Search Results (812)

We utilized silver nanoparticles synthesized from bitter melon (Momordica charantia) extracts for testing against the common agricultural pathogen Escherichia coli. The synthesized nanoparticles were characterized and confirmed as silver nanoparticles by using ultraviolet spectroscopy, Fourier transform infrared spectroscopy, and scanning electron microscopy analysis. The results show that AgNPs were effective against E. coli ATCC25922 strain. The AgNPs had an increased potency against the E. coli strain in optimum culture media compared to silver ions alone. AgNP-treated cultures achieved a kill percentage of 100% in less incubation time and at a lower dosage than those treated with silver ions alone. The powder form of the AgNPs also showed remarkable potency against E. coli in solution. Based on these findings, the current method is suitable for the industrial-scale production of AgNPs from a commonly available edible plant with known medicinal benefits in the fight against foodborne pathogens, including antibiotic-resistant strains. Full article

Ecosystem services—the benefits humans derive from nature—are foundational to environmental sustainability and economic well-being, with carbon sequestration and storage standing out as critical regulating services in the fight against climate change. This study presents a comprehensive financial valuation of the carbon sequestration, storage and product substitution ecosystem services provided by the Hungarian forest-based sector. Using a multi-scenario framework, four complementary valuation concepts are assessed: total carbon storage (biomass, soil, and harvested wood products), annual net sequestration, emissions avoided through material and energy substitution, and marketable carbon value under voluntary carbon market (VCM) and EU Carbon Removal Certification Framework (CRCF) mechanisms. Data sources include the National Forestry Database, the Hungarian Greenhouse Gas Inventory, and national estimates on substitution effects and soil carbon stocks. The total carbon stock of Hungarian forests is estimated at 1289 million tons of CO₂ eq, corresponding to a theoretical climate liability value of over EUR 64 billion. Annual sequestration is valued at approximately 380 million EUR/year, while avoided emissions contribute an additional 453 million EUR/year in mitigation benefits. A comparative analysis of two mutually exclusive crediting strategies—improved forest management projects (IFMs) avoiding final harvesting versus long-term carbon storage through the use of harvested wood products—reveals that intensified harvesting for durable wood use offers higher revenue potential (up to 90 million EUR/year) than non-harvesting IFM scenarios. These findings highlight the dual role of forests as both carbon sinks and sources of climate-smart materials and call for policy frameworks that integrate substitution benefits and long-term storage opportunities in support of effective climate and bioeconomy strategies. Full article

The emergence of multidrug-resistant (MDR) bacteria and biofilm-associated infections has created a significant hurdle for conventional antibiotics, prompting the exploration of alternative strategies. Photodynamic therapy (PDT), a technique that utilizes photosensitizers activated by light to produce ROS, has emerged as a beacon of hope in the fight against MDR microorganisms. Among the natural photosensitizers, hypocrellins (A and B) have shown remarkable potential with their dual-mode photodynamic action, generating ROS via both Type I (electron transfer) and Type II (singlet oxygen) pathways. This unique action disrupts bacterial biofilms and inactivates MDR pathogens. The amphiphilic nature of hypocrellins further enhances their promise, enabling deep biofilm penetration and ensuring potent antibacterial effects even in hypoxic environments, surpassing the capabilities of synthetic photosensitizers. This study critically examines the antimicrobial properties of hypocrellin-based PDT, emphasizing its mechanisms, advantages over traditional antibiotics, and effectiveness against MDR pathogens. Comparative analysis with other photosensitizers, the role of nanotechnology-enhanced delivery systems, and future clinical applications are explored. Its combination with nanotechnology enhances therapeutic outcomes, providing a viable alternative to conventional antibiotics. Further clinical research is essential to optimize its application and integration into antimicrobial treatment protocols. Full article

Acinetobacter baumannii is listed by the World Health Organization as an emerging bacterial priority pathogen, the prevalence and multidrug resistance of which have been increasing. This functional genomics study aimed to understand the drug-resistance mechanisms of an extensively drug-resistant (XDR) A. baumannii strain (IRMCBCU95U) isolated from a transtracheal aspirate sample from a female patient with end-stage renal disease in Saudi Arabia. The whole genome of IRMCBCU95U (4.3 Mbp) was sequenced using Oxford Nanopore long-read sequencing to identify and compare the antibiotic-resistance profile and genomic features of A. baumannii IRMCBCU95U. The antibiogram of A. baumannii IRMCBCU95U revealed resistance to multiple antibiotics, including cefepime, ceftazidime, ciprofloxacin, imipenem, meropenem and piperacillin/tazobactam. A comparative genomic analysis between IRMCBCU95U and A. baumannii K09-14 and ATCC 19606 identified significant genetic heterogeneity and mosaicism among the strains. This analysis also demonstrated the hybrid nature of the genome of IRMCBCU95U and indicates that horizontal gene transfer may have occurred between these strains. The IRMCBCU95U genome has a diverse range of genes associated with antimicrobial resistance and mobile genetic elements (ISAba1 and IS26) associated with the spread of multidrug resistance. The presence of virulence-associated genes that are linked to iron acquisition, motility and transcriptional regulation confirmed that IRMCBCU95U is a priority human pathogen. The plasmid fragment IncFIB(pNDM-Mar) observed in the strain is homologous to the plasmid in Klebsiella pneumoniae (439 bp; similarity: 99.09%), which supports its antimicrobial resistance. From these observations, it can be concluded that the clinical A. baumannii IRMCBCU95U isolate is an emerging extensively drug-resistant human pathogen with a novel combination of resistance genes and a plasmid fragment. The complex resistome of IRMCBCU95U highlights the urgent need for genomic surveillance in hospital settings in Saudi Arabia to fight against the spread of extensively drug-resistant A. baumannii. Full article

In a recent investigation the corrosion-fighting potential of five benzaldehyde derivatives were explored: 4-Formylbenzonitrile (BA1), 4-Nitrobenzaldehyde (BA2), 2-Hydroxy-5-methoxy-3-nitrobenzaldehyde (BA3), 3,5-Bis(trifluoromethyl)benzaldehyde (BA4), and 4-Fluorobenzaldehyde (BA5). Benzaldehyde derivative (BA-2) showed a maximum inhibition efficiency of 93.3% at 500 ppm. Several techniques were used to evaluate these compounds’ ability to protect mild steel from corrosion in a 1 M HCl solution, including potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), adsorption isotherms, and computational methods. Supporting techniques Fourier transform infrared spectroscopy (FTIR) and ultraviolet–visible (UV-Vis) spectroscopy were also employed to validate the results. Despite sharing a common benzene ring, the molecules differ in their substituents, allowing for a comprehensive examination of the substituents’ impact on corrosion inhibition. PDP analysis disclosed that the inhibitors exhibited mixed-type inhibition behavior, interacting with anodic as well as cathodic reactions, influencing the corrosion process. EIS analysis revealed that benzaldehyde derivatives formed a protective passive film on the metal, exhibiting high corrosion resistance by shielding the alloy from corrosive attacks. The benzaldehyde inhibitors followed the Langmuir adsorption isotherm, with high R² values near one, indicating a monolayer adsorption mechanism. DFT results indicate that BA 2 is the most effective inhibitor. FTIR and UV-vis spectroscopy revealed the molecular interactions between metal and benzaldehyde derivative molecules, providing insight into the binding mechanism. Experimental results support the outcomes obtained from the molecular dynamic (MD) simulations. Full article

Drought indices are important resources for monitoring and warning of drought impacts. However, regions like New Mexico, which are highly vulnerable to drought, as identified by the United States Drought Monitor (USDM), lack a comprehensive drought monitoring system that integrates multiple agrometeorological variables into a single indicator. The purpose of this study is to create a Combined Drought Indicator for New Mexico (CDI-NM) as an indicator tool for use in monitoring historical drought events and measuring its extent across the New Mexico. The CDI-NM was constructed using four key variables: the Vegetation Condition Index (VCI), temperature, Smoothed Normalized Difference Vegetation Index (SMN), and gridded rainfall data. A quantitative approach was used to assign weights to these variables employing Principal Component Analysis (PCA) to produce the CDI-NM. Unlike conventional indices, CDI-NM assigns weights to each variable based on their statistical contributions, allowing the index to adapt to local spatial and temporal drought dynamics. The performance of CDI-NM was evaluated against gridded rainfall data using the 3-month Standardized Precipitation Index (SPI3) over a 17-year period (2003–2019). The results revealed that CDI-NM reliably detected moderate and severe droughts with a strong correlation (R² > 0.8 and RMSE = 0.10) between both indices for the entire period of analysis. CDI-NM showed negative correlation (r < 0) with crop yield. While promising, the method assumes linear relationships among variables and consistent spatial resolution in the input datasets, which may affect its accuracy under certain local conditions. Based on the results, the CDI-NM stands out as a promising instrument that brings us closer to improved decision-making by stakeholders in the fight against agricultural droughts throughout New Mexico. Full article

Kumite is a karate sparring competition in which two players fight each other using various techniques. In kumite matches, it is essential to reduce a preliminary action (hereinafter referred to as “pre-action”), such as pulling the arms and lowering the shoulders just before performing an attack technique. This is because pre-actions reveal the timing of the attack to the opponent. However, players often find it difficult to recognize their own pre-actions, and accurately estimating their presence or absence is challenging with conventional motion analysis methods, as pre-actions are subtle compared to major techniques like punching or kicking. Previously, we proposed a method for detecting pre-actions during single punches performed in a static state using inertial sensors. While this method was effective in controlled situations, it failed to detect pre-actions in punches during actual kumite matches. The main reason is that players generally perform footwork during matches, and this footwork is often misrecognized as pre-action via conventional detection methods. To address misrecognition caused by footwork, we propose a new method that combines preprocessing designed to detect and smooth footwork segments in the inertial data with the conventional pre-action detection method, thereby enabling pre-action detection during kumite matches. In the preprocessing, we apply an autocorrelation function to assess the constancy of footwork and accurately separate the footwork segment from the kumite technique segment. Only the footwork segment is then smoothed to suppress its influence on the detection process. Our experimental results show that the proposed method can estimate the presence or absence of pre-action in the punch of an actual kumite match with an accuracy of 0.875. Full article

Human immunodeficiency virus (HIV) continues to be a threat to public health. An emerging technique with promise in the context of fighting HIV type 1 (HIV-1) focuses on targeting ribosomal frameshifting. A crucial –1 programmed ribosomal frameshift (PRF) has been observed in several pathogenic viruses, including HIV-1. Altered folds of the HIV-1 RNA frameshift element (FSE) have been shown to alter frameshifting efficiency. Here, we use RNA-As-Graphs (RAG), a graph-theory based framework for representing and analyzing RNA secondary structures, to perform conformational analysis in motif space to propose how sequence length may influence folding patterns. This combined analysis, along with all-atom modeling and experimental testing of our designed mutants, has already proven valuable for the SARS-CoV-2 FSE. As a first step to launching the same computational/experimental approach for HIV-1, we compare prior experiments and perform SHAPE-guided 2D-fold predictions for the HIV-1 FSE embedded in increasing sequence contexts and predict structure-altering mutations. We find a highly stable upper stem and highly flexible lower stem for the core FSE, with a three-way junction connecting to other motifs at increasing lengths. In particular, we find little support for a pseudoknot or triplex interaction in the core FSE, although pseudoknots can form separately as a connective motif at longer sequences. We also identify sensitive residues in the upper stem and central loop that, when minimally mutated, alter the core stem loop folding. These insights into the FSE fold and structure-altering mutations can be further pursued by all-atom simulations and experimental testing to advance the mechanistic understanding and therapeutic strategies for HIV-1. Full article

The COVID-19 pandemic has caused a profound interruption in the way people travel and has had a very negative impact on tourism and economics throughout the world, especially on the coastal fishing communities in South Korea. These previously problematic areas, having suffered a decrease in the local population as well as stood in the midst of the economic downturn, experienced a great cut in the number of tourists coming from far away, which additionally caused their collapse of resilience and sustainability. This research investigates the recovery trends of 45 seashore-fishing districts in South Korea and how the change in travel distance and the number of visitors before and after the pandemic have affected these trends. Through the utilization of big data from the Korea Tourism Data Lab (2019–2023) and Geographic Information System (GIS) analysis, we observe the changes in visitor flows, use the indices of resilience as an indicator to measure them, and investigate how proximity affects travel recovery. The survey results indicate that the regions neighboring metropolitan zones were not only the ones that suffered the most from travel distance during the pandemic but also experienced quick recovery after the pandemic. The new promotional campaigns, in tandem with an improved network of transportation, contributed to the swift recovery of these areas. The remote areas, on the other hand, persist in fighting the problems of regionalized tourism and have only limited accessibility. The proposition of “distance-dependent resilience” theory as well as the Blue Urbanism framework is offered in order to bring up the ideas of sustainable tourism and population stabilization. The study is expected to serve as a cornerstone for the practice of adaptive governance and strategic planning in the matter of the coastal areas after the pandemic. Full article

Background/Objectives: The aim of this study was twofold: first, to assess the extent to which patients diagnosed with lung cancer accept their condition and, second, to characterize the profiles and dimensions of the hope experienced by these patients. Methods: In order to achieve the aforementioned goals, the following research tools were utilized: the NCN-36 scale to examine hope, the AIS to ascertain the acceptance of one’s condition, and the KI scale to present socio-demographic–temperamental variables. Results: The patients exhibited an average level of acceptance of their disease while simultaneously demonstrating a high level of hope. Cluster analysis identified four groups of patients that differed significantly in terms of disease acceptance and felt hope (p < 0.001). Significantly higher acceptance of the disease was found in urban patients (p = 0.038) and those with higher education (p = 0.011), while lower acceptance was noted in those aged over 75 (p = 0.006). In turn, the experienced hope was influenced by variables such as age, place of residence, education, housing situation (living alone or with family), overall pace of activity, basic mood, and social and professional status. Conclusions: The researchers identified four distinct attitudes among the patients based on their disease-related experiences. These attitudes were categorized as follows: non-accepting–fearful, indifferent–desperate, non-accepting–fighting, and accepting–trusting. Full article

Low-income households face severe energy affordability issues due to poor housing quality. To fight this problem, Spanish public administrations and NGOs have collaborated with the Naturgy Foundation’s Energy Rehabilitation Solidarity Fund to improve the energy efficiency of vulnerable households through quick and low-cost interventions. This paper evaluates the impact of shallow renovation and micro-efficiency measures implemented within this program on energy poverty across various Spanish provinces. The analysis includes data from 416 households in 10 provinces, examining sociodemographic factors, housing conditions, energy bills, and thermal comfort perceptions. The methodology involved collecting data through two questionnaires and energy bills provided by collaborating entities. The study found that shallow renovation measures reduced the energy poverty gap by 14.51%, from EUR 554/year to EUR 483/year. Despite these gains, many households remain in severe hidden energy poverty, spending less than a quarter of their theoretical energy expenditure. The findings highlight the diversity among different provinces and measures and the need for more extensive structural measures to reduce energy poverty significantly. Eventually, the study underscores the effectiveness of energy renovations carried out by non-profit organizations. Thus, scaling these efforts nationally might help meet the goals of the public energy poverty plans. Full article

Background: This study investigated boxers’ activity profiles during the final matches (3 × 3 min format) of the IBA 2023 Women’s World Boxing Championships. Methods: Footage of the 12 finals was used to analyse the frequency and duration of fighting (F), punching (P), clinching (C), no-fighting (NF), and arbitral interruption (AI) phases. The analysis was conducted both for weight categories and divisions (lightweight (LWC): 48, 50, 52, 54, 57, and 60 kg; middleweight (MWC): 63, 66, 70, and 75 kg; heavyweight (HWC): 81 and 81+ kg). Results: Pooled data per round revealed significant differences for P (<0.001), C (p = 0.002), NF (p < 0.001), and AI (p < 0.001) phases, as well for P mean duration across rounds (p < 0.001). The MWC division showed significantly shorter F duration compared with the LWC (p = 0.007) and MWC divisions (<0.001). The F/NF total time ratio showed a prevalence of F in the 48, 50, 63, and 81+ kg categories, while NF prevailed in the 54, 57, 60, and 75 kg categories. Conclusions: While HWC primarily relied on C actions, the 54, 57, 60, and 75 kg categories showed higher NF frequency. This fact explains a different strategic match management approach with deliberate rhythm, controlled pauses, and opponent analysis, which coaches should consider for enhancing athletes’ performance by considering weight categories. Full article

The following work is based on the historical–anthropological analysis of 93 skeletal remains belonging to post-war casualties who died in 1946 and remained missing for years. In 2019, 93 metal boxes containing skeletal remains of Slavic origin, belonging to civilians and soldiers who perished in the immediate postwar period following World War II, were found inside the ossuary of the Monumental Cemetery in Bari (Italy). At the beginning of the search, these people were thought to have died in prison camps in Apulia, such as Torre Tresca and Grumo Appula, in the province of Bari. Later, thanks to the discovery of war badges and years of extensive historical research, it was discovered that these remains had been missing for 75 years and belonged to soldiers of the Royal Yugoslav Army and civilians, probably their relatives, who died in 1946 in the refugee camp of Eboli, in the province of Salerno, Campania (Italy). To unveil this truth that remained hidden for over 75 years, a multidisciplinary study divided into two phases was applied. The first phase, grounded in historical research study, aimed to determine the historical and temporal context in which they lived and confirm the life they actually lived in the Eboli refugee camp. The second phase, grounded in anthropological research, aimed to reconstruct the biological profile of each individual, identify the presence of antemortem, perimortem, and postmortem lesions, assess potential pathological conditions, and determine, where possible, the cause of death. Finally, a correlation of the collected data was conducted to ascertain and corroborate, with reasonable certainty, the living conditions to which they were subjected in the refugee camp where they resided. Italy after 1943 became the scene of intense fighting and a dramatic situation for prisoners of war, including many Yugoslav soldiers. This work brought to light a history that had been lost for as many as 75 years, highlighted the importance, specifically, of the role of the Eboli refugee camp, a context little known and forgotten by many, and above all made it possible to remember and restore dignity to the victims of the Great War. Full article

Wine markets have deeply changed in recent decades in many regards. In particular, wine trade patterns have been deeply reshaped, and this also affects traditional EU exporters, who operate in a more competitive environment, with new players challenging their position and forcing them to readjust their strategies. This study analyzes recent trends in the wine exports of major EU producers. Its goal is to contribute to assessing to what extent their positioning in the international wine markets differs, and to understand the kind of competition they engage in within destination markets, with a focus on the role of their export quality as a major competitive advantage. This analysis only looks at bottled wines, both still and sparkling. It combines the use of traditional trade indicators—such as export quotas, penetration rates, and the average unit value of exports (AUV) with an innovative indicator, called C-Consy, aimed at measuring the sophistication levels of the destination markets. The results show that EU competitors behave in different ways and move along different paths. Some of them show an increasing ability to sell their products in higher segments of sophisticated markets. Others are also quite well positioned in the global arena, but they are fighting to fully catch up with the increasing demand for more sophisticated products from their clients. Some have managed to improve quality and hence advance to higher market segments, while others have shown greater weakness in facing global competition. Looking at typologies, exporters do not always show the same positioning and trends for still and sparkling wines. Full article

Artificial intelligence (AI) is becoming not only an auxiliary tool, but also one of the main factors helping to shape natural resource management models. The application of artificial intelligence in protected areas allows for a transition to more sustainable management of protected areas. By applying artificial intelligence technologies, it is possible not only to respond to changes or violations that have already occurred but also to more effectively predict potential threats, form long-term protection strategies, and make rational decisions based on accurate and timely data analysis. This study aims to determine the possibilities and importance of applying artificial intelligence technologies to the sustainable management of protected areas. The sample group of this study consists of a total of 135 experts from Turkey, Lithuania, and Morocco (45 from each country). The sample includes professionals with expertise in the relevant field, namely lawyers (9), academics (9), managers of protected areas (9), government officials responsible for protected areas (9), and representatives of non-governmental organizations (9). This study employed qualitative research methods, within which a case study design was adopted. For the analysis of the findings, thematic analysis and content analysis techniques were utilized to ensure a comprehensive and in-depth interpretation of the data. Analysis of the results of this study showed that integrating AI into the management of protected areas increases management efficiency and helps create long-term strategies, but successful application depends on cooperation between technology developers, scientists, and environmental specialists. Also, AI applications are expected to be a critical part of the process of environmental sustainability and fighting climate change. Full article