Search Results (157)

The increase in Internet of Things (IoT) devices has introduced significant security challenges, primarily due to their inherent constraints in computational power, memory, and energy. This study provides a comparative performance analysis of selected modern cryptographic algorithms on a resource-constrained IoT platform, the Nordic Thingy:53. We evaluated a set of ciphers including the NIST lightweight standard ASCON, eSTREAM finalists Salsa20, Rabbit, Sosemanuk, HC-256, and the extended-nonce variant XChaCha20. Using a dual test-bench methodology, we measured energy consumption and performance under two distinct scenarios: a low-data-rate Bluetooth mesh network and a high-throughput bulk data transfer. The results reveal significant performance variations among the algorithms. In high-throughput tests, ciphers like XChaCha20, Salsa20, and ASCON32 demonstrated superior speed, while HC-256 proved impractically slow for large payloads. The Bluetooth mesh experiments quantified the direct relationship between network activity and power draw, underscoring the critical impact of cryptographic choice on battery life. These findings offer an empirical basis for selecting appropriate cryptographic solutions that balance security, energy efficiency, and performance requirements for real-world IoT applications. Full article

The present study is part of the efforts to develop a micropropagation protocol for Arracacia xanthorrhiza, focusing on improving in vitro establishment, reducing senescence, and balancing plant growth regulators. To control bacterial contamination during culture initiation, ampicillin and tetracycline were tested using impregnated paper disks. Ampicillin at 100 mg·L⁻¹ achieved 92.4% survival and reduced bacterial contamination to 25.2%, compared to 65.6% in the untreated control, confirming its effectiveness as a low-cost and non-toxic solution. Senescence reduction was evaluated through the addition of activated charcoal and silver nitrate (AgNO₃); the latter, at 26 µM, significantly enhanced explant survival, reduced leaf senescence, and promoted shoot and sprout formation. Three plant growth regulators—6-benzylaminopurine (BAP), kinetin (KIN), and meta-topolin (mT)—were tested at multiple concentrations. Meta-topolin at 1 µM produced 3.5 sprouts and 7.2 leaves per plant, demonstrating three times greater biological activity than BAP and optimal morphogenetic response. The integration of antimicrobial control, ethylene inhibition, and cytokinin optimization resulted in a reliable and scalable protocol for A. xanthorrhiza micropropagation. As a concluding remark, these findings provide a practical and efficient framework for clean plant production, with direct applications in conservation, breeding, and commercial propagation of this underutilized Andean crop, while highlighting the need for further validation across genotypes. Full article

Saline–alkaline wetlands represent critical ecosystems for maintaining biodiversity, regulating hydrological processes, and supporting regional ecological resilience. However, the extent to which dominant vegetation regulates soil functionality and microbial assemblages in these unique saline systems remains insufficiently understood. In this study, we examined five characteristic vegetation types—Phragmites communis Trin., Typha angustifolia L., Bryophytes, Suaeda salsa (L.) Pall., Echinochloa phyllopogon (Stapf) Koss.—across the saline wetlands of Chagan Lake, northeast China, which are embedded in a heterogeneous matrix of forests, grasslands, and agricultural lands. Comprehensive assessments of soil physicochemical properties, enzyme activities, and bacterial communities were conducted, integrating high-throughput sequencing with multivariate statistical analyses. Our results revealed that vegetation cover markedly influenced soil attributes, particularly total organic carbon (TOC) and alkali-hydrolyzed nitrogen (AN), alongside key enzymatic functions such as urease and alkaline phosphatase activities. Proteobacteria, Actinobacteria, and Acidobacteria emerged as dominant bacterial phyla, with their relative abundances tightly linked to vegetation-induced shifts in soil environments. Notably, soils under E. phyllopogon demonstrated elevated bacterial diversity and enzymatic activities, underscoring the synergistic effects of plant selection on soil biogeochemical health. Structural equation modeling further elucidated complex pathways connecting vegetation, microbial diversity, soil quality, and enzymatic functioning. These findings emphasize the pivotal role of vegetation management in improving soil fertility, shaping microbial communities, and guiding the sustainable restoration of saline–alkaline wetlands under environmental stress. Full article

Embedded vision systems play a crucial role in the advancement of intelligent transportation by supporting real-time perception tasks such as traffic sign recognition and lane detection. Despite significant progress, their performance remains sensitive to environmental variability, computational constraints, and scene complexity. This review examines the current state of the art in embedded vision approaches used for the detection and classification of traffic signs and lane markings. The literature is structured around three main stages, localization, detection, and recognition, highlighting how visual features like color, geometry, and road edges are processed through both traditional and learning-based methods. A major contribution of this work is the introduction of a practical taxonomy that organizes recognition techniques according to their computational load and real-time applicability in embedded contexts. In addition, the paper presents a critical synthesis of existing limitations, with attention to sensor fusion challenges, dataset diversity, and deployment in real-world conditions. By adopting the SALSA methodology, the review follows a transparent and systematic selection process, ensuring reproducibility and clarity. The study concludes by identifying specific research directions aimed at improving the robustness, scalability, and interpretability of embedded vision systems. These contributions position the review as a structured reference for researchers working on intelligent driving technologies and next-generation driver assistance systems. The findings are expected to inform future implementations of embedded vision systems in real-world driving environments. Full article

Background: Older adults with mild cognitive impairment are at increased risk for physical decline and falls due to decreased strength, flexibility, balance, and gait. Dance-based aerobic training has emerged as a promising and enjoyable intervention to promote physical function and cognitive stimulation. This study aimed to evaluate the efficacy of a 12-week structured dance-based aerobic program, based on line dancing and Latin rhythms (e.g., salsa, merengue, and bachata), in improving functional capacity and reducing the risk of falls in older adults with mild cognitive impairment. Methods: A randomized controlled trial was conducted with 92 participants aged ≥65 years diagnosed with mild cognitive impairment. The participants were randomly assigned to an experimental group (dance-based training, twice weekly for 12 weeks) or a control group (usual activity). Outcomes included muscle strength (grip dynamometry), flexibility (back scratch and chair sit-and-reach tests), gait speed (Timed Up and Go test), balance (Tinetti scale), and total falls risk score (Tinetti). Mixed ANOVA and Cohen’s d were used for statistical analysis. Results: Significant improvements were observed in the experimental group on all variables compared to the control group. Muscle strength (p < 0.001, d = 0.86), gait speed (p = 0.026, d = 0.48), and upper and lower extremity flexibility (d = 0.43–0.79) improved significantly. The balance and gait components of the Tinetti scale also increased (p = 0.007 and p = 0.048, respectively), as did the total Tinetti score (p = 0.002, d = 0.67), indicating a reduction in the risk of falls. Conclusions: These findings suggest that, under structured conditions, dance-based aerobic training may serve as a promising non-pharmacological strategy to support healthy aging in older adults with mild cognitive impairment, although further validation in larger cohorts is needed. Full article

Background/Objectives: Miscarriage is an increasingly common event worldwide arising from various factors, and identifying its etiology is important for planning and managing any future pregnancies. It is estimated that about half of early pregnancy loss cases are caused by genetic abnormalities, while a significantly lower rate is found in late pregnancy loss. Multiplex ligation-dependent probe amplification (MLPA) can detect small changes within a gene with precise breakpoints at the level of a single exon. The aim of our study was to identify the rate of copy number variations (CNVs) in spontaneous pregnancy loss samples after having previously tested them via quantitative fluorescence PCR (QF-PCR), with no abnormal findings. Methods: DNA was extracted from product-of-conception tissue samples, followed by the use of an MLPA kit for the detection of 31 microdeletion/microduplication syndromes (SALSA^® MLPA^® Probemix P245 Microdeletion Syndromes-1A, MRC-Holland, Amsterdam, The Netherlands). Results: A total of 11 (13.1%) out of the 84 successfully tested samples showed CNVs. Duplications accounted for 9.5% of the analyzed samples (eight cases), while heterozygous or hemizygous deletions were present in three cases (3.6%). Among all the detected CNVs, only three were certainly pathogenic (3.6%), with two deletions associated with DiGeorge-2 syndrome and Rett syndrome, respectively, and a 2q23.1 microduplication syndrome, all detected in early pregnancy loss samples. For the remaining cases, additional genetic tests (e.g., aCGH/SNP microarray) are required to establish CNV size and gene content and therefore their pathogenicity. Conclusions: MLPA assays seem to have limited value in detecting supplementary chromosomal abnormalities in miscarriages. Full article

Vegetation succession is a critical indicator of ecosystem structure and function and is often disrupted by the expansion of invasive species. However, ecosystem-scale studies elucidating invasion-driven succession mechanisms remain limited. This research focused on the Yancheng coastal salt marsh and analyzed the distribution variation of invasive species (Spartina alterniflora) and native species (Suaeda salsa and Phragmites australis) from 1987 to 2022 via the Google Earth Engine and random forest method. Logistic/Gaussian models were used to quantify land–sea distribution changes and vegetation succession trajectories. By integrating data on soil salinity, invasion duration, and fractional vegetation cover, generalized additive models (GAMs) were applied to identify the main factors influencing vegetation succession and to explore how Spartina alterniflora invasion affects the succession of salt marsh vegetation. The results indicated that the areas of Spartina alterniflora and Phragmites australis significantly increased by 3787.49 ha and 3452.60 ha in 35 years, respectively, contrasting with Suaeda salsa’s 82.46% decline. The FVC in the area has significantly increased by 42.10%, especially in the coexisted areas of different vegetation communities, indicating intensified interspecific competition. The overall trend of soil salinity was decreasing, with a decrease in soil salinity in native species areas from 0.72% to 0.37%. From the results of GAMs, soil salinity, tidal action, and invasion duration were significant factors influencing the distribution of native species, but salinity was not a significant factor affecting the Spartina alterniflora distribution. The findings revealed that the expansion of Spartina alterniflora changed the soil salinity and interspecific interactions, thereby altering the original plant community structure and establishing a new vegetation succession. This study enhances the understanding of the impacts of invasive species on ecosystems and offers theoretical support for salt marsh restoration. Full article

Suaeda salsa is relatively tolerant to cadmium (Cd) contamination. In order to investigate the bioaccumulation and stress responses of S. salsa under chronic exposure, we explored the growth, accumulation, and changes in antioxidant enzymes and glutathione (GSH) under different Cd concentrations over a 30-day soil culture experiment. Seedling height and weight in the 13.16 mg/kg Cd group were 13.26 cm and 0.21 g, significantly higher than the control group. Growth was significantly inhibited under high Cd concentration exposure, with a seedling and root length of 9.65 cm and 3.77 cm. The Cd concentration in all tissues was positively related to Cd treatment concentration, with the Cd contents in the roots being higher than in the other tissues. At a subcellular level, Cd was mainly concentrated in the cell walls, organelles, and soluble components within the range of 0.05–8.29, 0.02–2.40 and 0.08–1.35 μg/g, respectively. The accumulation of Cd in the roots tracked its proportion in the cell walls. The malondialdehyde (MDA) content of the plant tissues increased with increasing Cd concentration, indicating that Cd stress caused oxidative damage. The GSH content increased with increasing Cd concentration, with maximum values of 0.515 μmol/g in the stem in the 66.07 mg/kg Cd group. The catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD) activity showed different change trends under Cd exposure. The results in this study could provide useful information on the tolerance mechanism of Cd in S. salsa, which provides information for exploiting S. salsa as a candidate for phytoremediation of Cd contamination. Full article

Diabetic foot ulcers (DFUs) are a serious complication of diabetes, associated with high recurrence and amputation rates. Adherence to offloading devices is critical for wound healing but remains inadequately monitored in real-world settings. This study evaluates the SmartBoot edge-computing system—a wearable, real-time remote monitoring solution integrating an inertial measurement unit (Sensoria Core) and smartwatch—for its validity in quantifying cadence and step count as digital biomarkers of frailty, and for detecting adherence. Twelve healthy adults wore two types of removable offloading boots (Össur and Foot Defender) during walking tasks at varied speeds; system outputs were validated against a gold-standard wearable and compared with staff-recorded adherence logs. Additionally, user experience was assessed using the Technology Acceptance Model (TAM) in healthy participants (n = 12) and patients with DFU (n = 81). The SmartBoot demonstrated high accuracy in cadence and step count across conditions (bias < 5.5%), with an adherence detection accuracy of 96% (Össur) and 97% (Foot Defender). TAM results indicated strong user acceptance and perceived ease of use across both cohorts. These findings support the SmartBoot system’s potential as a valid, scalable solution for real-time remote monitoring of adherence and mobility in DFU management. Further clinical validation in ongoing studies involving DFU patients is underway. Full article

Limited research has been conducted on the potential and mechanisms of irrigating Suaeda salsa with wastewater and microalgae to improve saline–alkali land. This study used three irrigation treatments (freshwater, saline wastewater, and saline wastewater with microalgae) to irrigate S. salsa, and microalgae promoted the growth of S. salsa and increased soil nutrient content, increasing available nitrogen (4.85%), available phosphorus (44.51%), and organic carbon (24.05%) while alleviating salt stress through reduced soil salinity (13.52%) and electrical conductivity (21.62%). These changes promoted eutrophic bacteria while inhibiting oligotrophic bacteria. Bacterial community composition exhibited significant variations, primarily driven by soil pH, total nitrogen, and organic carbon content. Notably, rhizosphere bacteria showed enhanced functional capabilities, with increased abundance of salt stress resistance and nitrogen metabolism-related genes compared to original soil, particularly under saline irrigation conditions. Furthermore, microalgae addition enriched nitrogen metabolism-related gene abundance. These findings revealed the potential role of key bacteria in enhancing plant growth and the soil environment and highlighted the potential of applying S. salsa, wastewater, and microalgae for the synergistic improvement of saline–alkali land. Full article

This study developed a coupled hydrodynamic-sediment-vegetation model to investigate the effects of Spartina alterniflora management and Suaeda salsa restoration on coastal wetland geomorphological evolution and vegetation distribution. Special attention is paid to the regulatory roles of tidal dynamics, sea-level rise, sediment supply, and sediment characteristics. The study shows that the management of Spartina alterniflora significantly alters the sediment deposition patterns in salt marsh wetlands, leading to intensified local erosion and a decline in the overall stability of the wetland system; meanwhile, the geomorphology of wetlands restored with Suaeda salsa is influenced by tidal range, sediment settling velocity, and suspended sediment concentration, exhibiting different deposition and erosion patterns. Under the scenario of sea-level rise, when sedimentation rates fail to offset the rate of sea-level increase, the wetland ecosystem faces the risk of collapse. This study provides scientific evidence for the ecological restoration and management of coastal wetlands and offers theoretical support for future wetland conservation and restoration policies. Full article

Unmanned Aerial Vehicles (UAVs) have become powerful tools for high-resolution, quantitative remote sensing in ecological and environmental studies. In this study, we present a novel approach to accurately mapping and estimating the biomass of Suaeda salsa using UAV-based visible-light imagery combined with hue angle inversion modeling. By integrating diffuse reflectance standard plates into the flight protocol, we converted RGB pixel values into reflectance and derived hue angle metrics with enhanced radiometric accuracy. A hue angle cutoff threshold of 249.01° was identified as the optimal cutoff to distinguish Suaeda salsa from the surrounding land cover types with high confidence. To estimate biomass, we developed an exponential inversion model based on hue angle data calibrated through extensive field measurements. The resulting model—Biomass = 3.57639 × 10⁻¹⁵ × e^0.12201×α—achieved exceptional performance (R² = 0.99696; MAPE = 3.616%; RMSE = 0.02183 kg/m²), indicating strong predictive accuracy and robustness. This study highlights a cost-effective, non-destructive, and scalable method for the real-time monitoring of coastal vegetation, offering a significant advancement in remote sensing applications for wetland ecosystem management. Full article

Nowadays, the evolution and growth of machine learning (ML) algorithms and the Internet of Things (IoT) are enabling new applications. Smart weapons and people detection systems are examples. Firstly, this work takes advantage of an efficient, scalable, and distributed system, named SmartFog, which identifies people with weapons by leveraging edge, fog, and cloud computing paradigms. Nevertheless, security vulnerabilities during data transmission are not addressed. Thus, this work bridges this gap by proposing a secure data transmission system integrating a lightweight security scheme named GS3. Therefore, the main novelty is the evaluation of the GS3 proposal in a real environment. In the first fog sublayer, GS3 leads to a 14% increase in execution time with respect to no secure data transmission, but AES results in a 34.5% longer execution time. GS3 achieves a 70% reduction in decipher time and a 55% reduction in cipher time compared to the AES algorithm. Furthermore, an energy consumption analysis shows that GS3 consumes 31% less power than AES. The security analysis confirms that GS3 detects tampering, replaying, forwarding, and forgery attacks. Moreover, GS3 has a key space of $2^{544}$ permutations, slightly larger than those of Chacha20 and Salsa20, with a faster solution than these methods. In addition, GS3 exhibits strength against differential cryptoanalysis. This mechanism is a compelling choice for energy-constrained environments and for securing event data transmissions with a short validity period. Moreover, GS3 maintains full architectural transparency with the underlying armed detection system. Full article

Suaeda salsa, a halophytic plant species, exhibits a remarkable salt tolerance and demonstrates a significant phytoremediation potential through its capacity to absorb and accumulate saline ions and heavy metals from soil substrates, thereby contributing to soil quality amelioration. Furthermore, this species serves as a critical habitat component for avifauna populations and represents a keystone species in maintaining ecological stability within estuarine and coastal wetland ecosystems. With the development and maturity of UAV remote sensing technology in recent years, the advantages of using UAV imagery to extract weak targets are becoming more and more obvious. In this paper, for Suaeda salsa, which is a weak target with a sparse distribution and inconspicuous features, relying on the high-resolution and spatial information-rich features of UAV imagery, we establish an adaptive contextual information extraction deep learning semantic segment model (ACI-Unet), which can solve the problem of recognizing Suaeda salsa from high-precision UAV imagery. The precise extraction of Suaeda salsa was completed in the coastal wetland area of Dongying City, Shandong Province, China. This paper achieves the following research results: (1) An Adaptive Context Information Extraction module based on large kernel convolution and an attention mechanism is designed; this module functions as a multi-scale feature extractor without altering the spatial resolution, enabling a seamless integration into diverse network architectures to enhance the context-aware feature representation. (2) The proposed ACI-Unet (Adaptive Context Information U-Net) model achieves a high-precision identification of Suaeda salsa in UAV imagery, demonstrating a robust performance across heterogeneous morphologies, densities, and scales of Suaeda salsa populations. Evaluation metrics including the accuracy, recall, F1 score, and mIou all exceed 90%. (3) Comparative experiments with state-of-the-art semantic segmentation models reveal that our framework significantly improves the extraction accuracy, particularly for low-contrast and diminutive Suaeda salsa targets. The model accurately delineates fine-grained spatial distribution patterns of Suaeda salsa, outperforming existing approaches in capturing ecologically critical structural details. Full article

Cadmium and petroleum are the main pollutants in coastal wetland ecosystems that affect plant nutrient balance and growth. Scholars have discovered how saline plants adapt to single stresses. How plant ecology and physiology correspond to complex cadmium and petroleum pollution, especially regarding the pollution impacts on carbon (C), nitrogen (N), and phosphorus (P) stoichiometry and biomass allocation in coastal wetland plants, remains unclear, limiting their application in regard to pollution remediation. This study focuses on Suaeda salsa, a popular species used in vegetation restoration in the Yellow River Delta’s coastal wetlands. Through the use of pot experiments, the dynamic changes in plant–soil ecological stoichiometry and biomass allocation were systematically investigated in response to individual and combined cadmium (0, 5, and 10 mg kg⁻¹) and petroleum (0, 6, and 12 g kg⁻¹) treatments. Compared with the control (CK), petroleum stress significantly increased the total nitrogen (TN) and plant total phosphorus (TP) contents, but did not substantially impact the total carbon (TC) content, resulting in 19.7% and 26.6% decreases in the plant C/N and C/P ratios, respectively. The soil organic carbon (SOC) content increased significantly under petroleum stress, whereas the TN and TP contents did not notably change, considerably increasing the soil C/N and C/P ratios, which were 1.5 times and 1.3 times greater than those of the CK, respectively. Cadmium stress alone or with petroleum stress did not significantly affect the C, N, or P stoichiometry or biomass allocation in S. salsa. The soil C/N/P stoichiometry redundancy analysis revealed that the contribution rates (especially the soil C/P and C/N ratios) to the total biomass and its allocation in S. salsa (64.5%) were greater than those of the control group plants (35.5%). The correlation analysis revealed that the total growth biomass of S. salsa was negatively correlated with the soil carbon content, C/N ratio, and C/P ratio, but positively correlated with the plant C/N and C/P ratios. The aboveground biomass proportion in S. salsa was significantly negatively correlated with the soil N/P ratio. The belowground biomass proportion exhibited the opposite trend. Petroleum pollution was the main factor driving S. salsa stoichiometry and growth changes, increasing the soil C/N and C/P ratios, reducing the nitrogen and phosphorus nutrient absorption capacities in plant roots, limiting plant nitrogen and phosphorus nutrients, and inhibiting biomass accumulation. Appropriate N and P supplementation alleviated plant growth inhibition due to petroleum pollution stress, which was conducive to improving vegetation ecological restoration in the Yellow River Delta. Full article