Search Results (88)

The combined application of machine or deep learning algorithms and hyperspectral imagery for bathymetry estimation is currently an emerging field with widespread uses and applications. This research topic still requires further investigation to achieve methodological robustness and accuracy. In this study, we introduce a novel methodology for shallow bathymetric mapping using a one-dimensional convolutional neural network (1D-CNN) applied to PRISMA hyperspectral images, including refinements to enhance mapping accuracy, together with the optimization of computational efficiency. Four different 1D-CNN models were developed, incorporating pansharpening and spectral band optimization. Model performance was rigorously evaluated against reference bathymetric data obtained from official nautical charts provided by the Servicio de Hidrografía Naval (Argentina). The BoPsCNN model achieved the best testing accuracy with a coefficient of determination of 0.96 and a root mean square error of 0.65 m for a depth range of 0–15 m. The implementation of band optimization significantly reduced computational overhead, yielding a time-saving efficiency of 31–38%. The resulting bathymetric maps exhibited a coherent depth gradient from nearshore to offshore zones, with enhanced seabed morphology representation, particularly in models using pansharpened data. Full article

Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris (Foc), is a devastating disease of chickpea (Cicer arietinum L.), leading to vascular necrosis and plant death. This study evaluated 120 chickpea genotypes under natural infection field conditions during spring sowing in southeastern Kazakhstan, assessing disease incidence (DI) and severity (DS) to identify resistant germplasm. Molecular screening using eight SSR markers linked to Foc-1, Foc-2, Foc-3, and Foc-5 loci detected resistant alleles in 18, 26, 19, and 42 genotypes, respectively. The correlation between molecular marker data and phenotypic resistance evaluations confirmed UBC-170 (Foc-2) and TA-194 (Foc-5) as the most predictive diagnostic markers (p < 0.01). Ten genotypes showed complete disease resistance (DI < 5%, R), corresponding to the resistant control (cultivar “WR-315”), with confirmed presence of multiple Foc resistance genes. The results of this study revealed valuable genetic resources for marker-assisted breeding programs aimed at developing Fusarium wilt-resistant chickpea cultivars adapted to Central Asian agroclimatic conditions. Full article

This study develops a data-driven framework to prevent traffic isolation on snow-affected highways by analyzing vehicle detection system (VDS) data collected over the past decade in the Yeongdong region of the Republic of Korea. Specifically, we used hourly traffic volume and average travel speed between interchange to interchange (IC-IC) segments on days with cumulative snowfall exceeding 30 cm, enabling the identification of critical thresholds that trigger congestion and isolation under extreme snow conditions. By examining the correlation between hourly snowfall intensity, traffic volume, and travel speed, we identified critical thresholds that signal the onset of traffic congestion and isolation, where traffic congestion refers to temporary flow deterioration with average speeds falling below 40 km/h, and traffic isolation denotes and operational breakdown characterized by average travel speeds falling below 20 km/h and prolonged loss of roadway functionality. Results indicated that when snowfall intensity exceeded 2 cm per hour, traffic congestion generally emerged once hourly volumes surpassed 1500 vehicles, whereas traffic isolation became likely when volumes exceeded 2200 vehicles per hour. Building on these findings, this study proposes adaptive traffic control measures that can be proactively implemented during snowstorm conditions. The proposed framework further provides a basis for determining the optimal timing of intervention before isolation occurs, thereby preventing operational breakdowns and enhancing both the resilience and sustainability of winter highway operations. Full article

Background: Patients bearing large-volume, bulky primary or relapsed tumors, are usually referred to palliative low-dose radiotherapy with very poor results. Lattice Radiation Therapy (LRT) is able to produce a high number of high-dose foci or vortexes (multiple SBRT treatments), separated by low-dose zones (valleys). Treatment planning on vortex placing, valley definition, and dose administered depends on individual decisions of the treating team. The aim of our study is to assess for the first time the possibility of a dense fractionated LRT within the target volume. Methods: A total of 22 treatments in 20 patients were performed in the frame of a prospective observational study of fractionated LRT ongoing in our institution. According to our aim of achieving dense LRT, no GTV contraction was considered to create the LRTV (GTV is equal to LRTV). The vortexes were segmented as 1 cm diameter at a 1.5 cm vortex-to-vortex distance. Dose prescription to the vortexes per fraction was 12 Gy. Results: The vortex/LRTV ratio was 7.38 ± 2.13% (3.4–10.40%, median 7.60%). Mean dose to the vortex volume was 11.90 ± 0.09 Gy (11.70–12.10 Gy, median 11.90 Gy). Mean dose administered to the valley volume was 8.29 ± 0.70 (7.05–9.51 Gy, median 8.29 Gy). Valley/vortex (peak) dose ratio (VPDR) was 69.40 ± 6.02% (59.00–79.80%, median 69.70%). The mean peripheral tumor dose was 5.11 ± 0.8710 Gy (3.16–6.78 Gy, median 5.18 Gy). Conclusions: Our dense LRT schedule fulfilled most of the recommended guidelines for LRT, increasing the high dose points without risking the dose to the surrounding tissues. Further analysis of feasibility and safety are needed to secure the clinical relevance of our proposed protocol. Full article

This study was aimed at providing athletes a solution to replenish the muscle glycogen re-synthesis at an optimal rate with hemp seeds as a natural protein source and Bengal gram dal and its use for the preparation of gel. The gel contains the richest source of energy, and it is an effective way to provide energy and nutrients to athletes. The gel was prepared in three variations with different hemp seed concentrations. We then analyzed the gel for pH and macronutrient composition. The sensory characteristics were analyzed for seven parameters, including appearance, taste, color, texture, aroma, consistency, and acceptability, using a hedonic scale on 25 panelists. A sensory analysis showed that sample A received an overall acceptability score of 7.16 ± 0.99 from the sensory panel. The shelf life was observed at the recommended temperature of 4 degrees Celsius, which was 12 days. The best formulation was sample B with 38 g of hemp seeds, which showed better taste, color, aroma, and acceptability and a lower average pH value (6.68 ± 1.44, 6.56 ± 1.29, 7.6 ± 1.16, 7 ± 1.26, and 5.822 ± 0.0183, respectively). Sample B contained 30.8 g of protein, 16.09 g of carbohydrates, 8.4 g of fat, and 263.16 kcal of energy per 100 g. The resulting ratio of carbohydrates to protein is optimal for use as a high-protein post-workout meal. Hence, it can be considered a post-workout supplement. Full article

On the morning of 7 March 2025, the Argentine district of Bahía Blanca experienced a severe flooding that led to at least 15 fatalities. This study presents the main aspects of the event based on different data sources that helped to explain the exceptional precipitation of about 300 mm and rapid flooding. The results indicated that Bahía Blanca district presented flooded areas of approximately 33 km² (1.4% of the total area) on 10 March, most of them concentrated in the non-urbanized zones. However, a total of 18 km² (0.8% of the total area) was still identified on 11 March, with a greater impact on the low-lying urban areas of the Bahía Blanca, General Daniel Cerri, and Ingeniero White towns. The likelihood of severe weather development was confirmed from instability indices. The very high moisture content along a low-level convergence line, jointly with upper-level divergence, contributed to deep convective cloud development that affected Bahía Blanca for at least 6 h. Increasing knowledge of urban floods from different data sources can support weather forecasts to provide timely warnings, essential to mitigate the adverse impacts of these extreme weather events on low-lying urban areas. Full article

This study investigated the impact of soil properties under greenhouse conditions on the growth and productivity of two chickpea (Cicer arietinum) genotypes (V1 and V2) using two distinct soils collected from Marchouch and Beni Mellal sites. Soil analysis revealed significant differences in organic matter, phosphorus, potassium, and nitrogen levels between the two sites. Marchouch soil, characterized by higher nutrient content, especially phosphorus, demonstrated a more favorable environment for chickpea growth, resulting in enhanced plant height, leaf number, chlorophyll content, seed number, and seed weight. Variety V2 showed slightly better performance than V1 across both soil types, particularly in terms of seed yield and mineral content. This research highlights the importance of soil nutrient availability. Furthermore, this study emphasizes the important role of phosphorus in chickpea growth, with Marchouch soil having a higher phosphorus level (62.9 mg kg⁻¹), significantly boosting plant development and yield. Although soil mineral characteristics and genotypes had little effect on most minerals, zinc (19.77 mg uL⁻¹) and iron (69.43 mg uL⁻¹) levels stood out as significant exceptions. Therefore, further studies should focus on examining additional soil characteristics and expanding genotype selection. Based on the findings, Marchouch soil appears to be more favorable for chickpea cultivation. However, more research is needed on the effect of soil and genotypes on Rhizobium activity. Full article

Chickpea is among the major legume crops grown globally. In Ethiopia, it plays a vital role in the food security and economic stability of smallholder farmers. However, its production is often hampered by abiotic factors, particularly soil acidity, which is a major yet often overlooked challenge. Using tolerant genotypes alone or combined with soil amendments is a sustainable approach to improving chickpea production in acidic soils. Hence, the present study assessed the genetic variation of 64 Ethiopian chickpea accessions for acidic-soil tolerance using simple lattice design-based field experiments with two replications at two sites with acidic soil, Emdebir and Holetta. The study revealed significant genetic variation among the evaluated accessions for acid soil tolerance. The study also identified tolerant and high-yielding chickpea accessions with a high yield stability index (YSI) at both test sites. The landrace ETC_B_1_2016 exhibited the highest number of primary branches per plant (NPB), number of pods per plant (NPP), and total seed yield (TSY) at the Emdebir acidic soil trial. At the Holetta acidic soil trial, the landrace ETC_41237 recorded the highest TSY, followed by ETC_K_3_2016 and ETC_B_1_2016, while Akaki had the least. In addition, 14 accessions had the highest TSY and YSI at the Emdebir site, while 16 had the highest YSI at the Holetta site. Notably, NPP displayed the strongest positive correlation with TSY at both sites, irrespective of lime application. Higher genetic variance and broad-sense heritability observed for NPP, hundred-seed weight (HSW), and TSY suggest that genetic factors mainly influence these traits and are more likely to improve through selection. The identified acid-tolerant and high-yielding accessions could be considered for direct cultivation in areas with acidic soils, potentially increasing chickpea productivity. Additionally, these accessions can be crossbred with existing improved varieties to enhance their adaptability to acidic soils, ultimately contributing to food security in regions affected by soil acidity. Full article

The proliferation of 5G networks has revolutionized wireless communication by delivering enhanced speeds, ultra-low latency, and widespread connectivity. However, in heterogeneous cloud radio access networks (H-CRAN), efficiently managing inter-cell interference while ensuring energy conservation remains a critical challenge. This paper presents a novel energy-efficient, dynamic enhanced inter-cell interference coordination (eICIC) scheme based on deep reinforcement learning (DRL). Unlike conventional approaches that focus primarily on optimizing parameters such as almost blank subframe (ABS) ratios and bias offsets (BOs), our work introduces the transmission power during ABS subframes (TPA) and the channel quality indicator (CQI) threshold of victim user equipments (CTV) into the optimization process. Additionally, this approach uniquely integrates energy consumption into the scheme, addressing both performance and sustainability concerns. By modeling key factors such as signal-to-interference-plus-noise ratio (SINR) and service rates, we introduce the concept of energy-utility efficiency to balance energy savings with quality of service (QoS). Simulation results demonstrate that the proposed scheme achieves up to $70\%$ energy savings while enhancing QoS satisfaction, showcasing its potential to significantly improve the efficiency and sustainability of future 5G H-CRAN deployments. Full article

Legume crops play a key role in hastening both the agroecological and protein transition and improving the sustainability of cropping systems. Among legumes, chickpea (Cicer arietinum L.) is a valuable source of protein, fibers, and nutraceutical compounds, providing important agri-environmental effects. Nevertheless, few studies have explored the effect of genetic characteristics on production and quality traits in chickpea. Chickpea landraces seem particularly interesting for their positive agronomic and quality characteristics, opening the door for innovation in sustainable food systems. Thus, the present study aimed to characterize two chickpea Tuscan landraces (Rugoso della Maremma and Cappuccio della Valtiberina) in comparison with widely distributed commercial chickpea varieties (Ares, Maragià, Pascià, Principe, Reale, Sultano, and Vittoria). Our findings highlighted positive agronomic traits of landraces in terms of seed yield and yield components, demonstrating performance that is either superior or comparable to commercial varieties. Notably, Cappuccio della Valtiberina showed the highest 1000-seed weight (425.50 g), followed by Maragià (432.92 g), Principe (392.32 g), and Reale (382.79 g), and the highest harvest index (0.55), similar to Reale (0.55). Overall, landraces achieved 18.75% higher yields than commercial varieties. Regarding chickpea quality, landraces exhibited profiles comparable to those of commercial genotypes in terms of protein and oil content, as well as nutraceuticals. Interestingly, the two landraces had the most favorable ω-6/ω-3 ratios (Cappuccio della Valtiberina, 12.45; Rugoso della Maremma, 13.71) among the genotypes except for Maragià (11.78), indicating better nutritional quality compared to commercial varieties (>14.00). These results demonstrated that landraces could offer promising prospects for future chickpea breeding programs, aiding in the selection of genotypes capable of adapting to changing growing conditions and supporting the development of sustainable food systems. Full article

Sepsis is characterized by multiple organ dysfunction, which is now accepted to be due to oxidative damage. The lung is the first organ exposed to this damage, and its injury is one of the leading causes of death. Therefore, many pharmacological strategies are employed to attenuate sepsis. This study aimed to evaluate the in silico and in vitro antibacterial activity of Cicer arietinum extract (CAE) against Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa and the in vivo modulatory effect of CAE against sepsis induced by cecal ligation and puncture (CLP) in rats. This study identified seven bioactive components in Cicer arietinum extract, revealing promising interactions between these components and Staphylococcus aureus-PBP2a and Pseudomonas aeruginosa-PBP3 proteins, highlighting their potential as novel antibacterial agents. After ensuring the bactericidal ability of CAE against Staphylococcus aureus and Pseudomonas aeruginosa, an in vivo study was performed. Twenty-four rats were divided into sham-operated rats, CLP-septic rats, CLP rats treated with CAE (500 mg/kg b.wt), and CLP rats treated with hydrocortisone (25 mg/ kg b.wt). CAE was administered orally for 3 days post-operation, and animals were euthanized on the fourth day. Another twenty-four rats were used to study survival for 5 days. This study revealed that CAE, like hydrocortisone, can rescue CLP rats from death by suppressing lung procalcitonin (PCT) and MDA and enhancing SOD, CAT, and GSH levels significantly, as compared with the CLP group. The histopathological results were parallel with the biochemical results since the CLP rats treated with CAE had lower histological/inflammatory scores in the lung like hydrocortisone. The beneficial role of CAE may result from its antibacterial and antioxidant activities, and CAE can be considered as a lung antiseptic extract. This study provides a novel treatment for sepsis-induced ALI. However, the beneficial impact of CAE needs extensive study to obtain evidence. Full article

Enhancing plants’ resistance against FW is crucial for ensuring a sustainable global chickpea production. The present study focuses on the identification of fungal pathogens and the assessment of ninety-six chickpea samples for Fusarium wilt from the International Center for Agricultural Research in the Dry Areas (ICARDA)’s collection. Eight fungal isolates were recovered from the symptomatic chickpeas. Polyphasic identification was conducted by comparing the internal transcribed spacer region (ITS), the elongation factor 1-α (tef1-α), and beta-tubulin (tub2). Among them, Neocosmospora solani, N. nelsonii, N. falciformis, N. brevis, Fusarium brachygibbosum, and F. gossypinum were identified. An analysis of the genetic diversity of chickpeas, using 69 polymorphic simple sequence repeat (SSR) markers, revealed a total of 191 alleles across all markers, with, on average, each SSR marker detecting approximately 2.8 alleles. A STRUCTURE analysis delineated lines into two distinct sub-groups (K = 2). Association mapping, using the generalized linear model (GLM) and mixed linear model (MLM) approaches, identified six and five marker–trait associations (MTAs) for FW resistance, respectively. Notably, these TA42, TA125 (A) and TA125 (B), TA37, and TAASH MTAs, commonly found in both models, emerge as potential candidates for the targeted enhancement of FW resistance in chickpeas. To our knowledge, this study represents an inaugural report on the association mapping of genomic loci governing FW resistance in chickpeas from the ICARDA’s accessions. Full article

Chickpeas (Cicer arietinum L.) are an important legume crop known for their rich nutrient content, including proteins, carbohydrates, and minerals. Thus, they are enjoyed by people worldwide. In recent years, the production scale of chickpeas has been growing gradually. The planting area of chickpeas represents roughly 35–36% of the total planting area, and the output of the beans is roughly 47–48%. However, the growth and development process of chickpeas is limited by a number of factors, including high temperature, drought, salt stress, and so forth. In particular, high temperatures can reduce the germination rate, photosynthesis, seed setting rate, and filling rate of chickpeas, restricting seed germination, plant growth, and reproductive growth. These changes lead to a decrease in the yield and quality of the crop. Heat shock proteins (HSPs) are small proteins that play an important role in plant defense against abiotic stress. Therefore, in the present study, HSP20 gene family members were identified based on the whole-genome data of chickpeas, and their chromosomal positions, evolutionary relationships, promoter cis-acting elements, and tissue-specific expression patterns were predicted. Subsequently, qRT-PCR was used to detect and analyze the expression characteristics of HSP20 genes under different temperature stress conditions. Ultimately, we identified twenty-one HSP20 genes distributed on seven chromosomes, and their gene family members were found to be relatively conserved, belonging to ten subfamilies. We also found that CaHSP20 promoter regions have many cis-acting elements related to growth and development, hormones, and stress responses. In addition, under high-temperature stress, the relative expression of CaHSP20-17, CaHSP20-20, CaHSP20-7, CaHSP20-3, and CaHSP20-12 increased hundreds or even thousands of times as the temperature increased from 25 °C to 42 °C. Among them, excluding CaHSP20-5, the other five genes all contain 1-2 ABA cis-regulatory elements. This finding indicates that CaHSP20s are involved in the growth and development of chickpeas under heat stress, and the mechanisms of their responses to high-temperature stress may be related to hormone regulation. The results of the present study lay the foundation for exploring HSP20 gene family resources and the molecular mechanisms of heat resistance in chickpeas. Our results can also provide a theoretical basis for breeding high-temperature-resistant chickpea varieties and provide valuable information for the sustainable development of the global chickpea industry. Full article

Root rot caused by Fusarium spp. is a significant issue in the chickpea-growing regions of Montana. The specific Fusarium species responsible for the disease and their prevalence remain uncertain. A survey was conducted in 2020 and 2021 to identify Montana’s Fusarium species associated with chickpea. Four hundred and twenty-six Fusarium isolates were recovered from symptomatic chickpea roots across ten counties in the state. Isolates were identified by comparing translation elongation factor 1-α (TEF1-α) sequences in the FUSARIUM-ID database. Among the recovered isolates, Fusarium oxysporum was the most prevalent species (33%), followed by F. acuminatum (21%), F. avenaceum (15%), F. redolens (14%), F. culmorum (6%), F. sporotrichioides (6%), Neocosmospora solani (6%), F. equiseti (2%), F. torulosum (0.9%), F. gamsii (0.8%), F. proliferatum (0.2%), F. pseudograminearum (0.2%), and F. brachygibbosum (0.1%). The aggressiveness of a subset of 51 isolates representing various Fusarium spp. was tested on chickpea cv. ‘CDC Frontier’. A non-parametric variance analysis conducted on disease severity ranks indicated that F. avenaceum isolates were highly aggressive. This study reports for the first time that F. gamsii, F. proliferatum and F. brachygibbosum are causal agents of root rot in chickpea in the United States. This knowledge is invaluable for making informed decisions regarding crop rotation, disease management, and developing resistant chickpea varieties against economically significant Fusarium pathogens. Full article

Recently, nuclear abnormalities in avian erythrocytes have been used as biomarkers of genotoxicity in several species. Anomalous shapes are usually detected in the nuclei by means of microscopy inspection. However, due to inter- and intra-observer variability, the classification of these blood cell abnormalities could be problematic for replicating research. Deep learning, as a powerful image analysis technique, can be used in this context to improve standardization in identifying the biological configurations of medical and veterinary importance. In this study, we present a standardized deep learning model for identifying and classifying abnormal shapes in erythrocyte nuclei in blood smears of the hemispheric and synanthropic Kelp Gull (Larus dominicanus). We trained three convolutional backbones (ResNet34 and ResNet50 architectures) to obtain models capable of detecting and classifying these abnormalities in blood cells. The analysis was performed at three discrimination levels of classification, with broad categories subdivided into increasingly specific subcategories (level 1: “normal”, “abnormal”, “other”; level 2: “normal”, “ENAs”, “micronucleus”, “other”; level 3: “normal”, “irregular”, “displaced”, “enucleated”, “micronucleus”, “other”). The results were more than adequate and very similar in levels 1 and 2 (F1-score 84.6% and 83.6%, and accuracy 83.9% and 82.6%). In level 3, performance was lower (F1-score 65.9% and accuracy 80.8%). It can be concluded that the level 2 analysis should be considered the most appropriate as it is more specific than level 1, with similar quality of performance. This method has proven to be a fast, efficient, and standardized approach that reduces the dependence on human supervision in the classification of nuclear abnormalities in avian erythrocytes, and can be adapted to be used in similar contexts with reduced effort. Full article