As the global human population increases, animal agriculture must adapt to provide more animal products while also addressing concerns about animal welfare, environmental sustainability, and public health. The purpose of this review is to discuss the digitalization of animal farming with Precision Livestock Farming (PLF) technologies, specifically biosensors, big data, and block chain technology. Biosensors are noninvasive or invasive sensors that monitor an animal’s health and behavior in real time, allowing farmers to monitor individual animals and integrate this data for population-level analyses. The data from the sensors is processed using big data-processing techniques such as data modelling. These technologies use algorithms to sort through large, complex data sets to provide farmers with biologically relevant and usable data. Blockchain technology allows for traceability of animal products from farm to table, a key advantage in monitoring disease outbreaks and preventing related economic losses and food-related health pandemics. With these PLF technologies, animal agriculture can become more transparent and regain consumer trust. While the digitalization of animal farming has the potential to address a number of pressing concerns, these technologies are relatively new. The implementation of PLF technologies on farms will require increased collaboration between farmers, animal scientists, and engineers to ensure that technologies can be used in realistic, on-farm conditions. These technologies will call for data models that can sort through large amounts of data while accounting for specific variables and ensuring automation, accessibility, and accuracy of data. Issues with data privacy, security, and integration will need to be addressed before there can be multi-farm databases. Lastly, the usage of blockchain technology in animal agriculture is still in its infancy; blockchain technology has the potential to improve the traceability and transparency of animal products, but more research is needed to realize its full potential. The digitalization of animal farming can supply the necessary tools to provide sustainable animal products on a global scale.

The contemporary landscape of eHealth is characterized by major concerns related to electronic medical records (EMRs). In an EMR, critical patient health information gets its own repository, which is the core of the eHealth system. Notably, the EMR not only retrieves health information generated in ambulatory clinical settings but also includes court-generated records. These overlapping records assume the role of a foundational data source for a comprehensive electronic health record (EHR). This scholarly review sheds light on recent trends in medical records and associated challenges, while at the same time providing insights into Saudi Arabia’s targeted approaches to healthcare delivery. Additionally, the talk expands to include a description of blockchain technology and its underlying conceptual framework. This demonstration positions blockchain technology as a promising approach that requires consideration for future use in the healthcare system.

The final assembly of appliances and automotive industries is a rigorous process, that has limited capabilities of full traceability associated with: (1) the parts installed, (2) their fabrication processes, and (3) the assembly work. This is also the case for each of its sub-assemblies The many parts and sub-assemblies that compose the final assembly, make full traceability a challenging fit, that is almost unsurmountable. Such full traceability along the entire supply-chain is not existent today and must be based on documentation of most assembled parts, assembly tasks, and inspection tasks that compose the full assembled product. In addition, security measures are needed to prevent hostile hacking and unauthorized approach to the assembly documentation throughout the entire supply chain. The related documentation and repeated verifications require considerable effort and have many chances for human errors. So, automating these processes has a great value. This article expounds a framework that harnesses block-chain and smart-contract technology to offer traceable and protected documentation of the assembly process. We expand the concept of a Bill-Of-Assembly (BOA) to incorporate data from the bill of materials (BOM), the associated assembly activities, the associated activities’ specification parameters and materials, and the associated assembly resources (machines and/or operators). The paper defines the operation of the BOA with blockchain and smart-contract technology, for attaining full traceability, safety, and security, for the entire assembled product. Future research could extend the proposed approach to facilitate the usage of the BOA data structure in constructing a digital twin of the entire simulated system.

Randomized block Kaczmarz Method and randomized extended block Kaczmarz Method are proposed for solving matrix equation AXB=C, where the matrix A and B may be full rank or rank deficient. These methods are iterative methods without matrix multiplication, and are especially suitable for solving large-scale matrix equations. It is theoretically proved these methods converge to the solution or least square solution of the matrix equation. The numerical results show that these methods are more efficient than the existing algorithms for high-dimensional matrix equations.

The rabbit is a popular animal model for human biomechanical research involving surgery at the hind limb. General anesthesia in rabbits is associated with significantly higher mortality rates than in dogs and cats. In addition, as prey animals, rabbits tend to mask signs of pain, making early detection particularly difficult. Regional anaesthesia, as an adjunct to general anaesthesia, may markedly reduce the need for systemic anaesthetic and analgesic drugs, limiting their associated side effects. In other species, a block of the sciatic (ScN) and the femoral nerves (FN) is usually applied in patients undergoing hind limb surgery. In phase 1 of this study, the ScN and the FN have been localized and an appropriate approach under sonographic guidance has been evaluated. In phase 2, a mixture of methylene blue and lidocaine have been administered to the ScN and the FN in 10 cadavers (20 hind limbs). Staining of the nerves was evaluated by dissection. Ultrasonographically, the ScN appeared as a binocular structure surrounded by a hyperechoic rim. The FN appeared as a hypoechoic structure in the dorsal part of the IPM, becoming hyperechoic/honey-comb-like in the ventral part. Both nerves could be successfully stained in all animals over a median length of 2.3 cm which was considered effective. This technique allows a feasible and accurate access to block of the ScN and the FN and may lead to successful analgesia in rabbits undergoing hind limb surgery.

This research aims to explore the complex interplay between supply chain resilience (SCR), digital supply chain (DSC), and sustainability, focusing on the moderating influence of supply chain dynamism. The goal is to understand how these elements interact within the framework of contemporary supply chain management and how they collectively contribute to enhancing sustainability outcomes. The sample size is 300 CEOs and managers. The study approach integrates quantitative research methods. Structural equation modeling (SEM) is utilized to quantitatively analyze the direct and indirect effects of SCR and DSC on sustainability. The numerous surveys we conduct among supply chain ecosystem stakeholders provide a rich picture of practical implications and contextual nuances. In sum, our early findings generally support a positive relationship between SCR and sustainability in and of itself decrying the need for more resilient supply networks for sustainability. We further find the beneficial impact of digital technologies in promoting sustainability via enhancing environmental control and controlling for efficiency in supply chains. We also offer evidence to show that supply chain dynamism compounds the positive logic between SCR and DSC and sustainability. As a final word, it must be noted that our work speaks to the burgeoning Supply Chain Dynamism as moderator literature by examining the direct and contingent effects of SCR and DSC on not only performance but sustainability. By shedding light on the moderating role of dynamism, the study provides fresh insights into the multifaceted nature of supply chain management and sustainability practices. The study's findings enhance theoretical understanding by elucidating the synergistic effects of SCR, DSC, and sustainability in dynamic supply chain settings. It augments existing theoretical frameworks by integrating concepts of resilience, digitalization, and sustainability into a comprehensive model. Practical and economical, the research offers actionable guidance for organizations aiming to improve sustainability performance through resilient and digitally advanced supply chains. By acknowledging the role of supply chain dynamism, managers can tailor strategies to manage disruptions effectively and leverage digital innovations. Economically, adopting sustainable practices can result in cost savings and competitive advantages. The research emphasizes the importance of aligning supply chain strategies with sustainability goals to drive long-term value and societal impact.

The focus of this paper is on supply chain strategy formulation. A conceptual theory approach is used for investigating and identifying the relationship between multiple elements, dimensions, forces and factors that influence and affect the supply chain strategy formulation in Greenfield context, specific to the slate mining industry. The research study involved secondary data review and series of 20 qualitative interviews, followed by 2 group discussions, one with mining and transportation experts external to the supply chain and one group discussion with supply chain internal experts. Through critical analysis, a number of problems emerge and the process of addressing these problems, results in a new framework for evaluating the relationship between business and supply chain strategy, specific to Greenfield project and integration design context.

The objective of this study is to determine the type of governance of the four main agricultural value chains in Tamaulipas, northeast of Mexico. For the preparation of this research used a qualitative design, using a questionnaire and semi-structured interviews to a sample of representatives of the four selected chains. The results showed that in all the studied networks, control and coordination capacity is limited by the influence that has a link on the rest of the chain. In all cases, was that the industrial link is who leads the chains and exert control over the rest of the links. The results showed that, when the industrial link is located close geographically to the rest of the links (chains of rice and sugar cane), the chains showed a hierarchical type, where the industrial exercised dominion over the rest of the links and captures most of the income. On the other hand, in chains where control is exercised by links that are outside the territory (chains of soybeans and sorghum), they function as captive chains, putting the rest of the chain to its influence and control.

Green supply chain management (GSCM) is fundamentally growing as a key component of sustainability, owing to its ability to improve supply chain competitiveness and performance within firms. The body of literature on GSCM within the manufacturing sector in developing countries such as South Africa is still limited. The study examined the relationships between GSCM practices, dynamic capabilities, and supply chain performance in the South African manufacturing sector. The study was quantitative, involving a sample of 402 supply chain professionals drawn from the manufacturing sector across the four provinces of the country. Hypotheses were tested using structural equation modelling based on the SMART PLS technique. Eco-design Green distribution and green training impacted positively on dynamic capabilities, the latter of which in turn is linked to improved agility, reliability, and reduced supply chain costs. The study validates the importance of GSCM as a driver of dynamic capabilities and performance in manufacturing environments within developing countries such as South Africa.

In this paper, we work with a diffusion-perturbed risk model comprising a surplus generating process and an investment return process. The investment return process is of standard Black-Scholes type, that is, it comprises a single risk-free asset that earns interest at a constant rate and a single risky asset whose price process is modelled by a geometric Brownian motion. Additionally, the company is allowed to purchase noncheap proportional reinsurance priced via the expected value principle. Using the Hamilton-Jacobi-Bellman approach, we derive a second-order Volterra integrodifferential equation which we transform into a linear Volterra integral equation of the second kind. We proceed to solve this integral equation numerically using the block-by-block method for the optimal reinsurance retention level that minimizes the ultimate ruin probability. The numerical results based on light- and heavy-tailed distributions show that proportional reinsurance and investments play a vital role in enhancing the survival of insurance companies. But the ruin probability exhibits sensitivity to the volatility of the stock price.

Coronavirus 2019 (COVID-19) is an infectious disease that is becoming a pandemic. Hydroxychloroquine in combination with azythromycin are among drugs currently in use to eradicate COVID-19. Despite concerns due to its potential cardiac toxicity, hydroxychloroquine is widely accepted in mild and moderate COVID-19 pneumonia. In this case report, we report a case of a young Indonesian adult male with suspected COVID-19 pneumonia who received hydroxychloroquine and azythromycin therapies and during 24 hour experienced deterioration of atrioventricular block.

Lyme carditis (LC) is a manifestation of the early disseminated stage of Lyme disease and often presents as high-degree atrioventricular (AV) block. High-degree AV block in LC can be treated with antibiotics, usually resolving with highly favourable prognosis, thus preventing the unnecessary implantation of permanent pacemakers. We present a systematic approach to the diagnosis and management of LC that implements the Suspicious Index in Lyme Carditis (SILC) risk stratification score.

Today’s export-based manufacturers face the need to implement green supply chains more efficiently in order to overcome environmental barriers in increasingly competitive export markets and to improve export performance. This study examines the structural relationship between environmental collaboration, green innovation capacity, and performance based on the findings of previous studies in order to identify the factors affecting the green supply chain management (GSCM) performance of Korean export-based manufacturers. The study finds that environmental collaboration in the green supply chain environment is an important driver of green innovation capacity for export-based Korean manufacturers. It also finds that green innovation capacity has a positive effect on export performance through environmental performance. This study establishes a theoretical basis for the systematic study of the structural mechanisms of green supply chains and suggests strategic directions for export-based manufacturing firms’ successful GSCM implementation.

Aim: the main aim of this study is to compare the onset of effectiveness of mental nerve block with lingual infiltration and inferior alveolar nerve block on patients visiting dental hospital for extraction of mandibular anterior teeth. Materials and methods: The study was set in a clinical setting. This was a randomized controlled double-blind cross study, where 25 subjects received two treatments at an interval of at least 1 week in a within a dental hospital.Inferior alveolar nerve block and lingual nerve block injection is given with 2mL lignocaine 2% with 1:2,00,000 epinephrine was administered for the right side. Mental nerve block along with lingual infiltration of the corresponding tooth was given with 2mL lignocaine 2% with 1:2,00,000 epinephrine was administered on the left side.Visual analogue scale (VAS) was used in this study, which consists of a scale with range of 0-10 pain severity on which 0 indicated absence of pain and 10 the worst pain possible. The patients were asked to give scores corresponding to his/her pain, after IANB, mental nerve block and lingual infiltration and these scores were recorde.Results: From the results we can see that patients gave scores between 3-4, stating that they had moderate pain during extraction after administration of IANB (54%) (graph 2) and VAS scores of 0-1 were given by patients, which is suggestive of no pain during extraction after administration of Mental nerve block and lingual nerve infiltration (62%)Conclusion: Within the limits of the study we can conclude that mental nerve block along with lingual infiltration is an effective way to completely and quickly anaesthetise the central incisor to the 1st premolar region.

The article presents the case of a 27-year-old female patient with idiopathic congenital complete heart block who was referred by her primary care physician for cardiological evaluation. The conduction disturbance was recognized at the age of 6 years and was asymptomatic. The disqualification from pacemaker implantation included detailed history of a patient’s symptoms, echocardiographic assessment of the heart, exercise testing and ECG Holter monitoring. The aid of salbutamol administered orally was also useful.

Introduction and Objective: Caudal block has been used in children for many years and is considered the gold standard for multimodal analgesia in the pediatric age group. Caudal block belongs to the category of central neuraxial blocks, which can provide both visceral and somatic analgesia. With the introduction of ultrasound into the clinical practice of anaesthesia, the caudal block is now performed under USG guidance. In our study, we aimed to compare the efficacy of a single caudal block in postoperative acute pain management, the need for additional analgesics, the incidence of side effects, the timing of initial analgesic administration, and the need for rescue analgesic administration (paracetamol 10 mg/kg) in circumcision surgery. Materials and Methods: 120 patients undergoing circumcision surgery were divided into 3 groups. The caudal block was performed in all cases under USG guidance. Only the caudal block was applied for cases in the Caudal group (Group C). The Caudal + paracetamol group (Group CP) received paracetamol 10 mg/kg intravenously (i.v.) and the caudal block. Patients in the Caudal + meperidine group (Group CM) received 1 mg/kg meperidine intravenously. The caudal block was performed in each case with a 0.5 ml/kg volume of 0.125% bupivacaine. Results: As a result of our study, it was found that the least postoperative pain occurred in 12.50% of the CM group (p=0.011). Significant results were obtained when weight and age variables were analyzed according to the groups (p-values p=0.011 and p=0.003, respectively). Significant differences were found between the input pulse values, 5-minute pulse values, 15-minute pulse values, and input SpO2 values (p values p < 0.001, p < 0.001, p=0.011, p=0.037, respectively). Only Wong-Baker pain scores at the 24th hour differed significantly from the periods measured after the groups (p < 0.001). There was no significant difference between the FLACC and Wong-Baker pain scores in the other periods. There was no difference between the groups regarding the time when postoperative analgesics were administered and the total amount of analgesics administered (rescue analgesic 10 mg/kg oral paracetamol) (p=0.408, p=0.238). Conclusion: Caudal block can be safely applied during circumcision. Ultrasound guidance increases the chances of success and reduces the complication rate. Caudal block can be safely used in pediatric surgery since it does not cause serious complications, has low postoperative pain scores, and reduces the number of postoperative analgesics.

The global movement of inputs, raw materials, products, and the marketing of products requires the use of supply chains. Green logistics refers to the set of policies and measures aimed at reducing the environmental impacts generated by logistics activities. The traditional supply chain has a certain inability to adapt to the rules agreed in Coop 15. The Green Supply Chain deals with the distribution flows of goods with a view to generating low environmental impact. The Green Supply Chain (GSC) involves aspects of reducing negative impacts throughout the logistics chain, from raw material suppliers, production to the distribution of the product to the customer. In this way, this article seeks to identify the factors that generate negative impacts in the traditional Supply Chain, thus helping to decarbonize it, and create a path for the development of the GSC and thus avoid interruptions in the distribution flow due to not meeting environmental targets. The main problem in decarbonizing the Supply Chain is its difficulty in complying with the rules agreed by the nations in COOP 15. To this end, a systematic literature review was carried out based on the available literature. Based on various articles and books, the parameters that define a Green Supply Chain and the factors that generate environmental impacts in conventional chains were identified. As a result, it was possible to verify a positive relationship between the carbon emission reduction factors that are linked to the supply chain performance factors found in the literature. Of the factors relating to the decarbonization of supply chains, some were more clearly related, such as reducing carbon emissions, reducing environmental risks and the ability to operate using new technologies. Future research could build on the limitations of this study.

We humans are natural-born engineers. As such, we model after machines not only isolated, naturally occurring systems, but also the basic laws of physics, sharing with machines a local-evolution-of-state `grammar'. However, previous work by the author casts doubt upon this mechanistic paradigm, suggesting that it is to blame for the stubbornness of many open problems in physics. Simple experiments are therefore proposed to identify `non-machines'. In one experiment, `non mechanistic correlations' in the spirit of Bell are sought in a pair of separated but previously coupled (macroscopic) chaotic systems. In another it is tested whether chaotic systems could fuzzily `remember their future' in the sense that a future binary perturbation applied to them could be inferred from their present behavior with probability>1/2. Chaotic systems are chosen as candidates because the long-time application of their (deterministic) mechanistic description is conceptually groundless: All scales are significant and mutually coupled in that regime, down to scales governed by QM, yet the quantum-classical transition remains inexplicable---if only due to the measurement problem. Similarly for non-deterministic chaotic systems, modeled as such purely for defying a short-time deterministic mechanistic description. Should a non mechanistic signature be found in such simple systems, the implications for science as a whole and life sciences in particular cannot be overstated.

Advancements in computing technology have resulted in significant changes in education, healthcare, and manufacturing fields. Thus, personnel training in computer-related fields is directly related to national competitiveness. Therefore, the importance of programming education has been emphasized worldwide. Programming education has been conducted since the 1980s, however beginners often find programming tedious and difficult because of the cognitive burden of using text commands. Therefore, block-based programming environments, such as Scratch and Code.org, and beginner-oriented programming environments, such as Blockly and Pencil Code, have been de-veloped. However, they have limitations when transitioning from block to text-based programming. In this study, we conducted one semester of classes for 128 middle school, high school, and uni-versity students to determine whether an environment that allows using a text-based programming language in a block-based programming environment aids beginners’ understanding of program-ming instructions, command usage confidence, and programming usefulness. The results confirm that the usability of a block-based environment positively influences programming perception. This study is significant because it verifies the necessity and effectiveness of a block-based environment that employs a text-based programming language in programming education for beginners.

In urban areas, deep excavation-induced ground deformation may damage adjacent existing structures and is conventionally evaluated by levelling at installed settlement points. However, a small number of measurements cannot represent the total change in ground deformation adjacent to excavation sites. Furthermore, significant local subsidence may occur in places where settlement points have not been installed and only noticed after an accident. For deep excavation sites located in urban areas, paved pedestrian sidewalks are often located adjacent to sites, and construction activity can cause these paving blocks to displace. This study introduces a method to detect paving block displacement adjacent to deep excavation sites using terrestrial photogrammetry. A digital camera creating point cloud data (PCD) and an acquisition method satisfying the frontal and side overlap requirements were demonstrated. To investigate the displacement detection and measurement capabilities by PCD analysis, an experimental program was conducted, including a PCD comparison containing the uplift, settlement, and horizontal paving block displacement and reference data. The cloud-to-cloud distance computation algorithm was adopted for PCD comparison. Paving block displacement was detected for displacements of 5, 7.5, and 10 mm in the uplift, settlement, and horizontal directions; however, the horizontal displacements were less clear. PCD analysis enabled satisfactory measurements between 0.024 and 0.881 mm for the vertical-displacement cases, but a significant error was observed for the horizontal-displacement cases owing to the cloud-comparison algorithm. The measurement blind spot of limited settlement points was overcome by the proposed method that detected and measured paving block displacement adjacent to excavation sites.

Far too often, one meets patients who went for years or even decades from doctor to doctor, without getting a valid diagnosis. This brings pain to millions of patients and their families, not to speak of the enormous costs. Often patients cannot tell precisely enough which factors (or combinations thereof) trigger their problems. If conventional methods fail, we propose the use of statistics and algebra to give doctors much more useful inputs from patients. We use statistical regression for independent triggering factors for medical problems, and “balanced incomplete block designs” for non-independent factors. These methods can supply doctors with much more valuable inputs, and can also detect combinations of multiple factors by incredibly few tests. In order to show that these methods do work, we briefly describe a case in which these methods helped to solve a 60 year old problem in a patient, and give some more examples where these methods might be very useful. As a conclusion, while regression is used in clinical medicine, it seems to be widely unknown in diagnosing. Statistics and algebra can save the health systems much money, and the patients also a lot of pain.

A new generation of universal tools and languages for modeling and simulation multi-physical domain applications emerged and became widely accepted, which generate large-scale systems of differential algebraic equations (DAEs) automatically. Motivated by the characteristics of DAEs systems with large dimension, high index or block structures, we first propose a modified Pantelides’ algorithm (MPA) for any high order DAEs based on its Σ matrix, which is similar to Pryce’s Σ method. By introducing a vital parameter vector, a modified Pantelides’ algorithm with parameter has been presented.It leads to a block Pantelides’ algorithm (BPA) naturally which can immediately compute the crucial canonical offsets for whole (coupled) systems with block-triangular form. We illustrate these algorithms by some examples. And numerical experiments show that the time complexity of BPA can be reduced by at least O(ℓ) compared to the MPA, which is mainly consistent with the results of our analysis.

Prediction and early detection of atrial fibrillation (AF) remain a permanent challenge in everyday practice. Timely identification of an increased risk for AF episodes (which are frequently asymptomatic) is essential in the primary and secondary prevention of cardioembolic events. One of the noninvasive modalities of AF prediction is represented by the electrocardiographic P-wave analysis. This includes the study and diagnosis of interatrial conduction block (Bachmann`s bundle block). Bayés’ Syndrome (named after its first descriptor) denotes the association between interatrial conduction defect and supraventricular arrhythmias (mainly AF) predisposing to cardioembolic events. Our short review presents an update of the most important data concerning this syndrome: brief history, main ECG features, pathophysiological background and clinical implications.

In this paper, we proposed a high accurate and stable Legendre transform algorithm which can reduce the potential instability for very high order at a very small increase in the computational time. The error analysis of interpolative decomposition for Legendre transform is presented. By employing block partitioning of Legendre-Vandermonde matrix and butterfly algorithm, a new Legendre transform algorithm with computational complexity O(N(logN)^2/loglogN) in theory and less than O(N(logN)^4) in practical application is obtained. Numerical results are provided to demonstrate the efficiency and numerical stability of the new algorithm.

The cross-linkable PCL-PEG analogues block-graft copolymer was designed and synthesized, which with the copolymer of the MEO₂MA and OEGMA as graft chains to improve the mPEG-b-PCL-b-mPEG copolymer the aqueous solution properties. And successfully prepared two hydrogels via a copper-catalyzed 1, 3-dipolar azide-alkyne cycloaddition reaction of alkyne-terminated poly[glycidyl methacrylate-co-2-(2-methoxyethoxy) ethyl methacrylate-co-oligo (ethylene glycol) methacrylate] [P(GMA-co-MEO₂MA-co-OEGMA)] with azide end-functionalized PCL-PEG analogues block-graft copolymer, and tetrakis (2-propynyloxymethyl) -methane (TPOM) and with azide end-functionalized PCL-PEG analogues block-graft copolymer. The copolymer's chemical structure was characterized by proton nuclear magnetic resonance spectroscopy and fourier transform infrared spectroscopy. The molecular weights of the copolymers were decided with gel permeation chromatography. The water solubility and temperature sensitivity of the copolymers were studied by taking digital photos and transmittance change measured by UV spectrophotometer at different temperatures. Fluorescence probes, surface tension, dynamic light scattering and transmission electron microscopy were used to analyze the micelles that copolymers self-assembly in aqueous solution. The sol-gel behavior of copolymer solutions at high concentrations was explored by vial inversion experiments. Finally, the network structure of the gels was observed by scanning electron microscopy. These conclusions indicate that these hydrogels are expected to be used as a new material in the field of biomedicine.

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

This paper applied case study research to design architectures for green-field supply chain integration. The integration design is based on a case study of a supply chain integration of 5 companies, operating in different, but supply chain complimenting industry sectors. The case study research is applied to design and validate the architectures in a real world scenario. The supply chain integration architectures enable the conversion of individual into integrated strategies. The architectures are categorised and the process develops into a conceptual system for identifying the correlations between individual participants’ strategic areas of interest and the integrated supply chain areas of interest. The novelty of this paper is a conceptual system for green-field supply chain integration architectures, which can be applied in real world by supply chain practitioners.

Resilience is a particularly important quality for supply chains in this turbulent environment. Resilience in supply chain is the ability to retain, resume, and recover operations after an intense destructive incident. One of the strategic solutions for managing supply chain disruptions is to establish collaboration and strategic alliances in order to achieve competitive advantage. Therefore, given the increasing publication of articles in areas of strategic alliances and supply chain resilience, it is a good opportunity to review these articles, identify gaps in the current literature, demonstrate links between the two areas, and provide suggestions for future research. For these purposes, a bibliometric analysis has been performed on literature available on the Web of Science database. The distribution of articles based on year and country, influential journals, research areas, authors, affiliations, keywords, citations, and reference co-citation analysis are discussed. Results indicate that studies about strategic alliances, meant to increase resilience, are growing in areas such as “Management”, “Operations research”, “Management science”, and “Business”. Furthermore, the sources could be categorized in five clusters; namely “From knowledge concept to value creation”, “Internal and external relationships”, “Logistics and supply chain performance”, “Intellectual capital and strategic management”, and “Critical success factors and alliances”. This article can be useful for both practitioners and academics who explore the topic of strategic alliances and resilience in supply chain and also offers managers the opportunity to overcome supply chain disruptions and negative consequences of risks by becoming familiar with the key concepts of resilience. The persistence of businesses and supply chains is guaranteed through communicating with partners and even competitors in the light of alliance according to the findings of this research. Managers can pay attention to the integration of the supply chain to improve resilience and increase collaboration between suppliers and customers. Given the research results, strategic alliances can be noted in expanding organizational entrepreneurship, and shaping strategic collaboration networks in light of strategic alliances.

Background: Two types of medicinal systems are available in Korea: Western and oriental. These exist as separate services that independently provide medical care to patients. We determined the utility and benefits of compressive and integrated medical services (CIMS) comprising 12 sessions of acupuncture and healing programs over 6 weeks. Methods: In this two-group parallel single-center randomized controlled assessor-blinded trial, 24 participants were assigned to either the experimental (conventional medical treatment plus CIMS, n = 12) or control (conventional medical treatment, n = 13) group. Spinal nerve root block was performed on the compressed spinal nerve root (identified using magnetic resonance imaging) when no improvement was observed after the initial treatment. The experimental group received 12 cycles of acupuncture and manual therapy for 6 weeks; the control group received conventional medical treatment alone. Results: The average age of participants in the experimental and control groups was 70.73 ± 5.95 and 67.33 ± 8.89 years, respectively. There were no significant differences between the groups in terms of age, body mass index, Leeds Assessment of Neuropathic Symptoms and Signs, sex, and current medical history. We found high compliance for both programs (acupuncture and healing). On exclusion of between-group effects, the visual analog scale (VAS) score improved significantly over time (p = 0.045). Further, comparison of the groups after excluding the effects of visits revealed significantly lower VAS scores in the experimental group than in the control group (p = 0.000). Conclusions: Patients with degenerative lumbar spinal stenosis who mainly complain of radiating pain in the lower leg may benefit from CIMS after spinal nerve root block for ≤3 months after treatment. Our study findings suggest that this treatment improves spinal function and Oswestry Disability Index score. However, CIMS did not improve QoL.

Recently, with the rapid advancement of technology, Internet of Things (IoT‏‏‏‏) security has become more efficient and more complex, especially for resource-limited devices such as embedded devices, wireless sensors and radio frequency identification tags (RFID). Lightweight block ciphers (LBCs) provide security for these technologies to protect them against adversaries, but the need for low power consumption in LBCs is one of the most important challenges for IoT‏ technologies. Furthermore, these LBCs are subject to multiple attacks and side channel attacks (SCAs) are among the mentioned threats to these cryptosystems. A type of SCA is correlation power analysis (CPA) in which the attacker tries to reach the key using the relationship between the power consumption of the chip during the algorithm running, data processing, and operations. In this article, a CPA attack is designed to discover master key of the Midori-64 block cipher. According to the proposed method, an attack is done to the first round S-boxes to get half of the key bits. Then, the second round S-boxes were attacked to other half of key bits just use 300 plain text samples. Finally, the most important physical attacks performed on the Midori, are compared to our proposed CPA attack.

Severe postoperative pain affects most patients after thoracotomy and is a risk factor for post-thoracotomy pain syndrome (PTPS). This randomized controlled trial compared preemptively administered ketamine versus paravertebral block (PVB) versus control in patients undergoing posterolateral thoracotomy. The primary outcome was acute pain intensity on the visual analog scale (VAS) on the first postoperative day. Secondary outcomes included morphine consumption, patient satisfaction, and PTPS assessment with Neuropathic Pain Syndrome Inventory (NPSI). Acute pain intensity was significantly lower with PVB compared to other groups at four out of six time points. Patients in the PVB group used significantly less morphine via a patient-controlled analgesia pump than participants in other groups. Moreover, patients were more satisfied with postoperative pain management after PVB. PVB, but not ketamine, decreased PTPS intensity at 1, 3, and 6 months after posterolateral thoracotomy. Acute pain intensity at hour 8 and PTPS intensity at month 3 correlated positively with PTPS at month 6. Bodyweight was negatively associated with chronic pain at month 6. Thus, PVB but not preemptively administered ketamine decreases both acute and chronic pain intensity following posterolateral thoracotomies. The trial was prospectively registered at the Australian New Zealand Clinical Trial Registry (https://www.anzctr.org.au/; ACTRN12616000900415; 07 July 2016).

Homogeneous water dispersions of MWCNTs were prepared by ultrasonication in the presence of an amphiphilic polystyrene-block-poly(acrylic acid) (PS-b-PAA) copolymer. The ability of PS-b-PAA to disperse and stabilize MWCTNs was investigated by UV-vis, SEM and zeta potential. It is shown that the copolymer can disperse nanotubes directly by sonication in water. The results show that the addition of a styrene block to PAA enhances the dispersion efficiency compared to pure PAA, possibly due to the nanotube affinity with the polystyrene moiety. Notably, the dispersions show an evident pH-responsive behavior, being MWCNTs reaggregation promoted in basic environment. Furthermore, composites obtained by drop casting display electrical conductivity responsive to pH variations, showing the potential of such materials for sensing applications.

Many neuropsychological theories agree that the brain maintains a relatively persistent representation of one’s own body, as indicated by vivid “phantom” experiences. It remains unclear how the loss of sensory and motor information contributes to the presence of this representation. Here, we focus on new empirical and theoretical evidence of phantom sensations following damage to or an anesthetic block of the brachial plexus. We suggest a crucial role of this structure in understanding the interaction between peripheral and central mechanisms in health and in pathology. Studies of brachial plexus function have shed new light on how neuroplasticity enables “somatotopic interferences,” including pain and body awareness. Understanding the relations among clinical disorders, their neural substrate, and behavioral outcomes may enhance methods of sensory rehabilitation for phantom limbs.

The Cochran–Mantel–Haenszel (CMH) methodology is a suite of tests applicable to particular tables of count data. Inference is conditional on the treatment and outcome totals on each stratum being known before sighting the data. The CMH tests are important for analyzing randomised blocks data when the responses are categorical rather than continuous. This overview will first review the traditional CMH tests and then explore new alternative presentations of the ordinal CMH tests. Next the ordinal CMH tests will be extended so they can be used to test for higher moment effects. Finally unconditional analogues of the extended CMH tests will be developed.

This qualitative study explores the pivotal role of supply chain collaboration (SCC) in enhancing marketing effectiveness within organizations. By integrating supply chain management (SCM) practices with marketing strategies, companies can optimize operational efficiencies, anticipate consumer demands, and deliver personalized customer experiences. The study emphasizes technological integration, such as IoT, big data analytics, and blockchain, which enables real-time data sharing, predictive analytics, and enhanced visibility across the supply chain. Strategic alignment between SCM and marketing functions ensures efficient resource allocation and strategic deployment of marketing investments, fostering synergistic outcomes and maximizing market impact. Collaborative innovation within supply chains drives continuous improvement and product innovation, strengthening brand reputation and customer loyalty. Additionally, supply chain resilience, achieved through robust risk management and agile strategies, enables businesses to maintain operational stability and mitigate disruptions, safeguarding customer relationships and brand integrity. This research underscores the strategic imperative for organizations to embrace SCC as a driver of sustainable growth and competitive advantage in dynamic market environments. By leveraging SCC to integrate SCM and marketing functions, companies can navigate complexities, capitalize on market opportunities, and sustain long-term success. The findings provide valuable insights for business leaders seeking to enhance marketing effectiveness through effective SCC strategies.

The Covid-19 pandemic strained global supply chains, and companies faced numerous produc-tion, logistics, or material management problems. It is claimed that the digitalization of supply chains can have the potential to make supply chains more resilient to interruptions and disrup-tions. This article focuses on describing the experiences of three large Austrian family-owned business during the supply chain disruptions caused by the pandemic and the Ukraine war. This assessment is done from the perspective of the supply chain leaders in the organization. We provide insights on what worked and what did not for these firms and what we can take away from their experiences.

One of the most remarkable features in the 20th century was the digitalization of technical progress, which changed the output of companies worldwide and became a defining feature of the century. The growth of information technology systems and the implementation of new technical advances, which enhance the integrity, agility and long-term organizational performance of the supply chain, can distinguish a digital supply chain from other supply chains. For example, the Internet of Things (IoT)-enabled information exchange and Big Data analysis might be used to regulate the mismatch between supply and demand. In order to assess contemporary ideas and concepts in the field of data analysis in the context of supply chain management, this literary investigation has been decided. The research was conducted in the form of a comprehensive literature review. In the SLR investigation, a total of 71 papers from leading journals were used. SLR has found that data analytics integrate into supply chain management can have long-term benefits on supply chain management from the input side, i.e., improved strategic development, management and other areas.

(1) Background: Presentation of the method of increasing the competitiveness of the mining industry through the demonstration of the possibility and potential in closing the loop of supply chains through waste management; (2) Methods: The source literature analysis and an arithmetic analysis of the data of statistical materials and data obtained from business in static and dynamic perspectives; (3) Results: According to the latest data available, in Poland, mining wastes account for over a half of industrial wastes, while the annual growth of mining wastes is on the level of 4%. The recorded recovery of mining wastes is on the level of ca. 19%. The exemplary company that deals with the recovery of carbon wastes recovers ca. 80% of material, which is handed over for utilization (4) Conclusions: It has been found that the structure of the level of mining wastes and the level of their recovery rates demonstrate a large potential of closing the loop of chains in this industry and, at the same time, a potential to extend the chains through directing the material from recovery to various sectors. This constitutes an example of the direction of activities that are in line with the EU strategies for the economies of other states which possess this type wastes.

In modern times, sustainability in supply chain management is one of the keys to boosting the performance of the supply chain, and it enables the accomplishment of SSCM. It has been found in recent years that SSCM with assist of industry 4.0 applications, can benefit splendid productivity and efficiency in the supply chain. The numerous industry 4.0 applications that are involved are Artificial intelligence (AI), Machine Learning (ML), Internet of Things (IoT) Big Data Analytics (BDA), etc. Industry 4.0 with SSCM has gained a lot of interest from various authors and scholars across the world. Healthcare is one of the most critical sectors due to its importance in handling public health. More recently, the COVID-19 pandemic and other viruses (SARS and Ebola) have highlighted supply chain vulnerabilities that are further mitigated by their lean and globalized structures. Covid-19 underlined the need for supply chain visibility problems within the healthcare sector. When the need for medical supplies became urgent and global distribution was disrupted, companies faced the consequences of needing the technology, systems, and plans in place to correctly predict the onslaught. One report shows that about 94 percent of Fortune 1000 companies reported supply chain disruptions due to the COVID-19 global outbreak. Existing studies have discussed supply chain issues and the importance of AI in addressing these challenges. AI, like Industry 4.0 in the healthcare supply chain, is proving to be a game-changer. This paper aims to review and present the various aspects of SSCM and industry 4.0 applications to get a comprehensive literature review, which contains the analysis of multiple articles published from 2010-2020. In addition, the various challenges SSCM and industry 4.0 applications face are identified and discussed. Also, the impact of Industry 4.0 and sustainable practices brings together the healthcare supply chain. This study will help in getting a good understanding of the different industry 4.0 technologies that are important for setting up SSCM.

Research in complex network analysis, including tasks such as information dissemination and link prediction, has traditionally advanced by examining groups of nodes with similar characteristics. In multilayer complex networks, these analyses are performed layer-wise, with each layer representing a distinct feature. However, this approach often neglects interlayer interactions, leading to limited predictive power, underestimation of network resilience, and incomplete identification of influential nodes. This article introduces a novel block modeling technique that integrates dominant features from multiple layers, addressing these shortcomings. Our approach introduces a new centrality metric that combines layer weight and PageRank centrality to identify influential nodes within multilayer networks. Nodes are aggregated into blocks centered around these influencers, accounting for both intra- and interlayer connections. Empirical evaluation of various datasets demonstrates that our method effectively identifies influential nodes, thereby enhancing information dissemination and link prediction across diverse multilayer network structures. This technique offers significant potential for improving decision-making processes in various fields, including social network analysis, transportation systems, and biological networks.

Background: Pediatric mallet finger injuries lack specific treatment guidelines, necessitating an exploration of effective techniques. Our aim was to evaluate the outcomes of the extension block technique in adolescent mallet finger management. Methods: A comprehensive retrospective analysis was conducted involving 36 adolescents who underwent surgery between 2014 and 2022. Ishiguro’s extension block pinning technique was the primary method employed. Treatment outcomes were evaluated using Crawford's criteria, and complications were also assessed. Results: Bone union was achieved in all cases with a mean union time of 42 days (range: 30-92 days). According to Crawford's criteria, 27 cases (75%) were classified as excellent, 5 cases (14%) as good, and 4 cases (11%) as fair. Minimal complications were observed, including three cases (8%) of superficial infections, one case (3%) of dermal necrosis, and another rare instance (3%) of osteomyelitis. No cases of poor outcomes or significant long-term complications were noted. The average follow-up period was 8.6 months (range: 2-42 months). Conclusions: Ishiguro’s extension block technique is a promising surgical option for adolescent mallet fingers. Its adoption could enhance pediatric orthopedic care, offering a valuable child-friendly treatment alternative.

Tumor immunotherapy represented by immune target blocking and chimeric antigen receptor cell therapy has developed rapidly. Among them, Natural Killer Cell (NK) is gradually becoming another preferred immunotherapy method after T cell immunotherapy because of its unique killing effect in innate immunity and adaptive immunity. Although NK cell therapy has achieved promising results in clinical trials, there are still some problems, such as low efficacy in solid tumors, insufficient penetration of NK cells and high cost of treatment. Nanomaterials are expected to be an excellent tool to improve the anti-tumor immune response of NK cells due to their advantages such as chemical specificity, biocompatibility and simple synthesis. Nanomaterials can enhance the cytotoxicity of NK cells, participate in the modification and noninvasive cell-tracking patterns of NK cells，and mediate their homing and infiltration, and thus significantly improve the efficiency of NK cell immunotherapy. In this review, we will briefly introduce the methods and mechanisms of tumor immunotherapy, emphasize the research progress of NK cell-based immunotherapy and imaging, and finally summarize the direction and research progress of nanomaterials in NK cell-based immunotherapy.

In this study, carbon blocks were fabricated using isotropic coke and coal tar pitch as raw materials, with a variation in pressure during cold isostatic pressing (CIP). The CIP pressure was set to 50, 100, 150, and 200 MPa, and the effect of the CIP pressure on the mechanical and electrical properties of the resulting carbon blocks was analyzed. Microstructural observations confirmed that after the kneading, the surface of isotropic coke was covered with the pitch components. Subsequently, after the CIP, granules, which were larger than isotropic coke and the kneaded particles, were observed. The formation of these granules was attributed to the coalescence of kneaded particles under the applied pressing pressure. This granule formation was accompanied by the development of pores, some remaining within the granules, while others were extruded, thereby existing externally. The increase in the applied pressing pressure facilitated the formation of granules, and this microstructural development contributed to enhanced mechanical and electrical properties. At a pressing pressure of 100 MPa, the maximum flexural strength was achieved at 33.3 MPa, and the minimum electrical resistivity was reached at 60.1 μΩm. The higher the pressing pressure, the larger the size of the granules. Pores around the granules tended to connect and grow larger, forming crack-like structures. This microstructural change led to degraded mechanical and electrical properties. The isotropic ratio of the carbon blocks obtained in this study was estimated based on the coefficient of thermal expansion (CTE). The results confirmed that all carbon blocks obtained proved to be isotropic. In this study, a specimen type named CIP-100 exhibited the best performance in every aspect as an isotropic carbon block.

Fine-grained image classification remains an ongoing challenge in the computer vision field, which is particularly intended to identify objects within sub-categories. It is a difficult task since there is a minimal and substantial intra-class variance. The current methods address the issue by first locating selective regions with Region Proposal Networks (RPN), object localization, or part localization, followed by implementing a CNN Network or SVM classifier to those selective regions. This approach, however, makes the process simple by implementing a single-stage end-to-end feature encoding with a localization method, which leads to improved feature representations of individual tokens/regions by integrating the transformer encoder blocks into the Yolov5 backbone structure. These Transformer Encoder Blocks, with their self-attention mechanism, effectively captured the global dependencies and enabled the model to learn relationships between distant regions. This improved the model ability to understand context and captured long-range spatial relationships in the image. We also replaced the Yolov5 detection heads with three transformer heads at the output for object recognition using the discriminative and informative features maps from transformer encoder blocks. We established the potential of the single stage detector for the fine-grained image recognition task, by achieving state of the art 93.4% accuracy, as well as outperforming the existing Yolov5 model. The effectiveness of our approach is assessed using the Stanford car dataset, which includes 16,185 images of 196 different classes of vehicles with significantly identical visual appearances.

With the increased use of simulation based training using animal models for the education of surgical and anaesthetic techniques, an increased understanding of the anatomy of such models and how they compare to humans is required. The transversus abdominis plane block is a regional anaesthetic technique that requires an understanding of the abdominal wall anatomy along with proficient ultrasound use. The current review aims to compare the anatomy of the abdominal wall across species, particularly focussing on the pertinent differences within the class of mammals, and secondarily, it aims to address the implications of these differences for simulation based training of the transversus abdominis plane block. To achieve this, the PubMed, Web of Science and Google Scholar databases were searched for relevant literature. The mammalian abdominal wall differs in its musculature, vasculature or innervation from that of amphibians, birds or reptiles, however, among species of mammals, the structure of the abdominal wall follows a similar framework. Particular differences among mammals include the additional muscular layer of the panniculus carnosus found in most mammals other than humans, the variable arterial origins and dominant vascular supply of the abdominal wall and the number of thoracolumbar nerves innervating the abdominal wall. When using animal models for simulation based training, the pig is recommended for the transversus abdominis plane block given its closely homologous abdominal wall structure, availability and larger comparative size.

This paper investigates how blocks of buildings could fit into load shedding strategies. It focuses in particular on what could be the effects on peak shaving, occupants’ thermal comfort or CO2 emissions reduction and how to quickly quantify them. To achieve this goal, we focused on a new residential district, thermally fed by heat pumps. Four modeling approaches were confronted in order to estimate buildings' responses to load shedding orders. On the one hand, a quick estimation of the peak shaving impact can rely on experimental results if the buildings' envelope and uses of the experimentation match those of the study case. On the other hand, thermal simulation models allow us to assess thermal comfort while considering the building physical response. Finally, a hybrid modeling approach can provide a good compromise between modeling rapidity and accuracy of the impacts estimation. At district scale, it may be necessary to mix modeling approaches, from experimental results to detailed thermal models. Accuracy is not guaranteed for all approaches so that the choice should be made carefully in regards to study needs. However, results are sufficient to compare the effects of load shedding strategies on peak shaving, thermal comfort, and CO2 emissions reductions.

Fuel gas network (FGN) synthesis is a systematic method for reducing fresh fuel consumption in a chemical plant. In this work, we address the synthesis of fuel gas network using block superstructure originally proposed for process design and intensification (Demirel et.al. [1]). Instead of a classical source-pool-sink superstructure, we consider a superstructure with multiple feed and product streams. These blocks interact with each other through direct flows that connect a block with its adjacent blocks and through jump flows that connect a block with all blocks. The blocks with feed streams are viewed as fuel sources and the blocks with product streams are regarded as fuel sinks. Addition blocks can be added as pools when there exists intermediate operations among 9 source blocks and sink blocks. These blocks can be arranged in a I × J two-dimensional grid with I = 1 for problems without pools, or I = 2 for problems with pools. J is determined by the maximum number of pools/sinks. With this representation, we formulate fuel gas network synthesis problem as a mixed-integer nonlinear (MINLP) problem to optimally design a fuel gas network with minimal total annul cost. We present a real-life case study from LNG plant to demonstrate the capability of the proposed approach.

Pharmaceutical companies use crisis management as a vital technique to lessen the effects of catastrophes. In this study, the author highlighted the significance of supply chain management for crisis management in the pharmaceutical industry. The study concludes by discussing the role that supply chain management plays in crisis management and offering pharmaceutical businesses advice on how to run their supply chains in an emergency. We conclude after conducting a thorough analysis of the literature review and regress research. These are actions that pharmaceutical organizations can take to strengthen their supply chain management skills and enhance their crisis readiness: Identifying possible supply chain risks through routine risk evaluations; Creating backup strategies in case the supply chain is disrupted; Establishing procedures to guarantee a smooth and efficient supply of medications in an emergency; and Collaborating with vendors and other stakeholders to increase the resilience of the supply chain. The pharmaceutical industry is critical to healthcare, providing safe and effective medicines to patients. Supply chain management is essential for maintaining the flow of medicines during crises. Proactive risk assessment, backup plans, teamwork, and efficient communication are all critical for crisis management in the pharmaceutical industry, particularly in supply chain management. In India, inadequate transportation infrastructure leads to a significant expense for pharmaceutical businesses. To mitigate negative effects, such as reduced healthcare access and insurance coverage, the study suggests implementing multi-echelon, closed-loop green supply chain models. These strategies aim to minimize total costs and ensure efficient resource management. To improve the resilience of pharmaceutical and consumable medical equipment during crises, policymakers should integrate modern technologies and consider business complexity, economic development, intense competition, and changing customer needs. The relationship between manufacturers, distributors, prescribers, and insurance organizations as purchasers should also be considered.

Acute kidney injury (AKI) is a common complication post-cardiac surgery, impacting short- and long-term survival. Free light chains (FLCs) are being explored as markers for assessing kidney damage risk. A study aimed to validate early AKI detection by studying FLCs (kappa, lambda, and kappa/lambda ratio) in serum and saliva samples. Clinical data was collected from 149 patients who underwent cardiac surgery in Baghdad. Ninety of these patients provided saliva samples in addition to serum samples for free light chain evaluation. Patients were grouped by proteinuria severity. Serum kappa levels were significantly higher in severe proteinuria patients compared to mild or no proteinuria. Salivary kappa levels were significantly higher in mild proteinuria patients compared to severe or no proteinuria. Salivary lambda levels decreased with increasing proteinuria severity. Serum kappa increase could be due to immune system activation and kidney compromise. Both serum and salivary kappa showed good predictive ability for post-surgery AKI prognosis compared to lambda and the kappa/lambda ratio, depending upon ROC performance. The study suggests FLCs, especially kappa, could be valuable in early AKI detection post-cardiac surgery, indicating potential for improved patient outcomes through proactive monitoring and intervention.

The sudden onset of natural hazards such as a flash flood events can be devastating to a country or region, often affecting numerous communities, and humanitarian supply chains play a major role in enabling the timely recovery of economic and social activities. However, the uncertainty and suddenness of natural disasters such as flash floods, as well as the potential for aftershocks, require humanitarian supply chains to be resilient during the relief process. This research first adopts the Delphi and literature review methods to identify the key indicators in the humanitarian supply chain to form an evaluation index system. Then, taking the 2021 mega-flash flood event which affected four cities in the mountainous region under the jurisdiction of the Zhengzhou municipal government, the ANP method is used to calculate the weights of each indicator and combines the weighted results with the Multi-styling and stereotyping method under Pythagorean fuzzy (PFs-VIKOR) to make an evaluation of the resilience of the humanitarian supply chain in the relief process. The findings suggest that policy makers and decision makers should pay close attention to the coordination of the parties involved in the humanitarian supply chain and improve the level of resilience of the entire supply chain by enhancing the resource scheduling capacity and responsiveness. At the same time, the VIKOR evaluation of the 4 cities highlighted the humanitarian supply chain in Dengfeng City to be most effective in this event due to the close cooperation and positive response of all parties involved in the humanitarian supply chain. The findings of this research provide some useful suggestions and guidance to the various practitioners involved in the humanitarian supply chain. Furthermore, the evaluation of the performance of the four cities in this mega-flash flood event provides some helpful indication of the importance of the various emergency measures which can help to inform policy recommendations for the Zhengzhou municipal government.

‘‘Sustainable Supply Chain Management’’ (SSCM) has become a hot topic on which eminent researchers are working on every day. However, it is clear that we still observe in this field of research, an artistic vagueness on the fundamental differences between Sustainable Supply Chain Management and Green Supply Chain Management (GSCM) Moreover, it is regrettable to note that previous researchers haven't yet thought about having a specific theory which can be applied to SSCM, the use of macro theories still being observed. In addition, we observe a lack of research in the oil and gas industry especially in Developing Countries when we know that this industry is the most lucrative and polluting. Therefore, this paper’s purpose consists to make a Systematic Literature Review (SLR) of 38 papers published from 2005 to 2023 especially in oil and gas industry and in Developing Countries, in order to make a clear distinction between SSCM and GSCM while highlighting the practices related to them and at the same time, generating a united theory which will bring together the triple bottom line of the SSCM. As findings, the authors built a Conceptual Framework that applies the triple bottom line of the SSCM in oil and gas industry by demonstrating that GSCM which is more related to environmental issues and is a part of the SSCM. Therefore, in order to be more efficient and to have a great impact on their performances, Oil and gas companies should apply SSCM practices rather than GSCM practices which are very different from what is applied in Developed Countries because of certain barriers and pressures.

The world is facing an unprecedented socio-economic crisis caused by the novel coronavirus infection (COVID-19). It is also spreading through the import and export food supply chains. The Chinese authorities have discovered the COVID-19 virus in various imported frozen meat packages. Traceability plays a vital role in food quality and food safety. The Internet of Things (IoT) provides solutions to keep an eye on environmental conditions, product quality, and product traceability. These solutions are traditionally based on the centralized architecture, which does not guarantee tamper-proof data sharing. The blockchain is an emerging technology that provides tamper-proof data sharing in real-time. This article presents Hyperledger Fabric-based blockchain use case and a quick reference guide to develop the blockchain network for tracking and tracing the supply chain to minimize the risk of COVID-19 in the frozen meat supply chain.

Infrared and visible image fusion technologies are used to characterize the same scene by diverse modalities. However, most existing deep learning-based fusion methods are designed as symmetric networks, which ignore the differences between modal images and lead to the source image information loss during feature extraction. In this paper, we propose a new fusion framework for the different characteristics of infrared and visible images. Specifically, we design a dual-stream asymmetric network with two different feature extraction networks to extract infrared and visible feature maps respectively. The transformer architecture is introduced in the infrared feature extraction branch, which can force the network to focus on the local features of infrared images while still obtaining their contextual information. And the visible feature extraction branch uses residual dense blocks to fully extract the rich background and texture detail information of visible images. In this way, it can provide better infrared targets and visible details for the fused image. Experimental results on multiple datasets indicate that DSA-Net outperforms state-of-the-art methods in both qualitative and quantitative evaluations. In addition, we also apply the fusion results to the target detection task, which indirectly demonstrates the fusion performances of our method.

The study of interactions between polyelectrolytes (PE) and surfactants is of great interest for both fundamental and applied research. These mixtures can represent, for example, models of self-assembly and molecular organization in biological systems, but they are also relevant in industrial applications. Amphiphilic block polyelectrolytes represent an interesting class of PE, but their interactions with surfactants have not been extensively explored so far, most studies being restricted to non-associating PE. In this work, interactions between an anionic amphiphilic triblock polyelectrolyte and different types of surfactants bearing respectively negative, positive and no charge, are investigated via surface tension and solution rheology measurements for the first time. It is evidenced that the surfactants have different effects on viscosity and surface tension, depending on their charge type. Micellization of the surfactant is affected by the presence of the polymer in all cases; shear viscosity of polymer solutions decreases in presence of same charge or nonionic surfactants, while the opposite charge surfactant cause precipitation. This study highlights the importance of the charge type, and the role of the associating hydrophobic block in the PE structure, on the solution behavior of the mixtures. Moreover, a possible interaction model is proposed, based on the obtained data.

The objective of this case report is to introduce a customized CAD/CAM freeze-dried bone allograft (FDBA) block for its use in Guided Bone Regeneration (GBR) procedures for severely deficient maxillary bones. Additionally, a special newly developed remote incision technique is presented to avoid wound dehiscence. The results show an optimal integration behaviour of the FDBA block after six months and the formation of new vital bone. Thus, the results of the present case report confirm the use of the customized CAD/CAM bone block for augmentation of complex defects in the maxillary aesthetic zone as a successful treatment concept.

The development of the chicken value chain in The Gambia has immense potentials to lead to the modernisation of agriculture and creating employment for young people and women. Chicken can be raised throughout the year in most parts of The Gambia. With increasing populations, environmental degradation and loss of rangelands, chicken is easier to producer than other livestock, such as cattle and small ruminants. The development of the chicken value chain in The Gambia is also mainly constrained at commercialisation. Commercial farmers in The Gambia are not able to compete with cheap import. Critical inputs such as day-old chicks and feed are imported. Most farms are operating below 40% capacity and only less than 4% utilisation of the available processing capacity. At full capacity and with some needed investments along the value chain, The Gambia has the capacity to meet the demand for chicken and eggs. 88% of the value chain actors believe that the imposition of tariffs on chicken imports will lead to the upward transformation of the chicken value chain being able to employ at least 10% of the Gambian population.

Backyard production systems (BPS) are highly distributed in central Chile. Poultry BPS have been previously characterized; however, swine BPS have not yet been deeply characterized in central Chile. In addition, there is evidence that zoonotic pathogens, such as influenza A virus and Salmonella spp., are circulating in both poultry and pigs kept these production systems. A total of 358 BPS located in central Chile were evaluated between 2013 and 2015 by interviewing farm owners. Severe deficiencies in biosecurity measures were observed. The value chain of swine backyard production identified feeding, products and veterinary visits, and replacement or breeding animals as the main inputs to the backyard. The most common origin of swine replacements was from outside the BPS (63%). Meat and live animals (piglets and breeding animals) were identified as the main outputs of the system. In 16% of BPS, breeding animals were lent to other BPS, indicating the existence of animal and animal products movement in and out of backyard farms. Results from this study suggest that swine BPS in central Chile represent an animal-human interphase that need special attention to direct preventive measures aimed at avoiding the introduction and dissemination of animal pathogens and the emergence of zoonotic pathogens.

This study aims to summarize the literature on sustainable global supply chain management so that researchers and practitioners can see the trends in the area in a single place. Systematic literature review (SLR) or Content analysis is used as a methodology of this literature review, studies that are published within the time frame of 2010 to 2020 are included in this literature. Dimensions to analyze each article includes; year of publications, methodology of research, data collection type, unit of analysis, industry, a country in which data is being collected, respondents’ types, the theory that is used in the study, dimensions of the sustainability and finally the purpose of study either it is to test the already existing theory or building up a new theory. I found that sustainable global supply chain management is an emerging field and there is potential in the area for researchers to explore the area.

The folding of certain proteins (e.g., enzymes) into perfectly defined 3D conformations via multi-orthogonal interactions is critical to their function. Concerning synthetic polymers chains, the “folding” of individual polymer chains at high dilution via intra-chain interactions leads to so-called single-chain nanoparticles (SCNPs). This review article describes the advances carried out in recent years in the folding of single polymer chains into discrete SCNPs via multi-orthogonal interactions using different reactive chemical species where intra-chain bonding only occurs between groups of the same species. First, we summarize results from computer simulations of multi-orthogonally folded SCNPs. Next, we comprehensively review multi-orthogonally folded SCNPs synthesized via either non-covalent bonds or covalent interactions. Finally, we conclude by summarizing recent research about multi-orthogonally folded SCNPs prepared through both reversible (dynamic) and permanent bonds.

Clean use of photons from light to activate chemical reactions offer many possibilities in different fields, from chemistry and biology to materials science and medicine. This review article describes the advances carried out in last decades toward the phototriggered synthesis of single-chain polymer nanoparticles (SCNPs) as soft nanomaterials with promising applications in enzyme-mimicking catalysis and nanomedicine, among other different uses. First, we summarize different strategies developed to synthesize SCNPs based on photoactivated intrachain homocoupling, phototriggered intrachain heterocoupling and photogenerated collapse induced by external cross-linker. Next, we comprehensively review the emergent topic of photoactivated multifolding applied to SCNP construction. Finally, we conclude by summarizing recent strategies towards phototriggered disassembly of SCNPs.

The present study is to address performance of the dairy supply chain and emphasizes the significance of reliability of the chain as a fundamental and critical attribute for fulfilling the safety requirements. In order to evaluate the performance of the dairy supply chain, the present study utilizes the reliability attribute, which is an essential and informative system performance indicator. The study considers not only the inputs and outputs but also internal activities and relationships between customers, manufacturers, and suppliers. To minimize calculations and resolve uncertainties and vagueness that may be experienced in the performance evaluation process, this study proposes the use of the Fuzzy Inference System (FIS) approach and evaluates the reliability at each level of the supply chain: supply, manufacturing, and distribution. Combining the reliability of different levels, the study finally calculates the reliability of the entire supply chain. The proposed methodology offers a practical approach for evaluating the reliability performance of a dairy supply chain and can be easily extended to other industries as well. To verify the proposed methodology, a real case in the Iranian dairy industry is chosen to be studied. Results indicate that the proposed methodology can effectively identify bottlenecks or weaknesses in the dairy supply chain and help develop effective strategies to address them. Analyzing factors influencing supply chain reliability can optimize operations, reduce costs, and improve the overall quality of dairy product quality delivered to consumers.

This qualitative research explores consumer perceptions of supply chain responsiveness and its impact on brand loyalty within the apparel industry. The study investigates how consumers perceive supply chain practices such as reliability, agility, and sustainability, and examines their influence on brand loyalty decisions. Thirty participants, representing diverse demographics and purchasing behaviors, were interviewed to gather insights into their awareness, expectations, and experiences related to supply chain responsiveness. Findings reveal that consumers prioritize supply chain reliability, expecting brands to consistently deliver high-quality products, accurate sizing, and timely responses to market trends. Sustainability practices also emerged as a significant factor, with consumers favoring brands that demonstrate ethical sourcing and environmental responsibility. Technology plays a crucial role in enhancing supply chain responsiveness, as consumers value real-time updates, personalized experiences, and seamless transactions. Moreover, the study underscores the impact of supply chain disruptions on brand trust and loyalty, highlighting the importance of resilience and contingency planning in supply chain management. Brands that effectively navigate disruptions through agile strategies can enhance consumer trust and loyalty, even in challenging circumstances. Overall, this research contributes to understanding the intricate relationship between supply chain dynamics, consumer perceptions, and brand loyalty in the apparel industry. It offers practical implications for apparel brands seeking to enhance consumer satisfaction, differentiate themselves in a competitive market, and foster sustainable growth through strategic supply chain management.

The concept of supply chain leadership strategy has garnered increasing interest from policymakers and experts, because it is among the most dependable practices to sustainable innovation and competitiveness for large firms across developing economies. Effective implementation of supply chain leadership strategic actions at each level in the company can create sustainable innovative and competitiveness. The study collected statistical data using an online Survey- Monkey questionnaire from 46 of top 100 JSE-listed companies with the intention to discover supply chain leadership strategic actions that drive sustainable innovation and competitiveness in the company. The findings expose a significant empirical insight for companies to understand and leverage supply chain leadership strategic actions to influence sustainable innovative position in a developing economy. These results suggest that firms operating within emerging markets should embrace and acknowledge the importance of sustainable innovation in business practices in the provision of goods and services. This study therefore delivers major contributions to the literature to assist in planning sustainable innovation and supply chain practices in a developing economy to survive in a competitive global environment. The paper also offers a vigorous awareness and knowledge of the common characteristics and strategies for supply chain management that needs to be prioritized by the JSE-listed companies.

There are two purposes for this article. The first purpose is to perform a reiew of previous research on global supply chain management (GSCM) principles that can adapt and survive adversity, such as the COVID-19 pandemic. The second purpose is to put forth a conceptual framework for the GSCM that is sustainable in the event of future turbulence similar to that experienced during the COVID-19 pandemic. With regard to the issues raised, the article posits the following questions. Is there, perhaps, a sustainable post-COVID-19 pandemic GSCM? Can the COVID-19 pandemic-related international logistics system (GSC) turbulences be predicted with certainty using these sustainable post-COVID-19 pandemic GSCM concepts? Putting it all together, the paper concludes that, while debatable, sustainable GSCM is feasible and can be accomplished utilizing JIT, supply chain mitigation, and supply chain visibility, as demonstrated by the manufacturing firms referenced in the article.

The degree of collaboration among supply chain partners and the structure of the network are important determinants of the level of satisfaction customers derive from the products or services. However, the effects of these dimensions on customer satisfaction at the downstream section of the supply chain remain under-researched in Nigeria. This study precisely examined the effects of collaboration and supply chain design on customers’ satisfaction at the downstream end of the chain using Ekiti State as study area. The study employed descriptive survey design with the use of structured Likert scale questionnaire administered to 381 retailers of noodles in Ekiti State. The research hypotheses were analysed using simple linear regression as statistical technique with the aid of SPSS version 22.0. At the end of the study, it was observed that both collaboration and supply chain design were significant predictors of customers’ satisfaction of instant noodles in Ekiti State. However, collaboration among supply chain partners emerged as stronger determinant of customers’ satisfaction than supply chain design. The study concludes that these two practices of supply chain management are highly important criteria any manufacturing firm especially in the noodles industry must pay close attention to in order to satisfy her consumers.

Vascular anomalies are a diverse group of abnormal blood vessel developments that can occur at birth or shortly afterward. Embolization and sclerotherapy have been utilized as a treatment option for these malformations but may cause moderate to severe pain. This study aims to evaluate the utilization of peripheral nerve blocks in opioid consumption, pain scores, and length of stay. A retrospective chart review was conducted at the UPMC Children's Hospital of Pittsburgh for all patients who underwent embolization and sclerotherapy between 2011 and 2020. Patient data was collected to compare opioid consumption, pain scores, and length of stay. Eight hundred fifty-four procedures were performed on 347 patients. The morphine milligram equivalent per kilogram mean ratio between groups was 0.9 (0.86, 0.95) with a p-value of &lt;0.001. The pain score mean ratio was –1.17 (–2.2, -0.1) and a p-value of 0.027. Length of stay had a mean ratio of 0.94 (0.4, 2) and a p-value of 0.875. By decreasing opioid consumption and postoperative pain scores, peripheral nerve blocks may have utility in patients undergoing embolization and sclerotherapy while not clinically increasing the length of stay for patients. Their use should be individualized and carefully discussed with the interventional radiologist.

Coarse-grained molecular dynamics simulations are employed to investigate spatiotemporal evolution of vesicles (polymersomes) via self-assembly of randomly distributed amphiphilic diblock copolymers in water. Vesiculation pathway consists of several intermediate structures such as spherical/rodlike aggregates, wormlike micelles, lamellae, and cavities. Lamella to vesicle transition occurs at a constant aggregation number and is accompanied by a reduction in the solvent accessible surface area. Simulation predictions are in qualitative agreement with the mechanism of vesicle formation in which the unfavorable hydrophobic interactions between water molecules and polymer segments along the edge of the lamella are eliminated at the expense of gaining curvature energy. However, rod-lamella-vesicle transition is accompanied by an increase in copolymer packing density. Hence, the change in the surface area accompanying vesiculation predicted by the simulations is significantly lower than theoretical estimates. Changes in information entropy, quantified by the expectation of the logarithm of the probability distribution function of the segmental stretch parameter s, defined as the difference between the maximum and instantaneous segmental extension, are statistically insignificant along the vesiculation pathway. For rods, lamellae and polymersomes, s follows a log normal distribution. This is explained based on the configurational dynamics of a single diblock chain in water.

In neonatal equines, pathologies involving umbilical structures are an important cause of morbidity, and surgical removal of urachal remnants is a common procedure in clinical practice. Surgery involving the ventral abdominal wall can cause substantial pain, leading to complications and prolonged recovery. The objectives of this study were to describe a two-point bilateral ultrasound-guided rectus sheath block at the level of the umbilicus and to evaluate the extent of dye distribution in foal cadavers. Ten foal cadavers were included in the study, in which a bilateral two-point ultrasound-guided rectus sheath block was performed—one injection cranially and a second one caudally to the umbilicus. The injectate consisted of a mixture of iodinated contrast medium and blue dye at a volume of 0.25 mL kg-1 per injection point (total 1 mL kg-1). After the injection, computer tomography and subsequent dissection of the ventral abdominal wall were performed. The extension of the contrast medium, the number of stained nerves, and contamination of the abdominal cavity were evaluated. The cranio-caudal extension of the contrast ranged from 0.8 to 1.4 centimeters per milliliter of injectate. The most commonly stained ventral branches of spinal nerves were thoracic (Th) nerves 16, 17, and 18 (95%, 85%, and 80% of the nerves, respectively). Abdominal contamination was found in 4 animals. The results suggest that the block could provide periumbilical analgesia. Further studies with different volumes of injectate and living animals are warranted.

Due to the numerous heat sources in electronic equipment, the periodic nature of stream-wise flow occurs in a cooling channel so often, necessitating the development of an effective technique to improve the heat-cooling convection in such a situation. This paper investigates thermal convection enhancement in a heated-block duct through the periodic boundary conditions using the element-by-element (EBE) treatment in a semi-implicit projection finite element method (FEM) through preconditioned conjugate gradient (PCG) solver. This paper used the time-mean Nusselt number ratio, friction factor, and thermal performance to study how installing rectangular cylinders in the channel works with periodic boundary conditions varying Reynolds numbers (100, 175, and 250). The outcomes show that the rectangular cylinders installed stream-wise above an upstream block promote thermal convection in the heated-block duct. However, increasing the number of rectangular cylinders can raise friction factor. As a result, the case for periodic boundary conditions with a rectangular cylinder above every two blocks has the best thermal performance.

Given a square matrix $A$, we are able to construct numerous equalities that involve reasonable mixed operations of $A$ and its conjugate transpose $A^{\ast}$, Moore--Penrose inverse $A^{\dag}$, and group inverse $A^{\#}$. Such kind of equalities can be generally represented in the equation form $f(A, \, A^{\ast}, A^{\dag}, A^{\#}) =0$. In this article, the author constructs a series of simple or complicated matrix equalities, as well as matrix rank equalities involving the mixed operations of the four matrices. As applications, we give a sequence of necessary and sufficient conditions for a square matrix to be range-Hermitian.

It is a classic topic in algebras to construct and verify equalities that are composed of various algebraic operations of elements and their inverses or generalized inverses. In this note, the author constructs a matrix equality $(AB)^{\dag} = B^{\ast}(A^{\ast}ABB^{\ast})^{\#}A^{\ast}$ (called a mixed reverse-order law), where $A$ and $B$ are two matrices of appropriate sizes, $(\cdot)^{\ast}$, $(\cdot)^{\dag}$, and $(\cdot)^{\#}$ denote the conjugate transpose, the Moore--Penrose inverse, and the group inverse of a matrix, respectively, and shows that the mixed reverse-order law always holds. A list of variation forms of this matrix equality are also given, and necessary and sufficient conditions are obtained for them to hold. Especially, we show a remarkable fact that the two reverse-order laws $(AB)^{\dag} = B^{\dag}A^{\dag}$ and $(A^{\ast}ABB^{\ast})^{\#} = (BB^{\ast})^{\#}(A^{\ast}A)^{\#}$ are equivalent.

One of matrix equalities composed of multiple products of matrices and their generalized inverses is given by $A_1B_1^{-}A_2B_2^{-} \cdots A_kB_k^{-}A_{k+1}= A$ where $A_1$, $B_1$, $A_2$, $B_2$, $\ldots$, $A_k$, $B_k$, $A_{k+1}$, and $A$ are given matrices of appropriate sizes, and $B_1^{-}$, $B_2^{-}$, $\cdots$, $B_k^{-}$ are generalized inverses of matrices. The cases for $k = 1, 2$ and their special forms were properly approached in the theory of generalized inverses of matrices. In this note, the author presents an algebraic procedure to derive explicit necessary and sufficient conditions for the equality with $k = 3$ to always hold using certain rank equalities for the block matrices constructed by the given matrices, and then mention a key step of extending the previous work to a general situation.

This qualitative research investigates how supply chain innovations drive marketing differentiation in consumer goods companies. In a competitive global marketplace, firms are increasingly leveraging advanced supply chain management (SCM) practices to enhance operational efficiency and create distinctive market positions. The study explores five key supply chain innovations—digitalization, sustainability practices, predictive analytics, agile supply chain models, and collaborative partnerships—and their impact on marketing differentiation strategies. Data were collected through semi-structured interviews with 20 executives and managers from leading consumer goods companies, analyzing themes related to innovation adoption, challenges, and outcomes. Findings indicate that digital technologies such as IoT, AI, and blockchain are pivotal in improving supply chain visibility, optimizing inventory management, and enabling real-time decision-making, thereby supporting personalized customer experiences and agile responses to market dynamics. Sustainability practices, including sustainable sourcing and green logistics, emerge as critical drivers of brand reputation and consumer trust, aligning with growing consumer preferences for eco-friendly products. Predictive analytics facilitate better demand forecasting and pricing strategies, while agile supply chain models enhance flexibility and responsiveness in delivering products faster to market. Despite benefits, challenges include integrating innovations with legacy systems, managing resistance to change, and addressing data security concerns. Strategies for overcoming these barriers include leadership commitment, cross-functional collaboration, talent development, and strategic partnerships. By embracing these strategies and innovations, consumer goods companies can strengthen their competitive positioning, enhance customer satisfaction, and achieve sustainable growth in a rapidly evolving marketplace.

This qualitative research study delves into the intricate dynamics of how organizations adapt to supply chain disruptions during crises, offering profound insights into the strategies, practices, and challenges encountered in enhancing supply chain agility. Through in-depth interviews with supply chain managers across diverse industries, key themes such as proactive risk management, technological integration, collaboration with supply chain partners, and adaptive leadership have emerged as crucial determinants of agility and resilience. Additionally, the study highlights the significance of organizational culture, effective communication, and external factors such as regulatory requirements and market dynamics in shaping supply chain agility. By embracing a holistic approach that integrates these multifaceted factors, organizations can bolster their capacity to anticipate, detect, and respond to disruptions, thereby maintaining or enhancing overall performance even in the face of uncertainty and complexity. The insights gleaned from this research are poised to inform theory development, guide managerial practice, and influence policy-making in the realm of supply chain management, equipping organizations with the knowledge and tools needed to navigate future disruptions successfully.

The current trend in supply chain development requires the application of new knowledge to meet the challenges posed by new technologies. One such technology is blockchain, which facilitates supply chain solutions through the use of innovative data transfer, storage and verification systems. However, the use of blockchain can be challenging for certain stakeholders, such as small carriers, who may lack the necessary technical expertise or access to the technology. In this paper, we explore the potential for engaging small carriers that provide services within the blockchain supply chain but face technological barriers. We identify the barriers and opportunities for these carriers to participate, focusing on a case study of a small carrier that transports temperature-sensitive cargo. In addition, we introduce in-vehicle temperature measurement for use in cold chains and propose an ecosystem that can benefit different stakeholder groups.

Sustainable supply chain management (SSCM) represents a critical strategy for the electronics industry to balance economic objectives with environmental and social responsibility across complex global production networks. This multiple case study analysis investigates SSCM integration within leading Korean electronics manufacturers Samsung, LG, and Hyundai. In-depth qualitative data, focus groups, and sustainability report analysis reveals the policies, practices, results and implementation barriers related to incorporating sustainability criteria across procurement, manufacturing, distribution and recycling functions. Findings show sustainability considerations increasingly driven by cost, risk, reputational and regulatory factors, with vertical coordination initiatives helping transfer knowledge to assist suppliers on compliance and emissions reductions. Yet substantial obstacles persist around monitoring, coordination, transparency and technical capabilities, especially amongst lower tiers. The paper discusses how common reporting standards, ethical sourcing certification and partnerships can accelerate electronics supply chain sustainability. By mapping integration achievements and gaps, this study informs managerial best practices and policy reforms toward promoting socially and ecologically responsible models for Korea's vital export industry as it navigates rising stakeholder pressures.

The manuscript delves into the intricacies of food production chains, offering a comprehensive breakdown of their components. Moreover, it sheds light on the initiatives orchestrated by government agencies to endorse sustainable practices and fortify areas of opportunity for producer organizations. While the context paints a broad picture, we contend that, to the best of our knowledge, there exists no comparable publication that succinctly encapsulates the role of government in bolstering food production chains. The document unfolds with a detailed exploration of the interaction mechanisms among the various components of the chain. Subsequently, it introduces a set of twelve elements meticulously outlining the multifaceted role of the government. Each element undergoes thorough scrutiny, fostering a nuanced understanding of the intricate relationship between the food production chain and the government's pivotal role in enhancing stability and efficiency. In conclusion, the manuscript not only lays bare the structural elements of food production chains but also presents a unique and in-depth analysis of the government's role, encapsulated within the framework of twelve essential elements.

Deciding when to replace dairy bulls presents a complex challenge for artificial insemination (AI) companies. These decisions encompass multiple factors, including a bull's age, predicted semen production, and estimated genetic merit. This study's purpose was to provide a practical, objective tool to assist in these decisions. We utilized a Markov Chain model to calculate the economic valuation of dairy bulls, incorporating key factors such as housing costs, collection and marketing expenses, and the bull's probable tenure in the herd. Data from a leading AI company were used to establish baseline values. The model further compared a bull's net present value to that of a potential young replacement, establishing a relative valuation (BullVal$). The range of BullVal$ observed spanned from -$316,748 to $497,710. Interestingly, the model recommended culling for 49% of the bulls based on negative BullVal$. It was found that a bull's net present value was primarily influenced by market allocation and pricing, coupled with the interaction of semen production and genetic merit. This study offers a robust, data-driven model to guide bull replacement decisions in AI companies. Key determinants of a bull's valuation included market dynamics, semen production rates, and genetic merit.

Recently dairying becomes an important farming activity in the districts. Even if these districts are potential in milk production and marketing activities, little was known about determinates of participation and level of participation in milk value addition. This study was analyzing determinates of participation and level of participation in milk value addition in the study areas. Both primary and secondary data were used. Primary data were collected from 244 producers, 50 traders and 20 consumers by using semi-structured questionnaires. Data were analyzed by using descriptive statistics and econometrics model. Results from Heckman selection model first step revealed that milk producers’ participation decision on milk value addition was significantly affected by religion, distance the market, cooperative membership, volume of milk produced per day and market access. Whereas milk producers’ participation decision on the volume of milk value addition was significantly affected by religion, level of education, number of children less than six years, membership for milk cooperatives, volume of milk produced per day, access to market information, access to credit and access to livestock extension. Therefore, dairy sector development programs should take in to account determinants of participation decision on milk value addition as well as on volume of milk production.

Insulin-degrading enzyme (IDE) is a highly conserved metalloprotease mainly localized in the cytosol. Although IDE can degrade insulin and some other low molecular weight substrates efficiently, its ubiquitous expression suggests additional functions supported by experimental findings, such as a role in stress responses, cellular protein homeostasis. Translation of full-length (Met1) IDE transcripts has reported to result in targeting to mitochondria but the role of IDE in this compartment is unknown. To obtain initial leads on the function of IDE in mitochondria, here we used a proximity biotinylation approach to identify proteins interacting with wild-type and protease-dead IDE targeted to the mitochondrial matrix. We find that mitochondrial IDE interacts strongly with mitochondrial ribosomes as well as with proteins of the respiratory chain. The mitochondrial interactomes of wild type and mutant IDE are highly similar and do not reveal any proteolytic IDE substrates. We speculate that IDE could adopt similar functions in mitochondria as in the cytosol, acting as a chaperone and contributing to protein homeostasis and stress responses.

Life Cycle Assessment (LCA) is a widely recognized tool used to evaluate environmental impacts of a product or process, based on the environmental inventory database and bills of material. Data quality is one of the most significant factors affecting the analysis results. However, currently most datasets in inventory databases are generic i.e., they may represent material and energy flow of a process at market average, instead of a specific process used by a manufacturer. As a result, stockholders are unable to track their supply chain to find out the actual environmental impact from each supplier and to compare the environmental performance of alternative options. In this paper, we developed a new framework i.e., blockchain based LCA (BC-LCA), where block-chain technology is adapted to secure and transmit inventory data from upstream suppliers to downstream manufacturers. With BC-LCA, more specific data can be acquired along the supply chain in a real-time manner. Moreover, the availability, accuracy, privacy, and automatic update of inventory data can be improved. A case study is provided based on an industrial supply chain, to demonstrate the utilization of BC-LCA.

Kenyan coffee is ranked among the best in the world and 99% is exported mainly to Germany, Sweden and Belgium, the USA and Saudi Arabia. Kenya produces quality Arabica beans which are generally recognized and upgraded with other relatively lower brands. In 1937, the Kenya Planters Cooperative Union (KPCU) was formed to represent small farmers' interests. In 1944, in the Coffee Board of Kenya (CBA) the law required smallholders to join local growing cooperatives run by government to reduce the power of large estates to control the board. Many reforms in the coffee industry have been initiated. This review explores evolution and existing coffee varieties in Kenya, the coffee value chain and the regions that grow coffee in Kenya. Additionally, the variety agronomics and appearance that encompass; quality potential at different altitudes, yield potential and nematodes susceptibility.

Risk modelling along with multi-objective optimization problems have been at theepicenter of attention for supply chain managers. In this paper, we introduce a datasetfor risk modelling in sophisticated supply chain networks based on formal mathematical models. We have discussed the methodology and simulation tools used to synthesize the dataset. Additionally, the underlying mathematical models are discussed in granular details along with providing directions to conducting statistical analyses or neural machine learning models. The simulation is performed using MATLAB ™Simulink and the models are illustrated as well.

This article makes a general analysis of the supply chain of photovoltaic systems in Colombia, taking as a starting point a conceptual base and the current situation of the country in this sector. This article especially will contemplate the non-interconnected areas (ZNI) to the electricity grid in the national, due to its complexity in the logistics issues. Likewise, the work performs a graphical representation of the stages and processes of the supply chain using a powerful-modeled tool such as the Petri Nets (PNs). Finally, it identifies some of the flaws in the operation and the joint of all the links of the logistic part and from there it is based the importance of the strategy of orientation to the supply chain (SCO) as a possible alternative to improve and to enhance the logistic processes of this type of systems.

Making cities health-promoting places is an evolving theme. Numerous research confirm the health-promoting qualities of contact with nature and problems resulting from the deprivation of access to public green spaces. Easy access to safe and inclusive open public green spaces is still one of the long-lasting problems of urbanized areas around the globe. It is one of the sustainable development goals - SDGs proposed by the UN, 11. Make cities and human settlements inclusive, safe, resilient and sustainable. Point 11.7 By 2030, provide universal access to safe, inclusive and accessible, green and public spaces, in particular for women and children, older persons and persons with disabilities. The major question is how to implement this goal in practice and design cities to provide easy access to safe and inclusive open public green spaces. One of the important concepts for sustainable urban development is the urban block - Macrolot coined by Christian de Portzamparc, which led to the new urban morphology of eco-neighborhoods in France. It is a combination of the traditional, walkable urban grid with the Le Corbusier vision for a healthy modernist city offering daylight, fresh air, and greenery for everyone. Among the advantages of this particular urban morphology are the increased presence of green spaces which form public parks, and possibilities for placemaking. Studying the effects of the urban form of the Macrolot is of great significance for sustainable urban development. In this study, five neighborhoods: three eco-neighborhoods from France designed according to the open urban block – Macrolot urban morphology – ZAC Massena, ZAC Trapeze, and ZAC Clichy-Batignolles and two award-winning developments from Po-land – Riverview and Ostoja Wilanów were chosen as case studies. The application of the Macrolot concept to sustainable urban planning & design and possibilities for operationalization of the SDGs: 11. Make cities and human settlements inclusive, safe, resilient and sustainable are discussed. This study offers valuable evidence to inform urban planning and design.

A series of polyacrylonitrile (PAN)-based block copolymers with poly(methyl methacrylate) (PMMA) as sacrificial bock were synthesized by atom transfer radical polymerization and used as precursors for the synthesis of porous carbons. The carbons enriched with O- and S-containing groups, introduced by controlled oxidation and sulphuration, respectively, were characterized by Raman spectroscopy, scanning electron microscopy, and X-ray photoelectron spectrometry, and their surface textural properties were measured by a volumetric analyzer. We observed that the presence of sulphur tends to modify the structure of the carbons, from microporous to mesoporous, while the use of copolymers with a range of molar composition PAN/PMMA between 10/90 to 47/53 allows the obtainment of carbons with different degrees of porosity. The amount of sacrificial block only affects the morphology of carbons stabilized in oxygen, inducing their nanostructuration, but has not effect on their chemical composition. We also demonstrated their suitability for separating a typical N2/CO2 post-combustion stream.

Small submersible drainage pumps discharge leaking water and rainwater in buildings. In an emergency (e.g., heavy rain or accident), monitoring the flow rate in advance is necessary to enable optimal operation, considering the point where the pump operates abnormally when the water level increases rapidly. In another, pump performance optimization is crucial for energy saving policy. Therefore, it is necessary to meet the challenges of submersible pump systems, including sustainability and pump efficiency. The final goal of this study is to develop an energy-saving, high-efficiency submersible drainage pump capable of responding to emergencies. In particular, this paper targeted the hydraulic performance improvement of a submersible drainage pump model. Before the development of driving mode-related technology capable of emergency response, we first tried to find a way to improve the performance characteristics of the existing submersible drainage pump. Rather than designing a new pump, we disassembled the current pump and reverse engineering. Then, numerical simulation was performed to analyze the flow characteristics and efficiency of the pump. Then, the pump test was carried out to obtain the performance and validated with numerical results. Results revealed that changing the cross-sectional shape of the impeller reduced the flow separation and enhanced velocity and pressure distributions. Also, it reduced the power and increased efficiency. Results also showed that the pump's efficiency increased to 5.56% at a discharge rate of 0.17 m3/min, and overall average efficiency increased to 6.53%. In addition, the submersible pump design method could be suitable for the optimized pump's impeller and casing numerically. This paper can provide insight and information on the design optimization of pumps.

This study examines the balancing between urban transportation security and supply chain efficiency amid global disruptions like the COVID-19 pandemic, attacks on maritime lanes, and geopolitical conflicts. The authors combine bibliometric network analysis and natural language processing (NLP) to review scholarly literature from 2017 to 2023. This approach identifies and visualizes evolving thematic trends. Findings reveal a shift towards integrating advanced technologies such as blockchain, AI, and IoT to enhance security without compromising efficiency. This study highlights the significance of integrating urban planning principles and sustainable practices to enhance transportation security and supply chain efficiency within urban environments. Actionable insights for policymakers and supply chain managers emphasize the adoption of integrated, technology-driven security solutions to foster resilient and sustainable supply chains. This research contributes to academic discourse by refining the understanding of evolving priorities in transportation security and supply chain management, offering both theoretical and practical implications for secure and efficient global supply chains.

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.

A new type of artificial block is proposed by modifying the traditional block. Based on the physical model experiment, the wave reflection and run-up characteristics of the new ecological blocks under regular waves were examined, and the influence of the height of the "planting trough" border on the hydrodynamic properties was analyzed. The results indicate that the wave reflection and run-up would decrease with a decrease in the breakwater slope. As wave height increases, wave run-up increases, and the reflection coefficient falls. Wave reflection and run-up increase with an increasing wave period. The relative depth of the water has a smaller impact on the wave reflection than the wave run-up. The reflection coefficient of the new ecological blocks is consistently lower than that of the conventional and continues to decrease as the border of the "planting trough" is raised. The raised borders prevent water loss in the trough, resulting in no significant improvement in the wave run-up performance of the new blocks. The reflection coefficient and the relative run-up R/H gradually increase with the average wave breaking parameter ξ increase. The crude permeability coefficients for the new blocks, New Heights 1 and New Heights 2, are 0.53, 0.53, and 0.54, respectively.

We present a new penalized method for estimation in sparse logistic regression models with group structure. Group sparsity suggests us to consider the Group Lasso penalty. Being different from penalized log-likelihood estimation, our method can be viewed as a penalized weighted score function method. Under some mild conditions, we provide non-asymptotic oracle inequalities promoting group sparsity of predictors. A modified block coordinate descent algorithm based on a weighted score function is also employed. The net advantage of our algorithm over the existing Group Lasso-type procedures is that the tuning parameter can be pre-specified. The simulations show that this algorithm is considerably faster and more stable than competing methods. Finally, we illustrate our methodology with two real data sets.

In this paper, we consider the fourth-order parabolic equations with integer and fractional order time derivatives with Neumann boundary conditions. The integer order time derivatives are approximated by backward Euler difference quotients, and the fractional order time derivatives are approximated by L1 interpolation. We propose the block-centered finite difference scheme for fourth-order parabolic equations of integer and fractional order time derivatives. We prove the stability of the block-centered finite difference scheme and the second-order convergence of the discrete L2 norms of the approximate solution and its derivatives of every order. Numerical examples are given to verify the effectiveness of the block-centered finite difference scheme.

A block-diagonal fuzzy neural network for short-term load forecasting is proposed. DBD-FELF consists of fuzzy rules with consequent parts that are neural networks with internal recurrence. These networks have a hidden layer which consists of pairs of neurons with feedback connections between them. The overall fuzzy model partitions the input space in partially overlapping fuzzy regions, where the recurrent neural networks of the respective rules operate. The partition of the input space and determination of the fuzzy rule base is performed by use of Fuzzy C-Means clustering algorithm and the RENNCOM constrained optimization method is applied for consequent parameter tuning. The electric load time-series of the Greek power system is examined, and hourly-based forecasting for the whole year is performed. The performance of DBD-FELF is tested via extensive experimental analysis and the results are promising, since an average percentage error of 1.18% is attained, along with an average yearly absolute error of 76.2 MW. Moreover, DBD-FELF is compared with Deep Learning, fuzzy and neurofuzzy rivals, such that its particular attributes are highlighted.

Background: New regional techniques can improve pain management after nephrectomy. Methods: This study was a randomized controlled trial conducted at two teaching hospitals. Patients undergoing elective open and laparoscopic nephrectomy were eligible to participate in the trial. A total of 100 patients were divided into a quadratus lumborum block (QLB) group and a control (CON) group. At the end of surgery, but while still under general anesthesia, unilateral QLB with ropivacaine was performed on the side of nephrectomy for patients in the QLB group. The main measured outcome of this study was oxycodone consumption via a patient-controlled anesthesia (PCA) pump during the first 24 hours following surgery; other measured outcomes included postoperative pain intensity assessment, patient satisfaction with pain management, and persistent pain evaluation. Results: Patients undergoing QLB needed less oxycodone than those in the CON group (34.5 mg [interquartile range 23–40 mg] vs. 47.5 mg [35–50 mg]; p<0.001). No difference between the groups was seen in postoperative pain intensity measured on the visual analog scale, except for the evaluation at hour 2, which was in favor of the QLB group (p=0.03). Patients who received QLB were more satisfied with postoperative pain management than the CON group. Persistent postoperative pain was assessed with the Neuropathic Pain Symptom Inventory (NPSI) at months 1, 3, and 6 and was found to be significantly lower in the QLB group at each evaluation (p<0.001). We also analyzed the impact of the surgery type on persistent pain severity, which was significantly lower after laparoscopic procedures than open procedures at months 1, 3, and 6. Conclusions: QLB reduces oxycodone consumption in patients undergoing open and laparoscopic nephrectomy and decreases persistent pain severity months after hospital discharge.

This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which provides powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Despite advancements, Italy’s 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability.

In this paper, we study semiconic idempotent commutative residuated lattices. After giving some properties of such residuated lattices, we obtain a structure theorem for semiconic idempotent com- mutative residuated lattices. As an application, we make use of the structure theorem to prove that the variety of strongly semiconic idempotent commutative residuated lattices has the amalgamation property.

Acid stress poses a common challenge for bacteria in diverse environments by the presence of inorganic (e.g., mammals’ stomach) or organic acids (e.g., feed additives; acid-based disinfectants). Limited knowledge exists regarding acid-tolerant strains of specific serotypes, clonal lineages, or sources in human/animal pathogens, namely non-typhoidal Salmonella enterica (NTS) and Enterococcus faecium (Efm). This study evaluated acidic pH and peracetic acid (PAA) susceptibility of Efm (n=72) and NTS (n=60) from diverse epidemiological/genetic backgrounds, and with multiple antibiotic resistance profiles. Efm minimum growth/survival-pH was 4,5-5/3-4 and for NTS 4,0-4,5/3,5-4,0. Among Efm, only those of clade-non-A1 (non-hospital associated) or food chain demonstrated greater tolerance to acidic pH compared to clade-A1 (hospital-associated clones) or clinical isolates (P<0.05). MDR (multidrug-resistant) NTS survived better to acidic pH (P<0.05). The MICPAA/MBCPAA was 70-120/80-150mg/L for Efm and 50-70/60-100mg/L for NTS. Efm-clade-A1 or MDR strains exhibited higher PAA tolerance than clade-non-A1 or non-MDR ones (P<0.05). Higher tolerance was found in non-MDR and clinical NTS than in food chain isolates (P<0.05), but not between different serogroups. This unique study identifies specific NTS or Efm populations more tolerant to acidic pH or PAA, emphasizing the need for further research to tailor control measures of public health and food safety within a One Health framework.

This paper explores the ethical imperative of rehoming all healthy animals of sentient species after experiments have finished or when they have become otherwise redundant. We take into account disparate perspectives in animal ethics and see how they point in the same direction. We illustrate our case with our own rehoming experience from the joint Animal Welfare Body of Utrecht University and the University Medical Centre Utrecht, the Netherlands. The primary pilot proved successful, after which the principle of rehoming became standing policy and common practice. We discuss several challenges and our responses to those through continuous evaluation of the adoption program.

An integration between the principles in supply change management in sport tourism and sustainability balanced scorecard leads to development of guidance and assessment criteria for a city to be a sustainable sport tourist destination. This paper aims to present a sport tourism sustainability management model (STSM), consisting of 5 perspectives, namely financial perspective, customer perspective, internal process perspective, learning and growth perspective and sustainability perspective. By using Delphi technique to obtain a consensus from experts, university lecturers, independent organization/association and business entities in relation to sport tourism management, the researcher defines elements to assess complex perspective for sustainable development of sport tourism. The result shows that there are 5 perspectives and 18 elements in relation to sustainable development of sport tourism. All perspectives and elements have high consensus as measured by Kendall’s Coefficient of Concordance (W) of .488. To validate the model, the researcher examines correlation among the five perspectives with structural equation model and finds that the absolute fit is satisfactory, with the value of CMIN/DF at 1.830, RMSEA at .046, GFI at .951, AGFI at .919 and RMR at .038. In addition, the incremental fit also demonstrates positive result with the value of NFI at .962, CFI at .982, TLI at .973 and IFI at .982. As the model aligns and explains empirical data, it can support decision making for management team, effective and efficient strategy drafting for sustainable development in sport tourism and improving livelihoods of residents.

In recent years, Blockchain has been favorably adopted in the Supply Chain industry as it provides guaranteed transparency and traceability. The flexibility of Blockchain allows different applications to enable to exchange information; a significant middleweight layer is responsible for information transfer in the Agricultural Sector. The products that are manufactured at a global level in the agriculture industry are improved in safety, validation of some criteria, and quality. In the agriculture industry, the increasing number of complications associated with food safety and impurity risks needs high-level effective traceability solutions that act as necessary quality management tools to make sure satisfactory safety of crops. The agricultural supply chain today has complex ecosystems, consisting of several stockholders to authenticate criteria which are important like crop development stages, monitoring and validation, and compliance with the quality standard. In this proposed research, a systematic literature review will be done that includes smart contracts, Blockchain, and business transactions exclusively for crop production traceability across the agricultural and food supply chain. By using Blockchain in the agriculture sector, productivity, consistency, safety, reliability, and advanced security are increased. All transactions are kept and recorded on the immutable record of Blockchain associates with a decentralized system. Thus, it provides more traceability and clarity in the agriculture system in asafe, trustworthy, and effective way. A systematic literature review is thus enforced to classify the papers which are selected by the following classification: crop traceability, contribution type, research type, and their approach. For this systematic review, the papers which extracted are classified according to defined criteria. The purpose of this study is to fill the gap by collecting and analyzing studies available within the literature aiming to firstly, gain complete insight on the integration of Blockchain in the agriculture sector. Secondly, provide a summary of the present state of research on this area and identify gaps in existing studies. To achieve this aim an SLR was conducted. The findings of this SLR are discussed and researchers were provided with suggestions on possible directions for future research.