Search Results (2,339)

This study intends to portray how varying degrees of environmental policy stringency and the growing pressure of global competition reflect on high-tech (HT) sectors’ cost rationalization strategies and lead to environmental consequences in 15 G20 countries (1992–2019). Moreover, we center the pattern of cost rationalization management regarding the opportunity cost of ecosystem service consumption and propose to test the fundamental hypothesis stating the possible transmission of competition-induced technological innovations to green economic transformation. Our new methodology estimates quantile-specific effects with MM-QR, while identifying the main interaction effects between regulatory pressure and trade competition uses an extended STIRPAT model. The results reveal a paradoxical finding: despite higher environmental policy stringency and opportunity costs of ecosystem services, HT sectors persistently adopt environmentally detrimental cost-reduction approaches. These findings carry important policy implications: (1) environmental regulations for HT sectors require complementary innovation subsidies, (2) trade agreements should incorporate clean technology transfer clauses, and (3) governments must monitor sectoral emission leakage risks. Our dual machine learning–econometric approach provides policymakers with targeted insights for different emission scenarios, highlighting the need for differentiated strategies across clean and polluting HT subsectors. Full article

A scalable synthesis of two-dimensional titanium nitride chloride (TiNCl) via flash Joule heating (FJH) using titanium tetrachloride (TiCl₄) precursor has been developed. This single-step method overcomes traditional synthesis challenges, including high energy consumption, multi-step procedures, and hazardous reagent requirements. The structural and chemical properties of the synthesized TiNCl were characterized through multiple analytical techniques. X-ray diffraction (XRD) patterns confirmed the presence of TiNCl phase, while Raman spectroscopy data showed no detectable oxide impurities. Fourier transform infrared spectroscopy (FTIR) analysis revealed characteristic Ti–N stretching vibrations, further confirming successful titanium nitride synthesis. Transmission electron microscopy (TEM) imaging revealed thin, plate-like nanostructures with high electron transparency. These analyses confirmed the formation of highly crystalline TiNCl flakes with nanoscale dimensions and minimal structural defects. The material exhibits excellent structural integrity and phase purity, demonstrating potential for applications in photocatalysis, electronics, and energy storage. This work establishes FJH as a sustainable and scalable approach for producing MXenes with controlled properties, facilitating their integration into emerging technologies. Unlike conventional methods, FJH enables rapid, energy-efficient synthesis while maintaining material quality, providing a viable route for industrial-scale production of two-dimensional materials. Full article

Background/Objectives: Campylobacteriosis in human populations is an ongoing issue in both developed and developing countries. Poultry production is recognized as a reservoir for antimicrobial resistance and main source of human Campylobacter infection. Methods: In this study, sixty-five Campylobacter isolates were cultured from fecal samples collected from 17 flocks of broiler chickens in Alberta, Canada over two years (2015–2016). Susceptibility assays and PCR assays were performed to characterize resistance phenotypes and resistance genes. Conjugation assays were used to examine the mobility of AMR phenotypes. Results: Campylobacter jejuni was the predominant species recovered during both years of sampling. There were no Campylobacter coli isolates found in 2015; however, approximately 33% (8/24) of isolates collected in 2016 were Campylobacter coli. The two most frequent antimicrobial resistance patterns in C. jejuni collected in 2015 were tetracycline (39%) and azithromycin/clindamycin/erythromycin/telithromycin resistance (29%). One isolate collected in 2015 has resistance pattern ciprofloxacin/nalidixic acid/tetracycline. The tetO gene was detected in all tetracycline resistant isolates from 2015. The cmeB gene was detected in all species isolates with resistance to azithromycin/clindamycin/erythromycin/telithromycin, and from two isolates with tetracycline resistance. Alignment of the nucleotide sequences of the cmeB gene from C. jejuni isolates with different resistance patterns revealed several single nucleotide polymorphisms. A variety of multi-drug resistance patterns were observed through conjugation experiments. Conclusions: These data suggest that poultry production may serve as a potential reservoir for and source of transmission of multi-drug resistant Campylobacter jejuni and supports the need for continued surveillance. Full article

Avian influenza viruses (AIVs) pose significant risks to occupational populations engaged in poultry farming, livestock handling, and live poultry market operations due to frequent exposure to infected animals and contaminated environments. This review synthesizes evidence on AIV exposure patterns and risk factors through a comprehensive analysis of viral characteristics, host dynamics, environmental influences, and human behaviors. The main routes of transmission include direct animal contact, respiratory contact during slaughter/milking, and environmental contamination (aerosols, raw milk, shared equipment). Risks increase as the virus adapts between species, survives longer in cold/wet conditions, and spreads through wild bird migration (long-distance transmission) and live bird trade (local transmission). Recommended control measures include integrated animal–human–environment surveillance, stringent biosecurity measures, vaccination, and education. These findings underscore the urgent need for global ‘One Health’ collaboration to assess risk and implement preventive measures against potentially pandemic strains of influenza A viruses, especially in light of undetected mild/asymptomatic cases and incomplete knowledge of viral evolution. Full article

Lepidoptera typically exhibit a dichotomy in compound eye design: diurnal butterflies possess apposition eyes for high resolution in bright light, whereas nocturnal moths have superposition eyes for enhanced sensitivity under dim conditions. However, exceptions, particularly among diurnal moths, challenge this pattern and offer insights into the evolution of compound eyes in Lepidoptera. In this study, we investigated the compound eye design of the diurnal moth Histia flabellicornis (Fabricius) using light, scanning, and transmission electron microscopy to determine whether it has superposition or apposition eyes, and to quantitatively analyze the structural features and visual acuity. Our results reveal that H. flabellicornis possesses apposition-type compound eyes composed of over 2000 ommatidia, each comprising a cornea, a crystalline cone, nine retinula cells forming a fused rhabdom, and a few isolated tracheoles. The calculated interommatidial angles (Δϕ = 4.08°) and the eye parameter P (P = 1.74) suggest a visual system adapted to moderate light conditions, balancing spatial resolution with photon capture. These findings confirm the presence of apposition eyes in H. flabellicornis, supporting the moth’s adaptation to diurnal behavior and contributing to understanding the evolutionary diversification of compound eye designs in Lepidoptera. Full article

Regional HIV-1 epidemics are evolving with distinct patterns in transmission routes, subtype distribution, and molecular transmission cluster (MTCs) characteristics. We analyzed 9500 HIV-1 cases diagnosed over 30 years using phylogenetic and network methods, integrating molecular, epidemiological, demographic, and behavioral data. Subtype A6 remains dominant nationally (80.6%), followed by 63_02A6 (7.9%), subtype B (5.6%), 02_AG_FSU (1.2%), 03_A6B (0.7%), and 14/73_BG (0.6%). Non-A6 infections were more common among males (OR 1.51) and men who have sex with men (OR 7.33). Network analysis identified 421 MTCs, with 256 active clusters. Clustering was more likely among young individuals (OR: 1.31), those not receiving antiretroviral therapy (OR: 2.70), and injecting drug users (OR: 1.28). Non-A6 subtypes showed a higher likelihood of clustering. Phylogenetic analysis revealed that local clusters of the major subtypes originated between the late 1970s (subtype B) and the mid-2000s (63_02A6) with links to populations in Eastern Europe, Central Asia (subtypes A6, 63_02A6, 02_AG_FSU, 03_A6B), and Western Europe and the Americas (subtype B, 14/73_BG). These findings indicate a complex, evolving regional epidemic transitioning from subtype A6 dominance to a more diverse mix of subtypes. The ability of non-A6 subtypes to form active MTCs suggests their establishment in the local population. Full article

Respiratory pathogens are significant causes of morbidity and mortality worldwide. Since the emergence of SARS-CoV-2 in 2019 and the mitigation measures implemented to control the pandemic, other respiratory viruses’ transmission and circulation patterns were substantially disrupted. We leveraged the influenza hospitalization surveillance in Tanzania to understand the distribution of respiratory viruses shortly after nonpharmaceutical interventions (NPIs) were lifted. A total of 475 samples that tested negative for SARS-CoV-2 and influenza from March through May 2022 were included in this study. The samples were tested for 16 virus targets using Anyplex II RV16 multiplex assays. The findings indicate that most hospitalizations (74%) were among children under 15 years, with human bocavirus (HBoV) being the most prevalent (26.8%), followed by rhinovirus (RV, 12.3%), parainfluenza viruses (PIVs1–4, 10.2%), respiratory syncytial virus (RSV, 8.7%), adenovirus (AdV, 4.3%), and metapneumovirus (MPV, 2.9%). Notably, 54% of respiratory hospitalizations had no viruses detected. The findings highlight the broad circulation of respiratory viruses shortly after NPIs were lifted in Tanzania. Surveillance for respiratory pathogens beyond influenza and SARS-CoV-2 can inform public health officials of emerging threats in the country and should be considered an important pandemic preparedness measure at a global level. Full article

Limited molecular data exist on zoonotic parasites Cryptosporidium spp., Giardia duodenalis, and Enterocytozoon bieneusi in Angus calves from Guizhou, China. This study constitutes the first molecular epidemiological survey of these pathogens in this region. 817 fecal samples from Angus calves across 7 intensive beef farms (Bijie City). Nested PCR methods targeting SSU rRNA (Cryptosporidium spp.), gp60 (Cryptosporidium bovis subtyping), bg/gdh/tpi (G. duodenalis), and ITS (E. bieneusi) coupled with DNA sequencing were employed. DNA sequences were analyzed against the NCBI. database. Statistical differences were assessed via a generalized linear mixed-effects model. Cryptosporidium spp. prevalence 23.5% (192/817; 95% CI 28.1–34.6%), with C. bovis predominating 89.6% (172/192; 95% CI 84.4–93.5%) and six subtypes (XXVIa-XXVIf). Highest infection in 4–8-week-olds 29.9% (143/479; 95% CI 25.8–34.1%) (p < 0.01). G. duodenalis: 31.3% (256/817; 95% CI 28.1–34.6%) positive, overwhelmingly assemblage E 97.6% (6/256; 95% CI 0.9–5.0%), zoonotic assemblage A was marginal 0.7% (6/817; 95% CI 0.3–1.6%). Farm-level variation exceeded 10-fold (e.g., Gantang: 55.0% (55/100; 95% CI 44.7–65.0%) vs. Tieshi: 4.9% (5/102; 95% CI 1.6–11.1%). E. bieneusi: prevalence 19.7% (161/817; 95% CI 17.0–22.6%), exclusively zoonotic genotypes BEB4: 49.7% (80/161; 95% CI 41.7–57.7%); I: 40.4% (65/161; 95% CI 32.7–48.4%). Strong diarrhea association (p < 0.01) and site-specific patterns (e.g., Guanyindong: 39.2%). While Giardia exhibited the highest prevalence (31.3%) with minimal zoonotic risk, Enterocytozoon—despite lower prevalence (19.7%)—posed the greatest public health threat due to exclusive circulation of human-pathogenic genotypes (BEB4/I) and significant diarrhea association, highlighting divergent control priorities for these enteric parasites in Guizhou calves. Management/Public health impact: Dominant zoonotic E. bieneusi genotypes (BEB4/I) necessitate: 1. Targeted treatment of 4–8-week-old Angus calves. 2. Manure biofermentation (≥55 °C, 3 days), and 3. UV-disinfection (≥1 mJ/cm²) for karst water to disrupt transmission in this high-humidity region. Full article

To address the issues of bulky structure and complex transmission systems in current transplanters, a compact, electric-driven automatic transplanter was designed. Using pepper plug seedlings as the test subject, this study investigated plug tray dimensions and planting patterns. According to the design requirement that the width of the single-row transplanter must be less than 62.5 cm, a three-dimensional transplanter model was constructed. The transplanter comprises a coaxially installed dual-layer seedling conveying device and a sector-expanding automatic seedling picking and depositing device. The structural dimensions, drive configurations, and driving forces of the transplanter were also determined. Finally, the circuit and pneumatic system were designed, and the transplanter was assembled. Both bench and field tests were conducted to select the optimal working parameters. The test results demonstrated that the seedling picking and depositing mechanism met the required operational efficiency. In static seedling picking and depositing tests, at three transplanting speeds of 120 plants/min, 160 plants/min, and 200 plants/min, the success rates of seedling picking and depositing were 100%, 100%, and 97.5%, respectively. In the field test, at three transplanting speeds of 80 plants/min, 100 plants/min, and 120 plants/min, the transplanting success rates were 94.17%, 90.83%, and 88.33%, respectively. These results illustrate that the compact, electric-driven seedling conveying and picking and depositing devices meet the operational demands of automatic transplanting, providing a reference for the miniaturization and electrification of transplanters. Full article

Background: Chryseobacterium indologenes, an environmental bacterium, is increasingly recognized as an emerging nosocomial pathogen, particularly in Asia, and is often characterized by multidrug resistance. Objectives: This study aimed to investigate the genomic features of clinical C. indologenes isolates from Maharaj Nakorn Chiang Mai Hospital, Thailand, to understand their mechanisms of multidrug resistance, virulence factors, and mobile genetic elements (MGEs). Methods: Twelve C. indologenes isolates were identified, and their antibiotic susceptibility profiles were determined. Whole genome sequencing (WGS) was performed using a hybrid approach combining Illumina short-reads and Oxford Nanopore long-reads to generate complete bacterial genomes. The hybrid assembled genomes were subsequently analyzed to detect antimicrobial resistance (AMR) genes, virulence factors, and MGEs. Results: C. indologenes isolates were primarily recovered from urine samples of hospitalized elderly male patients with underlying conditions. These isolates generally exhibited extensive drug resistance, which was subsequently explored and correlated with genomic determinants. With one exception, CMCI13 showed a lower resistance profile (Multidrug resistance, MDR). Genomic analysis revealed isolates with genome sizes of 4.83–5.00 Mb and GC content of 37.15–37.35%. Genomic characterization identified conserved resistance genes (bla_IND-2, bla_CIA-4, adeF, vanT, and qacG) and various virulence factors. Phylogenetic and pangenome analysis showed 11 isolates clustering closely with Chinese strain 3125, while one isolate (CMCI13) formed a distinct branch. Importantly, each isolate, except CMCI13, harbored a large genomic island (approximately 94–100 kb) carrying significant resistance genes (bla_OXA-347, tetX, aadS, and ermF). The absence of this genomic island in CMCI13 correlated with its less resistant phenotype. No plasmids, integrons, or CRISPR-Cas systems were detected in any isolate. Conclusions: This study highlights the alarming emergence of multidrug-resistant C. indologenes in a hospital setting in Thailand. The genomic insights into specific resistance mechanisms, virulence factors, and potential horizontal gene transfer (HGT) events, particularly the association of a large genomic island with the XDR phenotype, underscore the critical need for continuous genomic surveillance to monitor transmission patterns and develop effective treatment strategies for this emerging pathogen. Full article

Viral infections persistently challenge global health through immune evasion and zoonotic transmission. Dendritic cells (DCs) play a central role in antiviral immunity by detecting viral nucleic acids via conserved pattern recognition receptors, triggering interferon-driven innate responses and cross-presentation-mediated activation of cytotoxic CD8⁺ T cells. This study synthesizes DC-centric defense mechanisms against viral subversion, encompassing divergent nucleic acid sensing pathways for zoonotic DNA and RNA viruses, viral counterstrategies targeting DC maturation and interferon signaling, and functional specialization of DC subsets in immune coordination. Despite advances in DC-based vaccine platforms, clinical translation is hindered by cellular heterogeneity, immunosuppressive microenvironments, and limitations in antigen delivery. Future research should aim to enhance the efficiency of DC-mediated immunity, thereby establishing a robust scientific foundation for the development of next-generation vaccines and antiviral therapies. A more in-depth exploration of DC functions and regulatory mechanisms may unlock novel strategies for antiviral intervention, ultimately paving the way for improved prevention and treatment of viral infections. Full article

Optical networks serve as the backbone of modern communication, requiring statistical analysis and modeling to optimize performance, reliability, and scalability. This review paper explores statistical methodologies for analyzing network characteristics, dimensioning, parameter estimation, and cost prediction of optical networks, and provides a generalized framework based on the idea of convex areas, and link length and shortest path length distributions. Accurate dimensioning and cost estimation are crucial for optical network planning, especially during early-stage design, network upgrades, and optimization. However, detailed information is often unavailable or too complex to compute. Basic parameters like coverage area and node count, along with statistical insights such as distribution patterns and moments, aid in determining the appropriate modulation schemes, compensation techniques, repeater placement, and in estimating the fiber length. Statistical models also help predict link lengths and shortest path lengths, ensuring efficiency in design. Probability distributions, stochastic processes, and machine learning improve network optimization and fault prediction. Metrics like bit error rate, quality of service, and spectral efficiency can be statistically assessed to enhance data transmission. This paper provides a review on statistical analysis and modeling of optical networks, which supports intelligent optical network management, dimensioning of optical networks, performance prediction, and estimation of important optical network parameters with partial information. Full article

Hydrogen is being increasingly integrated into the international trade system as a clean and flexible energy carrier, motivated by the global energy transition and carbon neutrality objectives. The rapid expansion of the global hydrogen trade network has simultaneously exposed several sustainability challenges, including a centralized structure, overdependence on key countries, and limited resilience to external disruptions. Based on this, we develop a risk propagation model that incorporates the absorption capacity of nodes to simulate the propagation of supply shortage risks within the global hydrogen trade network. Furthermore, we propose a composite sustainability index constructed from structural, economic, and environmental resilience indicators, enabling a systematic assessment of the network’s sustainable development capacity under external shock scenarios. Findings indicate the following: (1) The global hydrogen trade network is undergoing a structural shift from a Western Europe-dominated unipolar configuration to a more polycentric pattern. Countries such as China and Singapore are emerging as key hubs linking Eurasian regions, with trade relationships among nations becoming increasingly dense and diversified. (2) Although supply shortage shocks trigger structural disturbances, economic losses, and risks of carbon rebound, their impacts are largely concentrated in a limited number of hub countries, with relatively limited disruption to the overall sustainability of the system. (3) Countries exhibit significant heterogeneity in structural, economic, and environmental resilience. Risk propagation demonstrates an uneven pattern characterized by hub-induced disruptions, chain-like transmission, and localized clustering. Accordingly, policy recommendations are proposed, including the establishment of a polycentric coordination mechanism, the enhancement of regional emergency coordination mechanisms, and the advancement of differentiated capacity-building efforts. Full article

Risk zone delineation and mobility behavior control constitute critical measures in pandemic containment. Numerous studies utilize static demographic data or dynamic mobility data to calculate the high–risk zones present in cities; however, these studies fail to concurrently consider activity and mobility patterns of populations in both space and time, which results in many studies only being able to employ static geostatistical analytical methods, neglecting the transmission risks associated with human mobility. This study utilized the mobile phone signaling data of Shenzhen residents from 2019 to 2020 and developed a CP tensor decomposition algorithm to decompose the long-sequence spatiotemporal trajectory data to detect high risk zones in terms of detecting overlapped community structures. Tensor decomposition algorithms revealed community structures in 2020 and the overlapping regions among these communities. Based on the overlap in spatial distribution and the similarity in temporal rhythms of these communities, we identified regions with spatiotemporal co-location as high–risk zones. Furthermore, we calculated the degree of population mixing in these areas to indicate the level of risk. These areas could potentially lead to rapid virus spread across communities. The research findings address the shortcomings of currently used static geographic statistical methods in delineating risk zones, and emphasize the critical importance of integrating spatial and temporal dimensions within behavioral big data analytics. Future research should consider utilizing non-aggregated individual trajectories to construct tensors, enabling the inclusion of individual and environmental attributes. Full article

In Kenya, Rift Valley fever (RVF) outbreaks pose significant challenges, being one of the most severe climate-sensitive zoonoses. While machine learning (ML) techniques have shown superior performance in time series forecasting, their application in predicting disease outbreaks in Africa remains underexplored. Leveraging data from the International Livestock Research Institute (ILRI) in Kenya, this study pioneers the use of ML techniques to forecast RVF outbreaks by analyzing climate data spanning from 1981 to 2010, including ML models. Through a comprehensive analysis of ML model performance and the influence of environmental factors on RVF outbreaks, this study provides valuable insights into the intricate dynamics of disease transmission. The XGB Classifier emerged as the top-performing model, exhibiting remarkable accuracy in identifying RVF outbreak cases, with an accuracy score of 0.997310. Additionally, positive correlations were observed between various environmental variables, including rainfall, humidity, clay patterns, and RVF cases, underscoring the critical role of climatic conditions in disease spread. These findings have significant implications for public health strategies, particularly in RVF-endemic regions, where targeted surveillance and control measures are imperative. However, this study also acknowledges the limitations in model accuracy, especially in scenarios involving concurrent infections with multiple diseases, highlighting the need for ongoing research and development to address these challenges. Overall, this study contributes valuable insights to the field of disease prediction and management, paving the way for innovative solutions and improved public health outcomes in RVF-endemic areas and beyond. Full article