of this study is to analyze the aspects of educational tourism experience that are affected by tourism demand and supply. Data were collected by survey technique to 150 respondents and analyzed using path analysis. The results of analysis show that tourism demand and supply contributed to the variation of tourism activities by 45.1%, while the remaining was explained by other variables, such as National Budget, Local Budget, ticket sale, and cooperation with some stakeholders. Tourism supply had a higher effect than tourism demand. Tourism demand did not partially affect tourism experience. However, the results of the path analysis indicate that tourism supply had direct and indirect effects on tourism experience through the variation of tourism activities with indirect effect being dominant. In the management of Smart Park, there is still a gap between tourism demand and supply, so that the environment of tourism experience has not been created maximally.

Dual quaternions have wide applications in automatic differentiation, computer graphics, mechanics and others. Due to its application in control theory, the matrix equation AXB=C has been extensively studied. However, there is currently limited information on matrix equation AXB=C over the dual quaternion algebra. In this paper, we provide the necessary and sufficient conditions for the solvability of the dual quaternion matrix equation AXB=C, and present the expression for the general solution when it is solvable. As an application, we derive the ϕ-Hermitian solutions for the dual quaternion matrix equation AXAϕ=C, where the ϕ-Hermitian extends the concepts of Hermiticity and η-Hermiticity. Lastly, we present a numerical example to verify the main research results of this paper.

The co-occurrence of substance use disorders (SUDs) and psychiatric conditions, often referred to as comorbidity or concurrent disorders, presents intricate challenges in both diagnosis and treatment. This comprehensive narrative review aims to synthesize and critically evaluate the existing evi-dence surrounding the management of individuals with comorbid SUDs and psychiatric disorders. Comorbidity in these domains carries profound implications for clinical practice, research, and policymaking, emphasizing the need for a holistic understanding of the intricate dynamics that arise when these conditions coexist. This review explores recent research findings, evidence-based guidelines, and emerging trends within the field, offering valuable insights for clinicians, re-searchers, and policymakers seeking to navigate the complex terrain of comorbidity in substance use and psychiatric disorders.

FV (finger vein) identification is a biometric identification technology that extracts the features of FV images for identity authentication. To address the limitations of CNN-based FV identification, particularly the challenge of small receptive fields and difficulty in capturing long-range dependencies, an FV identification method Let-Net(Large kernel and attention mechanism Network) was introduced, which combines local and global information. Firstly, Let-Net employs large kernels to broaden the receptive field and incorporates depthwise convolution with residual connections to reduce parameter count. Secondly, Let-Net integrates an attention mechanism to enhance the information flows in channels and spaces for more comprehensive and distinctive FV feature extraction. The experimental results on nine public datasets show that Let-Net has excellent identification performance, and the EER and accuracy rate on the FV_USM dataset can reach 0.04% and 99.77%. The parameter number and FLOPs of Let-Net are only 0.89M and 0.25G, which means that the time cost of training and reasoning of the model is low, and it is easier to deploy and integrate into various applications.

Intrauterine adhesions (IUA) has become one of the main causes of female infertility, how to effectively prevent postoperative re-adhesion has been a clinical challenge. In this study, a mussel-inspired dual-network hydrogel was proposed for postoperative anti-adhesion of IUA. First, calcium alginate/polyacrylamide (CA-PAM) hydrogel was prepared by covalent and Ca2+ cross-linking. Benefiting from abundant phenolic hydroxyl groups, polydopamine (PDA) was introduced to further enhance the adhesion ability and biocompatibility. This CA-PAM hydrogel immersed in 10 mg/mL dopamine solution possessed remarkable mechanical strength (elastic modulus > 5 kPa) and super stretchability (with a breaking elongation of 720%). At the same time, it shown excellent adhesion more than 6 kPa. Surprisingly, the coagulation index of the hydrogel was 27.27 ± 4.91, demonstrating attractive coagulation performance in vitro and the potential for rapid hemostasis after surgery.

The utilization of dual-potential mode of integrated array (IDA) electrodes and other two-electrode systems has revolutionized electrochemical detection by enabling the simultaneous and independent detection of two species, accompanied by the exhibition of unique characteristics. In contrast to conventional dual-potential electrodes, the rotating ring disk electrodes (RRDE), IDA electrodes demonstrate analogous yet vastly improved performance metrics, characterized by remarkable collection efficiency and sensitivity. Notably, due to the distinctive microscale structure of IDA electrode, the special “feedback” effect makes IDA a unique signal amplifier. In recent decades, the research surrounding IDA electrodes has garnered escalating interest due to their attractive attributes. This review centers its focus on the fabrication and applications of IDA electrodes. In the realm of fabrication, two critical breakthroughs are poised for realization: the achievement of reduced dimensions and the diversification of materials. Established fabrication methods for IDA electrodes encompass photolithography, inkjet printing, and direct laser writing, each affording distinct advantages in terms of size and precision in IDA construction. Predominantly employed materials for IDA electrodes include gold, platinum, and carbon, with the selection of fabrication methods guided by considerations such as material properties, desired dimensions, cost-efficiency, and specific application requisites. Within the domain of applications, IDA electrodes, capitalizing on their distinctive attributes, have found utility in diverse fields. This review summarizes the applications of IDA electrodes based on their fundamental working principles, encompassing redox cycling, resistance modulation, capacitance variations, and more. The potential for further development of this specialized tool to exhibit enhanced properties holds substantial promise.

Stevia rebaudiana (Bert.) is a natural sweetener with diterpenic glycosides, offering 300 times more sweetness than sucrose, and boasting low-calorie content, along with medicinal and therapeutic properties. To address a limited genetic diversity, a germplasm bank comprising 115 segregated lines of stevia was established in Colombia. Notwithstanding, the fungus Athelia rolfsii adversely impacted key stevia lines, leading to wilting and plant mortality. For this reason our study aimed to explore the biocontrol potential of native strains of Trichoderma spp., isolated from productive lots in Colombia's Cordoba department, as a solution to manage A. rolfsii. Soil samples underwent serial dilution technique (103 conidia.mL-1) to obtain Trichoderma spp. isolates, which were thoroughly morphologically and molecularly characterized. A total five native strains were identified through sequencing the PCR products using universal ITS primers, and comparisons with the GENBANK database confirmed their identity (OK310695.1, ON237703.1, ON238106.1, ON237737.1, and ON237923.1). Their biocontrol efficacy against A. rolfsii was evaluated using the dual culture technique. Remarkably, all strains exhibited significant biocontrol capacity against the A. rolfsii isolate INVEPAR-05 (OK271308.1), except for Trichoderma viride INVEPAR-T10 (ON237923.1). These findings suggest that Trichoderma spp. could be a potential option to manage the fungus in stevia.

The minimum dominating tree (MDT) problem consists of finding a minimum weight sub-graph from an undirected graph, such that each vertex not in this sub-graph is adjacent to at least one of the vertices in it, and the sub-graph is connected without any ring structures. This paper presents a Dual Neighborhoods Search (DNS) algorithm for solving the MDT problem, which integrates several distinguishing features, such as two neighborhoods collaboratively working for optimizing the objective function, a fast neighborhood evaluation method to boost the searching effectiveness, and several diversification techniques to help the searching process jump out of the local optimum trap thus obtaining better solutions. DNS improves the previous best-known results for 4 public benchmark instances while providing competitive results for the remaining ones. Several ingredients of DNS are investigated to demonstrate the importance of the proposed ideas and techniques.

The present paper provides a new definition for dual spline curves in a geometric intuitive way based on adaptive curve refinement techniques. The dual spline is an implementation of the interpolatory subdivision scheme for curve modeling, which is comprised of polynomial segments of different degrees. Specially, the dual spline curves are mainly aims to solve the difficult geometry defeaturing problems in the existing computer-aided technology. Dual spline curves maintain various desirable properties of conventional curve modeling methods, such as local adaptive subdivision, high interpolation accuracy and convergence, continuous and discontinuous boundary approximation. By adding fictitious and intrinsic nodes inside or at the vertices of interpolation elements, the dual spline is flexible and convenient for approximating a set of ordered points or discrete segments. Combined with the Lagrange interpolation polynomial and meshless method, the proposed approach is capable of approximating the non-smooth boundary for geometry defeaturing. Experimental results are given to verify the validity, robustness, and accuracy of the proposed method.

Duchenne muscular dystrophy (DMD) is a yet incurable rare genetic disease that affects the skeletal and cardiac muscles, leading to progressive muscle wasting and premature death. DMD is caused by the lack of dystrophin, a muscle protein essential for the biochemical support and integrity of muscle fibers. Gene replacement strategies for Duchenne muscular dystrophy (DMD) employing the adeno-associated virus (AAV) face the challenge imposed by the limited packaging capacity of AAV, only allowing the accommodation of a short version of dystrophin (µDys) that is still far removed from correcting human disease. The need to develop strategies leading to the expression of a best performing dystrophin variant led to only few studies reporting on the use of dual vectors, but none reported on a method to assess in vivo transgene reconstitution efficiency, the degree of which directly affects the use of safe AAV dosing. We report here on the generation of a dual AAV vector approach for the expression of a larger dystrophin version (quasidystrophin) based on homologous recombination, and the development of a methodology employing a strategic droplet digital PCR design, to determine the recombination efficiency as well as the occurrence of unwanted concatemerization events or aberrant expression from the single vectors. We demonstrated that, upon systemic delivery in the dystrophic DBA2mdx mice, our dual AAV approach led to high transgene reconstitution efficiency and negligible ITR-dependent concatemerization, with consequent remarkable protein restoration in muscles and improvement of muscle pathology. This evidence supports the suitability of our system for gene therapy application and the potential of this methodology to assess and improve the feasibility for therapeutic translation of multiple vector approaches

The study presents the synthesis and characterization of dual-layer sulfonated polyphenylenesulfone (SPPSu) nanocomposite hollow fiber nanofiltration membranes incorporating titanium dioxide (TiO2) nanoparticles using the phase inversion technique. The newly developed membranes were systematically characterized using advanced tools and methods to evaluate their properties and performance. The study focused on investigating the effects of TiO2 addition in the SPPSu inner layer on pure water permeability, and salt rejection. The nanocomposite hollow fiber nanofiltration membranes exhibited a significant enhancement in pure water permeability, with a three-fold increase compared to the pristine membranes, achieving a flux of 5.4 L/m2h.bar. The addition of TiO2 also led to an improvement in the mechanical properties of the membranes, as evidenced by the increase in the expected tensile strength from 2.4 to 3.9 MPa. To evaluate the salt rejection performance, rejection tests were conducted using a laboratory-scale filtration setup in recycle mode. Aqueous solutions containing different divalent ions, specifically magnesium sulfate (Mg2SO4) and sodium sulfate (Na2SO4) at a concentration of 500 ppm, were used as the feed solution. The modified dual-layer hollow fiber nanocomposite membranes exhibited a maximal rejection of 95% for Mg2SO4, demonstrating their effective separation capabilities for divalent ions. The findings of this study highlight the successful synthesis and characterization of dual-layer SPPSu nanocomposite hollow fiber nanofiltration membranes incorporating TiO2 nanoparticles. The incorporation of TiO2 resulted in improved pure water flux, mechanical strength, and salt rejection performance. These enhanced properties make the developed nanocomposite membranes promising candidates for applications in nanofiltration processes, particularly for the selective separation of divalent ions from aqueous solutions.

Objective: To evaluate two different DECT postprocessing protocols for detection of MSU deposits in foot tendons of cadavers with verification by polarizing light microscopy as gold standard.Material and Methods: A total of 40 embalmed cadavers (15 male; 25 female; median age, 82 years; mean, 80 years; range, 52 - 99; SD ± 10.9) underwent DECT to assess MSU deposits in foot tendons.Two postprocessing DECT protocols with different Hounsfield unit (HU) thresholds 150/500 (=established) versus 120/500 (= modified) HU were applied to dual source acquisition with 80 kV for tube A and 140 kV for tube B.Six fresh cadavers (4 male; 2 female; median age, 78; mean, 78,5; range 61 - 95 ) were examined by DECT. Tendon dissection of 2/6 fresh cadavers with positive DECT 120 and negative DECT 150 studies were used to verify MSU deposits by polarizing light microscopy.Results: The tibialis anterior tendon was found positive in 57.5%/100% (DECT 150/120), peroneus tendon in 35%/100%, achilles tendon in 25%/90%, flexor halluces longus tendon in 10%/100%, and tibialis posterior tendon in 12.5%/97.5%. DECT 120 resulted in increased tendon MSU deposit detection, when DECT 150 was negative, with an overall agreement between DECT 150 and DECT 120 of 80 % (P = 0.013). Polarizing light microscope confirmed MSU deposits detected only by DECT 120 in tibialis anterior, achilles, flexor halluces longus and peroneal tendons.Conclusion: The DECT 120 protocol showed a higher sensitivity when compared to DECT 150.

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

A low-profile broadband dual-polarized antenna is investigated for base station applications. It consists of two orthogonal dipoles, fork-shaped feeding lines, an artificial magnetic conductor (AMC), and parasitic strips. By utilizing the dispersion Brillouin diagram, the AMC is designed as the antenna reflector. It has a wide in-phase reflection bandwidth of 54.7% (1.54-2.70 GHz) and a surface wave bound range of 0-2.65 GHz. This design effectively reduces the antenna profile by over 50% compared to traditional antennas without an AMC. For demonstration, a prototype is fabricated for 2G/3G/LTE base station applications. Good agreement between simulations and measurements is observed. The measured -10-dB impedance bandwidth of our antenna is 55.4% (1.58 –2.79 GHz), with a stable gain of 9.5 dBi and high isolation of more than 30 dB across the impedance passband. As a result, this antenna is an excellent candidate for miniaturized base station antenna applications.

Human induced pluripotent stem cells (hiPSCs) have two characteristic abilities 1) self-renewal and 2) differentiation into all cell types in the human body. It is this ability of iPSCs to differentiate into any desired cell type that makes them amenable to disease modeling. iPSCs can further be engineered to carry a disease-specific mutation or be derived from patients to phenocopy the disease. To model neurodegenerative/neurodevelopmental disorders iPSCs are differentiated into neurons. This chapter describes protocols for two different approaches to generate neurons from iPSCs, first using dual SMAD inhibition to generate neural progenitor cells which are then differentiated into neurons, and second using single transcription factor (NGN2) over-expression to drive differentiation of iPSCs directly into neurons.

To promote low-carbon and green travel, this study proposes a tripartite evolutionary game model among new energy vehicle manufacturers, consumers, and government agencies. The game strategy combinations of each party and the stability conditions of the equilibrium point in the evolutionary game system are analyzed, and the validity of the conclusions is verified through simulation results. The study shows a strong correlation between the three parties in the evolutionary game system. From the perspective of car manufacturers, the probability of producing new energy vehicles is positively proportional to the subsidy received from new energy policy, the additional revenue gained from the management of the carbon trading scheme, and the fine received for producing conventional fuel vehicles. However, from the consumer perspective, the likelihood that consumers purchase new energy vehicles is positively related to the utility value to consumers and the coverage of public charging points in the city, and inversely related to the sales price of new energy vehicles. From the government perspective, a combination of direct subsidy policies and indirect support strategies should be considered to stimulate the rapid development of the new energy vehicle industry.

Nowadays, many Muslim-majority countries have implemented a dual banking system, namely the sharia and conventional systems. The development of Islamic banks is to fulfill the Muslims' need for the existence of halal transactions in financial institutions. However, in some countries, it turns out that conventional banks still dominate the country's economy. Because of that, it is necessary to see whether there are differences in financial risk and Earnings management between Islamic and conventional banks. The samples are conventional and Islamic banks in Southeast Asia, analyzed by the purposive sampling method from 2010-2019. The analytical tool used is the statistical difference test and economometrics analysis using generalized least square (GLS) regression with panel data (time series and cross-sectional data). These models are intended to forecasting the macroeconomics effects in applying dual banking system in one country or region. The results using non parametrics means difference test showed that the first hypothesis is accepted It means that Earnings management in conventional banks is greater than in Islamic banks. The Random Model Effect (REM) for second and third hypotheses testing on Conventional banks shows the Bankruptcy Risk and NPL do not affect the dependent variable Earnings Management (LLP). While fixed effect model testing on Islamic banks, the second and third hypothesis testing is rejected. Therefor Islamic Banks the value of Bankruptcy Risk (z-score) and the value of Non-Performing Loans (NPL) do not affect Earnings management. It also means that hypothesis 2 and 3 are rejected both in conventional as well as Islamic Banking. Sensitivity analysis for conventional as well as Islamic banking altogether using fixed effect model shows that the second and third hypotheses show that the independent variables (Bankruptcy Risk and NPL) do not affect the dependent variable Earnings Management (LLP). These results can be concluded that Islamic bank are enganged in less earnings management. Therefor in the the long run there are still more research that should conduct in comparing dual banking system in one region.

Introduction: A dual malignancy with both Ewing Sarcoma and Prostate Adenocarcinoma has not been reported in the English literature. We report a case of simultaneous diagnosis of Ewing sarcoma and prostate adenocarcinoma with profound clinical manifestation. Case presentation: A 53-year-old male with advanced metastatic prostate cancer (Gleason-9) admitted with classical presentation of cauda equina syndrome including incontinence, back pain, and paresis following bilateral nephrostomy insertion for the treatment of bilateral renal hy-dronephrosis. The patient was diagnosed with an epidural abscess at the level of L5-S1 and an emergency surgical spine decompression was performed. No abscess was found, and pathology results showed a concomitant primary Ewing sarcoma in the spine. Conclusions: Very rare occurrences of a dual primary malignancy, in this case, Ewing sarcoma and prostate adenocarcinoma, should be kept in mind in patients suffering from complex clinical course of malignancies.

Aims: In late December 2019, early reports predicted the onset of a potential Coronavirus outbreak in china, given the estimate of a reproduction number for the 2019 Novel Coronavirus (COVID-19). Because of high ability of transmission and widespread prevalence, the mortality of COVID-19 infection is growing fast worldwide. Absent of an anti-COVID-19 has put scientists on the urge to repurpose already approved therapeutics or to find new active compounds against coronavirus. Here in this study, a set of computational approaches were performed in order to repurpose antivirals for dual inhibition of the frontier proteases involved in virus replication, papain-like protease (PLpro; corresponding to nsp3) and a main protease (Mpro), 3C‑like protease (3CLpro; corresponding to nsp5). Materials and Methods: In this regard, a rational virtual screening procedure including exhaustive docking techniques was performed for a database of 160 antiviral agents over 3CLpro and PLpro active sites of SARS-CoV-2. The compounds binding energies and interaction modes over 3CLpro and PLpro active sites were analyzed and ranked with the aid of free Gibbs binding energy. The most potent compounds, based on our filtering process, are then proposed as dual inhibitors of SARSC-CoV-2 proteases. Key findings: Accordingly, seven antiviral agents including two FDA approved (Nelfinavir, Valaganciclovir) and five investigational compounds (Merimepodib, Inarigivir, Remdesivir, Taribavirine and TAS106-106) are proposed as potential dual inhibitors of the enzymes necessary for RNA replication in which Remdesivir as well as Inagrivir have the highest binding affinity for both of the active sites. Significance: The mentioned drug proposed to inhibit both PLpro and 3CLpro enzymes with the aim of finding dual inhibitors of SARSC-CoV-2 proteases.

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new dynamic programming for seamlessly stitching UAV images using optical flow. Our solution consists of two steps: Firstly, an image-matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is develop based on the concept of a stereo dual-channel energy accumulation using optical flow. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for adjacent image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching. Beyond that, our solution is also direction-independent, which has more adaptability and robustness for UAV images.

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.

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

This paper is a detailed study on radio frequency identification (RFID) technology focused on its application for warehouse traceability in the company FRUMECAR. It highlights the importance of controlling the traceability of items in warehouses or logistics companies, highlighting the need for reliable, real-time information to effectively manage inventory and resolve incidents quickly. The paper discusses in depth what RFID is, its types, main components such as tags, readers, and antennas, as well as discussing how it works, advantages, disadvantages, and specific applications. It also examines factors such as return on investment, cost feasibility, and environmental factors that influence the implementation of RFID systems. The paper presents a practical approach, proposing RFID-based solutions to improve traceability in FRUMECAR, analyzing the current state of the company and its warehouses, with the aim of implementing an efficient system that allows real-time tracking of products.

Water networks are critical infrastructure components, ensuring the continuous supply of high-quality drinking water to consumers. To secure such water supply, regular maintenance, including the replacement of deteriorating pipelines, is essential. In this study, a methodology has been developed for determining optimal pipeline replacement solutions in water supply systems at water utilities with limited data availability. Hydraulic analysis has been conducted on the segment of 25 km of the water supply network using the free software EPANET. Applying water network optimization, eight pipeline replacement projects according to 13 pre-defined criteria have been identified and evaluated. The paper outlines the methods for evaluating the criteria, including defining specific quantitative limits. The Analytical Hierarchical Process (AHP) method was used in the paper to determine the weights of the criteria. The reason for applying this method refers to problems that involve a set of criteria with a mixed structure, including both quantitative and qualitative aspects. Also, the paper describes the steps of the multi-criteria optimization method VIKOR, used to select the optimal project. This paper, considered as case studie, describes a method, i.e. application of a new principles and an innovative way to solve a problem for developing countries.

The present distribution examines the effects of nozzle diameter, inlet mass rate, and channel geometry on the fuel distribution in annular combustion chambers of micro gas turbines, taking into account the importance of more uniform fuel distribution in the nozzles connected to the fuel supply channels. A comparison has been made between the numerically calculated pressure drop between the inlet and outlet of the fuel supply nozzle and the experimental value obtained. All fuel supply nozzles with a diameter of 500 micrometers are considered for the micro gas turbine. A more uniform distribution results in better combustion and higher efficiency. A geometrical change in the design of the fuel supply nozzle improved the uniformity of the flow distribution without increasing the pressure drop.

Plasma generation by means of electrical discharge requires specialized power supply systems. The applicability of plasma for various plasma processes depends on its parameters, and these in turn depend on the parameters of the power supply systems. Arc plasma can be unstable, generating a lot of electromagnetic interference and overvoltage and overcurrent. The power system of a plasma reactor must guarantee good plasma control characteristics, be immune to disturbances and ensure good cooperation with the power grid. The article analyzes the cooperation of a three-phase plasma reactor, with gliding arc discharge, with a power supply system of a new type. This system integrates an AC/DC/AC converter with a five-column transformer of special design in a single device. Using the properties of magnetic circuits, it was possible to integrate the functions of ignition and sustaining the burning of the discharge in the reactor in a single transformer. Proper design of the transformer is crucial to achieve good cooperation of the AC/DC/AC converter with both the plasma reactor and the power supply network. The presented power supply design shows a number of positive features predisposing it to powering arc plasma reactors.

The solar cell industry is a part of the green energy sector, and effectively combining the patents of various manufacturers within the supply chain to collectively create sustainable patent market value is of paramount importance. This study aimed to establish a business strategy framework for Project-based licensing through the analysis of solar cell patents and the integration of supply chain manufacturers' patents, with the goal of collectively creating market value for patents sustainably. The research methodology included literature analysis and focus group discussions. Initially, the study analyzed solar cell industry patents from the past decade using the WIPS Global Patent database to identify projects with the highest patent count. Subsequently, through the use of focus group discussions, the feasibility of a patent pool strategy within the supply chain was explored. Finally, a strategy framework was proposed for Project-based patent pool licensing, focusing on the top 15 projects with the highest count of 5,579 patents. The results indicated that adopting this strategy framework for supply chain manufacturer patents can result in higher commercial patent value.

The problem of blood delivery has been a critical concern in past decades. However, the unsteady behavior of blood donors, along with the uncertainties associated with demands in a crisis imposes several challenges for resource management. In this research work, we analyze the blood delivery behavior in a crisis modeled by coupled queues of patients and blood sources. Using Markovian modeling and results associated with G-network, we derive two critical probabilities, namely lack of unit of blood (unit of donations) or not having any storage capacity left to accept new donors' blood. We propose a closed-form solution to calculate the optimal blood storage size, and also we suggest sufficient conditions that guarantee the feasibility of the model. Finally, we conduct a sensitivity analysis to investigate the impact of model parameters on storage size and the proportion of time that storage is full.

Most of the literature on the optimization problem of transportation in supply chain networks (SCN) considered fixed costs (FC). However, in the practical applications of this problem it is important to study the effect of FC. This paper examines the impact of fixed cost increase as well as the variable cost on the optimization of a Two-Stage SCN. To do so, two mathematical models for mixed-integer nonlinear programming are developed. The first model optimizes fixed and variable costs in addition to the opening cost, whereas the second model only optimizes variable and opening costs. To evaluate the effect of considering FC on the optimization supply chain problem, four groups of instances are randomly generated, and solved using Lingo. The results of the two models are compared utilizing the average percentage deviation. In addition, sensitivity analysis is performed to determine the impact of changes in opening and variable costs on the considered optimization problem. The computational results and the sensitivity analysis show that the first model with minimized FC outperforms the second model, which does not consider the FC in minimization and FC affect the optimization.

Nowadays, with the development of laser weapons, the primary power supply of laser weapons puts forward more and more high demand for its performance. The pulsed power supply based on conventional homopolar inductor alternator (HIA) cannot meet the requirements any more. In order to improve the power density and efficiency, this paper proposes applying the high-temperature superconducting (HTS) HIA with slotless stator core to this power supply. In this paper, the design considerations of it are presented, and the comparisons between the two power supplies are discussed. The calculation results show that the power supply based on HTS machine has much larger power density than the conventional HIA, and the efficiency is also larger than the conventional HIA. This can improve the performance of laser weapons dramatically.

Distributed Manufacturing (DM) is becoming increasingly important in operations management due to its potential to support sustainability goals, reduce risks in global supply chains, and boost local economies. However, previous analyses of the advantages and disadvantages of DM have mainly focused on operations, overlooking additional benefits across the supply chain. For example, DM can enable local sourcing, better serve end-users, and tackle reverse supply chain challenges. While economies of scale are essential for reducing costs and improving productivity, highly centralised manufacturing can increase transportation costs, vulnerability, and supply chain disruptions, particularly during pandemics or other times of restricted transportation. To address these challenges, this study introduces a Multi-attribute Decision Support System (MADSS) and assessment process that considers impacts across the supply chain and guides stakeholders, academics, and decision-makers. The MADSS handles quantitative and qualitative information, missing data, and uncertainty, and a team of experts from academia and industry in New Zealand has developed the evaluation. The MADSS was used to analyse DM and traditional construction alternatives from economic, social, environmental, and resilience perspectives in New Zealand. The research contributes to a better understanding of the impacts of DM across the entire supply chain. Also, it proposes a flexible decision-making framework to engage with stakeholders and support decision-making in other industries and regions.

As traditional supply chains face increasingly severe environmental issues and countries promote green development and sustainable development policy concepts, cultivating green supply chain operation models is gradually being highly valued by current governments and enterprises. Generally speaking, the production of green products incurs higher additional costs and thus their total production costs also increase. In this work, the product green level is related to the random demand. Under the green supply chain buy-back contract with the green product R&amp;D cost sharing between the manufacturer and the retailer, both the product green level and the order quantity need to be decided to maximize the channel profit. In order to coordinate the green supply chain, the manufacturer needs to share both the risk of good salvage and the green product R&amp;D cost with the retailer. We find that both the wholesale price and buy-back price increase in the manufacturer’s proposition of the green product R&amp;D cost, but decrease in emission reduction efficiency coefficient or carbon trading price. In addition, the product green level, the optimal order quantity and the channel profit increase in emission reduction efficiency coefficient, but decrease in the R&amp;D cost coefficient of the product green level. Interestingly, we find that if the carbon trading price is low, the manufacturer will set a low product green level and the product carbon emission trading is a cost for the supply chain. The increment of the carbon trading price leads to a higher cost such that the channel profit is decreased. However, if the carbon trading price is high, the manufacturer will set a high product green level and the product carbon emission trading is a revenue for the supply chain. The increment of the carbon trading price leads to a higher revenue such that the channel profit is increased.

In recent years supply chains have evolved into huge ecosystems, demanding trust, provenance, and data privacy. Since blockchain technology (BCT) allows for the development of a distributed environment, it is ideal for supply chain management (SCM) applications. However, concerns regarding data privacy have impeded the development of blockchains. Despite the fact that some blockchains can restrict participants to read and write data, the blockchain’s transparency makes protecting sensitive data challenging. To solve the data privacy challenge, this paper proposes a framework, AccessChain, that is an SCM access control framework based on an attribute-based access control (ABAC) model that restricts access to competing parties while allowing for network scalability. This proposed AccessChain model has two types of ledgers in the system: local and global. Local ledgers are used to store business contracts between stakeholders and the ABAC model management, whereas the global ledger is used to record transaction data. AccessChain can enable decentralized, fine-grained and dynamic access control management in SCM when combined with the ABAC model and BCT. This paper’s experimental results illustrate that high throughput can be achieved in a large-scale request environment while maintaining data privacy and sustaining a scalable network.

This paper explores the coordination of the agricultural cooperative to supermarket or E-commerce sup-ply chain, under the condition of quantity loss with a mixed decay function of exponential and logistical distribution. The nature of this process is analyzed, and the corresponding demand and supply functions with single- and multi-stage discount strategies are constructed respectively to create a working model. The optimal discount ratios for supermarkets and agricultural cooperatives in decentralized and central-ized decision-making modes coupled with single- and multi-stage discounts are calculated respectively. Finally, a universal optimal strategy is designed, which can be applied to various quantity decay scenarios and makes the discount strategy more generalized. The results show that discounts can coordinate supply chains more effectively; not only is fresh agricultural produce sold before it starts to rot, but the benefit conflicts arising from both supermarkets vs. cooperatives and traditional vs. E-commerce channels are equilibrated. Further, multi-stage discounts are more effective than single-stage ones, but optimal discount ratios rely on the initial quantity of fresh agricultural produce in the supply chain; its market share in the traditional distribution channel; the potential market size; retail price; the price sensitivity coefficient of the channel; the cross-elasticity coefficient of prices between different channels; and the properties of the quantity loss.

The purposes of this study are to introduce the concept of Service Quality (SQ) in E-Supply Chain Management (E-SCM) and its impact on increasing Customer Satisfaction (CS) and provide insightful enhancements to the literature. In addition, the paper also examines the influence of SQ of E-SCM on CS in online shopping. After a comprehensive literature review, four key factors for measuring the E-Supply Chain (Process Control, Interaction with Supplier, Management Support, and Focus on Customers), four key factors for measuring CS (Informing Customers, Attention to Customers’ Needs, Staff Performance Accuracy, and Easy Access to Services), and four factors for measuring the quality of identification services (Assurance, Accountability, Tangibility and Reliability) were selected. The proposed conceptual model was then presented. This model was validated by data collected through a survey of 150 respondents in order to identify customer satisfaction, including that of customers of online websites in Iran. The sample data was analyzed using SPSS21, after which the interrelationships between the model and factors were examined based on the Partial Least Square-Structural (PLS). Model fit indices were then calculated for the dataset. The proposed model was validated using factor analysis and structural equation modeling techniques. The results indicated that E-SCM has a direct impact on CS. The effect of SQ was also confirmed. A positive and significant relationship was identified between E-SCM and CS, E-SCM and SQ, as well as SQ and CS (P> 0.05). The first limitation was to convince respondents to cooperate with the researchers. The second one was the lack of research-related background due to the subject being relatively new. This study, to the best of the authors’ knowledge, is the first empirical analysis on the CS assessment of SQ of E-Supply Chain in online shopping. This important link to online shopping has rarely been explored. It is expected that by filling this gap, this study will help in strengthening online shopping, which needs a change in the marketing area.

As fossil-fueled heating in the building sector is responsible for 16 % of Germanys total CO2 emissions, it is of great importance to use climate-neutral alternatives for the decarbonization of this sector. Options for the climate-neutral heating of buildings include electricity or hydrogen as energy carriers, both explicitly considered by German policy. In this paper, bottom-up studies are conducted to investigate the role of hydrogen for the climate-neutral energy supply of ten selected residential buildings in comparison to electricity-based systems. Based on a selection of as different typical buildings as possible for single- (SFH) and multi-family houses (MFH) of different construction years, demand profiles are simulated for each building and the respective cost-optimal supply system is determined. For the construction of this system, the electricity-based technologies available are electric heater and heat pump as well as the hydrogen-based technologies hydrogen boiler and fuel cell combined heat and power (CHP) system. Based on the results of the optimization, sensitivity analyses are performed. These analyses aim to identify threshold values of the hydrogen price for the use of hydrogen in building energy systems as well as to make the quantities of hydrogen consumed visible.The identified threshold values show the significant role of hydrogen-operated CHP in MFH if the hydrogen price reaches 0.17 €/kWh_H2 in 2050 at an electricity price of 0.31 €/kWh_el. So, hydrogen-based energy systems represent an economically viable alternative to electricity-based systems with heat pumps. We identify electricity to hydrogen price ratios for the economically viable use of hydrogen in the examined buildings that range from 1.67 to 2.82. According to these ratios, the economically reasonable use of hydrogen in buildings can be derived. For the individual building groups for the year 2050, a ratio of 2.5 can be determined for SFH and 1.8 for MFH, that is favored by the use of CHP which also supplies electricity to the buildings. However, the role hydrogen will finally play in German residential buildings in the future depends to a large extent on political decisions on distribution issues and price signals.

This study investigates optimal decisions in a green supply chain consisting of a manufacturer and a leading retailer considering the green marketing and fairness preferences of member firms. Four Stackelberg game decision models are constructed in which the manufacturer and the re-tailer engage in green marketing separately when the manufacturer has no and has fairness preferences. The impacts of fairness preferences and green marketing on the optimal decision in the green supply chain are comparatively analyzed. The study finds that member firms perform green marketing regardless of the presence or absence of fairness preferences and that such be-havior increases the wholesale price, retail price, and market demand of low-carbon products as well as the profits of member firms and the supply chain. A more interesting finding is that the profit growth of member firms and the supply chain due to the manufacturer’s green marketing is more pronounced than that due to the retailer’s green marketing. When the retailer and the manufacturer engage in conduct green marketing, the manufacturer's fairness preferences have different effects on the wholesale price, retail price, market demand, level of green marketing efforts, member enterprises and profits of supply chain. Therefore, firms should consider the impact of green marketing and fairness preferences to make pricing and performance decisions, so as to achieve efficient operation of the whole supply chain and avoid double marginal effects. Finally, the above conclusions are verified through numerical simulation, providing a reference for the decision-making of member firms in the green supply chain.

The specific demands inherent to supply chains built upon large IoT systems, make a must the design of a coordinated framework for cyber resilience provisioning intended to guaranteeing trusted supply chains of ICT systems, built upon distributed, dynamic, potentially insecure and heterogeneous ICT infrastructures. As such, the proposed solution is envisioned to deal with the whole supply chain system components, from the IoT ecosystem to the infrastructure connecting them, addressing security and privacy functionalities related to risks and vulnerabilities management, accountability and mitigation strategies as well as security metrics and evidence-based security assurance. In this paper we present FISHY, as a preliminary designed architecture, designed to orchestrate both existing and beyond state-of-the-art security appliances in composed ICT scenarios and also leveraging capabilities of programmable network and IT infrastructure through seamless orchestration and instantiation of novel security services, both in real-time and proactively. The paper also includes a thorough business analysis to go far beyond the technical benefits of a potential FISHY adoption as well as three real-world use cases where to strongly support the envisioned benefits of a FISHY adoption.

The threats of climate change and the sustainable supply of clean energy are global challenges that require an international approach to the energy supply. Utilizing the wind and solar energy potential of regions where these renewable sources are especially viable to produce hydrogen by means of water electrolysis represents an attractive option to counter the above-mentioned challenges. Within the scope of this techno economic analysis of a worldwide hydrogen supply infrastructure based on renewable energy, selected regions are assessed on the basis of their wind or solar energy potential. In contrast to established analyses of hydrogen infrastructures, this paper introduces a worldwide allocation approach to the supply hydrogen from strong wind and solar regions to different demand regions on the premise of a global supply cost minimum. The allocation results show a significant dependence of hydrogen export volumes and the oversea transport distances of potential trading partners. Hence, the transnational trading flows of hydrogen derived from wind and solar energy are concentrated in continental regions.

The future of the Colorado River water supply (WS) affects millions of people and the U.S. economy. A recent study suggested a cross-basin correlation between the Colorado River and its neighboring Great Salt Lake (GSL). Following that study, the feasibility of using the previously developed multi-year prediction of the GSL water level to forecast the Colorado River WS was tested. Time-series models were developed to predict the changes in WS out to 10 years. Regressive methods and the GSL water level data were used for the depiction of decadal variability of the Colorado River WS. Various time-series models suggest a decline in the 10-year-averaged WS since 2013 before starting to increase around 2020. Comparison between this WS prediction and the WS projection published in a 2012 government report (derived from climate models) reveals a widened imbalance between supply and demand by 2020. Further research to update similar multi-year prediction of the Colorado River WS is needed. Such information could aid in management decision making in the face of future water shortages.

This paper outlines a new methodology for developing strategy for supply chain integration of Autonomous Electrical Vehicles (AEV) to the Internet of Things (IoT). The methodology consists of external architecture and internal design that anticipates the business strategy in the development process. The methodology is designed to anticipate the impact of developments in new road transport technologies, such as Tesla Truck or Tesla Pickup. Since the methodology is designed to anticipate the impact of non-existing technologies, it represents green-field analysis. Green-field is defined as a new and non-existent operation. Green-field strategy architecture in this paper is presented as a process of accepting the world and acting upon that version of the world. The results of the analysis are presented as pathways and outcomes, emerging from the interrelated relationship between AEV and IoT. The emerging methodology is applied through two case studies to evaluate the impact to environment, performance and operationalisation. The methodology proposes architecture and design for integrating AEV and IoT in the supply chain strategy, and a set of new evaluation criteria that promote acceptance of Artificial Intelligence (AI) in the design process. The main contribution to knowledge is a new methodology for integrating AEV and the IoT to the supply chains. The paper applies interplay between inductive and deductive case study and grounded theory approach to build upon the concept of supply chain architecture and contribute to knowledge to the topic of formulating green-field integrated AEV- IoT supply chain strategy.

Logistics Engineering has transcended over the decades into an approach for competitive benefits in organisational performance and logistics efficiency. Most industries are recognising that significant savings are available to companies that are able to ordinate and improve within their logistics operations. Companies today face great challenges because the successful supply of many products and services needs to the effective integration of logistics activities across a prolongation supply chain and an increasing geographical separation. Moreover, logistics integration approach involves both internal integration for an ordinated, unified process as well as relationships to react flexibly, changeability, and responsibility to customer's demands. In this study, by using of Fuzzy Vikor (F-Vikor), the best combination of RIR was selected and RIR Locating was done. The main aim of this paper is survey and design of the integrated operational logistics network (IOLN) and also, a proposed IOLN to integration of the Iran Khodro Co Supply Network.

We study a two-echelon supply chain made up of a supplier and a manufacturer, both of which can reduce their component/product carbon emissions. With the vertical technology spillovers, we explore the optimal decisions of centralized and decentralized supply chains with price dependent demand and propose coordination strategy for the decentralized supply chain. Considering the cost contraction effectiveness of the technology spillovers, the centralized and decentralized game theoretic models of a two-echelon supply chain are developed to investigate optimal decisions of pricing and carbon emissions reduction. Through a systematic comparison and numerical analysis, we show that the profits of both players and the entire supply chain improve with the effect of technology spillovers increasing. Carbon emissions reduction will be taken by various protective measures so that the supplier and the manufacturer who do not innovate can hardly share the results of innovating via the “free-riding” methods when the technology spillover is relatively small. We also propose a revenue-cost sharing contract through bargaining to enhance the performance of the decentralized supply chain.

Durability monitoring of insecticide-treated nets (ITNs) containing a pyrethroid in combination with a second active ingredient (AI) must be adapted so that the insecticidal bioefficacy of each AI can be monitored independently. An effective way to do this is to measure rapid knock down of a pyrethroid-susceptible strain of mosquitoes to assess the bioefficacy of the pyrethroid component and to use a pyrethroid-resistant strain to measure the bioefficacy of the second ingredient. To allow robust comparison of results across tests within and between test facilities, and over time, protocols for bioefficacy testing must include either characterisation of the resistant strain, standardisation of the mosquitoes used for bioassays, or a combination of the two. Through a series of virtual meetings, key stakeholders and practitioners explored different approaches to achieving these goals. Via an iterative process we decided on the preferred approach and produced a protocol consisting of characterising mosquitoes used for bioefficacy testing before and after a round of bioassays, for example at each time point in a durability monitoring study. We present the final protocol and justify our approach to establishing a standard methodology for durability monitoring of ITNs containing pyrethroid and a second AI.

Sleep quality is known to affect automatic and executive brain functions such as gait control and cognitive processing. This study aimed to assess the effect of dual tasks on gait spatiotemporal parameters among young adults with good and poor sleep quality in the United Arab Emirates. In total, 65 young adults with a mean age of 21.1±2.5 were assessed for gait analysis during single-task and dual-task conditions. The participants’ sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and gait was assessed using the BTS Gaitlab System. The participants were asked to walk at natural speed as a single-task condition, followed by walking while performing a cognitive task as a dual-task condition. The parameters assessed included the gait velocity (m/s), cadence (steps/min), step width (m), and stride length (m). The DTC on each gait parameter was calculated. The Mann–Whitney U test was used to compare the differences in the DTC on gait variables between the good and poor sleep quality groups, and the Spearman correlation test was used to assess the correlation between total PSQI scores and the DTC. At a significance level of p&lt;0.05, a significant difference in cadence between the two sleep quality groups was observed, in addition to a positive correlation between sleep quality and the DTC effect on gait mean velocity, cadence, and stride length. Our findings also revealed a greater DTC on participants with poorer sleep quality. These findings contribute to our understanding of the significance of sleep quality in gait performance while multitasking in younger populations.

Computational simulations of three-dimensional flow around a NACA 0018 wing with an aspect ratio of AR=5 are carried out using the Unsteady Reynolds-Averaged Navier-Stokes (URANS) equations with the Shear-Stress Transport turbulence model closure. Simulations were performed to capture the aerodynamic stall hysteresis using a developed Pseudo-Transient Continuation (PTC) method based on a dual time step approach in the CFD code OpenFOAM. The flow was characterized by an incompressible Mach number of M=0.12 and a moderate Reynolds number Re=0.67×10^6. The results obtained indicate the presence of a noticeable aerodynamic hysteresis in the static dependencies of the force and moment coefficients, as well as the manifestation of bi-stable flow separation patterns, accompanied by the development of asymmetry in the stall zone. The URANS simulation results are in good agreement with the experimental data obtained for the NACA 0018 finite aspect ratio wing from the low-speed wind tunnel under the same test conditions. A new phenomenological bifurcation model of aerodynamic stall hysteresis under static and dynamic conditions is formulated, which is proven to be able to closely match the experimental data.

The dual-station Interferometric Synthetic Aperture Radar (InSAR) system can overcome the physical limitations imposed by the baseline of single-station dual-antenna InSAR. It provides greater flexibility and can enhance elevation measurement accuracy through a well-designed baseline configuration.Unmanned aerial vehicles (UAV) equipped with dual-station InSAR, with relatively low cost and high flexibility, are useful for mapping and land resource exploration. However, due to challenges including spatiotemporal synchronization and motion errors, there are limited reports on UAV-borne dual-station InSAR. This paper proposes a comprehensive method for processing data from small UAV-borne dual-station InSAR by integrating two-way synchronization chain signals. The proposed method includes compensation for time and phase synchronization errors, trajectory refinement with synchronized chain and Position and Orientation System (POS) data, high-precision dual-station InSAR imaging and interferometric processing. Height inversion results based on the proposed method is also provided, demonstrating the effectiveness of the proposed method and improving interferometric accuracy at calibration points from 0.66 meters to 0.42 meters.

The dual leucine zipper kinase (DLK) alias mitogen-activated protein 3 kinase 12 (MAP3K12) has gained much attention in recent years. DLK belongs to the mixed lineage kinases, characterized by homology to serine/threonine and tyrosine kinase but exerts serine/threonine kinase activity. DLK has been implicated in many diseases including several neurodegenerative diseases, glaucoma, and diabetes mellitus. As a MAP3K, it is generally assumed that DLK becomes phosphorylated and activated by upstream signals and phosphorylates and activates itself, the downstream serine/threonine MAP2K, and ultimately MAPK. In addition, other mechanisms such as protein-protein interactions, proteasomal degradation, dephosphorylation by various phosphatases, palmitoylation, and subcellular localization have been shown to be involved in the regulation of DLK activity or its fine-tuning. In the present review, the diverse mechanisms regulating DLK activity will be summarized to provide a better insight into DLK action and possibly new targets to modulate DLK function.

Pesticides are chemical products are used to protect crops to prevent or eliminate undesirable organisms. Pesticides can contaminate continental waters, air, soil and food products. The presence of pesticide residues must therefore be monitored in water and food using sensitive, reliable and broad-spectrum analytical methods, as there is a huge variety of pesticides. Biosensors are one of the screening methods with great potential for detecting residues below the maximum residue limits. The different sensing principles of enzymatic biosensors for pesticide analysis will be described. This review highlights the great potential of colorimetric, enzymatic biosensors for detecting pesticide residues in water and food. Moreover the development of dual colorimetric and fluorimetric sensors during the past years is presented. These methods are most often based on the enzyme acetylcholinesterase, whose activity is inhibited by pesticides. The different approaches used in the development of these biosensors will be detailed, based on different chemical substrates, fluorophores and nanomaterials. The advantages and disadvantages of each approach will be discussed. Finally, the development prospects for improving these biosensors will be presented.

Measuring pulmonary nodules accurately can help with early diagnosis of lung cancer, which can improve a patient’s chances of survival. Many methods for segmenting nodules have been developed, but they all rely on input from radiologists in the form of a 3D volume of interest (VOI) or use a constant region of interest (ROI) and only consider the presence of nodule within the given VOI. These approaches limit the networks’ ability to detect nodules outside the given VOI and can also include unnecessary structures in the VOI, leading to potentially inaccurate segmentation. In this work, we propose a novel approach for 3D lung nodule segmentation by using 2D region of interest (ROI) inputted from radiologist or computer-aided detection (CADe) system. Particularly, we design a dual-encoder-based hard attention network (DEHA-Net) which incorporates the full slice of thoracic computed tomography scan along with the ROI mask to produce an accurate segmentation mask of lung nodule in the given slice. The proposed architecture exploits the adaptive region of interest (A-ROI) algorithm to automatically investigates the penetration of lung nodule into surrounding slices while eliminating the need to drawing separate ROIs in each slice. Further, the framework performs the multi-view analysis, i.e., in sagittal and coronal views, to improve the segmentation performance. The proposed scheme has been rigorously evaluated on the lung image database consortium and image database resource initiative (LIDC/IDRI) dataset and an extensive analysis of results have been performed. The quantitative analysis shows that the proposed method not only improves the existing state-of-the-art in term of dice score but also, significantly robust against the different types, shape and dimensions of lung nodules.

In this paper a microstrip Wilkinson power divider with a 90^° phase delay at one output port is proposed to obtain circular polarization to feed a dual port RFID antenna. The 90^° phase delay was obtained by embedding an extra quarter wavelength at one port of the Wilkinson power divider. The feeding circuit is then mounted on the ground plane of the microstrip antenna feeding the radiating patch directly through the ground plane and dielectric layer thus reducing any fringing effect and resulting a mechanically compact unit. The proposed feeding method offers better expectation of antenna performance with minimal attenuation and coupling losses. The design process generalizes geometric pa- rameters of the Wilkinson power divider for variable port distances. The paper considers both UK and US RFID center frequencies, 870 MHz and 915 MHz respectively. Numeri- cally computed values for geometric design parameters for both frequencies are tabled as future design tools for port distances varying from 18 mm up to 34 mm at 870 MHz and 17 mm up to 32 mm at 915 MHz. Simulation results indicate a return loss (S11) of -20 dB and -26 dB at 870 MHz and 915 MHz operational frequencies respectively at 270^° angled quarter wavelength.

The kinetics and modeling of dual-wavelength controlled photopolymerization confinement (PC) are presented and measured data are analyzed by analytic formulas and numerical data. The UV-light initiated inhibition effect is strongly monomer-dependent and different monomers have different C=C bond rate constants and conversion efficacy. Without the UV-light, for a given blue-light intensity, higher initiator concentration (C₁₀) and rate constant (k’) lead to higher conversion, as also predicted by analytic formulas, in which the total conversion rate (R_T) is an increasing function of k’R, which is proportional to k[gB₁C₁]^0.5. However, the coupling factor b₁ plays a different role that higher b₁ leads to higher conversion only in the transient regime; whereas higher b₁ leads lower steady-state conversion. For a fixed initiator concentration C₁₀, higher inhibitor concentration (C₂₀) leads to lower conversion due to stronger inhibition effect. However, same conversion reduction was found for the same H-factor of H₀ = [b₁C₁₀ - b₂C₂₀]. Conversion of blue-only are much higher than that of UV-only and UV-blue combined, in which high C₂₀ results a strong reduction of blue-only-conversion, such that the UV-light serves as the turn-off (trigger) mechanism for the purpose of spatial confirmation within the overlap area of UV and blue light. For example, UV-light controlled methacrylate conversion of a glycidyl dimethacrylate resin formulated with a tertiary amine co-initiator, and butyl nitrite, subject to a continuous exposure of a blue light, but an on-off exposure of a UV-light. Finally, we developed a theoretical new finding for the criterion of a good material/candidate governed by a double ratio of light-intensity and concentration, [I₂₀C₂₀.]/[I₁₀C₁₀].

Lung cancer remains the leading cancer killer worldwide. Early diagnosis can effectively increase the patient cure rate but existing diagnostic methods limit early lung cancer diagnosis. Therefore, development of a simple but efficient lung cancer screening method is important to improvement of both the diagnosis rate and the survival rate of lung cancer patients. In this study, ten photosensitive materials with high sensitivity and high specificity were screened accurately to construct a microarray sensor that can rapidly identify six types of lung cancer biomarkers in exhaled breath. Results from hierarchical cluster analysis (HCA), principal component analysis (PCA) and difference maps showed that the classification of the analytes agreed with structure similarity laws. The detection results from parallel experiments and structurally similar analytes, in turn, cluster into a group; the fingerprints of the different analytes have specific response regions. The well-screened sensor chip fabrication workload and cost were both reduced by approximately two thirds, while the microfluidic device sensitivity and stability increased by approximately 1.3 times their corresponding values before optimization. The dual-channel device also offers real-time contrast detection and synchronous parallel detection functions and has potential application prospects for use in extensive screening of high-risk populations for lung cancer.

This study addresses the prediction of recurring failures in water supply networks, a complex and costly task, but essential for the effective maintenance of these vital infrastructures. Using historical failure data provided by Companhia de Água e Esgotos da Paraíba (CAGEPA), the research focuses on predicting the time until the next failure at specific points in the network. The authors divided the failures into two categories: Occurrences of New Faults (ONF) and Recurrences of Faults (RF). To make the predictions, they used predictive models based on Machine Learning, more specifically on MLP (Multi Layer Perceptron) neural networks. The study revealed that, by analyzing data from past failures and considering factors such as altitude, number of failures on the same street and days between failures, it is possible to achieve an accuracy greater than 80% in predicting failures within a 90-day interval. This demonstrates the feasibility of using fault history to predict future water supply outages with significant accuracy. These forecasts allow water utilities to plan and optimize their maintenance, minimizing inconvenience and losses. The article contributes to the field of water infrastructure management by suggesting that the data-driven approach can be applied in other cities or in networks of different types, such as energy or communication networks. The conclusions highlight the importance of data collection and analysis in preventing failures and optimizing water utilities’ resources.

With the increasing of China's international status and the acceleration of the process of global economic integration, the internationalization strategy of Chinese enterprises is getting deeper and deeper. This paper analyzes the problems and challenges faced by the international supply chain management of Chinese bamboo weaving and creative products, and puts forward a set of supply chain management model that ADAPTS to the international development. Firstly, the concept, connotation and types of supply chain management are sorted out through literature review. Secondly, this paper analyzes the current situation of international supply chain management of bamboo editing and creative products, and points out the existing problems. Thirdly, based on the theory and practice of international supply chain management, this paper puts forward a set of supply chain management model suitable for the international development of bamboo editing and creative products. Finally, taking a bamboo weaving and creative products enterprise as an example, the application effect of the supply chain management model is empirically analyzed. The results show that the supply chain management model can effectively reduce the cost and improve the efficiency, and is conducive to the international development of bamboo editing and creative products.

This study investigates the relationship between housing prices and vacancy rates in Hong Kong, offering insights distinct from previous cross-sectional analyses. Addressing limitations in data availability and methodological approaches, the study examines annual data spanning multiple housing size categories to uncover nuanced dynamics in the housing market. Two major contributions emerge: firstly, the analysis reveals the price elasticity of vacancy, elucidating how housing prices respond to changes in vacancy rates over time. Secondly, by considering housing vacancy changes as outcomes of the interactions between supply and demand, the study challenges the conventional independence assumption between these variables. The results support the hypothesis that housing vacancies exert a negative impact on housing prices, holding other factors constant. These findings have significant implications for policymakers, urban planners, and real estate investors, providing valuable insights for crafting targeted interventions and informing investment decisions.

In contrast to its traditional form, in which large, powerful companies were solely and exclusively responsible for supplies, manufacturing, and distribution, the supply chain has undergone substantial change over the past half-century. Today, nearly all supply chain processes are outsourced, thanks to the efforts of innovative, modern companies. The degree of risk associated with contemporary supply chains is greater than the majority of supply chain managers acknowledge, according to an accumulation of studies, analysts, and news outlets. Vulnerabilities within the supply chain remain a significant challenge for numerous organizations. Inadequate management of these risks—which include, but are not limited to, natural disasters, acts of terrorism, cyber assaults, the credit crisis, pandemic scenarios, and war—could lead to significant declines in profitability, productivity, revenue, competitive advantage, and other metrics. Concerns regarding the risk assessment of the supply chain remain unresolved. The objective of this article is to present a risk evaluation framework that can be effectively implemented in the assessment of supply chain risks. This study makes a fundamental contribution to the body of knowledge by providing supply chain managers with a practical instrument for assessing their processes, irrespective of the mathematical underpinnings or the diverse variables employed in risk assessment. A case study from an automotive EMS production is used to compare the outcomes of multiple aggregation methods; the conclusions are then validated by risk and FMEA specialists from the same factory.

The implementation of residential distributed generation (DG) in South America has shown significant growth in the last decade, driven by increased research on photovoltaics and renewable energy sources. Regulatory policies and business models have been crucial in fostering the adoption of DG in the region, with residential self-supply being the most receptive sector for implementing the concept. This article presents a literature review on DG as applied to residential self-supply in South America by comprehensively analyzing documents published between 2013 and 2023, applying the PRISMA methodology. In total, 37 literature resources have been systematically selected and reviewed to contribute to the identification of trends and developments in the field of DG in the residential sector, as well as highlighting areas that require further research and attention from stakeholders, including policymakers, investors, technology providers and consumers in the South American context.

To solve the benefit allocation problem between the subjects of the supply chain of general contracting projects. The Cobb-Douglas function is applied to establish the benefit distribution model when the two cooperate in the supply chain system, analyze the optimal benefit situation of one-time cooperation between the two parties under two modes of egoistic decision and collectivistic decision as well as the benefit distribution problem of multiple cooperation, and conduct numerical simulation to calculate the functional relationship between each decision variable and the contribution degree of the general contractor under different effort cost coefficients. The results show that：In the case of one-time cooperation between general contractors and subcontractors, regardless of the decision mode, the degree of effort of both parties is positively related to their own contributions and negatively related to each other's contributions; the overall benefit of the supply chain system is positively proportional to the degree of contribution of the general contractor and inversely proportional to the share of benefit distribution of the subcontractor; in multiple cooperation, the equilibrium result of both parties achieving Pareto optimality at each stage is that both parties choose to cooperate.

Poultry eggs are a critical source of protein, vitamins, and minerals for people worldwide; facing the current global egg shortage is a significant concern. The shortage results from various factors, including avian flu outbreaks, changes in consumer demand, and supply chain disruptions caused by the COVID-19 pandemic. The economic crisis caused by the pandemic has also impacted the availability and affordability of eggs, particularly in low-income countries. The global egg shortage has implications for public health, particularly for vulnerable populations who rely on eggs for essential nutrients. One Health, an approach that recognizes the interconnectedness of human, animal, and environmental health, provides a useful framework for understanding and addressing the egg shortage. One Health approaches to the egg shortage involve collaboration between agriculture and environmental sectors to address the root causes of the lack and ensure the sustainable production and distribution of eggs. Addressing the global egg shortage requires a multifaceted approach considering the complex social, economic, and environmental factors. One Health perspectives offer a way to understand and address the interconnected factors contributing to the shortage to ensure access to affordable, nutritious eggs for all in a healthy way

This article provides a comprehensive analysis of the global gas and liquefied natural gas (LNG) markets. The article begins by discussing the increasing demand for gas and LNG, particularly in Asia, as countries aim to transition to cleaner sources of energy. It explores how market volatility has led to energy security interventions and lasting economic and emissions impacts. It then explores the global supply and demand dynamics, highlighting the structural change expected in the market and the competition between Europe and Asia for limited new LNG supply. The article also focuses on Europe's increased flexibility and dependence on LNG imports, which have risen by 60% to 121 million tonnes, offsetting lower Russian pipeline imports. Furthermore, the article delves into global supply and demand dynamics, how the market is expected to remain tight, and how record gas and LNG prices have led to demand reductions. Additionally, it analyzes the future outlook and investment needs, highlighting the continued uptake of gas in heavy-duty transport and the need for further investment to avoid a supply-demand gap. The article concludes with an analysis of the implications for the future of the global gas and LNG markets.

The quickest and easiest way to avoid greenhouse gas (GHG) emissions is to purchase renewable electricity and offset the remaining emissions. However, the industrial sector’s electricity needs already exceed renewable electricity generation. Moreover, electricity accounts for only one third of the industry’s energy needs. Simultaneously, the advance of sectoral coupling and the decarbonisation of industrial processes, as well as the desire to rapidly decrease dependence on fossil fuels, are creating significant additional demand for renewable energy. Neither existing nor planned generation and transmission infrastructure will suffice to meet the expected short-term demand. Based on survey data from the German Industry Energy Efficiency Index, this article therefore examines the share of GHG savings that companies intend to achieve on- and off-site. Understanding how much additional generation and transmission capacity is needed by the industry to decarbonise and by when is crucial to identify and address the extent of excess demand. On average, companies plan to avoid 22 % of their 2019 emissions by 2025 and 27 % by 2030, primarily through on-site measures. In combination with the extrapolation of the entire industry’s needs for off-site capacity, the data calls for a rapid expansion of planning authority and green generation capacities.

Given the recent emergence of Rift Valley Fever (RVF) in Rwanda and its profound impact on livelihoods and health, improving RVF prevention and control strategies is crucial. Vaccinating livestock is one of the most sustainable strategies to mitigate the impact of RVF on health and livelihoods, yet vaccine supply chain constraints severely limit the effectiveness of vaccination programs. In the human health sector, unmanned aerial vehicles, i.e., drones, are increasingly being used to improve supply chains and last-mile vaccine delivery. We investigated perceptions on whether delivering RVF vaccines by drone in Rwanda might help to overcome logistical constraints in the vaccine supply chain. We conducted semi-structured interviews with stakeholders in the animal health sector and Zipline employees in Nyagatare District in the Eastern Province of Rwanda and used content analysis to identify key themes. We found that stakeholders in the animal health sector and Zipline employees believe that drones could improve RVF vaccination in Nyagatare. The main benefits study participants identified included decreased transportation time, improved cold chain maintenance, and cost savings.

The general circuit topology and principles of low-noise high-voltage power supply are investigated to meet the requirements of the high-voltage bias application in air kerma meters. Two topologies, flyback converter and Royer converter are simulated using SPICE simulation program. The simulation results indicate that the circuit structure of the Royer converter is more complex, but it obtains lower output high voltage noise. While we develop an adjustable high-voltage power supply according to the circuit structure of the Royer converter, and tested it to ensure the design requirements for continuously adjustable output high-voltage linearity. The test results show that the linear adjustment rate is not more than ±0.0025%, the load regulation rate is less than ±0.1%, and the output ripple noise voltage percentage is less than 0.01%. These tested performance make it more suitable for accurate nuclear measurements.

The paper explains the dynamics of monetary aggregates in Russia with the help of country's trade balance, the creation of deposits by commercial banks and cross-border flows of rubles and (foreign) currency. The volumes of deposits and flows, in turn, depend on changes in the currency/ruble exchange rate and favorable external economic conditions. The model was estimated by the Kalman filter, the adequacy was confirmed by stimulation. Monthly money supply forecasts have an accuracy of ~ 1%. It was found that the volume of additional deposits created per month is ~ 300 billion RUB (this leads to real inflation of 9.5% per annum), money flows that are not related to payments for goods: rubles inflow from abroad ~ 100 billion RUB, currency goes abroad ~ 15 billion USD. With the growth / fall of the dollar exchange rate by 1 RUB per month, during the same month, the creation of additional ruble deposits and the arrival of rubles from outside decreases / increases by 0.114 billion USD. The increase of the Currency Reserve Assets of Russia is accompanied by going abroad ~ 5% of the increase.

“Money has always been something of an embarrassment to economic theory. Everyone agrees that it is important; indeed, much of macroeconomic policy discussion makes no sense without reference to money. Yet, for the most part theory fails to provide a good account for it.” (Banerjee and Maskin, 1996, p. 955)The debate about whether or not a growth imperative exists in debt based, interest bearing mone- tary systems has not yet been settled. It is the goal of this paper to introduce a new perspective in this discussion.For that purpose an SFC computational model is constructed which simulates a post Keynesian Endogenous Money system without including economic parameters such as production, wages, consumption and savings. A case is made that isolating the monetary system allows for better analysis of the inherent properties of such a system.Loan demands, which are assumed to happen, are the driving force of the model. Simulations can be run in two modes, each based on a different assumption. Either the growth rate of the money stock is assumed to be constant or the loan rate, expressed as a percentage of the money stock, is assumed to be constant.Simulations with varying parameters are run in order to determine the conditions under which the model converges to stability, which is defined as converging to a bounded debt rate.The analysis shows that stability of the model is dependent on net bank profit ratios, expressed relative to their debt assets, remaining below the growth rate of the money stock. Based on these findings it is argued that the question about the existence of a growth imperative in debt based, interest bearing monetary systems needs to be reframed. The question becomes whether a steady state economy can realistically support such a system without destabilising it. In order to answer this question real world behavior of economic actors must be included in the model.It is concluded that there are indications that it might not be feasible for a steady state economy to support a stable debt based, interest bearing monetary system without strong interventions. However, more research is necessary for a definite answer. Real world observable data should be analysed through the lens of the presented model to bring more clarity.

Unpaid family caregivers might suffer losses in income as a result of care provision. Here we used data from the baseline survey of the China Health and Retirement Longitudinal Study to assess the relationship between hours of weekly caregiving provided to grandchildren/parents/parents-in-law and individual’s monthly employment income. Our study sample comprised 3,718 middle-aged Chinese adults who were of working age (45-60 years). For women and men separately, we used a likelihood-based method to determine a caregiving threshold in a two-stage Heckman selection procedure. Instrumental variables were used to rule out the endogeneity of caregiving hours. Our analysis revealed a negative association between caregiving and income for women that depended on a caregiving threshold of 63-hours per week. There was an absence of caregiving-income relationship among men. These results offer new insights into the opportunity costs of unpaid caregiving and support tailored policies to protect the financial well-being of female caregivers.

In light of the latest trends in global installed capacities, the importance of variable renewable energy sources (VRES) to future energy supply systems is evident. Despite this, the inherent intermittency of VRES remains an obstacle to their widespread adoption. Green hydrogen is often suggested as an energy carrier that can account for this in a sustainable manner. In the analysis, a robust European energy system in the context of 2050 and with 100% VRES energy supply is designed through an iterative minimal cost-optimization approach that ensures robust security of supply over 38 weather-year scenarios (1980-2017). The impact of spatial VRES variability is factored in by defining exclusive VRES groups within each optimization region and, from this, it can be seen that higher numbers of groups in each region offer cheap electricity generation locations to the optimizer and thus decrease the total annual cost of the system. Beyond this, the robust system design and impact of inter-annual variability is identified by iteratively combining the installed capacities of different system designs obtained by applying 38 historical weather years. The robust system design outlined here has significantly lower capacities in comparison to the maximum regional capacities obtained in the first round of optimization.

Global financial investments in energy production and consumption are significant since all aspects of a country's economic activity, and development require energy resources. In this paper, we assess the investment trends in the global energy sector during, before and after financial crises of 2008 using two data sources: (1) Dealogic database providing cross‐border mergers and acquisitions (M&As), and (2) fDi Intelligence fDi Markets database providing greenfield (GF) foreign direct investments (FDIs). We highlight the changing role of China and compare its M&A and GF FDI activities to those of the United States, Germany, UK, Japan and others during this period. We analyze the investments along each segment of the energy supply chain of these countries to highlight the geographical origin and destination, sectoral distribution, and cross‐border M&As and GF FDI activities. Our paper shows that while energy accounts for nearly 25% of all GF FDI, it only accounts for 4.82% of total M&A FDI activity in the period 1996-2016. China's outbound FDI in the energy sector started its ascent around the time of the global recession and had accelerated in the post-recession phase. In the energy sector, the development of China's outbound cross‐border M&As is similar to USA or UK, located mostly in the developed countries in the west, while their outbound GF investments are spread across many countries around the world. Also, China's outbound energy M&As are concentrated in certain segments (extraction, and electricity generation) while their GF covers all segments of the energy supply chain.

Secondary transportation of raw and comminuted forest products is a major component in forest harvesting operations in terms of economics, public perception, and safety. Consequently, there is a substantial amount of literature on this topic. The existing literature has dealt with many of the technical aspects of transportation with a majority of them focusing on improving supply chain issues; However, there are only few specific to secondary transportation issues in general. This annotated bibliography will help practitioners, researchers, and stakeholders gain a better understanding of the existing literature from 2000 to 2015. To this end, we began by classifying the selected literature into six themes: cost, roads and routes, trucking, efficiency & safety, other modes of transportation, and supply chain & optimization. Woody biomass for bioenergy production was the most researched forest product with respect to transportation. About one-third of the articles were presented in the context of supply chain modeling and optimization. More than half of the studies originated from Europe while the United States had the most publications for any given country. The most articles (16) were published in 2013. Biomass and Bioenergy published the highest number of articles (29) during the timeframe.

This paper proposes a re-conceptualization of the port supply chain as a smart service system, according to the theory of the Service science. Starting from a short literature review about the port supply chain approach and the Service science, a new comprehensive framework is provided to better understand the seaport dynamics and the creation of competitive port supply chains. The methodology used is the case study approach. The authors examined the port of Salerno (Italy), and re-conceptualized it as a smart port service systems. Both theoretical and practical implications are provided to enrich the literature about the port supply chain and to support the port operators.

Osteoporosis is considered a serious public health problem, particularly affecting the postmenopausal period. In 2018, in the Republic of Kazakhstan the total and primary incidence was 10 and 3.7 cases per 100,000 adults, respectively. The objective is to study osteoporosis prevalence and indicate main factors affecting low bone mineral density by screening adult population of Abay region, Kazakhstan. The target group were 641 respondents aged between 18 and 65 years old, Kazakh population living in Abay region since birth. All participants filled out questionnaire and had a bone mineral density measurement by dual energy X-ray absorptiometry (DXA) between July 15, 2023 and February 29, 2024. Logistic regression analysis was conducted to assess the association between low bone mineral density and key demographic characteristics, aforementioned lifestyle factors and nutrition habits. We identified the prevalence of low bone density and osteoporosis at the level of 34.1% with the highest prevalence in the older population group (50+ years) - 48.3%. Regression analysis revealed a number of indicators associated with the likelihood of bone sparing. However, only 4 of these showed significance in the final multivariate model (R2=22.4%). These included age (AOR 1.05), body mass index (AOR 0.92), fracture history (AOR 1.64), consumption of nuts and dried fruits were associated with lower prevalence of osteoporosis (AOR 0.48). Our study was the first in Kazakhstan that investigates the association of key demographic, behavior and anamnestic factors with low mineral density.

Ralstonia solanacearum is the pathogen responsible for Ralstonia solanacearum, which is soil-borne, infests plant conduits to cause disease.They are not easy to control and are harmful.Therefore the development of a controlled-release agent responsive to the pathogen's soil temperature and moisture conditions could aid in its control. Corn kernel powder is used as a carrier for Tetramycin biopesticide, with various compounds tested for bonding.They were then made by extrusion moulding.Temperature and wetness responsive components, including Pentaerythritol Tetrastearate, Pentaerythritol Tetraoleate, Polyethylene Glycol Stearate, and Polyethylene Glycol Monooleate,are compounded and coated onto Tetramycin cores to form an intermediate shell layer. Finally, Ethyl cellulose(EC)and Hydroxypropyl methyl cellulose(HPMC) are dissolved and sprayed onto the outermost layer to complete the pellet's shell layer.After the evaluation of texture performance test,DSC analysis,TG test,temperature and humidity response performance test, as well as pellet cross-section SEM observation, field effectiveness test, etc., the preferred formulations were screened.The results showed that the preferred Core formulation:Corn kernel powder:Tetramycin aqueous:Xanthan gum mass ratio=13.5:23:2; Intermediate Shell layer:PETS: PETO: PEG400MO mass ratio=10:30:10; and Outer Shell layer: Ethyl cellulose (EC):Hydroxypropyl methyl cellulose (HPMC) mass ratio=5:1.Under soil conditions of high incidence of Ralstonia solanacearum, i.e., sustained warmth (30-35℃) and high humidity (30% moisture content), the formulated pills showed a release rate of 95.18% to 96.24% over a period of 35 days. Moreover, they showed a stepwise cyclic release process under alternating warm and humid-dry and cold conditions.In field tests on tobacco, a relative preventive efficacy of 54.74% was achieved 106 days post-transplanting. Soil bacterial community structure analysis revealed a significant decrease (2.28-2.84 times) in the abundance of Solanaceae Raelia under Tetramycin pellet treatment compared to the control. Additionally, fungal community structure showed highter consistency initially across various soil depths, with diversity differences between soil layers reestablished later (106 days), while the predominant categories of bacteria and fungi remained unchanged.In this study, we successfully developed a nucleoshell-type slow-controlled release pill embedded with Tetramycin. This pill effectively responded to temperature and humidity changes, resulting in high efficacy in disease prevention.This development holds significant promise for effectively improving drug utilization and easing application challenges, offering broad prospects for Ralstonia solanacearum prevention and control in agriculture.

Chest X-ray (CXR) is the first tool globally employed to detect cardiopulmonary pathologies. These acquisitions are highly affected by scattered photons due to the large field-of-view required. Scatter in CXRs introduces background in the images, which reduces their contrast. We developed three deep learning-based models to estimate and correct the scatter contribution to CXRs. We used a Monte Carlo (MC) ray-tracing model to simulate CXRs from human models obtained from CT scans using different configurations (depending on the availability of dual-energy acquisitions). The simulated CXRs contained the separated contribution of direct and scattered X-rays in the detector. These simulated datasets were then used as the reference for the supervised training of several NN. Three NN models (single and dual energy) were trained with the MultiResUNet architecture. The performance of the NN models was evaluated on CXRs obtained with the MC code from chest CTs of patients affected by COVID-19. The results showed that the NN models were able to estimate and correct the scatter contribution to CXRs with an error &lt;5%, being robust to variations in the simulation setup and improving the contrast in soft tissue. The single-energy model was tested with real CXRs, providing robust estimations of the scatter-corrected CXRs.

Legume-rhizobial symbiosis leads to to the formation of root nodules, where rhizobia reside and develop into bacteroids to reduce nitrogen into ammonium for plant growth, which leaves an opening question as how plant immunity is attenuated in nodules in the presence of large number of foreign bacteria. In Medicago truncatula, mutation in NAD1 (Nodules with Activated Defense 1) only produces necrotic nodules with overactivated immunity, indicating NAD1 is an indispensable component required for suppressing immunity in nodules. In this study, a dual RNA-seq transcriptomic technology was performed to extensively analyze gene expressions in nad1-1 mutant nodules. We indenifited 89 DEGs in symbiotic nitrogen fixation and 89 DEGs in immunity in Medicago truncatula at 10 dpi. Simultaneously, we indenifited 27 DEGs in fix and nif genes in Sinorhizobium meliloti. Then we identified 56 DEGs related to stress, including ROS, NO, and NCR, most of which were upregulated in Sinorhizobium meliloti. Our analyses of nitrogen fixation-defective plant nad1-1 mutants with overactivated defense indicate that host use plant immunity to control massive bacterial colonization during early and late symbiotic stages. Our findings provide insight into the function of NAD1 in improvement or inhibition of plant immune response to maintain symbiosis during rhizobial endosymbiosis.

To compare the quality of low-energy VMIs obtained with three DECT platforms according to phantom diameter. Three sections of the Mercury Phantom 4.0 were scanned on two generations of split-filter CTs (SFCT-1st and SFCT-2nd) and on one Dual-source CT (DSCT). Noise power spectrum (NPS), task-based transfer function (TTF) and detectability index (d’) were assessed on VMIs from 40 to 70keV. Highest noise magnitude values were found with SFCT-1st and noise magnitude was higher with DSCT than with SFCT-2nd for 26-cm (10.2±1.3%) and 31-cm (7.0±2.5%), and the opposite for 36-cm (-4.2±2.5%). The highest average NPS spatial frequencies and TTF values at 50% (f50) values were found with DSCT. For all energy levels, f50 values were higher with SFCT-2nd than SFCT-1st for 26-cm (3.2±0.4%) and the opposite for 31-cm (-6.9±0.5%) and 36-cm (-5.6±0.7%). The lowest d’ values were found with SFCT-1st. For all energy levels, d’ values were lower with SFCT-2nd than with DSCT for 26-cm (-6.2±0.7%), similar for 31-cm (-0.3±1.9%) and higher for 36-cm (5.4±2.7%). In conclusion, compared to SFCT-1st, SFCT-2nd exhibited lower noise magnitude and higher detectability values. Compared with DSCT, SFCT-2nd had lower noise magnitude and higher detectability for the 26-cm but the opposite was true for the 36-cm.

Relay protection service is the most crucial service carried by the electric power communication network, which is directly linked to the safe operation of the power grid. In the route planning of power services, a route planning architecture for the power communication network is constructed in this paper, considering the operation and maintenance requirements, such as relay protection service overload (RPSO) and dual route. To minimize network risk variance, the problem of single-service route allocation is formulated by taking the factors into account such as service delay, link bandwidth utilization, and RPSO constraints. Based on $k$ shortest paths algorithm, a route planning scheme for the power services is proposed, which considers RPSO and risk balance, and a strategy for implementing multi-service route planning of the communication network is studied. The simulation results show that the proposed route planning strategy can effectively avoid relay protection service overload, reduce network risk variance, and balance network risk.

Cross-field innovation in faba bean breeding has added significant value to the traditional faba bean planting industry by allowing for the selection of faba bean varieties with a dual purpose as ornaments and food. In order to improve the selection efficiency, we determined 17 phenotypes related to ‘dual purpose’ faba beans and evaluated 37 new breeding lines, which were bred for 10 years by our team, and two traditional faba bean varieties by means of an Analytic Hierarchy Process. The lines and varieties were evaluated and sorted into five grades, from which two breeding lines with excellent comprehensive phenotypes and dual ornamental and food functions were selected. The new line GS5 passed the identification of Crop Identification Committee of Chongqing Seed Industry Association on November 25, 2021 and was renamed "Doumei 1 hao" with the identification number of " 202111". The results confirmed that the comprehensive evaluation system constructed in this study can be used for the effective selection of dual-purpose faba bean lines, providing an empirical approach for strategic decision-making by breeders.

Type 2 diabetes mellitus (T2DM) accounts for one-sixth of deaths, globally, whereas cancer is the second leading cause of death in the U.S. T2DM is a known risk factor for many cancers. This review examines the link of Reactive oxygen Species (ROS)-altered metabolic and signaling pathways in T2DM to cancer. These reprogrammed metabolic and signaling pathways are activated that contribute to diabetic complications, impact redox balance (Oxidative Stress), and have differential roles in early and late stages of cancer. If the respiratory chain is highly reduced (as under hyperglycemic conditions) or if reduced cofactors accumulate, ROS are greatly elevated. ROS may cause mutations in mitochondrial DNA (mtDNA) that result in further ROS elevation. Amplification of ROS results in activation of PKC, an overarching signaling pathway that activates MAPK with subsequent regulation of several factors that result in pathophysiological manifestations of T2DM and cancer. Upregulation of PKC leads to deregulation of NF-kß that regulates the PKB/P13/Akt pathway that orchestrates cell survival, growth, proliferation, and glucose metabolism manifested in cancer. It also affects Insulin Receptor Substrate (IRS-1), decreasing insulin stimulated glucose transport and glucose uptake, disrupting subsequent cell signaling pathways contributing to the development of T2DM. Dyslipidemia is a hallmark of T2DM and cancer. ROS-induced lipid peroxidation leads to systemic inflammation, producing inflammatory prostaglandins, cytokines and chemokines that result in tumor proliferation, rapid tumor growth, and modulation of immunity. The dual role of ROS in early and late stages of cancer make antioxidant therapy precarious and may be responsible for controversial results. A system that delivers an antioxidant directly to mitochondria may be useful in inhibiting formation of ROS early during the pre-diabetic stage whereas antioxidant therapy must be halted in later stages to retard metastasis.

Starch is widely applied in various industrial sectors, including the food industry. Starch is used as a thickener, stabilizer, or emulsifier. However, arrowroot starch generally has weaknesses, such as unstable under heating and acidic conditions, which are generally applied to processing in the food industry. Modifications were applied to improve the characteristics of native arrowroot starch. In this study, arrowroot starch was modified by heat-moisture treatment (HMT), octenylsuccinylation (OSA), and dual modification between OSA and HMT in a different sequence, namely HMT followed by OSA, and OSA followed by HMT. This study aims to determine the effect of different modification methods on the physicochemical and functional properties of native arrowroot starch. The result shows that both single HMT and dual modification caused damage to native starch granules, such as the formation of cracks and roughness. Especially for single OSA treatment, there is no significant change in granule morphology after modification. All modification treatments did not change the crystalline type of starch but reduced the RC of native starch. Both single HMT and dual modifications (HMT-OSA, OSA-HMT) increased pasting temperature and setback, conversely decreasing the peak and breakdown viscosity of native starch. Whereas, single OSA has the opposite trend compared with the other modifications. HMT played a greater role in increasing the thermal stability and retrogradation ability of arrowroot starch. Both single modifications (HMT and OSA) increase the hardness and gumminess of native starch, conversely for dual modifications. HMT has a greater effect on color characteristics, where decreased the lightness and whiteness index of native arrowroot starch. Single OSA modification increased swelling volume higher than dual modification. Both single HMT and dual modifications increase water absorption capacity and decrease the oil absorption capacity of native arrowroot starch.

Environmental regulation has dual effects on water resource utilization performance through various channels such as the "three red lines" and the "Porter hypothesis". Based on the detailed analysis of the impact path of environmental regulation on water resource utilization performance, the two-step system GMM method was adopted to test the dual effects of environmental regulation on water resource utilization performance by using panel data of 30 provinces and cities from 2004 to 2020. The results show that: (1) Environmental regulation has a significant direct impact on water resource utilization performance, and is currently in the stage of positive relationship of an inverted u-shaped relationship. (2) Environmental regulation has a significant indirect impact on water resource utilization Environmental regulation has dual effects on water resource utilization performance through various channels such as the "three-red lines" and the "Porter hypothesis". In accordance with a detailed examination of the influence path of environmental regulation on the performance of water resource utilization, the double effects of environmental regulation on water resource utilization performance were examined using panel statistics from 30 provinces and cities from 2004 to 2020 using the two-step system GMM approach. The results demonstrate that: (1) Environmental regulation has a direct effect on water resource utilization performance which is currently in the stage of the positive relationship of an inverted u-shaped relationship. (2) The influence of environmental regulation on water resource utilization performance through government intervention and industrial structure adjustment is indirect, among which government intervention can significantly improve water resource utilization performance, while the growth of the tertiary industry as a percentage can lower water resource utilization performance. (3) Both direct and indirect impacts indicate that enhancing the efficiency of the use of water resources is sustainable, and the water resource utilization performance of the preceding period had a major positive impact over the present phase. Therefore, the paper sets out a few policy suggestions, such as choosing reasonable environmental regulation tools, actively guiding the market-oriented reform with constraints, and upgrading the industrial structure in a green way.

The tumour-associated isoenzymes, hCA IX and hCA XII catalyze the hydration of carbon dioxide to bicarbonate and protons. These isoforms are highly overexpressed in many types of cancer, where they contribute for the acidification of the tumor environment promoting the tumor cell invasion and metastasis. In this work, in order to identify novel dual hCA IX and XII inhibitors, virtual screening techniques and biological assays were combined. A structure based virtual screening towards hCA IX and XII was performed using a database of approximately 26000 natural compounds. The best shared hits were submitted to a thermodynamic analysis and 3 promising best hits were identified and evaluated in terms of their hCA IX and XII inhibitor activity. In vitro biological assays are in line with the theoretical studies and revealed that Syringin, Lithospermic acid, and (-)- Dehydrodiconiferyl alcohol behave as good hCA IX and hCA XII dual inhibitors.

The hybrid numbers are a generalization of complex, hyperbolic and dual numbers. In this paper, we introduce the Horadam hybrid polynomials called Horadam hybrinomials. We also give some special cases and algebraic properties of the Horadam hybrinomials. Finally we obtain some applications related to the Horadam hybrinomials in matrices.

Though the energy density of lithium-ion batteries continues to increase, safety issues related with the internal short-circuit and the resulting combustion of highly flammable electrolyte impede the further development of lithium-ion batteries. It has been well-accepted that a thermal stable separator is important to postpone the entire battery short-circuit and thermal-runaway. Traditional methods to improve the thermal stability of separators includes surface modification and/or developing alternate material systems for separators which may always affect the battery performance negatively. Herein, a thermostable and shrink-free separator with little compromise in battery performance is prepared by coaxial electrospinning and tested. The separator consists of core-shell fiber networks where poly(vinylidene fluoride-hexafluoropropylene) (PVDF-HFP) layer serves as shell and polyacrylonitrile (PAN) as the core. This core-shell fiber network exhibits little or even no shrinking/melting at elevated temperature over 250 °C. Meanwhile, it shows excellent electrolyte wettability and can take large amount of liquid electrolyte three times more than that of conventional Celgard 2400 separator. In addition, the half-cell using LiNi1/3Co1/3Mn1/3O2 as cathode and the aforementioned electrospun core-shell fiber network as separator demonstrates superior electrochemical behavior, stably cycling for 200 cycles at 1 C with a reversible capacity of 130 mAh g-1 and little capacity decay.

In the last decades, the impacts of urbanization on the hydrological cycle have led to an increase in the frequency and magnitude of urban flooding events, also amplified by the effects of climate change. Sustainable Drainage Systems (SuDS) provide a revolutionary change in this field, improving the sustainability and resilience of cities. This research explores the integration of different SuDS with the aim of significantly reducing both flow volume and celerity of floods in a residual urban catchment area of metropolitan city of Querétaro (Mèxico), where extreme rainfall frequently occurs. This catchment is a representative suburb of urban pressure and environmental degradation problems. Currently, managing storm water under climate uncertainty through a multi-disciplinary approach is a major concern in this urban area. A 1D-2D coupling model of shallow water equations, finite volume method, unstructured meshing method, and hybrid parallel computing application defined the optimal configuration of SuDS at catchment scale to reduce the flood vulnerability in Querétaro. Specifically, in this paper we explore the management issues of the proposed SuDS configuration that acts as a water resource system with multiple purposes. A generic simulation model called MODSIM was applied to simulate the designed urban drainage system under a balanced IPCC future climate scenario in terms of reliability, resilience and vulnerability against water scarcity.

The modern supply chain (SC) is growing in terms of data, devices, users, and stakeholders, which introduced new security challenges and threats, especially with the reliance on centralized servers or cloud platforms. In addition, increased trust among system participants exposes the SC to a higher risk of vulnerabilities which require strong security measures. This article proposes a hybrid security framework for SC systems, BC-DRLzSC, that integrates Blockchain (BC) and Deep Reinforcement Learning (DRL) designed to operate in a zero trust (ZT) environment. In particular, we propose a decentralized BC-based approach integrated with smart contracts to manage system participant registration and authentication and to control access to system resources. BC-DRLzSC adopts a ZT architecture to reinforce SC security, which can be achieved with an advocate to verify each entity’s trustworthiness before granting or retaining access to system resources. Incorporating the ZT architecture, with BC and DRL, can potentially and significantly bolster SC system security. DRL is employed to develop a proactive attack detection model that continuously monitors the incoming traffic from authenticated nodes within the network and predicts any malicious actions. Finally, we evaluate the performance of our proposed DRL solution using the NSL-KDD dataset.

The circular supply chain was applied to many industries in the past studies, whereas the rubber recycling industry has not been explored in detail yet. Therefore, this study indentified the key factors of the circular supply chain used in remanufactured products, thereby perfecting its framework. This study put forward 5 aspects and 19 criteria for reference, so that companies in the rubber recycling industry are able to clearly know the direction of implementation when con-structing the circular supply chain for remanufactured products. This study integrated expert opinions with the fuzzy Delphi method and the fuzzy decision making trial and evaluation laboratory proposed key factors, and performed the ranking of importance. The results have displayed that key aspects include the circular business model (A3), increasing the value of resources in the supply chain (A4), and risk management of the circular supply chain (A2). The factors that the rubber recycling industry needs to pay attention to are: optimizing the production process (C2), sharing data in the product lifecycle (C4), effectively tracking and recycling products (C5), redesigning remanufactured products (C13), enhancing resource efficiency (C16), and identifying waste composition and separating materials (C14) . Based on the abovementioned, we had a discussion in this study.

The rapid advancement of technology has led to increased electronic consumption and a corresponding rise in e-waste generation. To address this issue, this study develops a low-carbon e-commerce closed-loop supply chain (LCE-CLSC) system with remanufacturer, platform, and the government as key stakeholders. An evolutionary game approach is employed to investigate the system's dynamics, analyzing the impact of stakeholder strategies on system equilibrium. Numerical simulations reveal important findings: Firstly, government initiatives promoting recycling, carbon taxes on traditional products, can incentivize remanufacturers to produce low-carbon items and encourage platform investment in recycling services. Secondly, higher sales revenues motivate remanufacturers to produce low-carbon products. Thirdly, consumer sensitivity to recycling services strengthens waste recovery when platforms increase investments in these services, leading to remanufacturers choosing low-carbon production. Lastly, government subsidies may become ineffective if the cost of remanufacturers' carbon reduction and platforms' recycling services exceeds their affordability. These findings offer insights for the sustainable development of obsolete electronic product recycling systems.