Search Results (707)

With deepening global higher education reforms, outcome-based education has emerged as the core paradigm for teaching model innovation. This study investigates the structural dependencies and teaching effectiveness of the Environmental Design curriculum at Hubei Engineering University in medium-sized cities, China, addressing challenges of enrollment decline and market contraction critical for urban sustainability. Using network analysis, we construct curriculum support and contribution networks and course temporal networks to assess structural dependencies and teaching effectiveness, revealing structural patterns and optimizing the OBE-based Environmental Design curriculum to enhance educational quality and student competencies. Analysis reveals computer basic courses as knowledge transmission hubs, creating a course network with a distinct core–periphery structure. Technical course reforms significantly outperform theoretical course reforms in improving student performance metrics, such as higher average scores, better grade distributions, and reduced performance gaps, while innovative practice courses show peripheral isolation patterns, indicating limited connectivity with core curriculum modules, which reduces their educational impact. These findings provide empirical insights for curriculum optimization, supporting urban sustainable development through enhanced professional talent cultivation equipped to address environmental challenges like sustainable design practices and resource-efficient urban planning. Network analysis applications introduce innovative frameworks for curriculum reform strategies. Future research expansion through larger sample validation will support urban sustainable development goals and enhance professional talent cultivation outcomes. Full article

Wellington, New Zealand, is highly vulnerable to disaster-induced food security crises due to its geography and geological characteristics, which can disrupt transportation and isolate the city following disasters. Urban agriculture (UA) has been proposed as a potential alternative food source for post-disaster scenarios. This study examined the potential of urban agriculture for enhancing post-disaster food security by calculating vegetable self-sufficiency rates. Specifically, it evaluated the capacity of current Wellington’s community gardens to meet post-disaster vegetable demand in terms of both weight and nutrient content. Data collection employed mixed methods with questionnaires, on-site observations and mapping, and collecting high-resolution aerial imagery. Garden yields were estimated using self-reported data supported by literature benchmarks, while cultivated areas were quantified through on-site mapping and aerial imagery analysis. Six post-disaster food demand scenarios were used based on different target populations to develop an understanding of the range of potential produce yields. Weight-based results show that community gardens currently supply only 0.42% of the vegetable demand for residents living within a five-minute walk. This rate increased to 2.07% when specifically targeting only vulnerable populations, and up to 10.41% when focusing on gardeners’ own households. However, at the city-wide level, the current capacity of community gardens to provide enough produce to feed people remained limited. Nutrient-based self-sufficiency was lower than weight-based results; however, nutrient intake is particularly critical for vulnerable populations after disasters, underscoring the greater challenge of ensuring adequate nutrition through current urban food production. Beyond self-sufficiency, this study also addressed the role of UA in promoting food diversity and acceptability, as well as its social and psychological benefits based on the questionnaires and on-site observations. The findings indicate that community gardens contribute meaningfully to post-disaster food security for gardeners and nearby residents, particularly for vulnerable groups with elevated nutritional needs. Despite the current limited capacity of community gardens to provide enough produce to feed residents, findings suggest that Wellington could enhance post-disaster food self-reliance by diversifying UA types and optimizing land-use to increase food production during and after a disaster. Realizing this potential will require strategic interventions, including supportive policies, a conducive social environment, and diversification—such as the including private yards—all aimed at improving food access, availability, and nutritional quality during crises. The primary limitation of this study is the lack of comprehensive data on urban agriculture in Wellington and the wider New Zealand context. Addressing this data gap should be a key focus for future research to enable more robust assessments and evidence-based planning. Full article

SARS-CoV-2 undergoes frequent mutations that drive viral evolution and genomic diversity, influencing transmissibility, immune escape, and disease severity. In this study, we performed whole-genome sequencing on SARS-CoV-2 isolates from patients in New York City and identified several globally rare mutations across multiple viral lineages. The isolates analyzed for rare mutations belonged to three lineages: B.1.1.7 (Alpha), B.1.526 (Iota), and B.1.623. We identified 16 rare mutations (global incidence <1000) in non-structural protein genes, including nsp2, nsp3, nsp4, nsp6, nsp8, nsp13, nsp14, ORF7a, and ORF8. Three of these mutations—located in nsp2, nsp13, and ORF8—have been reported in fewer than 100 individuals worldwide. We also detected five rare mutations in structural proteins (S, M, and N), including two—one in M and one in N—previously reported in fewer than 100 cases globally. We present clinical profiles of three patients, each infected with genetically distinct viral isolates from the three lineages studied. Furthermore, we illustrate a local transmission chain inferred from unique mutation patterns identified in the Omicron genome. These findings underscore the importance of whole-genome sequencing for detecting rare mutations, tracking community spread, and identifying emerging variants with clinical and public health significance. Full article

Yeasts possess a range of environmental adaptations that allow them to colonize soil and sand. They can circulate seasonally between different components of lake ecosystems, including beach sand, water, and the coastal phyllosphere. The accumulation of people on beaches promotes the development and transmission of yeasts, posing an increasing sanitary and epidemiological risk. The aim of this study was to determine the species and quantitative composition of potentially pathogenic and pathogenic yeasts for humans present in the sand of supervised and unsupervised beaches along the shores of lakes in the city of Olsztyn (northeastern Poland). The study material consisted of sand samples collected during two summer seasons (2019; 2020) from 12 research sites on sandy beaches of four lakes located within the administrative boundaries of Olsztyn. Standard isolation and identification methods used in diagnostic mycological laboratories were applied and are described in detail in the following sections of this study. A total of 259 yeast isolates (264, counting species in two-species isolates separately) belonging to 62 species representing 47 genera were obtained during the study. Among all the isolates, five were identified as mixed (two species from a single colony). Eight isolated species were classified into biosafety level 2 (BSL-2) and risk group 2 (RG-2). The highest average number of viable yeast cells was found in sand samples collected in July 2019 (5.56 × 10² CFU/g), August, and September 2020 (1.03 × 10³ CFU/g and 1.94 × 10³ CFU/g, respectively). The lowest concentrations were in samples collected in April, September, and October 2019, and October 2020 (1.48 × 10² CFU/g, 1.47 × 10² CFU/g, 1.40 × 10² CFU/g, and 1.40 × 10² CFU/g, respectively). The results indicate sand contamination with yeasts that may pose etiological factors for human mycoses. In light of these findings, continuous sanitary-epidemiological monitoring of beach sand and further studies on its mycological cleanliness are warranted, along with actions leading to appropriate legal regulations. Full article

Among synanthropic species, European hedgehogs are widely distributed throughout Europe. In recent decades, these animals have increasingly adapted to anthropogenic environments, where they find abundant shelter and food resources, along with fewer natural predators. As with other wildlife, it is likely that their coexistence in cities is also affecting their microbiota, promoting the development of antimicrobial resistance (AMR). This study aimed to assess the occurrence and patterns of AMR in commensal enteric Escherichia coli isolated from hedgehogs (n = 53) living in anthropogenic environments upon admission to a wildlife rescue center in Turin (Italy). The effects of hospitalization on the prevalence and trends of AMR were also assessed. Our results confirm that hedgehogs can harbor resistant E. coli upon admission, in particular against cefazolin (41.5%), ampicillin (37.7%), and enrofloxacin (22.6%). In addition, hospitalization promoted an increase in minimum inhibitory concentration (MIC) values of all antibiotics except imipenem, which led to a significant increase in E. coli that was resistant towards doxycycline, enrofloxacin, and trimethoprim-sulfamethoxazole. Admitted hedgehogs were also carriers of extended-spectrum beta-lactamase-producing E. coli (5.7%), whose presence increased during hospitalization (to 20.8%). These results highlight the role of hospitalizations longer than five days in the acquisition of AMR and suggest that European hedgehogs can become potential carriers of resistant E. coli following hospitalization. Full article

The widespread integration of electric vehicles (EVs) into smart grid infrastructures necessitates intelligent and robust battery health diagnostics to ensure system resilience and performance longevity. While numerous studies have addressed the estimation of State of Health (SOH) and the prediction of remaining useful life (RUL) using machine and deep learning, most existing models fail to capture both short-term degradation trends and long-range contextual dependencies jointly. In this study, we introduce V2G-HealthNet, a novel hybrid deep learning framework that uniquely combines Long Short-Term Memory (LSTM) networks with Transformer-based attention mechanisms to model battery degradation under dynamic vehicle-to-grid (V2G) scenarios. Unlike prior approaches that treat SOH estimation in isolation, our method directly links health prediction to operational decisions by enabling SOH-informed adaptive load scheduling and predictive maintenance across EV fleets. Trained on over 3400 proxy charge-discharge cycles derived from 1 million telemetry samples, V2G-HealthNet achieved state-of-the-art performance (SOH RMSE: 0.015, MAE: 0.012, $R^2$: 0.97), outperforming leading baselines including XGBoost and Random Forest. For RUL prediction, the model maintained an MAE of 0.42 cycles over a five-cycle horizon. Importantly, deployment simulations revealed that V2G-HealthNet triggered maintenance alerts at least three cycles ahead of critical degradation thresholds and redistributed high-load tasks away from ageing batteries—capabilities not demonstrated in previous works. These findings establish V2G-HealthNet as a deployable, health-aware control layer for smart city electrification strategies. Full article

Developing agricultural new productive forces (ANPF) according to local conditions is a key strategy for agricultural modernization. Using panel data from 16 prefecture-level cities in Anhui Province from 2010 to 2022, this study constructed indicator systems for ANPF and the construction of a strong agricultural province (CSAP). The entropy-weight TOPSIS method was used to calculate the levels of ANPF and the SAP index. This study employed a modified gravity model and social network analysis (SNA) to investigate the spatial correlation and evolutionary characteristics of these networks. Geographical detectors were also used to identify the driving factors behind agricultural transformation. The findings indicate that both ANPF and CSAP showed an upward trend during the study period, with significant regional heterogeneity, with Central Anhui being the most prominent. This study revealed spatial spillover effects and strong network correlations between ANPF and CSAP, with the spatial network structure exhibiting characteristics of multi-core, multi-association, and multidimensional connections. The entities within the network are tightly connected, with no “isolated island” phenomenon, and Hefei, as the central hub, showed the highest number of connections. Laborer quality, tangible means of production, and new-quality industries emerged as the core driving forces, working in synergy to propel CSAP. This study contributes new insights into the spatial network dynamics of agricultural development and offers actionable recommendations for policymakers to enhance agricultural modernization globally. Full article

In the context of globalization and the Belt and Road Initiative, maintaining the stability and security of the China Railway Express network (CRN) is critical for international logistics operations. However, unexpected events can lead to node and edge failures within the CRN, potentially triggering cascading failures that critically compromise network performance. This study introduces a Coupled Map Lattice model that incorporates cargo flow dynamics, distributing cargo based on distance and the residual capacity of neighboring nodes. We analyze cascading failures in the CRN under three scenarios, isolated node failure, isolated edge disruption, and simultaneous node and edge failure, to assess the network’s vulnerability during emergencies. Our findings show that deliberate attacks targeting cities with high node strength result in more significant damage than attacks on cities with a high node degree or betweenness. Additionally, when edges are disrupted by unexpected events, the impact of edge removals on cascading failures depends on their strategic position and connections within the network, not just their betweenness and weight. The study further reveals that removing collinear edges can effectively slow the propagation of cascading failures in response to deliberate attacks. Furthermore, a single-factor cargo flow allocation method significantly enhances the network’s resilience against edge failures compared to node failures. These insights provide practical guidance and strategic support for the CR Express in mitigating the effects of both unforeseen events and intentional attacks. Full article

Brown spot, caused by Alternaria alternata, is the most important leaf fungal disease threatening kiwifruit production in China, and it is typically controlled through the application of fungicides, such as procymidone and difenoconazole. To date, fungicide resistance development has not yet been systematically reported for the pathogen of kiwifruit. A total of 135 single-conidium A. alternata isolates were collected from different cities in Zhejiang Province, China. Alternaria alternata developed prevailing resistance to procymidone and initial resistance to difenoconazole, with resistance frequencies of 60.7 and 13.3%, respectively. Positive cross-resistance was observed between procymidone and iprodione but not between procymidone and difenoconazole, tebuconazole, prochloraz, pydiflumetofen, pyraclostrobin, or thiophanate-methyl. Moreover, no cross-resistance was observed between difenoconazole and all other tested fungicides, including the two other demethylation inhibitors, tebuconazole and prochloraz. A fitness penalty was not detected in procymidone-resistant (Pro^R) or difenoconazole-resistant (Dif^R) isolates. However, double-resistant (Pro^R Dif^R) isolates had a fitness penalty, showing significantly decreased sporulation, germination, and pathogenicity. The P894L single point mutation, caused by the change from CCA to CTA at the 894th codon of Os1, was detected in Pro^R isolates. Molecular dynamic simulation showed that the P894L mutation significantly decreased the inhibitory activity of procymidone against AaOs1 in A. alternata. These results provide insight into the development and characteristics of fungicide resistance, offering guidance for the study and management of kiwifruit diseases. Full article

With the increase in keeping exotic companion mammals as pets, concerns about antimicrobial resistance (AMR) and its impact on animal and human health are growing. Guinea pigs, a popular pet in Hong Kong and globally, have limited studies regarding antimicrobial culture and sensitivity results. We reviewed bacteriologic and antimicrobial sensitivity results from clinically ill pet guinea pigs from 2019 to 2023 using data from the City University Veterinary Diagnostic Laboratory. Of the 234 clinical samples from 22 veterinary clinics in Hong Kong, 134 (57.3%) showed positive bacterial growth, of which 23 (17.2%) showed mixed bacterial growth. In total, 156 bacterial isolates were identified. Gram-positive bacteria (n = 104, 66.7%) were most commonly recovered, representing 25 bacterial species, most commonly Streptococcus spp., Staphylococcus spp., and Corynebacterium spp. The majority of positive samples were from the integument (43.6%) and urinary tract (33.8%). A total of 85.9% of all isolates were resistant to at least one antimicrobial agent, with over 40% of isolates exhibiting resistance to three or more antimicrobial agents, and 27.6% were multidrug resistant (resistant to at least one agent in three or more antimicrobial classes). High resistance rates were observed for penicillin (45.6%), gentamicin (43.7%), doxycycline (42.1%), and azithromycin (36.3%). In contrast, isolates were highly susceptible to ceftazidime (84.1%), chloramphenicol (82.6%), ciprofloxacin (72.7%), and marbofloxacin (72.2%). These findings highlight the high frequency of AMR in this population of clinically ill pet guinea pigs in Hong Kong and the need for informed and judicious antimicrobial use. Full article

As China’s economy grows and travel demand increases, its aviation market has evolved to become the second-largest in the world. This study presents a pioneering analysis of China’s aviation network evolution (1990–2024) by integrating temporal dynamics into a network density matrix theory, addressing critical gaps in prior static network analyses. Unlike conventional studies focusing on isolated topological metrics, we introduce a triangulated methodology: ① a network sequence analysis capturing structural shifts in degree distribution, clustering coefficient, and path length; ② novel redundancy–entropy coupling quantifying complexity evolution beyond traditional efficiency metrics; and ③ economic-network coordination modeling with spatial autocorrelation validation. Key innovations reveal previously unrecognized dynamics: ① Time-embedded density matrices ($\rho$) demonstrate how sparsity balances information propagation efficiency ($\eta$) and response diversity, resolving the paradox of functional yet sparse connectivity. ② Redundancy–entropy synergy exposes adaptive trade-offs. Entropy ($H$) rises 18% (2000–2024), while redundancy ($R$) rebounds post-2010 (0.25→0.33), reflecting the strategic resilience enhancement after early efficiency-focused phases. ③ Economic-network coupling exhibits strong spatial autocorrelation ($Moran’sI>0.16$, $p<0.05$), with eastern China achieving “primary coordination”, while western regions lag due to geographical constraints. The empirical results confirm structural self-organization. Power-law strengthening, route growth exponentially outpacing cities, and clustering ($C$) rising 16% as the path length ($L$) increases, validating the hierarchical hub formation. These findings establish aviation networks as dynamically optimized systems where economic policies and topological laws interactively drive evolution, offering a paradigm shift from descriptive to predictive network management. Full article

The development of retail stores is determined by many factors, including the availability of retail space. The construction of a new building requires time, resources, and permits. This article aims to examine the possibilities of implementing small modular retail facilities built on the principles of vending machines, which do not require constant service and social space, by examining important groups of factors: architectural and structural, production, environmental, and costs. A vending machine in modular construction technology provides new opportunities for the development of a retail network in previously inaccessible places. The research presented in this article was conducted based on a literature review and interviews with experts, on the basis of which, using the network thinking methodology, critical factors were isolated and analysed in detail. The research results show the benefits of using modular technology, meeting the assumptions of the circular economy in terms of reducing the carbon footprint and improving the construction stage and investment costs, while taking into account the aesthetics of the surroundings. The results can contribute to the popularisation of the use of modular facilities, which can complement the development of downtown areas, making cities more sustainable. Full article

This paper addresses the critical need for detailed electricity and peak power demand maps for urban public transportation vehicles. Current approaches often rely on overly general assumptions, leading to considerable errors in specific applications or, conversely, overly specific measurements that limit generalisability. We aim to present a comprehensive data-driven methodology for analysing energy consumption within a large urban agglomeration. The method leverages a unique and extensive set of real-world performance data, collected over two years from onboard recorders on all public bus lines in the Capital City of Warsaw. This large dataset enables a robust probabilistic analysis, ensuring high accuracy of the results. For this study, three representative bus lines were selected. The approach involves isolating inter-stop trips, for which instantaneous power waveforms and energy consumption are determined using classical mathematical models of vehicle drive systems. The extracted data for these sections is then characterised using probability distributions. This methodology provides accurate calculation results for specific operating conditions and allows for generalisation with additional factors like air conditioning or heating. The direct result of this paper is a detailed urban map of energy demand and peak power for public transport vehicles. Such a map is invaluable for planning new traffic routes, verifying existing ones regarding energy consumption, and providing a reliable input source for strategic charger deployment analysis along the route. Full article

Invasive fungal infections (IFIs), primarily caused by Candida species, represent a significant global public health concern due to their high mortality rates and growing antifungal resistance. In Honduras, data on their epidemiology remains scarce. This study aimed to characterize Candida species associated with candidemia and assess key virulence factors. A total of 80 clinical isolates were collected from four hospitals in Honduras’s major cities, Tegucigalpa and San Pedro Sula. Identification was performed using both phenotypic and molecular methods. Hemolytic activity, phospholipase and protease production, and biofilm formation were evaluated. C. albicans and C. tropicalis were the most prevalent species (30% each), followed by C. parapsilosis (27.5%). Phenotypic methods misidentified 13.8% of the isolates. Most strains (96.3%) exhibited strong hemolytic activity. C. albicans showed the highest phospholipase activity, while C. tropicalis was the most robust film producer. These findings highlight an evolving epidemiological landscape characterized by an increasing prevalence of non-albicans Candida species, often less susceptible to antifungal agents, and diverse virulence profiles such as strong biofilm formation. This underscores the clinical need for accurate species-level identification through molecular diagnostics and ongoing surveillance to guide targeted antifungal therapy and enable early, locally adapted interventions. Full article

Untreated water bodies are critical ecological niches where environmental conditions can drive the adaptive evolution of bacterial populations, enabling them to acquire new traits such as antibiotic-resistance genes. Escherichia coli is typically a commensal bacterium but can evolve into a pathogenic form, known as Diarrheagenic E. coli, responsible for both intestinal and extraintestinal diseases. This study focuses on the characterization of E. coli isolates from water samples collected from the Matasnillo River and the influence of the Juan Díaz Wastewater Treatment Plant (WWTP). While isolates from the Matasnillo River were classified as commensal, 18% of the isolates from the WWTP belonged to either phylogroups D or B2. Pathotype analysis revealed the presence of Entero-Toxigenic and Entero-Hemorrhagic E. coli in the WWTP. Moreover, Matasnillo River isolates exhibited resistance mainly to the quinolone ciprofloxacin, whereas those from the WWTP influent showed resistance to multiple broad-spectrum antibiotics. Sequencing analysis revealed the prevalence of the transmissible quinolone resistance qnrB19 among the Matasnillo River isolates and mutations conferring resistance to quinolone in gyrA, parC, and parE. These findings highlight the importance of monitoring antibiotic-resistant bacterial contamination in both freshwater and wastewater to mitigate the risk of the spread of resistant pathogens and potential epidemic outbreaks. Full article