Search Results (110)

Commercial forest plantations (CFPs) provide timber and ecosystem services, particularly carbon (C) sequestration, but the performance of native tropical hardwoods in pure versus mixed systems is still poorly understood. We evaluated growth, productivity, biomass, and C storage in 17-year-old plantations of Tabebuia rosea, T. donnell-smithii, and Swietenia humilis in western Mexico. Four plantation systems were assessed: pure T. rosea (PPT1), pure T. donnell-smithii (PPT2), mixed T. rosea + T. donnell-smithii (MPT1T2), and mixed T. donnell-smithii + S. humilis (MPT2S). Tree structure (DBH, height, basal area, volume), litter layer, and soils (0–15 cm) were measured. Thirty trees per species were destructively sampled to develop species-specific biometric models. Model performance was evaluated with adjusted R², RMSE, and residual analysis. PPT1 was the most productive system (39.8 m³ ha⁻¹; 55 Mg C ha⁻¹), while PPT2 had the lowest values (20.5 m³ ha⁻¹; 45.1 Mg C ha⁻¹). MPT1T2 increased basal area (+29.8% vs. PPT1) and litter layer C (3.3 Mg C ha⁻¹; +190% vs. PPT2) but did not surpass PPT1 in standing volume. Soil C was highest in PPT1 (36.5 Mg C ha⁻¹). Biometric models achieved high accuracy (R² = 0.91–0.99), confirming DBH as a reliable predictor of biomass and C. We conclude that pure T. rosea maximizes short-term productivity and soil C, whereas mixed systems diversify C allocation by enhancing litter layer pools. These findings highlight the complementary roles of pure and mixed CFPs and provide reliable models for C accounting in tropical hardwood plantations. Full article

Coccidiosis represents a major constraint to sheep productivity worldwide, with increasing concerns regarding anticoccidial resistance and growing interest in reducing dependency on conventional synthetic anticoccidials. This investigation evaluated the anticoccidial properties of faveira pods (Parkia platycephala pod—PpP) and their influence on productive performance in naturally infected lambs. Eighteen uncastrated Dorper × Santa Inês crossbred males (20.0 ± 2.5 kg, 5 months) were randomly allocated to three groups: G1 (0% PpP; n = 6), G2 (100% PpP replacing roughage, 30.0% of total diet; n = 6), and the control group (0% PpP plus 20 mg/kg toltrazuril; n = 5). Parasitological assessments, productive performance, and behavioral parameters were monitored over 45 days using oocyst counts, morphometric analysis, digestibility trials, and biometric measurements. Nine Eimeria species were identified, with E. crandallis, E. parva, and E. bakuensis representing 53.5% of total oocyst shedding. Group G2 demonstrated a numerical 8.5% reduction in parasite load compared to G1 (p = 0.42), while toltrazuril achieved 36.6% efficacy (p < 0.05). Species-specific effects were significant for E. crandallis, E. parva, and E. ovinoidalis (p < 0.01). A robust correlation emerged between parasite load and water consumption (r = 0.652, p = 0.0045), establishing a novel behavioral biomarker for coccidiosis monitoring. Environmental oocyst elimination decreased by 43.4% in the P. platycephala group. These findings demonstrate that PpPs possess moderate anticoccidial properties, offering a sustainable complementary strategy for integrated coccidiosis management while contributing to environmental sustainability. Full article

Due to its benefits and efficiency, mechanized sugarcane harvest is a common practice in Brazil; however, continuous traffic of agricultural machinery leads to soil compaction at the end of each harvest cycle. Hence, this study evaluated whether machine traffic affects soil physical and hydraulic properties, root growth, and crop productivity in sugarcane areas during different harvest cycles. Four treatments were performed consisting of an area planted with different stages (years) of sugarcane crop: T1 = after the first harvest—plant cane (area 1); T2 = after the second harvest—first ratoon cane (area 2); T3 = after the third harvest—second ratoon cane (area 3); T4 = after fourth harvest—third ratoon cane (area 4). Five sampling sites were considered in each area, constituting five replicates collected from four layers. Two collection positions were considered: wheel track (WT) and planting row (PR). Soil physical properties, root system, productivity, and biometric characteristics of the sugarcane crop were evaluated at depths of 0.00–0.05 m, 0.05–0.10 m, 0.10–0.20 m, and 0.20–0.40 m. Traffic during the sugarcane crop growth cycles affected soil physical and hydraulic properties, showing sensitivity to the effects of the different treatments, producing variations in root growth and crop productivity. Plant cane cycle showed lower soil penetration resistance, bulk density, microporosity, higher saturated soil hydraulic conductivity, and macroporosity when compared with the other cycles studied. In the 0.10–0.20 m layer, all treatments produced higher soil penetration resistance and density, and lower saturated soil hydraulic conductivity. Dry biomass, volume, and root area were higher for the plant cane cycle in the 0.00–0.05 m and 0.05–0.10 m layers compared with the other crop cycles. Root dry biomass is directly related to crop productivity in layers up to 0.40 m deep. Sugarcane productivity was affected along the crop cycles, with higher productivity observed in the plant cane and first ratoon cane cycles compared with the second and third ratoon cane cycles. Full article

Using the biometric differences (i.e., plant physical characteristics) between the C. pallida populations previously treated with herbicide and those of the untreated populations, we tested the prediction that herbicidal treatment suppresses C. pallida plant growth in South Africa, where invasive cacti display high resilience to herbicide treatment. We also determined whether the surrounding communities knew of C. pallida invasion and whether they experienced any negative impacts. Overall, biometric analyses supported the study’s prediction because C. pallida plant height in treated populations was significantly lower than in untreated populations and before treatment. The average plant height of populations not treated with herbicide (i.e., experimental control) and those measured before treatment were not significantly different, but both were significantly greater than the heights of populations previously treated with herbicide. Similarly, the mean number of fruits, cladodes and juveniles per C. pallida plant treated with herbicide was significantly lower than in the untreated populations. We found a significant positive correlation between all measured parameters and C. pallida plant height. Out of 39 participants, 16 (41.0%) confirmed C. pallida presence in and around their properties, with 21 (53.9%) participants having experienced negative impacts directly and indirectly through fatal injuries on pets and livestock in the sampled sites. We confirmed the effectiveness of herbicide in suppressing the invasion of C. pallida and that people experience substantial negative impacts in areas where the species has established. Full article

Chenopodium quinoa Willd. (quinoa) is a very promising crop due to its nutraceutical properties and strong tolerance to extreme conditions, including high UVB. However, the physiological mechanisms underlying its adaptation to high UVB are still unclear, especially during germination as its traditional sowing consists of either broadcasting or continuous stream distribution in furrows. We evaluated the response of germinating quinoa seeds to acute UVB radiation, looking at the mobilization of starch reserves as well as the utilization of starch and free sugars. Biometric and physiological traits were evaluated in control (0 W m⁻²) and UVB (3.4 W m⁻²)-exposed seeds during a 24 h treatment starting with seed imbibition. Quinoa exposed to UVB showed a delay in germination and strong reduction in root elongation. Although the negative effect of UVB on germination was fully recovered at 48 h of imbibition, that on root elongation was irreversible, especially with a longer exposure time. Further analysis showed low differences in the concentration of free sugars, except at 2 and 24 h of treatment. Furthermore, starch mobilization in UVB-treated seeds was strongly reduced compared to control. This was associated with the amylolytic activity analysis, which showed strong reductions in both α- and β-amylase activities during the whole treatment, indicating that UVB strongly reduced enzyme activation for the mobilization and use of starch reserves. Overall, these data suggest that quinoa seeds can regulate the expression of genes encoding enzymes involved in reserve mobilization, in order to resist to acute UVB radiation and maintain seed viability. Full article

Hazelnut is an important crop worldwide, and the characteristics of the fruits are quite variable according to a number of factors, including variety and cultivation conditions, which in turn can vary according to harvest year. This study aimed to investigate some physical and chemical characteristics of three hazelnut varieties grown in Portugal (Grada de Viseu, Tonda di Giffoni and Butler) along two different harvesting years (2021 and 2022). Also, the microbial quality was investigated for its relevance to the conservation of the fruits. The physical properties evaluated were biometric characteristics and colour, the chemical components analysed were moisture, lipids, protein, ash and fibre, and the microbial properties investigated were the microorganisms, moulds and yeasts. The results showed that, generically, statistically significant differences were found between the three varieties under study on several properties investigated. The kernel was confirmed as the lighter part of all hazelnuts, and when comparing between varieties, Tonda di Giffoni presented the lighter fruits in both harvesting years. With respect to weight, the Tonda di Giffoni variety was the lightest in both harvest years. Moisture content was observed to be higher than the recommended limits for two of the samples (Grada de Viseu in 2021: 6.01 ± 0.26 g/100 g and Butler in 2022: 6.02 ± 0.37 g/100 g), although the difference was marginal given that the recommended limit is 6%. Not surprisingly, lipids were the major chemical component, ranging from 66.46 ± 1.67 to 70.14 ± 1.75 g/100 g in 2021 and from 64.38 ± 1.67 to 77.77 g/100 g in 2022. It was further observed that the three varieties presented a satisfactory microbiological quality. Finally, applying factor analysis with principal components and Varimax rotation, a solution that explains 92.8% of the variance was obtained. This study provided information that is relevant for the characterisation and evaluation of variability according to the year of hazelnuts of three varieties cultivated in Portugal. Full article

Fuzzy signature (${\mathsf{SIG}}_{\mathsf{F}}$) is a type of digital signature that preserves the core functionalities of traditional signatures, while accommodating variations and non-uniformity in the signing key. This property enables the direct use of high-entropy fuzzy data, such as biometric information, as the signing key. In this paper, we define the m-existentially unforgeable under chosen message attack ($\mathfrak{m}{-\mathrm{EUF}-\mathrm{CMA}}^{\ast }$) security of fuzzy signature. Furthermore, we propose a generic construction of fuzzy signature, which is composed of a homomorphic secure sketch ($\mathsf{SS}$) with an error-recoverable property, a homomorphic average-case strong extractor ($\mathsf{Ext}$), and a homomorphic and key-shift* secure signature scheme ($\mathsf{SIG}$). By instantiating the foundational components, we present a $\mathfrak{m}{-\mathrm{EUF}-\mathrm{CMA}}^{\ast }$ secure fuzzy signature instantiation based on the Computational Diffie–Hellman (CDH) assumption over bilinear groups in the standard model. Full article

The proliferation of biometric technology across various domains including user identification, financial services, healthcare, security, law enforcement, and border control introduces convenience in user identity verification while necessitating robust protection mechanisms for sensitive biometric data. While chaos-based encryption systems offer promising solutions, many existing chaos-based encryption schemes exhibit inherent shortcomings including deterministic randomness and constrained key spaces, often failing to balance security robustness with computational efficiency. To address this, we propose a novel dual-layer cryptographic framework leveraging a four-dimensional (4D) Qi hyperchaotic system for protecting biometric templates and facilitating secure feature matching operations. The framework implements a two-tier encryption mechanism where each layer independently utilizes a Qi hyperchaotic system to generate unique encryption parameters, ensuring template-specific encryption patterns that enhance resistance against chosen-plaintext attacks. The framework performs dimensional normalization of input biometric templates, followed by image pixel shuffling to permutate pixel positions before applying dual-key encryption using the Qi hyperchaotic system and XOR diffusion operations. Templates remain encrypted in storage, with decryption occurring only during authentication processes, ensuring continuous security while enabling biometric verification. The proposed system’s framework demonstrates exceptional randomness properties, validated through comprehensive NIST Statistical Test Suite analysis, achieving statistical significance across all 15 tests with p-values consistently above 0.01 threshold. Comprehensive security analysis reveals outstanding metrics: entropy values exceeding 7.99 bits, a key space of ${10}^{320}$, negligible correlation coefficients (<${10}^{-2}$), and robust differential attack resistance with an NPCR of 99.60% and a UACI of 33.45%. Empirical evaluation, on standard CASIA Face and Iris databases, demonstrates practical computational efficiency, achieving average encryption times of 0.50913s per user template for 256 × 256 images. Comparative analysis against other state-of-the-art encryption schemes verifies the effectiveness and reliability of the proposed scheme and demonstrates our framework’s superior performance in both security metrics and computational efficiency. Our findings contribute to the advancement of biometric template protection methodologies, offering a balanced performance between security robustness and operational efficiency required in real-world deployment scenarios. Full article

This overview examines recent advancements in EEG-based biometric identification, focusing on integrating emotional recognition to enhance the robustness and accuracy of biometric systems. By leveraging the unique physiological properties of EEG signals, biometric systems can identify individuals based on neural responses. The overview discusses the influence of emotional states on EEG signals and the consequent impact on biometric reliability. It also evaluates recent emotion recognition techniques, including machine learning methods such as support vector machines (SVMs), convolutional neural networks (CNNs), and long short-term memory networks (LSTMs). Additionally, the role of multimodal EEG datasets in enhancing emotion recognition accuracy is explored. Findings from key studies are synthesized to highlight the potential of EEG for secure, adaptive biometric systems that account for emotional variability. This overview emphasizes the need for future research on resilient biometric identification that integrates emotional context, aiming to establish EEG as a viable component of advanced biometric technologies. Full article

3D printing (3DP) enables the development of highly customizable skincare solutions, offering precise control over formulation, structure, and aesthetic properties. Therefore, this study explores the impact of patches’ microstructure on hydration efficacy using conventional and advanced chemical/morphological confocal techniques. Moreover, it advances to the personalization of under-eye 3D-printed skincare patches and assesses consumer acceptability through emotional sensing, providing a comparative analysis against a non-3D-printed market option. The results indicate that increasing the patches’ internal porosity enhances water retention in the stratum corneum (53.0 vs. 45.4% µm). Additionally, patches were personalized to address individual skin needs/conditions (design and bioactive composition) and consumer preferences (color and fragrance). The affective analysis indicated a high level of consumer acceptance for the 3D-printed option, as evidenced by the higher valence (14.5 vs. 1.1 action units) and arousal (4.2 vs. 2.7 peaks/minute) scores. These findings highlight the potential of 3DP for personalized skincare, demonstrating how structural modifications can modulate hydration. Furthermore, the biometric-preference digital approach employed offers unparalleled versatility, enabling rapid customization to meet the unique requirements of different skin types. By embracing this advancement, a new era of personalized skincare emerges, where cutting-edge science powers solutions for enhanced skin health and consumer satisfaction. Full article

Many of today’s innovative materials used to carry trace elements (TEs) are derived from chelates. Most of the materials used for this purpose have been produced on the basis of EDTA, which is not considered to be environmentally friendly due to its high persistence. Research is therefore being carried out to produce materials that do not pose an environmental risk. Therefore, a study was carried out to determine the effects of newly developed innovative materials with embedded biodegradable and environmentally safe chelates (IDHA—iminodisuccinic acid—and N-butyl-D-gluconamide ligands) containing copper, molybdenum and iron on the yield, biometric characteristics and chemical composition of soybean and selected soil properties. It is difficult to find publications on their effects in soybean cultivation. The greatest increase in soybean leaf greenness index (SPAD) was found after the addition of pure Salmag^® (Sal.^®). The effect of the chelates on the SPAD index was lower, with Sal.^® + Fe chelate having the greatest effect during the vegetative development stage and Cu chelate having the greatest effect during the flowering stage. Sal.^® + Cu, especially with Fe, accelerated pod and seed ripening in the last vegetative stage of soybean. Sal.^® + Cu had the most favourable impact on plant height, pure Sal.^® on the pod number per plant, Sal.^® + Fe on the seed number per pod, Sal.^® with Mo and Fe chelates on soybean seed yield, and pure Sal.^® on fresh weight remaining above-ground part yield, while pure Sal.^® and Sal.^® + Fe had the most favourable impact on dry weight aerial yield. The fertiliser materials (especially Sal.^® + Cu) generally increased the N content of the tested soybean organs and the Cu content of the other above-ground soybean parts (especially those containing chelates) and had an antagonistic effect on the Mg content of the soybean above-ground parts. Sal.^® + Cu also had a negative effect on the Fe content of other above-ground soybean parts. Sal.^® + Fe had a positive impact on the iron content, and Sal.^® + Mo had a positive impact on the molybdenum content of soybean. The applied fertilisers had little effect on the contents of Cu, Mo and Fe in the soil. There was only a significant increase in the Cu content of the soil after the addition of Sal.^® + Cu and a significantly smaller increase under the influence of Sal.^® without chelates, as well as an increase in the Mo content of the soil with Sal.^®. The present study confirms the beneficial impact of the novel materials with chelates. It has been demonstrated that the presence of materials containing Mo and, in particular, Cu has a considerable effect on the yield and quality characteristics of soybeans. Full article

Human identification using gait as a biometric feature has gained significant attention in recent years, showing notable advancements in medical fields and security. A review of recent developments in remote radar-based gait identification is presented in this article, focusing on the methods used, the classifiers employed, trends and gaps in the literature. Particularly, recent trends highlight the increasing use of Artificial Intelligence (AI) to enhance the extraction and classification of features, while key gaps remain in the area of multi-subject detection. In this paper, we provide a comprehensive review of the techniques used to implement such systems over the past 7 years, including a summary of the scientific publications reviewed. Several key factors are compared to determine the most suitable radar for remote gait-based identification, including accuracy, operating frequency, bandwidth, dataset, range, detection, feature extraction, size and number of features extracted, multiple subject detection, radar modules used, AI used and their properties, and the testing environment. Based on the study, it was determined that Frequency-Modulated Continuous-Wave (FMCW) radars were more accurate than Continuous-Wave (CW) radars and Ultra-Wideband (UWB) radars in this field. Despite the fact that FMCW is the most closely related radar to real-world scenarios, it still has some limitations in terms of multi-subject identification and open-set scenarios. In addition, the study indicates that simpler AI techniques, such as Convolutional Neural Network (CNN), are more effective at improving results. Full article

Internet of Things (IoT) user authentication protocols enable secure authentication and session key negotiation between users and IoT devices via an intermediate server, allowing users to access sensor data or control devices remotely. However, the existing IoT user authentication schemes often assume that the servers (registration center and intermediate servers) are fully trusted, overlooking the potential risk of insider attackers. Moreover, most of the existing schemes lack critical security properties, such as resistance to ephemeral secret leakage attacks and offline password guessing attacks, and they are unable to provide perfect forward security. Furthermore, with the rapid growth regarding IoT devices, the servers must manage a large number of users and device connections, making the performance of the authentication scheme heavily reliant on the server’s computational capacity, thereby impacting the system’s scalability and efficiency. The design of security protocols is based on the underlying security model, and the current IoT user authentication models fail to cover crucial threats like insider attacks and ephemeral secret leakage. To overcome these limitations, we propose a new security model, IoT-3eCK, which assumes semi-trusted servers and strengthens the adversary model to better meet the IoT authentication requirements. Based on this model, we design an efficient protocol that ensures user passwords, biometric data, and long-term keys are protected from insider users during registration, mitigating insider attacks. The protocol also integrates dynamic pseudo-identity anonymous authentication and ECC key exchange to satisfy the security properties. The performance analysis shows that, compared to the existing schemes, the new protocol reduces the communication costs by over 23% and the computational overhead by more than 22%, with a particularly significant reduction of over 95% in the computational overhead at the intermediate server. Furthermore, the security of the protocol is rigorously demonstrated using the random oracle model and verified with automated tools, further confirming its security and reliability. Full article

Arnica montana L. is an important herbal medicinal plant that belongs to the family Asteraceae. This plant has been known for its medicinal uses for centuries. A. montana exhibits several pharmacological properties, including immunomodulatory, anti-inflammatory, anticancer, antioxidant, and antibacterial effects. For the first time, the impacts of the biotic elicitor yeast extract, and the abiotic elicitor salicylic acid on micropropagation, antioxidant potential, and accumulation of caffeoylquinic acids in arnica in vitro shoots were assessed. The results showed that yeast extract applied at 100 mg/L significantly promotes shoot multiplication, biomass yield, total phenolic content, and synthesis of caffeoylquinic acids compared to control untreated shoots. Flavonoid content was the highest in samples treated with 200 mg/L of yeast extract, although at this concentration the measured biometric parameters began to decrease. Salicylic acid at 100 µM was found to be effective in the induction of vigorous shoots, shoot height growth, and biomass accumulation; nevertheless, this elicitor downregulated the caffeoylquinic acid level, total phenolics, and flavonoids. Increasing the concentration of salicylic acid to 200 µM caused shoot multiplication and fresh biomass accumulation reduction. Both elicitors modulated the activity of antioxidant enzymes against oxidative stress. Overall, the use of these substances can improve the growth and biomass yield in Arnica in vitro shoots. Full article

Brain biometrics has received increasing attention from the scientific community due to its unique properties in comparison to traditional biometric methods. Many studies have shown that EEG features are distinct among individuals. SSVEP signals, generated by stationary localized sources and distributed sources in the parietal and occipital regions of the brain, serve as a reliable basis for biometrics. In this study, we present a novel approach that leverages the spatial patterns of brain responses elicited by visual stimulation at specific frequencies. Specifically, we propose integrating common spatial patterns with Sparse Representation Classification (SRC) frameworks for person identification and verification. The use of common spatial patterns enables the design of personalized spatial filters, which play a crucial role in constructing the dictionary used by SRC frameworks. We conducted extensive evaluations of the proposed method, comparing it with several traditional approaches using two SSVEP datasets. Our analysis also explored a broad range of flickering frequencies in the SSVEP experiments. The results from these datasets demonstrated the effectiveness of our approach for person identification and verification, achieving an average correct recognition rate above 90% across various visual stimulus frequencies and short durations of electrophysiological signals. Full article