Search Results (4,717)

The multimodal North Sea–Baltic corridor, consisting of 6934 km of road, is an integral part of the EU’s trans-European transport network. However, an unsatisfied level of development of alternative fuels infrastructure for road transport is considered one of the obstacles to connecting northern Member States and North-East countries. A “what-if” scenario was employed to obtain useful insights into how a given situation might be handled, and a comparison of several paths forward to make better decisions was analysed. Environmental insights for transportation sector scenarios in 2030–2035 were explored and analysed using the COPERT v5.5.1 software program. In this study, the installation of natural gas infrastructures of various station sizes and with varying capacities and types of natural gas (LNG, CNG, bio-methane) dispensed was evaluated in detail. Replacement of the existing HDV fleet (heavy-duty vehicles) with LNG-powered trucks would result in the following investment to upgrade the existing network and build new stations to meet rising LNG demand: from €21.47 to €32.3 million (the scenario of 10% market share for HDVs running on LNG), €42.94 to €64.6 (20%), and €64.4 to €96.9 (30%). The dual-fuel 10–diesel fuel 90% scenario seems to be the safest option for a large-scale investment until 2035 which may lead to moderate emission savings of 84.6 kton CO₂ eq. compared to 2022 levels. Full article

Digital technologies that continuously quantify animal behavior, physiology, and production offer significant potential for the early identification of health and welfare disorders of dairy cows. In this study, a multimodal artificial intelligence (AI) framework is proposed for real-time health monitoring of dairy cows through the integration of physiological, behavioral, production, and thermal imaging data, targeting veterinarian-confirmed udder, leg, and hoof infections. Predictions are generated at the cow-day level by aggregating multimodal measurements collected during daily milking events. The dataset comprised 88 lactating cows, including veterinarian-confirmed udder, leg, and hoof infections grouped under a single ‘sick’ label. To prevent information leakage, model evaluation was performed using a cow-level data split, ensuring that data from the same animal did not appear in both training and testing sets. The system is designed to detect early deviations from normal health trajectories prior to the appearance of overt clinical symptoms. All measurements, with the exception of the intra-ruminal bolus sensor, were obtained non-invasively within a commercial dairy farm equipped with automated milking and monitoring infrastructure. A key novelty of this work is the simultaneous integration of data from three independent sources: an automated milking system, a thermal imaging camera, and an intra-ruminal bolus sensor. A hybrid deep learning architecture is introduced that combines the core components of established models, including U-Net, O-Net, and ResNet, to exploit their complementary strengths for the analysis of dairy cow health states. The proposed multimodal approach achieved an overall accuracy of 91.62% and an AUC of 0.94 and improved classification performance by up to 3% compared with single-modality models, demonstrating enhanced robustness and sensitivity to early-stage disease. Full article

The global shipping fleet uses vast quantities of fossil fuels and releases significant levels of pollution. Supplying ships moored at quays in ports with onshore power allows them to shut down onboard engines, cutting fossil fuel use and reducing emissions. This is particularly significant when ports utilize green electricity. Equipping ports to connect serviced ships to onshore power grids involves substantial investments, which must be carefully optimized. The aim of this article is to develop a methodology, grounded in probability theory, for determining the electrical power required to connect ships to onshore power grids in ports. The proposed methodology was developed and validated through a case study of container terminal operations. By applying this methodology and considering the conditions of ship service in ports, it is possible to estimate both the number of ships and their berthing durations at quays, as well as the electrical power required from onshore networks to connect the vessels. The results of this research may be of interest to port managers, terminal operators, shipowners, and other stakeholders involved in the development of onshore power grids for ship connections in ports. Full article

The patch-clamp technique is widely regarded as the gold standard in cellular electrophysiology and can be applied in several configurations. In the cell-attached (C-A) mode, it enables the recording of single-channel currents, whereas the whole-cell (W-C) mode allows for the measurement of macroscopic currents, representing the collective activity of many channels. When the recording configuration was switched from C-A to W-C on the same cell, the current amplitude increased dramatically, while action currents (ACs) were completely abolished, indicating a profound alteration in the cell’s electrophysiological response under the new setup. In excitable cells, the occurrence of ACs, representing propagated action potentials, can interfere with C-A single-channel recordings. To address this, a high-K⁺ solution is typically applied to the bath to suppress the ACs. The inwardly rectifying K⁺ (Kir), ATP-sensitive K⁺ (K_ATP) and large-conductance Ca²⁺-activated K⁺ (BK_Ca) channels are crucial members of the K⁺ channel family that facilitate the efflux of K⁺ ions, driven by the K⁺ electrochemical gradient. These channels are primarily distinguished by their rectification properties and gating kinetics. For instance, K_ATP channels exhibit a bursting kinetic pattern with inward rectifying property, while BK_Ca channels display strong outward rectification. Mitoxantrone, which belongs to a class of drugs called anthracenediones, can suppress the activity of Kir channels in differentiated RAW 264.7 cells, with no change in single-channel conductance. The respiratory stimulator GAL-021 acts as a BK_Ca channel inhibitor, and it suppresses channel activity and shifts the activation curve to the right, suggesting a voltage-dependent blockade that stabilizes the channel in a closed state. GAL-021 does not change the single-channel conductance, indicating it is a gating modifier rather than an open-pore blocker. The functional roles of ion channels are fundamentally important. Correspondingly, the field is transitioning to artificial intelligence for automated single-cell patch-clamp experiments, though brain slice recordings still require manual techniques. Full article

Although sympatric carnivores typically exhibit dietary differentiation to reduce interspecific competition, contemporary isotopic comparisons of European mustelids remain scarce. In this study, we present the first modern stable isotope analysis of hair to evaluate the dietary niches and trophic relationships of pine martens (Martes martes), stone martens (Martes foina), and European polecats (Mustela putorius) in Lithuania and Latvia. The stable carbon and nitrogen isotope values differed among the species. M. martes showed lower δ¹⁵N values and more depleted δ¹³C signatures than the two more synanthropic species. Isotopic niche analyses revealed that M. martes occupied the broadest niche, while M. foina and M. putorius exhibited narrower niches with substantial overlap. Habitat influenced trophic position: individuals from settlements showed higher δ¹⁵N values than those from forests or wetlands. In contrast, sex- and age-related differences were weak or absent. These results demonstrate that despite partial spatial coexistence, sympatric mustelids differ primarily in isotopic niche structure rather than mean isotope values and that human-modified environments promote trophic convergence among generalist mesocarnivores. However, the small sample sizes for M. foina and M. putorius mean that estimates of isotopic niche width and overlap should be regarded as preliminary, and observed sex- and age-related patterns likely reflect limited statistical power rather than the absence of intraspecific dietary variation. Full article

Recently, increasing attention has been paid to the application of sulfonic acids as alternative materials for the pickling process. The aim of the present study was to investigate the action of pickling with p-toluenesulfonic acid monohydrate on derma’s collagen and the influence of this action on subsequent processes and properties of chromed and crust leather. The application of p-toluenesulfonic acid monohydrate in the pickling process led to a similar effect on collagen compared with conventional process. The solutions after experimental pickling contained lower amounts of total dissolved solids, total suspended solids, and chlorides. The chrome tanning process is improved after the pickling with p-toluenesulfonic acid monohydrate: the exhaustion of chromium compounds reaches 98%, while after conventional pickling, it is only 68.7%; accordingly, lower amounts of basic chromium sulfate can be used for chrome tanning to achieve the same chromium content in the wet blue leather. The crust leather produced after experimental pickling has properties close to the conventional one. Full article

This pilot hypothesis-generating study evaluated whether lipid-related biomarkers (Lp(a), ApoB, and oxLDL), endothelial injury markers (endocan, vimentin), and extracellular matrix glycoproteins (TSP-1, TSP-2) reflect the severity of coronary artery disease (CAD) in patients with stable angina pectoris. 93 patients underwent invasive coronary angiography/coronary CT angiography. CAD severity was evaluated using Gensini, SIS, SSS, and CAD-RADS scores. CAD was confirmed in 76.3% (n = 71). OxLDL correlated with Gensini (r = 0.455; p = 0.006), atherosclerotic segments (r = 0.469; p = 0.005), arteries (r = 0.479; p = 0.004), revascularization indication (r = 0.318; p = 0.003), circumflex artery stenosis (r = 0.323; p = 0.005). OxLDL also correlated with vimentin (r = 0.459; p < 0.001). Vimentin correlated with Gensini (r = 0.480; p = 0.005), SIS (r = 0.349; p = 0.003), SSS (r = 0.320; p = 0.008), CAD-RADS (r = 0.331; p = 0.005), atherosclerotic segments (r = 0.515; p = 0.003), arteries (r = 0.384; p = 0.030), revascularization indication (r = 0.324; p = 0.003). Endocan, TSP-1, and TSP-2 showed no significant associations. These exploratory findings suggest that oxLDL and vimentin may be associated with CAD severity; however, confirmation in larger, prospective cohorts is required. Full article

Background/Objectives: This study examines the application of the novel double emulsion gel system for the delivery and release of encapsulated cannabidiol (CBD) and the probiotic strain Lactiplantibacillus plantarum DSM 24624. Methods: During a six-week experimental period comprising stabilization, treatment, and wash-out phases, the dynamic Simulator of the Human Intestinal Microbial Ecosystem (SHIME^®) model was employed to assess a system. The evaluation focused on the delivery of CBD and probiotics, as well as the system’s effects on microbial composition, diversity, and metabolic activity throughout the digestion process using 16S rRNA gene sequencing and digital PCR methods. Results: Microbial community analysis revealed significant shifts in both mucosal and luminal microbiota following supplementation. The treatment increased beneficial bacterial families such as Lachnospiraceae and Clostridiaceae, demonstrated effective delivery, release, and persistence of the probiotic L. plantarum, as well as enhanced butyrate and lactate production. Diversity analyses highlighted a transient rise in alpha diversity within the mucin layer and a decrease in the lumen, with significant changes in beta diversity across experimental phases. Conclusions: Findings suggest that double emulsion gel can be employed for the delivery of probiotics and CBD to the gastrointestinal tract. In addition, an innovative CBD-probiotic formulation can modulate gut microbiota composition and metabolic activity, suggesting its potential as a functional food innovation for intestinal health. However, the results are based on an in vitro model, which lacks the complexity of the human host environment, and further clinical studies are necessary to confirm the biological relevance and therapeutic potential of such delivery systems for gastrointestinal health. Full article

Background: Green logistics practices are crucial for achieving the EU’s Green Deal objectives, addressing environmental challenges, improving supply chain efficiency, and fostering business sustainability. This paper presents a conceptual framework for green logistics practices and their application for ensuring sustainable organisational development. Methods: Using the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methodologies, this study assesses the importance of green logistics practices in Lithuanian SMEs and their future application. The AHP method facilitates pairwise comparisons to determine the weights of green logistics criteria, while the SAW method evaluates the final sub-criteria by aggregating normalized scores according to the identified weights. Results: A survey of ten companies revealed that green transportation is the most developed green logistics practice, with the focus on infrastructure, skills and transport optimisation. Green warehousing is the second most significant practice, with SMEs considering it vital to green logistics because of its sustainable warehousing measures. Green packaging is considered third in terms of importance, due to the attention paid to the packaging materials used. Conclusions: The full potential of green logistics has yet to be realised. Adopting a more balanced approach could enhance environmental outcomes and bolster the resilience of the long-term supply chain. Full article

Intensive agriculture, ecosystem degradation, and declining soil quality highlight the urgent need for sustainable land use strategies. The cultivation of short-rotation woody crops (SRC), combined with fertilization using sewage sludge digestate (SSD), offers a promising approach to recycle nutrient-rich waste and promote soil organic carbon (SOC) accumulation. This study evaluated SOC concentrations, stocks and their spatial distribution in the 0–20 cm soil layer under SRC cultivation, with and without SSD fertilization, across contrasting soil types in Eastern Lithuania. The investigated soils included mineral (Luvisols (LV), Retisols (RT), Planosols (PL), Arenosols (AR)), organo-mineral (Gleysols (GL)), and organic soils (Histosols (HS)), representing textures from sand to peat and classified according to the World Reference Base for Soil Resources (WRB). Part I assessed baseline SOC variability in unproductive areas planted with hybrid poplars (Populus spp.) and hybrid aspen (Populus tremula × P. tremuloides) up to 20 years old. Part II examined SOC changes in three SRC fields of different ages (3–10 years), including unfertilized and SSD-fertilized stands. SOC concentrations increased consistently from mineral (1.14–1.80%) to organo-mineral (2.13–3.20%) and organic soils (6.37–17.53%). Heavier-textured soils accumulated more SOC than lighter soils, showing a strong positive correlation between SOC and soil texture (r = 0.82, p ≤ 0.01). SRC cultivation increased SOC across all soil types, while SSD fertilization further enhanced accumulation, with fertilized fields showing SOC increases of 0.50–1.07 percentage points and carbon stocks by 18.8–41.7 t ha⁻¹, compared with smaller increases in unfertilized fields. Spatial visualization of SOC further highlighted long-term accumulation patterns across soil types, confirming the trends observed under SRC cultivation and SSD fertilization. Full article

The increasing demand for sustainable and clean-label foods has intensified the search for natural preservatives that are capable of replacing synthetic additives. In this study, an exploratory assessment of two distinct spruce needle aqueous extracts were conducted—an aqueous extract of Picea pungens (NWE-1) and an aqueous extract of Picea abies obtained after prior supercritical CO₂ treatment (NWE-2)—and both were investigated as potential bioactive ingredients for plant-based meat analogues. Using UPLC–MS, both extracts were comprehensively characterized, revealing a diverse array of phenolic acids, flavonoids, and glycosides. Even though NWE-2 contained a broader range of bioactive compounds, NWE-1 exhibited superior antibacterial performance (total microbial count (TMC)—4.94 log CFU/g), effectively limiting microbial contamination and ensuring product stability for up to 16 days of storage below the typical spoilage threshold (6.0–7.0 log CFU/g). Sensory analysis indicated that the model plant-based meat analogue matrix tolerated up to 3% (w/w) inclusion of NWE-1 and 5% (w/w) inclusion of NWE-2 before significant degradation of flavor and overall acceptability occurred. By utilizing conifer needles as an underexploited side-stream biomass, this work offers an approach for the valorization of conifer needle material through combined green extraction and food application, contributing to circular and resource-efficient processing concepts. The study provides an exploratory perspective on the potential role of forest-derived resources in the development of natural preservatives and their possible contribution to more sustainable food preservation strategies within a circular bioeconomy framework. Full article

Autonomous navigation in cluttered and dynamic industrial environments remains a major challenge for mobile robots. Traditional occupancy-grid and geometric planning approaches often struggle in such unstructured settings due to partial observability, sensor noise, and the frequent presence of moving agents (machinery, vehicles, humans). These limitations seriously undermine long-term reliability and safety compliance—both essential for Industry 4.0 applications. This paper introduces S3PM, a lightweight entropy-regularized framework for simultaneous mapping and path planning that operates directly on dense 3D point clouds. Its key innovation is a dynamics-aware entropy field that fuses per-voxel occupancy probabilities with motion cues derived from residual optical flow. Each voxel is assigned a risk-weighted entropy score that accounts for both geometric uncertainty and predicted object dynamics. This representation enables (i) robust differentiation between reliable free space and ambiguous/hazardous regions, (ii) proactive collision avoidance, and (iii) real-time trajectory replanning. The resulting multi-objective cost function effectively balances path length, smoothness, safety margins, and expected information gain, while maintaining high computational efficiency through voxel hashing and incremental distance transforms. Extensive experiments in both real-world and simulated settings, conducted on a Raspberry Pi 5 (with and without the Hailo-8 NPU), show that S3PM achieves 18–27% higher IoU in static/dynamic segmentation, 0.94–0.97 AUC in motion detection, and 30–45% fewer collisions compared to OctoMap + RRT* and standard probabilistic baselines. The full pipeline runs at 12–15 Hz on the bare Pi 5 and 25–30 Hz with NPU acceleration, making S3PM highly suitable for deployment on resource-constrained embedded platforms. Full article

Given global efforts to promote sustainable energy transitions, this study investigates how the deployment of renewable energy technologies (RETs) relates to multidimensional societal welfare and provides empirical evidence on these linkages in Lithuania. The purpose of the study is to provide an integrated, Lithuania-specific assessment of how economic, social, and environmental determinants associated with RET deployment are related to multiple dimensions of societal welfare. Drawing on scientific literature, an integrated indicator framework is developed that links the economic, social, and environmental determinants of renewable energy technology (RET) deployment to six societal welfare dimensions, as defined by the Lithuanian Quality of Life Index. Using official Lithuanian statistics for 2020–2024, a standardized panel dataset is constructed and Pearson correlation analysis and multiple linear regression are applied using aggregated determinant categories, with model assumptions verified using the Breusch–Pagan and Durbin–Watson tests. Correlation results show very strong positive links between RET intensity indicators and key economic welfare measures (for example, wages, GDP per capita, foreign direct investment, disposable income), with absolute correlation coefficients typically between 0.90 and 0.99 (p < 0.05), and strong negative correlations between air-pollution indicators and GDP, income, FDI, and education (correlation coefficients between −0.96 and −0.90; p < 0.05). The results indicate that RET-related economic determinants have a statistically significant positive effect on the societal welfare dimensions of material living conditions; entrepreneurship/business competitiveness; and public infrastructure, living-environment quality/safety. Social factors also significantly support the societal welfare dimensions of entrepreneurship/business competitiveness and public infrastructure, living-environment quality/safety. In the retained regression models, explanatory power is very high (R² between 0.91 and 0.999), with positive and statistically significant coefficients for the economic determinant (regression coefficients between 0.43 and 0.96; p < 0.05) and negative, statistically significant coefficients for the environmental determinant in the entrepreneurship and public-infrastructure dimensions (regression coefficients between −1.13 and −1.51; p < 0.05). Environmental determinants are associated with lower air pollution but show negative effects on the societal welfare dimensions of entrepreneurship/business competitiveness and public infrastructure, living-environment quality/safety. Overall, the findings suggest that RET deployment is an important correlate of the economic aspects of societal welfare, while environmental and social dimensions display more complex, domain-specific impacts. Full article

Sour cherry is one of the most popular stone fruits in Poland. In the organic production system of sour cherries, no artificial pesticides and fertilizers are allowed, which is one of the organic production requirements increasingly appreciated by producers and consumers. The taste of fruits is created by the sugar and organic acid content and their ratio. Vitamin C is known for its health-promoting properties. The aim of the present study was to analyze and compare the concentrations of vitamin C, sugars, and organic acids and their profiles in organic vs. conventional sour cherry fruits representing different cultivars, in a three-year experiment. In the presented experiment, four sour cherry cultivars, ‘Kelleris’ 16, ‘Oblacińska’, ‘Pandy 103’, and ‘Debreceni Bötermö’, were cultivated in two horticultural systems, organic and conventional, and the content of sugars and organic acids was analyzed in the fruit with HPLC methods. Organically cultivated sour cherry fruits were characterized by significantly higher concentrations of sugars and vitamin C only in the first year of the experiment, when the mean concentrations of fructose, glucose, and sucrose in these fruits reached 4.15 g/100 g F.W., 0.37 g/100 g F.W., and 0.27 g/100 g F.W., respectively, and the concentration of vitamin C reached 17.28 mg/100 g F.W. In the two subsequent years, conventional cherries were more abundant in these compounds. Among the tested sour cherry cultivars, ‘Oblačińska’ performed the best in terms of sugar content. The mean value for total sugars for ‘Oblačińska’ cv. was 5.53 g/100 g F.W. In the case of vitamin C, the highest levels (av. 28.13 mg/100 g F.W.) were noted in the fruits of ‘Pandy 103’ cv. The strong year-to-year variability underscores the need for multi-year experiments and, where possible, multi-site trials, to disentangle cultivar × system × environment interactions. Because the quality of sour cherry for fresh consumption and for processing depends mostly on sugar content, for organic production, ‘Oblačińska’ cv. is strongly recommended. Full article

Background: Diagnosing CNS tumors through MRI is limited by significant variability in scanner hardware, acquisition protocols, and intensity characteristics at clinical centers, resulting in substantial domain shifts that lead to diminished reliability for automated models. Methods: We present a Domain-Adaptive MRI Learning Model (DA-MLM) consisting of an adversarially aligned hybrid 3D CNN–transformer encoder with contrastive regularization and covariance-based feature harmonization. Varying sequence MRI inputs ($T1$, $T1ce$, $T2$, and $FLAIR$) were inputted to multi-scale convolutional layers followed by global self-attention to effectively capture localized tumor structure and long-range spatial context, with domain adaptation that harmonizes feature distribution across datasets. Results: On the BraTS 2020 dataset, we found DA-MLM achieved 94.8% accuracy, 93.6% macro-F1, and 96.2% AUC, improving upon previously established benchmarks by 2–4%. DA-MLM also attained Dice score segmentation of 93.1% (WT), 91.4% (TC), and 89.5% (ET), improving upon 2–3.5% for CNN and transformer methods. On the REMBRANDT dataset, DA-MLM achieved 92.3% accuracy with segmentation improvements of 3–7% over existing U-Net and expert annotations. Robustness testing indicated 40–60% less degradation under noise, contrast shift, and motion artifacts, and synthetic shifts in scanner location showed negligible performance impairment (<0.06). Cross-domain evaluation also demonstrated 5–11% less degradation than existing methods. Conclusions: In summary, DA-MLM demonstrates improved accuracy, segmentation fidelity, and robustness to perturbations, as well as strong cross-domain generalization indicating the suitability for deployment in multicenter MRI applications where variation in imaging performance is unavoidable. Full article