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Solid waste management is a major concern for the Kingdom of Saudi Arabia. The rapid urban development and the accelerating population growth have made solid waste management a sincere challenge. Globally, recycling has proved to be efficient in managing solid waste. Recycling reduces the amount of waste dumped in landfills, offers a cheap source of raw materials, and aids in sustaining the environment. Household recycling is sadly not widely adopted in Saudi Arabia Eastern Province. The participation rate of the public in the Eastern Province in recycling activities is still limited. This research aims to investigate the barriers to household recycling and to provide insights into the potential causes of low local population engagement in local recycling programs. A survey was used to collect raw data. The barriers were rated, and the overall score for each barrier was assessed using the relative importance index (RII). The results show that the two most crucial household recycling barriers are the lack of official recycling programs (84.5% RII) and insufficient recycling bins (84.1% RII). An ISM model of the barriers is also developed to explore the interrelationships among barriers at a deeper level. The ISM model suggests that, in addition to the above two barriers, the lack of convenient infrastructure, inefficient curbside collection, and lack of incentives/penalties are the additional barriers driving the public away from recycling. This work should present a road map for the local authorities to initiate vital recycling initiatives capable of attracting public attention to the importance of recycling. [ABSTRACT FROM AUTHOR]

The seasonal prediction of the Indian summer monsoon (ISM) and Monsoon Intraseasonal Oscillations (MISO), as well as the Madden Julian Oscillations (MJO) that strongly modulate MISO, is important to the country for water and crop management. We have analyzed the precipitation, convection, and cloud in the selected models from the sixth generation Coupled Model Intercomparison Projects (CMIP6). This study highlights the significant differences in simulating MISO and MJO features between the selected CMIP6 models and their possible reasons. The mean and intraseasonal features of MISO and MJO varied significantly in CMIP6 models, which may impact better depiction of convection and total cloud fraction. The probability distributions of rainfall and OLR in CMIP6 models also indicate significant variations in simulating the MISO and mean ISM. The results demonstrate the importance of cloud and convection in CMIP6 models to depict realistic MISO and MJO and provide a road map for improving ISM climate prediction and projections. [ABSTRACT FROM AUTHOR]

This document is an editorial introduction to the second part of a special issue of the journal Queueing Systems. The special issue focuses on product forms, stochastic matching, and redundancy models in the analysis of queueing systems. The papers in this collection explore various aspects of matching queues and redundancy systems, including fluid approximation, heavy traffic limits, and different scheduling policies. The goal of the special issue is to highlight the connections between these models and their product-form stationary distributions, and to inspire new directions for future research. [Extracted from the article]

Recently, driven by redundancy systems and matching systems, there has been renewed interest in models with product form stationary distributions. By a "product form," we mean that the stationary distribution can be expressed as a product of terms, each of which corresponds to a job in the system. Given the recent discovery of many such systems, it is natural to ask: how broad is this class of systems? In this paper, we consider extensions and generalizations of the recently-proposed pass-and-swap queue, which has a product-form stationary distribution. We make three main contributions. First, we identify sufficient conditions under which pass-and-swap queues can be connected in a closed network, while still preserving the product form. Second, we identify dimensions along which the pass-and-swap system can be extended while preserving the product-form stationary distribution. At the same time, we also identify cases in which generalizing the pass-and-swap queue causes the product-form nature of the stationary distribution to break. Finally, we identify questions that remain open and present a road map for future study. [ABSTRACT FROM AUTHOR]

Responsible Business Model Innovation is increasingly becoming a relevant challenge in academic research and business practice, mainly in the Asian context. Changes in business models are widely acknowledged as a key strategy for achieving long-term innovation. However, little is known about the design journey of Responsible Business Model Innovation. By applying the knowledge-based view and stakeholder theory, this paper introduces the founding pillars of Responsible Business Model Innovation, namely: Corporate Social Responsiveness, Inclusiveness, and Reflective Knowledge Exchange. Based on the analysis of extended bodies of literature published between 2011 and 2021 on business model innovation, sustainability innovation, stakeholder theory and responsible innovation, the article explores the state of the art of business ethics and dynamic capabilities in Asian organizations. Findings show that recent research in the field of sustainability and ethical values are improving the impact on business models, thus encouraging the advent of Responsible Business Model Innovation. This article contributes to the emerging field of responsible innovation and offers novel theoretical and practical implications for academy and practitioners, including a first attempt to develop a road map to be followed to achieve of sustainable and ethical values for business and society at large. [ABSTRACT FROM AUTHOR]

Purpose: This work presents an environmental assessment of two adhesives to evaluate the replacement of the traditional adhesive (PU) used in the footwear industry by a novel adhesive based on a microencapsulation approach (PUMC) which is more favorable from the safety and technical perspectives. The PU adhesive is polyurethane-based, while the PUMC adhesive is polyurethane-based but with its isocyanate compounds microencapsulated, increasing storage life and reducing risks related to the exposure of workers with the adhesives. Methods: The potential environmental impact of the adhesives was evaluated using the life cycle assessment (LCA) methodology. A detailed process model was developed (both for laboratory and for a pilot-scale implementation) to investigate the environmental impacts associated with these processes. The functional unit was one kilogram of adhesive (PU and PUMC adhesives) produced. A cradle-to-customers' gate approach was defined. The system boundary starts from extraction of resources, through material production, until adhesive use. This includes microcapsule production in the case of the PUMC adhesive. This study investigates the important drivers behind the environmental impacts to help guide commercialization efforts. A scenarios study/sensitivity analysis was conducted to determine the response of the PUMC adhesive system to the variability of the model, scenarios, and parameters. Results: The results show that the PU adhesive environmental impact is due to acetone and polyol consumption in the production stage. In the PUMC adhesive system, acetone consumption and microcapsule production are the major factors responsible for the environmental impact. Polybutylene adipate terephthalate (PBAT), dichloromethane (DCM), and isophorone diisocyanate (IPDI) consumption are the major factors responsible for the environmental impact of the microcapsules' production. A sensitivity analysis was conducted using three alternative scenarios focused on the reduction in material consumption and increase in material recuperation, as well as using an alternative renewable energy source. Although the traditional PU adhesive has a lower impact, it was found that the three alternative PUMC adhesive systems can become comparable to the traditional PU adhesive. Conclusions: This study shows the advance and development of a new technology for microencapsulation of isocyanate in adhesives and its environmental advantages and disadvantages with respect to a traditional product that uses non-encapsulated isocyanate. Finally, it was shown that there is significant potential for minimizing some environmental impacts of the PUMC adhesive, such as optimizing the microcapsules' production stage, increasing the production efficiency to decrease the required material consumption. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic served as a reminder of the limited treatments available for acute respiratory distress syndrome (ARDS). The pandemic has highlighted the need to identify different clinical phenotypes of ARDS and investigate various interventions and treatments, both new and old. Case Presentation: We present a patient with severe ARDS secondary to COVID-19 who rapidly deteriorated despite neuromuscular blockade and prone ventilation. He was aggressively managed using a combination of high frequency oscillatory ventilation (HFOV), high dose methylprednisolone, TPE, and direct instillation of liquid surfactant. He had an excellent clinical response and ultimately discharged to inpatient rehabilitation, then home, totally independent. Conclusion: Relatively few effective treatment options exist for ARDS. Our patient's response to a combination of interventions that have fallen out of clinical practice serves as a reminder that research is needed to help identify distinct phenotypes so that clinical trials can be designed to investigate interventions and treatments specific to the different phenotypes. [ABSTRACT FROM AUTHOR]

The next generation vehicular networks would be expected to support a wide array of cutting edge applications concerning intelligent transportation system (ITS). Due to this reason, the scale and complexity of ITS-based compute-intensive tasks has exhibited a phenomenal increase and will continue to grow in future. Thus, a large quantity of data requiring different levels of processing is generated, that necessities the need of in-vehicle computational resources as well as collaboration from technologies like, cloud and edge computing. This has led to the development of paradigms such as vewehicular cloud computing (VCC) and vehicular edge computing (VEC). Although VCC provides rich computing resources of the cloud servers to process tasks but it is affected due to long latency and instability of connections. In contrast, VEC provides compute resources closer to the data source to offset the relatively higher latency but the task requester should be able to perceive the computing and communication environment so as to allocate tasks effectively. Thus, it is essential to utilize both edge and cloud capabilities to create a collaborative cloud edge network that can cater to the demand of vehicular networks. A distributed task orchestration framework (DTOF) supporting a Vehicle-to-Vehicle based task orchestration scheme has been proposed that utilizes the vehicular movements along urban roads for creation of vehicular edges. The edge creation process utilizes an innovative light weight string processing algorithm based on hashing technique. The performance of DTOF has been evaluated based on extensive simulation by considering Chandigarh city road maps and the obtained results exhibit the satisfactory performance of DTOF for task orchestration. [ABSTRACT FROM AUTHOR]

Background: Currently preoperative magnetic resonance imaging (MRI) brain and High-Resolution Computed Tomography (HRCT) scanning of temporal bones form part of routine Cochlear implantation (CI) assessment. Pre- operative imaging demonstrates anatomic details or anomalies if any, that prove essential in pre-surgical evaluation of patients. These form a road map for the surgeon to anticipate any difficulty during surgery, to aid in decision making to implant the most appropriate ear, plan surgical technique, or select electrode arrays. Methods: A descriptive observational pilot study was conducted at tertiary care hospital involving 51 paediatric patients worked-up for CI. Patients after detailed clinical evaluation and MRI Brain, a tentative surgical plan was formulated by a candidacy CI screening committee. Patients selected for surgery underwent HRCT temporal bones and surgical plan was modified after analysing the same. Percentage of cases in which surgical plan changed (in terms of laterality of surgery) after correlating with HRCT findings were determined and data analysed. Results: A total of 51 patients worked up for CI were included in the study. In 37.3% cases, there were unfavourable MRI findings. HRCT scan was used to aid the surgical road map in these patients, which based on MRI findings would have had suboptimal outcome. Conclusion: With this understanding, we recommend that, MRI with precise interpretation would be sufficient to furnish all necessary information in preoperative assessment of CI patients, and a HRCT temporal bones maybe indicated only in difficult cases or those with unfavourable MRI findings, may aid predict surgical events. [ABSTRACT FROM AUTHOR]

A 4-year-old female was diagnosed with Type II Aortopulmonary window after being seen for a murmur. By utilizing multimodality advanced imaging, including 2D and 3D echo, computed tomography (CTA) with semi-transparent overlay as a road map, we were able to preoperatively plan camera angles and device selection as well as close the defect percutaneously under echocardiography guidance. This report highlights the importance of a multimodality imaging approach to interventional procedures. [ABSTRACT FROM AUTHOR]

Water loss management (WLM) in water distribution systems (WDSs) is generally time consuming, costly and difficult. Therefore, the most appropriate methodology should be defined based on the current status, requirements and technical capacity of the utilities. In this study, a novel WLM model was developed to improve the WLM practices, to define the most appropriate and applicable targets and to determine the components that need to be improved primarily using the Harris Hawk Optimization (HHO) algorithm. Firstly, a total of 144 components in the CSAS proposed by Bozkurt et al. (Welcome Sigma J Eng Natural Sci 40:1–13, 2022b) are scored in three utilities. The averages of current scores in utilities are 3.4167, 2.9792 and 1.1597, respectively. Then the most appropriate targets were defined with the optimization algorithm by considering the current situation and the dynamic structure of utility. The target scores defined by optimization model in utilities are 4.4097, 4.3958 and 3.2292, respectively. This novel model will contribute to the prevention of time-consuming and costly processes by determining the most appropriate progress. It is thought that this study will provide significant benefits for creating a road map for practitioners in WLM. [ABSTRACT FROM AUTHOR]

By using edge caching and edge computing, fog radio access networks (F-RANs) are viewed as suitable architectures to serve Internet of Things services. Current research on resource management in F-RANs, however, mostly takes into account a static method with a single communication mode. Resource management in F-RANs becomes highly difficult due to network dynamics, resource variety, and linkage of resource management with mode selection. This study suggests a unique method for data transmission and optimisation in radio access networks utilising a machine learning model. Here, photonic integrated circuits with dynamic optimisation are used to improve network optimisation. Then, data is sent using MASORL, a multi-agent self-organizing reinforcement learning system based on a fog edge model. The experimental study is done in terms of network efficiency, scalability, QoS, throughput, and energy consumption. We show how employing team learning rather than individual learning agents might improve network performance. Finally, in order to give scholars in the field a road map, we identify problems and unresolved concerns. [ABSTRACT FROM AUTHOR]

The increasing amount of air pollution on a global scale is a major source of worry. The elevated levels of pollution are affecting the health of urban dwellers and motorists to a great extent. Since the situation has become so dire, it has become an absolute necessity to find effective ways to reduce air pollution and mitigate the negative effects of air pollution on human health. In this paper, the task of determining the least polluted route is addressed and how this can be used to curb pollution is discussed. The proposed work uses Dijkstra's algorithm, suggests a weight selection metric for air pollution parameters and analyzes the efficacy of the proposed algorithm in determining the least polluted route. The algorithm is tested on real-time data extracted from the Central Pollution Control Board, a statutory organization under the Ministry of Environment, Forest and Climate Change, Government of India. From the results obtained, it is found that the least polluted routes between a given source location and other different locations of a city can be determined using Dijkstra's algorithm accurately and the algorithm has a time complexity of O(V2). Further, using a least polluted route map will help motorists take less polluted routes, diverting air pollution off congested streets and enabling national governments to create policies like constructing flyovers or widening roads in increasingly polluted areas. [ABSTRACT FROM AUTHOR]

Quality function deployment (QFD) method allows reviewing of customer requirements (CRs) and design requirements (DRs) simultaneously in order to handle the correlations and relationships of CRs and DRs in calculations. It has been often combined with fuzzy numbers, because it provides to gather the judgments of experts in vagueness environment more correctly and easily. This paper suggests employing q-rung orthopair fuzzy number (q-ROFN) for improving the fuzzy QFD approach. The proposed q-ROFN based QFD method uses q-ROFN to adjust the importance degrees of CRs based the relationships between CRs and DRs with the help of the correlations and relationships of CRs and DRs. q-ROFN presents more information than numbers such as intuitionistic fuzzy number and Pythagorean fuzzy number about the correlations and relationships of CRs and DRs. Furthermore, this work proposes integrating Fine-Kinney method and QFD method to cope with limitations of Fine-Kinney method. VIKOR (VIsekriterijumska optimizacija i KOm-promisno Resenje) approach based on q-ROFN is also used to rank DRs. The proposed integrated method provides a novel decision support model for the natural gas pipeline project (NGPP) risk assessment. There is no study about the integration of Fine-Kinney, q-ROFN-based QFD, VIKOR methods. The most significant DR and the second most important DR for NGPP risk assessment are electrical sparks and coating type factor, respectively. The results of this model present a road map to the managers of NGPP for an occupational health and safety policy by ordering the failure modes. [ABSTRACT FROM AUTHOR]

Advances in single-cell technologies have transformed the ability to identify the individual cell types present within tissues and organs. The musculoskeletal bionetwork, part of the wider Human Cell Atlas project, aims to create a detailed map of the healthy musculoskeletal system at a single-cell resolution throughout tissue development and across the human lifespan, with complementary generation of data from diseased tissues. Given the prevalence of musculoskeletal disorders, this detailed reference dataset will be critical to understanding normal musculoskeletal function in growth, homeostasis and ageing. The endeavour will also help to identify the cellular basis for disease and lay the foundations for novel therapeutic approaches to treating diseases of the joints, soft tissues and bone. Here, we present a Roadmap delineating the critical steps required to construct the first draft of a human musculoskeletal cell atlas. We describe the key challenges involved in mapping the extracellular matrix-rich, but cell-poor, tissues of the musculoskeletal system, outline early milestones that have been achieved and describe the vision and directions for a comprehensive musculoskeletal cell atlas. By embracing cutting-edge technologies, integrating diverse datasets and fostering international collaborations, this endeavour has the potential to drive transformative changes in musculoskeletal medicine. A single-cell atlas of the human musculoskeletal system could help to improve the understanding of musculoskeletal function in growth, homeostasis, ageing and disease. This Roadmap delineates the steps required and challenges involved in creating such an atlas. Key points: Musculoskeletal diseases present a large, and growing, global burden and delivery of effective treatments for these diseases requires improved understanding of the cellular basis of musculoskeletal tissue health and disease. The advent of single-cell sequencing methods allows us to build a 'human cell atlas' that identifies and maps every cell of the human body. The application of single-cell technologies in the study of musculoskeletal tissue has historically been difficult owing to the low cellularity and extracellular matrix-rich composition of these tissues. Advances in laboratory and computational methodologies and sharing of knowledge and data among the research community should make it possible to deliver a musculoskeletal cell atlas. Future expansion of the atlas, incorporating a greater number of ancestrally diverse donors, more tissue types and life stages, and diseased samples, will help to accelerate the development of improved diagnostic and therapeutic capabilities. [ABSTRACT FROM AUTHOR]

Purpose: The anatomy of the medial wall of the cavernous sinus (MWCS) and parasellar ligaments (PLs) has acquired increasing importance in endoscopic endonasal (EE) surgery of the cavernous sinus (CS), including resection of the MWCS in functioning pituitary adenomas (FPAs). Although anatomical studies have been published, it represents a debated topic due to their complex morphology. The aim is to offer a description of the PLs that originate from the MWCS and reach the lateral wall of the cavernous sinus (LWCS), proposing the "candy wrapper" model. The relationships between the neurovascular structures and histomorphological aspects were investigated. Methods: Forty-two CSs from twenty-one human heads were studied. Eleven specimens were used for EE dissection; five underwent a microscopic dissection. Five specimens were used for histomorphological analysis. Results: Two groups of PLs with a fan-shaped appearance were encountered. The anterior group included the periosteal ligament (55% sides) and the carotico-clinoid complex (100% sides), formed by the anterior horizontal and the carotico-clinoid ligaments. The posterior group was formed by the posterior horizontal (78% sides), and the inferior hypophyseal ligament (34% sides). The periosteal ligament originated inferiorly from the MWCS, reaching the periosteal dura. The anterior horizontal ligament was divided in a superior and inferior branch. The superior one continued as the carotid-oculomotor membrane, and the inferior branch reached the CN VI. The carotico-clinoid ligament between the middle and anterior clinoid was ossified in 3 sides. The posterior horizontal ligament was related to the posterior genu and ended at the LWCS. The inferior hypophyseal ligament followed the homonym artery. The ligaments related to the ICA form part of the adventitia. Conclusion: The "candy wrapper" model adds further details to the previous descriptions of the PLs. Understanding this complex anatomy is essential for safe CS surgery, including MWCS resection for FPAs. [ABSTRACT FROM AUTHOR]

Biodegradable polymers have emerged as fascinating materials due to their non-toxicity, environmentally benign nature and good mechanical strength. The toxic effects of non-biodegradable plastics paved way for the development of sustainable and biodegradable polymers. The engineering of biodegradable polymers employing various strategies like radical ring opening polymerization, enzymatic ring opening polymerization, anionic ring opening polymerization, photo-initiated radical polymerization, chemoenzymatic method, enzymatic polymerization, ring opening polymerization and coordinative ring opening polymerization have been discussed in this review. The application of biodegradable polymeric nanoparticles in the biomedical field and cosmetic industry is considered to be an emerging field of interest. However, this review mainly highlights the applications of selected biodegradable polymers like polylactic acid, poly(ε-caprolactone), polyethylene glycol, polyhydroxyalkanoates, poly(lactide-co-glycolide) and polytrimethyl carbonate in various fields like agriculture, biomedical, biosensing, food packaging, automobiles, wastewater treatment, textile and hygiene, cosmetics and electronic devices. [ABSTRACT FROM AUTHOR]

As notifications on carcinogenicity of heavy metals increase, more and more attention is paid recently to heavy metals exposure. In our study, the human exposure to heavy metals and cancer knowledge epistemology was investigated using bibliometric analysis. The bibliometric data of the research articles were retrieved using following keywords: "heavy metal," "trace element", "cancer", "carcinogen", and "tumor" in the Scopus database. Specifically, 2118 articles published between 1972 and 2023 were found, covering a total of 1473 authors, 252 sources, and 2797 keywords. Retrospective data obtained from 251 documents and 145 journals were further analyzed by performance analysis and techniques of science mapping. The number of studies conducted in this field increased from one article published in 1972 to 18 articles published in 2022 in the study of Michael P Waalkes. The most impactful author regarding the number of published papers was Masoudreza Sohrabi with 7 publications. In the majority of the published papers, the most popular keywords were "cadmium" and "carcinogenicity". However, in recent 4 years, the emphasis has been placed more on epidemiology studies. Our study provides general knowledge about the trend of publication on the role of heavy metals in causing cancer. The leading researchers in the field of the effects of heavy metals on the development of cancer were identified in our studies. Our results might also create a better understanding of new and emerging issues and can be used as a comprehensive road map for future researchers. [ABSTRACT FROM AUTHOR]

Repressor element-1 silencing transcription factor (REST) or also known as neuron-restrictive silencing factor (NRSF), is the key initiator of epigenetic neuronal gene-expression modification. Identification of a massive number of REST-targeted genes in the brain signifies its broad involvement in maintaining the functionality of the nervous system. Additionally, REST plays a crucial role in conferring neuroprotection to the neurons against various stressors or insults during injuries. At the cellular level, nuclear localisation of REST is a key determinant for the functional transcriptional regulation of REST towards its target genes. Emerging studies reveal the implication of REST nuclear mislocalisation or dysregulation in several neurological diseases. The expression of REST varies depending on different types of neurological disorders, which has created challenges in the discovery of REST-targeted interventions. Hence, this review presents a comprehensive summary on the physiological roles of REST throughout brain development and its implications in neurodegenerative and neurodevelopmental disorders, brain tumours and cerebrovascular diseases. This review offers valuable insights to the development of potential therapeutic approaches targeting REST to improve pathologies in the brain. The important roles of REST as a key player in the nervous system development, and its implications in several neurological diseases. [ABSTRACT FROM AUTHOR]

Spinal ultrasonography has increasingly been used to image axial structures from the cervical to sacral region in recent years. In this work, we propose a comprehensive, systematic cervical scanning protocol that we refined as a route map, especially for beginners, to facilitate teaching, learning, diagnosis, and treatment in clinical pain practice. As a simple and clear tool to demonstrate the scanning protocol, the route map is delineated with rectangles, lines, and arrows. The rectangles represent the positions of the transducer, the arrows indicate route directions, and the lines show the routes of transducer movement. In this article, we describe cervical spinal ultrasonography to illustrate the route map interpretation, scanning protocol and target anatomical structures in detail. We believe that this comprehensive, clear, systematic, and portable route map will be beneficial for inexperienced pain clinicians and ultrasound beginners. [ABSTRACT FROM AUTHOR]

The central, regional, provincial and local territorial model in Chile was designed and implemented under the authoritarian Pinochet regime in 1980 and remained unchanged for fifty years. The direct election of regional governors in 2021 and the rejected constitutional proposal of 2022 are generating a new "road map" in the discussion of Intergovernmental Relations (IGR). Through a review of the press and available literature, two scenarios that will influence this discussion are analyzed: the tension between the regional governor and the presidential delegate, and the model of autonomous territorial entities -regions, municipalities and indigenous communities- proposed by the Constituent Assembly. [ABSTRACT FROM AUTHOR]

An increase in policy ambition is needed to close the gaps related to climate change mitigation and those required to meet the targets of Paris Agreement. This article examines the contemporary situation of carbon pricing and suggests how carbon costs would help countries adopt comprehensive climate policies. This paper explores the carbon pricing imitative across different regions and the associated issues and proposes how to format holistic, ambitious approaches for effective implementation of carbon pricing. The carbon taxes and emission trading programs are the primary tools for implementation costs. Carbon taxes, fuel taxes, subsidies for fossil energy, and emission trading systems (ETSs) all contribute to these costs. Different countries have adopted different approaches to adopt and mitigate the adverse effect of carbon emissions, but coordinated and integrated efforts are needed. This paper emphasizes the effective carbon pricing and integrating role of finance departments in climate policy; new synergies can be developed to boost government agencies' ability to implement climate policy. Governments may increase their involvement in carbon pricing beyond direct carbon pricing if they implement efficient carbon pricing. Governments, international organizations, and civil society can all play a role in pushing for effective carbon prices to encourage more ambitious targets. Furthermore, the article stresses the need for open communication and a proper understanding of carbon pricing potential to implement climate policy. [ABSTRACT FROM AUTHOR]

Routing and parking problems are considered a real challenge in the populated cities. An intelligent routing and parking algorithm is needed to facilitate locating the most appropriate parking spots to vehicles in a way that efficiently utilizes parking resources, reduces the traffic congestion, and minimizes trip driving time. This work proposes a hierarchical optimal algorithm to solve the routing and parking problem (HOPRA) using multi-criteria decision concept and historical traffic data. The problem is divided into three parts: finding the preferred parking lot, identifying the parking entrance (in case there are multiple), and then selecting the preferred route to the destination point. The optimal parking lot is defined based on an objective function that depends on the availability rates of the parking lots. After finding the parking lot and the parking entrance, a multi-objective function is used to specify the preferred route to the selected parking lot. This function depends on the travel distance, the traffic rate of a specific route, and the driver's preferences. We use the Open Street Maps from the AnyLogic software in the implementation stage. We compare HOPRA against the Shortest Route (SR) algorithm that was implemented also in AnyLogic with historical traffic data obtained from HERE technologies for a sample city (Al-Madinah City in Saudi Arabia). The results show that the HORPA algorithm outperforms the SR algorithm in balancing the traffic congestion on the roads and reducing the driving time of the trip. [ABSTRACT FROM AUTHOR]

Understanding and managing hospital Organizational Readiness to Change is a key topic with strong practical implications on society worldwide. This study provides, through a scoping literature review, a framework aimed at creating a road map for hospital managers who are implementing strategic processes of change. Ideally, the framework should act as a check-list to proactively detect those items that are likely to impede successful change. 146 items were identified and clustered into 9 domains. Finally, although built for the hospital setting, similar research approaches could be highly effective also in other large, public organizations. [ABSTRACT FROM AUTHOR]

Inappropriate e-waste processing in the informal sector is a serious issue in developing countries. Field investigations in microscale informal recycling sites have been performed to study the impact of hazardous metal(loid)s (released from e-waste dismantling) on the environment (water and soil). Eight hazardous metal(loid)s (Pb, Cd, Cu, Zn, As, Hg, Ni, and Cr) were primarily found in the monitored water and soil samples (Sangrampur, West Bengal) because of widespread informal e-waste handling and primitive processing. Elevated concentrations of Cd, Pb, As, Cu, and Cr were observed in pond water samples (0.04, 1.62, 0.03, 1.40, 1.74 mg/L respectively). These ponds, which are regularly used for e-waste handling/dismantling, are usually flooded during the monsoon season mixing with further larger water resources — posing a serious threat to public health. Enriched levels of Pb, Cd, Cu, and Zn were detected in collected soil samples, both top surface soil (Pb up to 2042.27 ± 206.80, Cd up to 25.90 ± 9.53, Cu up to 6967.30 ± 711.70, and Zn up to 657.10 ± 67.05 mg/Kg) and deeper subsurface soil (Pb, 419.70 ± 44.70; Cd, 18.34 ± 3.81; Cu, 3928.60 ± 356.40; and Zn, 134.40 ± 33.40 mg/Kg), compared to the levels of As, Hg, Ni, and Cr. Seasonal variation of soil metal(loid) content indicated that higher levels of most of the metal(loids) were detected in the pre-monsoon (Nov–May) season, possibly due to the monsoonal dilution effect, except for Pb and Cd. The results highlighted that the composition and the handling of e-waste were important factors affecting the metal(loid) concentrations. E-waste policy and legislation have great influence on the handling and disposal procedures. An improved e-waste management practice has been proposed to encourage eco-friendly and safe e-waste disposal. It is recommended that regulatory agencies and manufacturers should create a road map to convince the informal sector to develop a systematic approach towards a more standardized formal e-waste management practices at the microscale field level. [ABSTRACT FROM AUTHOR]

The SNARE complex assembles from vesicular Synaptobrevin-2 as well as Syntaxin-1 and SNAP25 both anchored to the presynaptic membrane. It mediates fusion of synaptic vesicles with the presynaptic plasma membrane resulting in exocytosis of neurotransmitters. While the general sequence of SNARE complex formation is well-established, our knowledge on possible intermediates and stable off-pathway complexes is incomplete. We, therefore, follow the stepwise assembly of the SNARE complex and target individual SNAREs, binary sub-complexes, the ternary SNARE complex as well as interactions with Complexin-1. Using native mass spectrometry, we identify the stoichiometry of sub-complexes and monitor oligomerisation of various assemblies. Importantly, we find that interactions with Complexin-1 reduce multimerisation of the ternary SNARE complex. Chemical cross-linking provides detailed insights into these interactions suggesting a role for membrane fusion. In summary, we unravel the stoichiometry of intermediates and off-pathway complexes and compile a road map of SNARE complex assembly including regulation by Complexin-1. Chemical cross-linking and native mass spectrometry aid the thorough investigation of complex formation and multimerisation of synaptic vesicle fusion-mediating SNARE complex, including the role of complexin-1 in its assembly. [ABSTRACT FROM AUTHOR]

For the last ten years, software product line (SPL) tool developers have been facing the implementation of different variability requirements and the support of SPL engineering activities demanded by emergent domains. Despite systematic literature reviews identifying the main characteristics of existing tools and the SPL activities they support, these reviews do not always help to understand if such tools provide what complex variability projects demand. This paper presents an empirical research in which we evaluate the degree of maturity of existing SPL tools focusing on their support of variability modeling characteristics and SPL engineering activities required by current application domains. We first identify the characteristics and activities that are essential for the development of SPLs by analyzing a selected sample of case studies chosen from application domains with high variability. Second, we conduct an exploratory study to analyze whether the existing tools support those characteristics and activities. We conclude that, with the current tool support, it is possible to develop a basic SPL approach. But we have also found out that these tools present several limitations when dealing with complex variability requirements demanded by emergent application domains, such as non-Boolean features or large configuration spaces. Additionally, we identify the necessity for an integrated approach with appropriate tool support to completely cover all the activities and phases of SPL engineering. To mitigate this problem, we propose different road map using the existing tools to partially or entirely support SPL engineering activities, from variability modeling to product derivation. [ABSTRACT FROM AUTHOR]

In China, manufacturing is the industry that consumes the most energy and emits the most carbon, and the effect of emission reduction on the process of reaching carbon peaking and carbon neutrality is decisive. The existing research on the driving factors of manufacturing carbon emissions has not analyzed the specific structural characteristics of manufacturing carbon emissions from the perspective of industrial relevance, and little attention has been paid to the discussion of carbon emission reduction paths of different manufacturing sectors from the perspective of final demand. This study examines the direct carbon emissions and carbon emissions from final demand in China's manufacturing sector, and decomposes the carbon emissions from final demand into six distinct components using input-output analysis. In addition, this study examines the carbon emission path in manufacturing production activities, as well as the carbon emission reduction potential and scenario prediction of the factors influencing manufacturing carbon emissions. In 2018, the direct carbon emissions and carbon emissions from final demand were approximately 4.61 billion tons and 3.50 billion tons, respectively. Meanwhile, direct and indirect spillovers accounted for 62.1% and 23.1% of carbon emissions from final demand, respectively. Using the carbon emission transfer route map of the manufacturing industry, the direction and amount of carbon emission transfer from various energy sources can be accurately determined. The CR scenario predicts that the manufacturing industry will reach its carbon peak between 2025 and 2030, with a corresponding peak between 4.02 and 4.06 billion tons, and that carbon emissions in 2060 will be 40% lower than in 2018. [ABSTRACT FROM AUTHOR]

How hosts respond to and cope with infectious agents can change the environment and in so doing, alter selective pressures and evolutionary trajectories. To date, such eco-evolutionary feedbacks are best known from simplified mathematical models and laboratory experiments with a limited number of genetically homogenous model systems. However, the extent to which ecology and (co)-evolution interact to shape disease over space and time in natural communities remains poorly understood. Studies in this theme issue break new ground by integrating empirical and field studies stemming from a diverse array of taxa and ecosystems to understand how ecological and evolutionary feedbacks shape host-parasite interactions. Contributing papers synthesize emerging research and diverse perspectives on pathogen life history, virulence, resistance, leveraging novel methodological advances and integrating infection processes across multiple scales of biological organization. Two key take-aways emerge from this theme issue. First, more research tackling the eco-evolutionary dynamics of infectious disease in truly multi-species contexts is needed. Second, while we are far from understanding eco-evolutionary dynamics in the 'natural theater' where hosts encounter their parasites, exciting advances and foundational studies provide a well-defined road map. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this study was to evaluate and compare the diagnostic performance of ultrasonography (USG) assessment using structured reporting with intraoperative laparoscopic assessment in deep infiltrating endometriosis (DIE) using the recent update of the #ENZIAN classification. Methods: This was a retrospective study conducted in Tertiary Multi-disciplinary Endometriosis Care Hospital over a period of 8 months which included 50 patients who underwent a planned laparoscopic endometriosis excisional surgery after a dedicated USG assessment using International Deep Endometriosis Analysis (IDEA) protocol and #ENZIAN score (updated ENZIAN classification), between Feb 2021 and Sept 2021 at Apollo Hospitals, Hyderabad. The pre-operative USG findings were reported in a structured reporting format and intraoperative findings were classified using the standard #ENZIAN classification. No prospective interventions were done. A review of pre-operative ultrasound and laparoscopic findings as per the #ENZIAN was done. Results: Sensitivity and the negative predictive value of ultrasound were 86% and 84.2% for peritoneal lesions, 97% and 93.3% for left ovarian lesions, 93% and 91.6% for right ovarian lesions, 91% and 84% for left tubal lesions, 90% and 86.3% for right tubal lesions, 93% and 75% for uterosacral ligaments, 93.3% and 97% for rectal lesions and sensitivity and negative predictive values were 100% for rectovaginal lesions, adenomyosis, and ureteric lesions as confirmed on laparoscopy. Conclusion: Dynamic ultrasound assessment with a structured report based on IDEA protocol and #ENZIAN score is accurate for mapping of pelvic endometriosis in all forms, and it correlates with laparoscopic findings, thus helps surgeon for better planning and providing a road map for surgeons. From a clinical perspective, a uniform and shared reporting system across imaging and therapeutic modalities will simplify communication, improving patient management by conservative or surgical treatments, avoiding multiple repeat surgeries, and improving quality of treatment. [ABSTRACT FROM AUTHOR]

Quinolinone/quinoline is one of the most unique structures in the discovery of heterocycles that have attracted much attention in the field of medicinal chemistry. The basic scaffold of fused quinoline derivatives is of great interest to medicinal chemists since large road maps of the gene and protein expression can be used to classify cancers or predict responses to certain types of treatments targeting the level of both transcription and translation and the level of enzyme activity. These specific regulations may open the door for the discovery of new drug candidates including anticancer targets. This review provides a comprehensive description of various quinolinone derivatives, especially by concentrating on compounds containing benzimidazole rings. Quinolone moieties are experimentally proven anticancer pharmacophores which may further enhance their activity due to various functional groups, mostly the electron-withdrawing groups such as fluoro, chloro, nitro, amino, and carbonyl groups that showed stronger activity than those with electron-donating groups such as methyl and methoxy groups. The presence of an electron-withdrawing or electron-donating group at the quinolone ring influences the redox properties affecting DNA synthesis. Structural motifs attributed to noteworthy inhibitory results are identified and highlighted to encourage further research and drug development. This work aims to help researchers in discovering more powerful, active, and less toxic quinoline-based anticancer drugs and developing new vision in the search for their rational design. [ABSTRACT FROM AUTHOR]

In complex and volatile transportation traffic situations, accurately forecasting traffic flow can greatly facilitate to manage and plan real-time traffic. However, due to complex road map and traffic conditions, forecasting temporal traffic is a highly challenging task. In literature, most existing works rely on various spatial–temporal models solely built on the topological structure of road networks, to capture both spatial and temporal dependencies of traffic flow at multiple sensing sites. However, besides the road topological relationship, the dynamics of real-world traffic is indispensably affected by the complex but unknown inter-dependency of multiple sites. Based on the above consideration, this paper proposed a novel traffic forecast framework based on multiple-view graph construction and learning, and spatiotemporal graph neural network (STGNN). Specifically, our work’s contributions are following. First, considering transfer entropy (TE)-based relationship graph can characterize the causal influence from one sensing sites to another, the traditional undirected topological graph is transformed into a directed graph through multiplying with the constructed TE relationship graph, which can capture both the topological relationship, and latent casual influence from one site to another, and greatly facilitate to accurately forecast traffic. Meanwhile, a learnable graph matrix is trained to complement the TE-enhanced causality graph. Second, the proposed STGNN-based forecasting framework smoothly integrates recurrent neural network and GNN that works on directional and learnable graphs, so-called DL-GNN. In detail, the aggregation process in DL-GNN is formulated as three parts: aggregation on indegree and outdegree directions of the causality graph, and on learnable graph to fully extract the sites’ representations. The comprehensive experiments on real traffic data demonstrate that our proposal outperforms other state-of-the-art STGNN-based traffic forecasting schemes. [ABSTRACT FROM AUTHOR]

The ever increasing demand in passenger and freight transportation is leading to the saturation of railway network capacity. Virtual Coupling (VC) has been proposed within the European Horizon 2020 Shift2Rail Joint Undertaking as a potential solution to address this problem. It allows to dynamically connect two or more trains in a single convoy, thus reducing headway between them. In this work, we investigate the main challenges related to the potential deployment of VC in railways. Its feasibility through Reinforcement Learning techniques is explored, discussing about technical implementation and performance issues. A qualitative analysis based on a Deep Deterministic Policy Gradient control algorithm is proposed. The aim is to give a first insight towards the definition of a qualitative and technology roadmap which could lead to the deployment of artificial intelligence applications aiming at enhancing rail safety and automation. [ABSTRACT FROM AUTHOR]

In recent years, increasing research attention has been directed to structurally diverse pyrazole derivatives, many of which have become commercially available drugs with antispasmodic, anti-inflammatory, antibacterial, analgesis, antihyperglycemic, hypoglycemic, antineoplastic, antidepressive activities, etc. Due to their wide range of biological activities, pyrazole derivatives can be used to treat a range of diseases, such as cancers, respiratory diseases, infections, and neurological diseases. This review summarizes recent advances in the use of the pyrazole scaffold and provides pharmacologists with a road map for developing novel preclinical and clinical pyrazole-based drugs. [ABSTRACT FROM AUTHOR]

The world is changing fast, and so is the space sector. Planning for large scientific experiments two decades ahead may no longer be the most sensible approach. I develop the argument that large science experiments are becoming comparable to terrestrial civil infrastructures in terms of cost. As a result, these should incorporate plans for a return on investment (or impact, not necessarily economic), require a different approach for inter-division coordination within the European Space Agency (ESA), and a broader participation of all society stakeholders (civil society representatives, and the broader public). Defining which experiments will be relevant two decades ahead adds rigidity and quenches creativity to the development of cutting edge science and technology. This is likely to discourage both senior and earlier career professionals into supporting such long-term (and often precarious) plans. A more sensible strategy would be increasing the rate of smaller well understood experiments, engage more society sectors in the development of a truly space-bound infrastructure, and formulate a strategy more in tune with the challenges faced by our society and planet. We argue that such strategy would lead to equally large -even larger- scale experiments in the same time-scale, while providing economic returns and a common sense of purpose. A basic but aggressive road map is outlined. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have emerged as a fast-growing industry not only in India but all over the world due to their environment friendly and economic properties. Moreover, it is being seen as a future replacement for fast depleting fossil fuels. But still, the international vehicle market cannot accept EVs as a ubiquitous vehicle manufacturing standard due to their short cruising range and underdeveloped charging infrastructure. Therefore, as an immediate and cost-effective solution to a problem subject to limited battery capacity, the EV route regularization, i.e., optimum energy usage route selection becomes utmost important. To accomplish this objective, this paper proposes a meta-heuristic routing model based on the principles of Artificial Bee Colony (ABC). The proposed model has been designed to consider prominent energy consumption influencing parameters like speed, battery health, road elevation, etc. Moreover, tractive effort modeling on different road surfaces like dry, wet, snow, and icy is also embedded in the design of EV route modeling. The simulation of the proposed model has been done to quantify its performance bys utilizing route maps as well as real-time information of vehicles' location by the Warrigal project as input. The analysis of obtained results has revealed the traces of saving in EVs' energy consumption of about 7.1% in comparison with Google maps if the route suggested by the proposed model is followed. [ABSTRACT FROM AUTHOR]

An opportunity-based model of rural entrepreneurial process was developed using a case study of 24 businesses representing rural entrepreneurship. The model was applied in the current study based on interviews with rural entrepreneurs who were successful in exploiting rural entrepreneurial opportunities successfully in Fars province, Iran. Rural entrepreneurial opportunity is a situation in which creation of a value for the rural setting through a new product or service, new market or marketing, new resource or exploitation of the resource, and new method or innovation would be profitable. The developed model contained two basic parts: (a) five principal stages including rural entrepreneurial opportunity recognition, evaluation, examination, exploitation, and revision; (b) the important factors at each stage of the process. These factors were confirmed by a focus group with 9 participants (rural entrepreneurs, researchers, and experts). For the future research, this model suggests a clear image of the rural entrepreneurial process as a contribution to the rural entrepreneurship literature. The model will also be a useful road map for the prospective rural entrepreneurs. [ABSTRACT FROM AUTHOR]

A long time ago in the machine learning literature, the idea of incorporating a mechanism inspired by the human visual system into neural networks was introduced. This idea is named the attention mechanism, and it has gone through a long development period. Today, many works have been devoted to this idea in a variety of tasks. Remarkable performance has recently been demonstrated. The goal of this paper is to provide an overview from the early work on searching for ways to implement attention idea with neural networks until the recent trends. This review emphasizes the important milestones during this progress regarding different tasks. By this way, this study aims to provide a road map for researchers to explore the current development and get inspired for novel approaches beyond the attention. [ABSTRACT FROM AUTHOR]

The coupling between two or more objects can generally be categorized as strong or weak. In cavity quantum electrodynamics for example, when the coupling strength is larger than the loss rate the coupling is termed strong, and otherwise it is dubbed weak. Ultrastrong coupling, where the interaction energy is of the same order of magnitude as the bare energies of the uncoupled objects, presents a new paradigm for quantum physics and beyond. As a consequence profound changes to well established phenomena occur, for instance the ground state in an ultrastrongly coupled system is not empty but hosts virtual excitations due to the existence of processes which do not conserve the total number of excitations. The implications of ultrastrong coupling for quantum topological systems, where the number of excitations are typically conserved, remain largely unknown despite the great utility of topological matter. Here we reveal how the delicate interplay between ultrastrong coupling and topological states manifests in a one-dimensional array. We study theoretically a dimerized chain of two-level systems within the ultrastrong coupling regime, where the combined saturation and counter-rotating terms in the Hamiltonian are shown to play pivotal roles in the rich, multi-excitation effective bandstructure. In particular, we uncover unusual topological edge states, we introduce a flavour of topological state which we call an anti-edge state, and we reveal the remarkable geometric-dependent renormalizations of the quantum vaccum. Taken together, our results provide a route map for experimentalists to characterize and explore a prototypical system in the emerging field of ultrastrong quantum topology. [ABSTRACT FROM AUTHOR]

This study aims to reveal the interest toward sustainability and effects of sustainability motivation factors in the management of hotels in the case of Palandöken Winter Tourism Center (WTC). Sustainability motivation factors are of great importance not only for the sustainability of the hotels but also for the sustainable future of WTCs, the winter tourism sector, and even for the cities and the countries. In other words, the motivations of firms regarding sustainability play a role in ensuring economic, ecological, and social sustainability from the individual to the country scale. Therefore, it is critically important to determine the effects of sustainability motivation factors. Since then, a road map can be drawn to strengthen the internal and external motivations that support sustainable practices and eliminate factors that disrupt their motivations. The study was designed as a case study. A questionnaire consisting of Likert-type questions was applied to the managers of the hotels in the Palandöken WTC in January 2020. Quantitative data were gathered from 40 samples and later analyzed using descriptive statistics, regression, and discriminant analysis techniques. As a result, the interests in sustainability, the effectiveness of sustainability motivation factors, the relationship between motivation factors and interest in sustainability, and the differences between respondent groups in terms of their interest in sustainability were determined. [ABSTRACT FROM AUTHOR]

Delleman-Oorthuys or oculocerebrocutaneous syndrome (OCCS) is an extremely rare condition which relies on three pillars of manifestations: ophthalmological, neurological, and dermatological. It was first described by Delleman and Oorthuys in 1981, and since then, very few other cases have been reported. We report the case of a 13-month-old boy, referred to an ophthalmological tertiary service for investigation of a microglobe with a cystic retrobulbar mass on translucency test. MRI revealed a left microphthalmia, with extensive retrobulbar cystic lesions occupying the remaining orbit and protruding anteriorly the microglobe. Cerebral findings included polymicrogyria, subependymal nodular heterotopia at the level of the left occipital horn of the lateral ventricle, and an importantly enlarged mesencephalic tectum observed in association with an absent cerebellar vermis. The ensemble of malformations met the criteria for definite OCCS. Being a tremendously rare syndrome, OCCS will always represent a diagnostic challenge. However, its emblematic cutaneous manifestations might be an important part of the road map leading to its correct interpretation. Thus, when absent, diagnosis can be harder than usual, and, on these cases, neurologists, ophthalmologists, and radiologists play a crucial role. [ABSTRACT FROM AUTHOR]

As a step toward probabilistic seismic hazard assessment in the Ibero–Maghreb region, this study focuses on the estimation and the analysis of main seismic hazard parameters, namely the magnitude of completeness mc, the occurrence rate λ, the Gutenberg–Richter b value, and the maximum expected magnitude Mmax. The most recent earthquake catalog database has been compiled using different earthquake sources, including historical and instrumental earthquake records covering the time period 1045 − 2019. International Seismological Centre catalog database has been used to get the preliminary instrumental catalog covering the study region. Then, a magnitude inter-scale conversion analysis has been carried out to obtain magnitude conversion empirical laws. These later have been used to compile a homogenized catalog with all magnitudes unified to the moment magnitude Mw scale, which is quite reliably linked to fault physical parameters. The completeness magnitude has been estimated for different time periods using the maximum curvature and the entire magnitude range methods. Subsequently, the spatio-temporal variation of the completeness magnitude has been studied to better appreciate regional data quality. This analysis resulted in three complete sub-catalogs corresponding to different magnitude of completeness, namely mc = 3.5, 4.5, and 5.5, starting from 1997, 1967 and 1959. The remaining seismic hazard parameters (λ, b and Mmax) were analyzed taking into account former magnitudes of completeness. Indeed, the use of incomplete data may add significant bias to seismic hazard parameters estimates. Main results are presented as spatial maps showing variation of seismic hazard parameters for different mc values. In particular, for the first time, a combined maximum magnitude–intensity map is elaborated and analyzed. The region corresponding to the largest maximum possible magnitude Mmax has been delimited as including Cheliff basin and its surrounding areas west of the capital city Algiers. Mmax hotspots with values exceeding 7 have been delimitated close to Lakhdaria and Boumerdes cities east of the capital Algiers. The corresponding hotspots include the epicenter of the 1910 Mw7 and the 2003 Mw6.8 Aumale and Zemmouri earthquakes, respectively. The magnitude of completeness mc has been found to decrease significantly during the last two decades, especially in the western part. The results obtained in this study can serve as a road map for future seismic hazard studies performed on the Ibero–Maghreb region. [ABSTRACT FROM AUTHOR]

The aims of this work were analysis of the effect of the synthesis conditions on the microstructure, structure, and electrical properties of electrospun carbon nanofibers/disordered carbon nanotubes (eCNF/dCNT) nanocomposites, and analysis of the correlations between these properties. The nanocomposites were obtained in the combined process involving electrospinning of precursor nanofibers and catalytic chemical vapor deposition (CCVD) synthesis of carbon nanotubes directly on the surface of nanofibers. The evaluation of microstructural-structural characteristics was conducted using microscopic, spectroscopic, and diffractometric methods. Electrical properties were investigated through measurements of temperature-dependent conductivity, and interpreted in terms of Mott's variable range hopping model. The study showed that the control of the temperature and duration of CCVD synthesis of CNT enables tailoring of the microstructure, defect density, and electrical transport in nanocomposites. Increasing the temperature up to 850 °C led to extension of the planar π-conjugated structure of nanoprotrusions, which resulted in facilitated conductivity of nanocomposites. The prolongation of the CCVD growth significantly increased the amount, and length of nanoprotrusions, which resulted in further enhancement of conductivity. The analysis of Raman spectra suggests the existence of an interesting correlation between the half-width of the G-band and T0 parameter describing the electrical properties. The study provides a solid background and route map for the synthesis of eCNF/CNT nanocomposites in applications such as energy storage and conversion, electrochemistry, nanoelectronics, semiconductors etc. [ABSTRACT FROM AUTHOR]

Articular cartilage damage is a universal health problem. Despite recent progress, chondrocyte dedifferentiation has severely compromised the clinical outcomes of cell-based cartilage regeneration. Loss-of-function changes are frequently observed in chondrocyte expansion and other pathological conditions, but the characteristics and intermediate molecular mechanisms remain unclear. In this study, we demonstrate a time-lapse atlas of chondrocyte dedifferentiation to provide molecular details and informative biomarkers associated with clinical chondrocyte evaluation. We performed various assays, such as single-cell RNA sequencing (scRNA-seq), live-cell metabolic assays, and assays for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), to develop a biphasic dedifferentiation model consisting of early and late dedifferentiation stages. Early-stage chondrocytes exhibited a glycolytic phenotype with increased expression of genes involved in metabolism and antioxidation, whereas late-stage chondrocytes exhibited ultrastructural changes involving mitochondrial damage and stress-associated chromatin remodeling. Using the chemical inhibitor BTB06584, we revealed that early and late dedifferentiated chondrocytes possessed distinct recovery potentials from functional phenotype loss. Notably, this two-stage transition was also validated in human chondrocytes. An image-based approach was established for clinical use to efficiently predict chondrocyte plasticity using stage-specific biomarkers. Overall, this study lays a foundation to improve the quality of chondrocytes in clinical use and provides deep insights into chondrocyte dedifferentiation. [ABSTRACT FROM AUTHOR]

Phase Change Memory (PCM) is an emerging technology exploiting the rapid and reversible phase transition of certain chalcogenides to realize nanoscale memory elements. PCM devices are being explored as non-volatile storage-class memory and as computing elements for in-memory and neuromorphic computing. It is well-known that PCM exhibits several characteristics of a memristive device. In this work, based on the essential physical attributes of PCM devices, we exploit the concept of Dynamic Route Map (DRM) to capture the complex physics underlying these devices to describe them as memristive devices defined by a state—dependent Ohm's law. The efficacy of the DRM has been proven by comparing numerical results with experimental data obtained on PCM devices. [ABSTRACT FROM AUTHOR]

High surrounding road density could increase traffic-related air pollution, noise and the risk of traffic injuries, which are major public health concerns for children. We collected geographical data for all childcare centers (16,146) in Australia and provided the data on the road density surrounding them. The road density was represented by the child care center's nearest distance to main road and motorway, and the length of main road/motor way within 100~1000-meter buffer zone surrounding the child care center. We also got the data of PM2.5 concentration from 2013 to 2018 and standard Normalized Difference Vegetation Index (NDVI) data from 2013 to 2019 according to the longitude and latitude of the child care centers. This data might help researchers to evaluate the health impacts of road density on child health, and help policy makers to make transportation, educational and environmental planning decisions to protect children from exposure to traffic-related hazards in Australia. Measurement(s) road density • PM2.5 • NDVI Technology Type(s) open street map, google map • satellite-, simulation- and monitor-based PM2.5 sources • Moderate resolution Imaging Spectroradiometer Factor Type(s) ServiceNam • ServiceTyp • ServiceAdd • Suburb • State • Postcode • NumberOfAp • QualityAre • OverallRat • Long_Day_C • Preschool_ • Outside_sc • type • lon_final.x • lat_final.x • PM2.5_2013 • PM2.5_2014 • PM2.5_2015 • PM2.5_2016 • PM2.5_2017 • PM2.5_2018 • NDVIMax_2013 • NDVIMax_2014 • NDVIMax_2015 • NDVIMax_2016 • NDVIMax_2017 • NDVIMax_2018 • NDVIMax_2019 • dismain • dismotorway • main_50 • main_100 • main_300 • main_500 • main_1000 • moto_50 • moto_100 • moto_300 • moto_500 • moto_1000 Sample Characteristic - Organism child care center Sample Characteristic - Environment road density • PM2.5 • NDVI Sample Characteristic - Location Australia [ABSTRACT FROM AUTHOR]

In today's era, the world economy needs to move towards a green transformation. Green total factor productivity provides the judgment about a country or region's ability to achieve long-term sustainable development goals. However, many factors considerably affect green total factor productivity that needs to be explored and clarified. This panel study investigates the link between technological input, environmental policies, governmental involvement, manufacturing and logistics industry cooperation, renewable energy consumption, and green total factor productivity in the context of Chinese's manufacturing and logistics industry. Hypotheses are tested through fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) econometric technique. The study used 12 cities data mainly taken from China Urban Statistical Yearbook (2005–2019) and National Economic and Social Development Statistics Bulletin. The results indicate that technological input, environmental policies, governmental involvement, manufacturing and logistics industry cooperation, and renewable energy consumption are significantly linked to green total factor productivity. The result also implies that the factors mentioned above have a crucial role in the transformation process. Moreover, the current research results will help popularize green total factor productivity and provide a new starting point for reducing non-renewable energy consumption and environmental pollution. [ABSTRACT FROM AUTHOR]

The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor that can be activated by structurally diverse compounds arising from the environment and the microbiota and host metabolism. Expanding evidence has been shown that the modulation of the canonical pathway of AHR occurs during several chronic diseases and that its abrogation might be of clinical interest for metabolic and inflammatory pathological processes. However, most of the evidence on the pharmacological abrogation of the AHR-CYP1A1 axis has been reported in vitro, and therefore, guidance for in vivo studies is needed. In this review, we cover the state-of-the-art of the pharmacodynamic and pharmacokinetic properties of AHR antagonists and CYP1A1 inhibitors in different in vivo rodent (mouse or rat) models of disease. This review will serve as a road map for those researchers embracing this emerging therapeutic area targeting the AHR. Moreover, it is a timely opportunity as the first AHR antagonists have recently entered the clinical stage of drug development. [ABSTRACT FROM AUTHOR]

A reverse nearest neighbour (RNN) query returns every object for which the query is its nearest neighbour. Recently, a new useful variant of the RNN query has emerged, called reverse nearest neighbourhood (RNNH) query, to discover the neighbourhood that find query point is the nearest facilities among all other fa- cilities. However, the existing research focuses on computing RNNH in Euclidean space and, to the best of our knowledge, there does not exist any technique to compute RNNH in road networks. The existing techniques designed for Euclidean space cannot be applied for road networks mainly because all objects and facilities of interest are connected on a road network. Thus, there is a need for techniques specifically designed for computing RNNH in road networks. In this paper, we introduce the reverse nearest neighbourhood concept for road networks (RNNH-RN) where a neighbourhood is a collection of at least m chained objects such that the maximum road network distance between any pair of objects is at most d. We demonstrate the flexibility and effectiveness of the proposed RNNH-RN query through extensive experiments based on real-world, road network data for Melbourne, Victoria. Our experimental results demonstrate that our solutions are feasible for networks with low, medium or high levels of object density. [ABSTRACT FROM AUTHOR]

A new book by the Professor of the Odessa I.I. Mechnikov National University, Tatyana Popova, entitled I Istoriografija, bioistoriopisanie, bitsillievedenie: teorija, metodologija, praktika i ( I Historiography, Biohistoriography, Bicilliography: Theory, Methodology, Practice i ) was printed and became available to readers in the first days of the current war. The structural sequence of the book reflects the triad of the leading areas of Popova's research interests - historiography, biohistoriography, and Bitsillian studies, i.e., the interdisciplinary investigation of the heritage of Peter Bitsilli (1879-1953), a historian of the first wave of Russian emigration. At the same time, Popova vividly expresses her own research passion and even intellectual love for the figure of Peter Bitsilli. [Extracted from the article]