Assessment of climate change on river streamflow under different representative concentration pathways.

Climate change and excessive greenhouse gas emissions profoundly impact hydrological cycles, particularly in arid and semi-arid regions, necessitating assessments of their effects on water resource management, agriculture, soil fertility, nutrient transport, hydropower generation, and flood risk. This study investigates climate change repercussions on streamflow in the Zarrineh River Basin, Iran, across three decadal intervals (2020-2029, 2055-2064, and 2090-2099) aiming to develop effective adaptation and mitigation strategies. Four General Circulation Models (GCMs), chosen based on distinct Representative Concentration Pathways (RCPs) determined by the annual mean temperature gradient, are employed. These models generate daily maximum (Tmax) and minimum (Tmin) temperatures along with precipitation data. Subsequently, these variables are integrated into the Soil and Water Assessment Tool (SWAT) model to analyze river flow alterations for each decadal timeframe. Comparison between future projections and observed climate data reveals a gradual decline in precipitation and Tmax, coupled with a substantial increase in Tmin. The average precipitation diminishes from 0.77 mm in the period 1985-1994 to a range of 0.42-0.28 mm in 2090-2099. The simulated flow at the basin outlet highlights that the GCM with the highest annual mean temperature gradient yields the lowest streamflow, while conversely, the model with the lowest gradient generates the highest. Consequently, streamflow experiences a decline from 52 m3/s in 1985-1994 to a range of 41-20 m3/s in 2090-2099.

Acute quadriplegia and death following a routine MRI for undiagnosed degenerative cervical myelopathy.

Bilateral upper limb paraesthesia and pain are common symptoms of degenerative cervical myelopathy (DCM). Such symptoms instigate investigation by cervical spine magnetic resonance imaging (MRI). This was the case for our patient, who was 72-years-in age and otherwise fit and well. During the scan he unfortunately developed sudden onset quadriplegia secondary to an intervertebral disc prolapse. This necessitated intubation due to respiratory failure and urgent transfer to the neurosciences critical care unit at a tertiary neurosciences centre. Despite prompt surgical decompression, he did not regain function. Extubation was unsuccessful on three occasions. Following discussion between the patient and his family, ventilation was withdrawn, and he died the following day. This case highlights the potentially devastating consequences of DCM and poses questions about the aetiology of DCM.

Combination of pricing and inventory policies for deteriorating products with sustainability considerations.

Economic, environmental, and social criteria are all being taken into consideration simultaneously when determining pricing policies or inventory levels in sustainable production management. The combination of pricing and inventory policies is an important source of leverage for the efficient management of perishable products. This paper, among the first studies, proposes the problem of devising optimal pricing and inventory management decisions simultaneously where the environmental and social criteria are contributed for perishable complementary products replenished and sold by the same company. This study considers two interrelated price-sensitive linear demand functions to consider the possibility of shortage with both budget and warehouse capacity constraints. Another contribution of the proposed model is to consider an upper bound for environmental pollution and a lower bound for job opportunities as the constraints to the model. As a complex optimization model, the challenge of complexity is addressed by a heuristic algorithm for finding an optimal solution. After an extensive analysis using numerical examples, some managerial insights are concluded from the results. One finding from these analyses confirms that the total capacity of the warehouse, the total available budget, carbon emissions, and variable job opportunities have a high impact on the optimal solution to find a balance between sustainability criteria for making pricing and inventory policies.

Perfusate Composition and Duration of Ex-Vivo Normothermic Perfusion in Kidney Transplantation: A Systematic Review.

Ex-vivo normothermic perfusion (EVNP) is an emerging strategy in kidney preservation that enables resuscitation and viability assessment under pseudo-physiological conditions prior to transplantation. The optimal perfusate composition and duration, however, remain undefined. A systematic literature search (Embase; Medline; Scopus; and BIOSIS Previews) was conducted. We identified 1,811 unique articles dating from January 1956 to July 2021, from which 24 studies were deemed eligible for qualitative analysis. The perfusate commonly used in clinical practice consisted of leukocyte-depleted, packed red blood cells suspended in Ringer's lactate solution with Mannitol, dexamethasone, heparin, sodium bicarbonate and a specific nutrient solution supplemented with insulin, glucose, multivitamins and vasodilators. There is increasing support in preclinical studies for non-blood cell-based perfusates, including Steen solution, synthetic haem-based oxygen carriers and acellular perfusates with supraphysiological carbogen mixtures that support adequate oxygenation whilst also enabling gradual rewarming. Extended durations of perfusion (up to 24 h) were also feasible in animal models. Direct comparison between studies was not possible due to study heterogeneity. Current evidence demonstrates safety with the aforementioned widely used protocol, however, extracellular base solutions with adequate oxygenation, supplemented with nutrient and metabolic substrates, show promise by providing a suitable environment for prolonged preservation and resuscitation. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021231381, identifier PROSPERO 2021 CRD42021231381.

A hybrid computational intelligence approach for bioremediation of amoxicillin based on fungus activities from soil resources and aflatoxin B1 controls.

Nowadays, releasing the Emerging Pollutants (EPs) in the nature is one of the main reasons for many health and environmental disasters. Amoxicillin as an antibiotic is one of the EPs and categorized as the Endocrine Disrupting Compounds (EDCs) in hazardous materials. Accumulation of amoxicillin in the soil bulk increases the cancer risk, drug resistances and other epidemiological diseases. Hence, the soil bioremediation of antibiotics can be a solution for this problem which is more environmental-friendly system. This study technically creates a bio-engine setup in soil bulk for remediation of amoxicillin based on Aspergillus Flavus (AF) activities and Removal Percentage (RP) of amoxicillin with Aflatoxin B1 Generation (AG) controls. The main novelty is to propose a hybrid computational intelligence approach to do optimization for mechanical and biological aspects and to predict the behavior of bio-engine's effective mechanical and biological features in an intelligent way. The optimization model is formulated by the Central Composite Design (CCD) which is set by the Response Surface Methodology (RSM). The prediction model is formulated by the Random Forest (RF), Adaptive Neuro Fuzzy Inference System (ANFIS) and Random Tree (RT) algorithms. According to the experimental practices from real soil samples in different times and places, concentration of amoxicillin and Aflatoxin B1 are set equal to 25 mg/L (ppm) and 15 µg/L (ppb). Likewise, the outcomes of experiments in CCD-RSM computations are evaluated by curve fitting comparisons between linear, 2FI, quadratic and cubic polynomial equations with considering to regression coefficient and predicted regression coefficient values, ANOVA and optimization by sequential differentiation. Based on the results of CCD-RSM, the RP performance in the optimum conditions is measured around 86% and in 25 days after runtime, the RP and AG are balanced in the safe mode. The proposed hybrid model achieves the 0.99 accuracy. The applicability of the research is done using real field evaluations from drug industrial park in Mashhad city in Iran. Finally, a broad analysis is done and managerial insights are concluded. The main findings of the present research are: (I) with application of bioremediation from fungus activities, amoxicillin amounts can be control in soil resources with minimum AG, (II) ANFIS model has the best accuracy for smart monitoring of amoxicillin bioremediation in soil environments and (III) based on the statistical assessments Aeration Intensity and AF/Biological Waste ratio are most effective on the amoxicillin removal percentage.

Investigation of cholestasis-related changes in characteristics of spermatogonial stem cells in testis tissue of male Wistar rats.

Paternal metabolic status is an important factor in the health status of offspring. Cholestasis, as a metabolic disorder, significantly disrupts spermatogenesis. Spermatogonial stem cells (SSCs) are considered the dividing germ cells, which maintain spermatogenesis throughout the lifespan. Here, we investigated the in vivo and in vitro effect(s) of cholestasis on SSCs. Cholestasis was induced in rats by bile duct ligation. Four weeks after the cholestasis induction, testicular tissues were analysed using histopathological examinations. The expression of SSC markers, including Plzf and Thy-1, was determined using the immunofluorescent technique. Also, SSCs were isolated from animals, and their proliferation was examined in vitro. The histological examinations revealed that cholestasis caused irregularities in the structure of seminal tubes. Immunostaining showed that the total number of Thy-1- and Plzf-expressing cells was declined in the cholestasis group compared with the control group. In vitro culture of SSCs indicated that the number of SSC colonies and those expressing Plzf were significantly reduced in the culture medium of the cholestasis group. Our results indicated that cholestasis affects the functionality of SSCs and reduces the number and proliferation of them. This finding may be of interest to the effect of metabolic diseases such as cholestasis on spermatogenesis.

Sustainable closed-loop supply chain network for an integrated water supply and wastewater collection system under uncertainty.

Today, an increase in the drought and water shortage all around the world is a challengeable threat for different governments and international committees. Water supply chain aims to manage the water consumption and to control the water shortage. Contrary to most of previous studies focused on the forward directions of the water supply chain, this paper also considers the reverse logistics known as a Closed-Loop Supply Chain (CLSC). Hence, an integrated Water Supply and Wastewater Collection System (WSWCS) under uncertainty is proposed. Furthermore, regarding the trend of sustainable development, the environmental dimensions and social benefits of the integrated WSWCS are contributed. To meet the standards of the sustainable development in developing countries, a case study in Iran is applied to a novel multi-objective stochastic optimization model based on triple bottom lines of sustainability. Having already been employed to similar optimization problems, the Social Engineering Optimizer (SEO) has been never applied in this research area. Another innovation of this study is to introduce an improved multi-objective SEO to solve this complicated model. Eventually, with regards to an extensive comparison contributing to the Pareto-based metrics and different sensitivities, some managerial implications are concluded as the main findings.

A bi-objective home healthcare routing and scheduling problem considering patients' satisfaction in a fuzzy environment.

Home care services are an alternative answer to hospitalization, and play an important role in reducing the healthcare costs for governments and healthcare practitioners. To find a valid plan for these services, an optimization problem called the home healthcare routing and scheduling problem is motivated to perform the logistics of the home care services. Although most studies mainly focus on minimizing the total cost of logistics activities, no study, as far as we know, has treated the patients' satisfaction as an objective function under uncertainty. To make this problem more practical, this study proposes a bi-objective optimization methodology to model a multi-period and multi-depot home healthcare routing and scheduling problem in a fuzzy environment. With regards to a group of uncertain parameters such as the time of travel and services as well as patients' satisfaction, a fuzzy approach named as the Jimenez's method, is also utilized. To address the proposed home healthcare problem, new and well-established metaheuristics are obtained. Although the social engineering optimizer (SEO) has been applied to several optimization problems, it has not yet been applied in the healthcare routing and scheduling area. Another innovation is to develop a new modified multi-objective version of SEO by using an adaptive memory strategy, so-called AMSEO. Finally, a comprehensive discussion is provided by comparing the algorithms based on multi-objective metrics and sensitivity analyses. The practicality and efficiency of the AMSEO in this context lends weight to the development and application of the approach more broadly.

Laying the Foundations of Lifelong Health at the Beginning of Life: Islamic Perspective.

In this systematic literature review, all the Shiite-Islamic documents (Quran and Hadith) without any time limitation were surveyed, analyzed and synthesized for the purpose of determining the foundations of lifelong health. The data were analyzed and combined using inductive qualitative content analysis method. Two main categories were emerged from the analysis: "prevention of health problems" and "health maintenance and promotion." In conclusion based on Islamic perspective, the foundations of comprehensive health of a person, i.e., health in all physical, mental, social, and spiritual dimensions, are begun to form at four stages: the time of marriage of his parents, the moment of their conception, when he is unborn in his mother womb, and during infancy period. Observing religion instructions in this regard is not the sufficient condition for being completely healthy; however, such instructions can provide a base for being a healthy person.

Finite Element Analysis for Degenerative Cervical Myelopathy: Scoping Review of the Current Findings and Design Approaches, Including Recommendations on the Choice of Material Properties.

BACKGROUND: Degenerative cervical myelopathy (DCM) is a slow-motion spinal cord injury caused via chronic mechanical loading by spinal degenerative changes. A range of different degenerative changes can occur. Finite element analysis (FEA) can predict the distribution of mechanical stress and strain on the spinal cord to help understand the implications of any mechanical loading. One of the critical assumptions for FEA is the behavior of each anatomical element under loading (ie, its material properties). OBJECTIVE: This scoping review aims to undertake a structured process to select the most appropriate material properties for use in DCM FEA. In doing so, it also provides an overview of existing modeling approaches in spinal cord disease and clinical insights into DCM. METHODS: We conducted a scoping review using qualitative synthesis. Observational studies that discussed the use of FEA models involving the spinal cord in either health or disease (including DCM) were eligible for inclusion in the review. We followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The MEDLINE and Embase databases were searched to September 1, 2021. This was supplemented with citation searching to retrieve the literature used to define material properties. Duplicate title and abstract screening and data extraction were performed. The quality of evidence was appraised using the quality assessment tool we developed, adapted from the Newcastle-Ottawa Scale, and shortlisted with respect to DCM material properties, with a final recommendation provided. A qualitative synthesis of the literature is presented according to the Synthesis Without Meta-Analysis reporting guidelines. RESULTS: A total of 60 papers were included: 41 (68%) "FEA articles" and 19 (32%) "source articles." Most FEA articles (33/41, 80%) modeled the gray matter and white matter separately, with models typically based on tabulated data or, less frequently, a hyperelastic Ogden variant or linear elastic function. Of the 19 source articles, 14 (74%) were identified as describing the material properties of the spinal cord, of which 3 (21%) were considered most relevant to DCM. Of the 41 FEA articles, 15 (37%) focused on DCM, of which 9 (60%) focused on ossification of the posterior longitudinal ligament. Our aggregated results of DCM FEA indicate that spinal cord loading is influenced by the pattern of degenerative changes, with decompression alone (eg, laminectomy) sufficient to address this as opposed to decompression combined with other procedures (eg, laminectomy and fusion). CONCLUSIONS: FEA is a promising technique for exploring the pathobiology of DCM and informing clinical care. This review describes a structured approach to help future investigators deploy FEA for DCM. However, there are limitations to these recommendations and wider uncertainties. It is likely that these will need to be overcome to support the clinical translation of FEA to DCM.

Mini-MEndR: a miniaturized 96-well predictive assay to evaluate muscle stem cell-mediated repair.

Background: Functional evaluation of molecules that are predicted to promote stem cell mediated endogenous repair often requires in vivo transplant studies that are low throughput and hinder the rate of discovery. To offer greater throughput for functional validation studies, we miniaturized, simplified and expanded the functionality of a previously developed muscle endogenous repair (MEndR) in vitro assay that was shown to capture significant events of in vivo muscle endogenous repair. Methods: The mini-MEndR assay consists of miniaturized cellulose scaffolds designed to fit in 96-well plates, the pores of which are infiltrated with human myoblasts encapsulated in a fibrin-based hydrogel to form engineered skeletal muscle tissues. Pre-adsorbing thrombin to the cellulose scaffolds facilitates in situ tissue polymerization, a critical modification that enables new users to rapidly acquire assay expertise. Following the generation of the 3D myotube template, muscle stem cells (MuSCs), enriched from digested mouse skeletal muscle tissue using an improved magnetic-activated cell sorting protocol, are engrafted within the engineered template. Murine MuSCs are fluorescently labeled, enabling co-evaluation of human and mouse Pax7+ cell responses to drug treatments. A regenerative milieu is introduced by injuring the muscle tissue with a myotoxin to initiate endogenous repair "in a dish". Phenotypic data is collected at endpoints with a high-content imaging system and is analyzed using ImageJ-based image analysis pipelines. Results: The miniaturized format and modified manufacturing protocol cuts reagent costs in half and hands-on seeding time ~ threefold, while the image analysis pipelines save 40 h of labour. By evaluating multiple commercially available human primary myoblast lines in 2D and 3D culture, we establish quality assurance metrics for cell line selection that standardizes myotube template quality. In vivo outcomes (enhanced muscle production and Pax7+ cell expansion) to a known modulator of MuSC mediated repair (p38/ß MAPK inhibition) are recapitulated in the miniaturized culture assay, but only in the presence of stem cells and the regenerative milieu. Discussion: The miniaturized predictive assay offers a simple, scaled platform to co-investigate human and mouse skeletal muscle endogenous repair molecular modulators, and thus is a promising strategy to accelerate the muscle endogenous repair discovery pipeline. Supplementary Information: The online version contains supplementary material available at 10.1186/s44330-024-00005-4.

Brain MRI changes in degenerative cervical myelopathy: a systematic review.

BACKGROUND: Degenerative cervical myelopathy (DCM) is the most common cause of adult spinal cord dysfunction globally. Associated neurological symptoms and signs have historically been explained by pathobiology within the cervical spine. However, recent advances in imaging have shed light on numerous brain changes in patients with DCM, and it is hypothesised that these changes contribute to DCM pathogenesis. The aetiology, significance, and distribution of these supraspinal changes is currently unknown. The objective was therefore to synthesise all current evidence on brain changes in DCM. METHODS: A systematic review was performed. Cross-sectional and longitudinal studies with magnetic resonance imaging on a cohort of patients with DCM were eligible. PRISMA guidelines were followed. MEDLINE and Embase were searched to 28th August 2023. Duplicate title/abstract screening, data extraction and risk of bias assessments were conducted. A qualitative synthesis of the literature is presented as per the Synthesis Without Meta-Analysis (SWiM) reporting guideline. The review was registered with PROSPERO (ID: CRD42022298538). FINDINGS: Of the 2014 studies that were screened, 47 studies were identified that used MRI to investigate brain changes in DCM. In total, 1500 patients with DCM were included in the synthesis, with a mean age of 53 years. Brain alterations on MRI were associated with DCM both before and after surgery, particularly within the sensorimotor network, visual network, default mode network, thalamus and cerebellum. Associations were commonly reported between brain MRI alterations and clinical measures, particularly the Japanese orthopaedic association (JOA) score. Risk of bias of included studies was low to moderate. INTERPRETATION: The rapidly expanding literature provides mounting evidence for brain changes in DCM. We have identified key structures and pathways that are altered, although there remains uncertainty regarding the directionality and clinical significance of these changes. Future studies with greater sample sizes, more detailed phenotyping and longer follow-up are now needed. FUNDING: ODM is supported by an Academic Clinical Fellowship at the University of Cambridge. BMD is supported by an NIHR Clinical Doctoral Fellowship at the University of Cambridge (NIHR300696). VFJN is supported by an NIHR Rosetrees Trust Advanced Fellowship (NIHR302544). This project was supported by an award from the Rosetrees Foundation with the Storygate Trust (A2844).

The significance of metabolic disease in degenerative cervical myelopathy: a systematic review.

Introduction: Degenerative cervical myelopathy (DCM) is a form of chronic spinal cord injury, with a natural history of potential for progression over time. Whilst driven by mechanical stress on the spinal cord from degenerative and congenital pathology, the neurological phenotype of DCM is likely to be modified by multiple systemic factors. The role of metabolic factors is therefore of interest, particularly given that ischaemia is considered a key pathological mechanism of spinal cord injury. The objective was therefore to synthesise current evidence on the effect of metabolism on DCM susceptibility, severity, and surgical outcomes. Methods: A systematic review in MEDLINE and Embase was conducted following PRISMA guidelines. Full-text papers in English, with a focus on DCM and metabolism, including diabetes, cardiovascular disease, anaemia, and lipid profile, were eligible for inclusion. Risk of methodological bias was assessed using the Joanna Briggs Institute (JBI) critical assessment tools. Quality assessments were performed using the GRADE assessment tool. Patient demographics, metabolic factors and the relationships between metabolism and spinal cord disease, spinal column disease and post-operative outcomes were assessed. Results: In total, 8,523 papers were identified, of which 57 met criteria for inclusion in the final analysis. A total of 91% (52/57) of included papers assessed the effects of diabetes in relation to DCM, of which 85% (44/52) reported an association with poor surgical outcomes; 42% of papers (24/57) discussed the association between cardiovascular health and DCM, of which 88% (21/24) reported a significant association. Overall, DCM patients with diabetes or cardiovascular disease experienced greater perioperative morbidity and poorer neurological recovery. They were also more likely to have comorbidities such as obesity and hyperlipidaemia. Conclusion: Metabolic factors appear to be associated with surgical outcomes in DCM. However, evidence for a more specific role in DCM susceptibility and severity is uncertain. The pathophysiology and natural history of DCM are critical research priorities; the role of metabolism is therefore a key area for future research focus. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier: CRD42021268814.

An intelligent decision support system for groundwater supply management and electromechanical infrastructure controls.

This study presents an intelligent Decision Support System (DSS) aimed at bridging the theoretical-practical gap in groundwater management. The ongoing demand for sophisticated systems capable of interpreting extensive data to inform sustainable groundwater decision-making underscores the critical nature of this research. To meet this challenge, telemetry data from six randomly selected wells were used to establish a comprehensive database of groundwater pumping parameters, including flow rate, pressure, and current intensity. Statistical analysis of these parameters led to the determination of threshold values for critical factors such as water pressure and electrical current. Additionally, a soft sensor was developed using a Random Forest (RF) machine learning algorithm, enabling real-time forecasting of key variables. This was achieved by continuously comparing live telemetry data to pump design specifications and results from regular field testing. The proposed machine learning model ensures robust empirical monitoring of well and pump health. Furthermore, expert operational knowledge from water management professionals, gathered through a Classical Delphi (CD) technique, was seamlessly integrated. This collective expertise culminated in a data-driven framework for sustainable groundwater facilities monitoring. In conclusion, this innovative DSS not only addresses the theory-application gap but also leverages the power of data analytics and expert knowledge to provide high-precision online insights, thereby optimizing groundwater management practices.

Novel paraneoplastic mechanism for cerebellar ataxia in Erdheim-Chester disease.

We report a case of BRAF-mutation positive Erdheim-Chester disease presenting with a cerebellar ataxia. This is the first such case to be reported without structural MRI abnormalities but with a single intrathecally produced oligoclonal band. Now that the histiocytoses have been recharacterised as neoplastic, we speculate that the mechanism of the ataxia in our case is paraneoplastic. We highlight the importance of searching for BRAF mutations in this disease, as their presence leads to effective personalised treatments.

Analysis of Incidence and Reasons for Re-intervention After Aortic Valve Replacement Using the Trifecta Aortic Bioprosthesis.

Trifecta bioprosthesis claims favorable hemodynamic performance. However, reports of structural valve deterioration (SVD) raise concerns of its long-term durability. We assessed outcomes with the Trifecta valve over a 10-year period. All patients receiving Trifecta bioprostheses between October 2011 and October 2020 were included. Perioperative and survival characteristics were prospectively collated in an independent database. Re-intervention was recorded as a surrogate for SVD. Nine hundred and forty-four patients (mean age 72.82 years ± 8.13, 58% male) underwent aortic valve replacement with the Trifecta valve. At 10-years, 1.4% of patients required a redo operation, giving an overall freedom from re-intervention of 98.6%. The mean time to re-intervention was 48.87 months. Survival was 73.58% and 76.92% in patients who did not require re-intervention vs re-intervention group, respectively. In a large, single-center cohort, the Trifecta aortic bioprosthesis had a 1.4% all-cause re-intervention rate at 10-years, with insignificant impact on survival.

Meeting the Shared Goals of a Student-Selected Component: Pilot Evaluation of a Collaborative Systematic Review.

BACKGROUND: Research methodology is insufficiently featured in undergraduate medical curricula. Student-selected components are designed to offer some research opportunities but frequently fail to meet student or supervisor expectations, such as completion or publication. We hypothesized that a collaborative, educational approach to a systematic review (SR), whereby medical students worked together, may improve student experience and increase success. OBJECTIVE: This study aimed to establish whether offering a small team of students the opportunity to take part in the screening phase of SRs led by an experienced postgraduate team could enhance the learning experience of students, overcome the barriers to successful research engagement, and deliver published output. METHODS: Postgraduate researchers from the University of Cambridge led a team of 14 medical students to work on 2 neurosurgical SRs. One student was appointed as the lead for each SR. All students were provided with training on SR methodology and participated in title and abstract screening using Rayyan software. Students completed prepilot, midscreening, and postscreening questionnaires on their research background, perceptions, knowledge, confidence, and experience. Questions were scored on a Likert scale of 1 (strongly disagree) to 10 (strongly agree). RESULTS: Of the 14 students involved, 29% (n=4) reported that they had received sufficient training in research methodology at medical school. Positive trends in student knowledge, confidence, and experience of SR methodology were noted across the 3 questionnaire time points. Mean responses to "I am satisfied with the level of guidance I am receiving," "I am enjoying being involved in the SR process," and "I could not gain this understanding of research from passive learning e.g., textbook or lecture" were greater than 8.0 at all time points. Students reported "being involved in this research has made me more likely to do research in the future" (mean 8.57, SD 1.50) and that "this collaborative SR improved my research experience" (mean 8.50, SD 1.56). CONCLUSIONS: This collaborative approach appears to be a potentially useful method of providing students with research experience; however, it requires further evaluation.

Wildlife resource conservation and utilization for achieving sustainable development in China: main barriers and problem identification.

The rapid growth of the industrial economy has affected the survival of wildlife, and the decline in wildlife resources will in turn have some negative impact on the industrial economy. For the sustainable development of the industrial economy, human beings began to reflect on traditional development thinking and strive to find a development strategy that harmonizes industrial economic development and resource protection, and wildlife protection gradually attracted people's attention. "Protecting wild animals, maintaining ecological balance, and promoting economic development" has become a hot topic in the new century. Wildlife resources are valuable natural resources and play an important role in the ecosystem, which is related to the well-being and future of human beings. In recent years, China has made great progress in wildlife protection, while protecting and expanding wildlife habitats, introducing relevant laws and regulations, and other measures which have been implemented recently. However, there are still shortcomings in the protection of wildlife in China. Over-utilization, habitat loss and degradation, environmental pollution, climate change, weak legal awareness, and indiscriminate hunting all pose serious threats to wildlife in China. In this regard, this paper summarizes the main problems and barriers to wildlife resource conservation and utilization in China. Based on the analytic hierarchy process (AHP), the main technology factors influencing wildlife resource conservation and utilization in China are identified. Finally, the future research development direction of wildlife conservation is discussed based on the critical factors. This can provide some guidance for developing wildlife resource conservation and utilization for a sustainable ecosystem in China.

Application and planning of an energy-oriented stochastic disassembly line balancing problem.

End-of-life (EOL) products are getting more and more attention as a result of the rapid decline in environmental resources and the dramatic rise in population at the moment. Disassembly is a crucial step in the reuse of EOL products. However, the disassembly process for EOL products is highly uncertain, and the disassembly planning method may not produce the anticipated outcomes in actual implementation. Based on the physical nature of the product disassembly process with multiple uncertain variables, certainty disassembly cannot adequately characterize the uncertain variables effectively. Uncertainty disassembly takes into account the changes in parts caused by product use, such as wear and corrosion, which can better coordinate the arrangement of disassembly tasks and better match the actual remanufacturing process. After analysis, it was found that most of studies on uncertain disassembly focus on the economic efficiency perspective and lack of energy consumption considerations. For the gaps in the current study, this paper proposes a stochastic energy consumption disassembly line balance problem (SEDLBP) and constructs a mathematical model of SEDLBP based on the disassembly of spatial interference matrix, In this model, the energy consumption generated by the disassembly operation and workstation standby is not a constant value but is generated stochastically in a uniformly distributed interval. In addition, an improved social engineering optimization algorithm that incorporates stochastic simulation (SSEO) is proposed in this paper to effectively address the issue. The incorporation of swap operators and swap sequences in SSEO makes it possible to solve discrete optimization problems efficiently. A comparison of a case study with some well-tested intelligent algorithms demonstrates the efficacy of the solutions produced by the proposed SSEO.

A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems.

With the increasing severity of environmental problems, low-carbon development has become an inevitable choice. Nowadays, low-carbon green sustainable development is influenced by a variety of factors such as social, environmental, technological, and economic development levels, making its development complex, which in turn imposes challenges on decision-makers. In this context, the application of multi-criteria decision-making (MCDM) in different areas of sustainable development engineering has become a hot topic. Although many reviews of MCDM techniques already exist, there is a lack of holistic review efforts on MCDM in the field of low-carbon transport and green logistics. Considering these shortcomings in the state of the art, this paper systematically reviews more than 190 papers from 2010 to 2022, constructs a general structure of MCDM techniques for this research topic, provides a comprehensive review and analysis of it, and clarifies the current practices. Furthermore, future directions for the development of MCDM techniques for green logistics and low-carbon transportation systems are presented as well.