Search Results (74)

Background/Objectives: Artificial intelligence (AI) is beginning to be applied in wound ballistics, showing preliminary potential to improve the accuracy and objectivity of forensic analyses. This review explores the current state of AI applications in forensic firearm wound analysis, emphasizing its potential to address challenges such as subjective interpretations and data heterogeneity. Methods: A systematic review adhering to PRISMA guidelines was conducted using databases such as Scopus and Web of Science. Keywords focused on AI and GSW classification identified 502 studies, narrowed down to 4 relevant articles after rigorous screening based on inclusion and exclusion criteria. Results: These studies examined the role of deep learning (DL) models in classifying GSWs by type, shooting distance, and entry or exit characteristics. The key findings demonstrated that DL models like TinyResNet, ResNet152, and ConvNext Tiny achieved accuracy ranging from 87.99% to 98%. Models were effective in tasks such as classifying GSWs and estimating shooting distances. However, most studies were exploratory in nature, with small sample sizes and, in some cases, reliance on animal models, which limits generalizability to real-world forensic scenarios. Conclusions: Comparisons with other forensic AI applications revealed that large, diverse datasets significantly enhance model performance. Transparent and interpretable AI systems utilizing techniques are essential for judicial acceptance and ethical compliance. Despite the encouraging results, the field remains in an early stage of development. Limitations highlight the need for standardized protocols, cross-institutional collaboration, and the integration of multimodal data for robust forensic AI systems. Future research should focus on overcoming current data and validation constraints, ensuring the ethical use of human forensic data, and developing AI tools that are scientifically sound and legally defensible. Full article

Multi-Key Fully Homomorphic Encryption (MKFHE) offers a powerful solution for secure multi-party computations, where data encrypted under different keys can be jointly computed without decryption. However, existing MKFHE schemes still face challenges such as large parameter sizes, inefficient evaluation key generation, complex homomorphic multiplication processes, and limited scalability in multi-hop scenarios. In this paper, we propose an enhanced multi-hop MKFHE scheme based on the Brakerski-Gentry-Vaikuntanathan (BGV) framework. Our approach eliminates the need for an auxiliary Gentry-Sahai-Waters (GSW)-type scheme, simplifying the design and significantly reducing the public key size. We propose novel algorithms for evaluation key generation and key switching that simplify the computation while allowing each party to independently precompute and share its evaluation keys, thereby reducing both computational overhead and storage costs. Additionally, we combine the tensor product and key switching processes through homomorphic gadget decomposition, developing a new homomorphic multiplication algorithm and achieving linear complexity with respect to the number of parties. Furthermore, by leveraging the Polynomial Chinese Remainder Theorem (Polynomial CRT), we design a ciphertext packing technique that transforms our BGV-type MKFHE scheme into a batched scheme with improved amortized performance. Our schemes feature stronger multi-hop properties and operate without requiring a predefined maximum number of parties, offering enhanced flexibility and scalability compared to existing similar schemes. Full article

Homomorphic encryption is an important means for cloud computing to ensure information security when outsourcing data. Among them, threshold fully homomorphic encryption (ThFHE) is a key enabler for homomorphic encryption and, from a wider perspective, secure distributed computing. However, current ThFHE schemes are unsatisfactory in terms of security and efficiency. In this paper, a novel ThFHE is proposed for the first time based on an NTRU-based GSW-like scheme of symmetric encryption—Th-S-NGS scheme. Additionally, the threshold structure is realized by combining an extended version of the linear integer secret sharing scheme such that the scheme requires a predetermined number of parties to be online, rather than all the parties being online. The Th-S-NGS scheme is not only more attractive in terms of ciphertext size and computation time for homomorphic multiplication, but also does not need re-linearization after homomorphic multiplication, and thus does not require the computing key, which can effectively reduce the communication burden in the scheme and thus simplify the complexity of the scheme. Full article

In this paper, we investigate closed-form meromorphic solutions of the fifth-order Sawada-Kotera (fSK) equation and (3+1)-dimensional generalized shallow water (gSW) equation. The study of high-order and high-dimensional differential equations is pivotal for modeling complex nonlinear phenomena in physics and engineering, where higher-order dispersion, dissipation, and multidimensional dynamics govern system behavior. Constructing explicit solutions is of great significance for the study of these equations. The elliptic, hyperbolic, rational, and exponential function solutions for these high-order and high-dimensional differential equations are achieved by proposing the extended complex method. The planar dynamics behavior of the (3+1)-dimensional gSW equation and its phase portraits are analyzed. Using computational simulation, the chaos behaviors of the high-dimensional differential equation under noise perturbations are examined. The dynamic structures of some obtained solutions are revealed via some 2D and 3D graphs. The results show that the extended complex method is an efficient and straightforward approach to solving diverse differential equations in mathematical physics. Full article

With global climate change ongoing, the frequency and intensity of extreme weather events have increased annually. Hulless barley (Hordeum vulgare L. var. nudum), a primary crop cultivated in the Qinghai–Tibet Plateau mountains, frequently encounters multiple abiotic stresses including low temperature, high salinity, and drought. Among these stresses, drought has emerged as a critical environmental constraint affecting sustainable agricultural development worldwide. Establishing a drought resistance evaluation system for the hulless barley germplasm during its seedling stages could provide a theoretical foundation for screening and breeding drought-tolerant cultivars to address climate change challenges. This study employed two drought-sensitive (YC85 and YC88) and two drought-tolerant (ZY1252 and ZY1100) cultivars to develop an effective drought resistance evaluation protocol for hulless barley. Our findings identified several reliable indicators for assessing drought tolerance at the seedling stage: fresh mass, chlorophyll fluorescence parameters (F_v/F_m, NPQ, and R_FD), photosynthetic parameters (E and gsw), and reactive oxygen species (ROS) levels. The established evaluation system was subsequently applied to three uncharacterized cultivars (ZY673, ZY1403, and KL14). The results classified all three as drought-sensitive, with ZY1403 exhibiting the highest sensitivity. Our work has established a comprehensive drought resistance evaluation framework for Tibetan hulless barley. Furthermore, this study provides valuable insights for optimizing cultivation practices and water resource management strategies, offering theoretical guidance for agricultural adaptation to climate change. Full article

Objective: To characterize facial fracture patterns and understand predictors of surgical repair and LOS with the objective of assisting providers in managing and understanding these complex injuries. Study Design: This is a retrospective cohort chart review study. Methods: A retrospective review was conducted for patients admitted with gunshot wounds (GSWs) to the head, neck, or face between January 2013 and March 2020 at a level one trauma tertiary care hospital. Univariate and multivariate analysis were performed to identify associations with surgical repair and LOS. Results: Of the 578 patients with head, neck, or facial GSWs, 204 survived and sustained facial fractures. The maxilla (n = 127, 62%), orbit (n = 114, 55%), and mandible (n = 104, 51%) were the most fractured. Operative rates differed by location (p < 0.001) with highest rates for fractures involving the mandible (76%). In univariate analysis, overall facial fracture surgery was associated with transfacial injuries; mandible, palate and nasal fractures; tracheostomy; gastrostomy tube placement; ICU admission; and a longer-than-24 h ICU stay (all p < 0.05). In multivariate analysis, predictors of surgical repair included a length of stay greater than 3 days (OR 2.9), transfascial injury (OR 3.7) and tracheostomy placement (OR 5.1; all p-values < 0.05), while nasal and mandible fractures were also associated with overall operative repair (OR 2.5 and 9.3, respectively; p-value < 0.05 for both). Univariate analysis showed that among patients with GSW injuries who underwent facial plastic reconstructive surgery (FPRS) with comorbid serious polytrauma, the inpatient LOS was predicted solely by the presence of subarachnoid, subdural and intracranial hemorrhage (p-value < 0.005). Subsequent multivariate analysis found that the only predictor for greater hospital LOS for patients who underwent surgical repair was earlier timing to FPRS of less than five days (OR 0.17) and placement of a gastrostomy tube (OR 7.85). Conclusions: Managing facial fractures in GSW patients requires complex medical decision making with a consideration of functional and esthetic outcomes in the context of concomitant injuries and overall prognosis. Certain characteristics such as ICU admission, longer hospital stay, trajectory of GSW, tracheostomy placement, and specific operative locations are associated with higher rates of operative repair. Inpatient hospitalization LOS for patients who underwent FPRS was predicted by timing from admission to surgical repair. Full article

Urban forests play important roles in carbon sequestration and climate change mitigation. However, their adaptive mechanisms and limitations on photosynthesis throughout the canopy are poorly understood. This study takes the most widely distributed 50-year-old camphor plantations (Cinnamomum camphora) in Shanghai as the research objects. We investigated the variations in leaf morphology and photosynthetic physiology and biochemistry at six different canopy positions during a summer and an autumn period. We discovered that on account of leaf nitrogen loss and water deficit, light-saturated photosynthesis (A_max) declined in upper sunlit leaves despite being exposed to high sunlight in the same fashion as stomatal and mesophyll conductance (g_sw, g_m), photochemical quenching coefficient and actual photochemical efficiency of PSII (Φ_PSII, q_P), and maximum rate of electron transport and carboxylation (J_max, V_cmax) during the growing season. Although seasonal change had little effect on A_max, the relative importance of limitations varied temporally. Mesophyll and biochemical limitation were the major contributors to the decline in the A_max in upper sunlit leaves between summer and autumn, respectively. Our study highlights the constraints of carbon fixation capacity in dense stands of mature camphor trees and offers technical support for the accurate prediction of canopy photosynthesis and the enhancement of carbon sequestration management in urban forests. Full article

Terminal drought is the major constraint for chickpea production, leading to yield losses of up to 90% in tropical environments. Understanding the morphological, phenological, and physiological traits underlying drought tolerance is crucial for developing resilient chickpea genotypes. This study elucidates the drought-tolerant traits of eight kabuli chickpea genotypes under a controlled environment using polyvinyl chloride (PVC) lysimeters. Terminal drought was imposed after the flowering stage, and the response was assessed against non-stress (well-watered) treatment. Drought stress significantly impacted gas-exchange parameters, reducing the stomatal conductance (16–35%), chlorophyll content (10–22%), carbon assimilation rate (21–40%) and internal carbon concentration (7–14%). Principal component analysis (PCA) indicated three groups among these eight genotypes. The drought-tolerant group included two genotypes (AVTCPK#6 and AVTCPK#19) with higher water use efficiency (WUE), deep-rooted plants, longer maturity, and seed yield stability under drought stress. In contrast, the drought-susceptible group included two genotypes (AVTCPK#1 and AVTCPK#12) that were early-maturing and low-yielding with poor assimilation rates. The intermediate group included four genotypes (AVTCPK#3, AVTCPK8, AVTCPK#24, and AVTCPK#25) that exhibited medium maturity and medium yield, conferring intermediate tolerance to terminal drought. A significantly strong positive correlation was observed between seed yield and key physiological traits (stomatal conductance (gsw), leaf chlorophyll content (SPAD) and carbon assimilation rate (A_sat)) and morphological traits (plant height, number of pods, and root biomass). Conversely, carbon discrimination (Δ¹³C) and intrinsic WUE (iWUE) showed a strong negative correlation with seed yield, supporting Δ¹³C as a surrogate for WUE and drought tolerance and a trait suitable for the selection of kabuli chickpea genotypes for drought resilience. Full article

This paper explores advancements in the Gentry-Sahai-Waters (GSW) fully homomorphic encryption scheme (FHE), addressing challenges related to message data range limitations and ciphertext size constraints. We leverage the well-known parallelizing technology—the Chinese Remainder Theorem (CRT)—to tackle the message decomposition, significantly expanding the allowable input message range to the entire plaintext space. This approach enables unrestricted message selection in the GSW scheme and supports parallel homomorphic operations without intermediate decryption. Additionally, we adapt existing ciphertext compression techniques, such as the PVW-like scheme, to reduce the memory overhead associated with ciphertexts. Our experimental results demonstrate the effectiveness of combining the proposed CRT-based decomposition with the PVW-like compression in increasing the upper bound of message values and improving the scheme’s capacity for consecutive homomorphic operations. However, compression introduces a trade-off, necessitating a reduced message range due to error accumulation in successive HE operations. This research contributes to enhancing the practicality and efficiency of the GSW encryption scheme for complex computational scenarios while managing the balance between expanded message range, computational complexity, and storage requirements. Full article

The mountainous Samian Watershed hosts important rivers recently, significantly triggered by fast and unplanned urbanization, population growth, environmentally hazardous industrialization, and inappropriate dam construction. Nonetheless, this watershed has not yet been evaluated through the lens of river restoration. Therefore, this study aims (1) to apply the River Restoration Index (RRI), (2) to assess the significance of each river restoration criterion and sub-index, and (3) to identify priority hotspots for immediate restoration efforts across 27 sub-watersheds in this case study. First, we built a database containing meteorological, hydrological, land use, physiographic, soil, and economic data. Then, we calculated the general state of the watershed (GSW), connectivity (Con), riverbank conditions (RbC), and hydraulic risk reduction (HRR) sub-indices to develop a multi-domain RRI. Finally, the MEREC-ORESTE hybrid method supported sustainable government planning. The findings reveal significant environmental issues, notably in sanitation conditions, transversal connectivity, and urban encroachment on riverbanks. Sanitation risks were high throughout the watershed, while other eco-environmental risks varied across regions. The weights of 0.36, 0.16, 0.32, and 0.16 were assigned for GSW, Con, RbC, and HRR, respectively, highlighting the importance of GSW and RbC in river restoration activities. Priority management areas (with RRI below 0.50) cover 78% of the watershed. Full article

This experiment was conducted at the Fruit Research Institute, MAREM, Eğirdir-Isparta, Turkey, to detect the effects of different glycine betaine doses in drought stress conditions on young pear trees in 2019. The pear trees used in the study were one-year-old Deveci (Pyrus Comminus L.) variety grafted onto OHxF 333 rootstock. There were three different irrigation treatments in the experiment. Treatments were I₁₀₀ treatment—available soil water reached field capacity for each irrigation, 100% (control); I₅₀ treatment—irrigated with 50% of the water used in the I₁₀₀ treatment (50% water deficit, moderate stress); I₂₅ treatment—irrigated with 25% of the water used in the I₁₀₀ treatment (75% water deficit, severe stress). Four different GB doses were used: GB₀: 0, control; GB₁: 1 mg L⁻¹; GB₅: 5 mg L⁻¹; and GB₁₀: 10 mg L⁻¹. GB was not applied to pear trees in the I₁₀₀ treatment. That is, there were nine different treatments in this study. GB applications provided a 19% increase in Pn of both the I₂₅ and I₅₀ treatments. According to the results of g_sw, g_sw increased between 18.0% and 27.8% for GB₅₀ and GB₂₅ treatments, respectively. In total, 10.9% and 14.8% increasing rates in shoot length were detected in GB₁₀ applications in both the 50% and 75% water deficit treatments. The highest trunk diameter and fresh root weight results were determined in 10 mg L⁻¹ GB dose applications under 50% water deficit conditions (I₅₀GB₁₀). Full article

Quercus, commonly known as oak, has great potential as one of the most widely cultivated plant species. However, the lack of superior varieties is a bottleneck for its usage and application in Southwest China. Here, this study aims to explore the growth and photosynthetic traits of 18 oak varieties with the goal of identifying the adaptable superior varieties for the region, focusing on nutrient growth, leaf morphology, chlorophyll content, and photosynthetic parameters over a 32-week growth period. The results showed that a significant diversity was observed among the varieties. Growth rhythm and fitted curves divided the 18 oak varieties into three patterns. Additionally, for the leaf morphological parameters, Q. denta boasted the maximum leaf area (167.24 cm²), leaf width (13.62 cm), and leaf aspect ratio (156.6); Q. mongo showed the greatest leaf length (20.37 cm); while Q. acutis had the largest leaf form factor (3.44) and leaf gap (0.39). Chlorophyll content was based on three-time-points investigation, with higher levels observed in Q. mongo, Q. robur 4, Q. wutai, Q. denta, Q. acutis, and Q. robur 1. The transpiration rate (E) (5.03 mmol m⁻²), stomatal conductance (gsw) (0.22 mol m⁻² s⁻¹), and total water vapor conductance (gtw) (0.19 mol m⁻² s⁻¹) were dominantly obtained in Q. robur 1, while Q. denta exhibited the highest intercellular CO₂ concentration (Ci) (564.67 µmol mol⁻¹). Conversely, Q. wutai displayed a significantly higher leaf chamber CO₂ concentration (Ca) (502.11 µmol mol⁻¹). Furthermore, growth traits showed a correlation with leaf morphological and photosynthetic traits. PCA analysis grouped the oak varieties into five clusters, with Q. acutis, Q. robur 1, Q. palus 3, Q. denta, Q. nutta, Q. mongo, and Q. wutai identified as superior varieties. These findings not only offer promising oak candidate varieties for Southwest China, but also provide insights for establishing efficient breeding program for other woody plants. Full article

Chickpea is one of the economically important legume crops adapted for winter season production in tropical climates. This study evaluated the physiological, morphological, and biochemical traits of eight Kabuli chickpea genotypes in an Australian tropical environment. The result revealed significant differences between genotypes for seed emergence, plant height, primary shoots, leaf number, leaf area index, gas-exchange parameters, seed yield, carbon discrimination (Δ¹³C), and natural abundance for nitrogen fixation. Among the tested genotypes, AVTCPK#6 and AVTCPK#19 exhibited late flowering (60–66 days) and late maturity (105–107 days), and had higher leaf photosynthetic rate (A_sat) (28.4–31.2 µmol m⁻² s⁻¹), lower stomatal conductance (gsw) (516–756 mmol m⁻² s⁻¹), were associated with reduced transpiration rate (T) (12.3–14.5 mmol m⁻² s⁻¹), offered greater intrinsic water-use efficiency (iWUE) (2.1–2.3 µmol m⁻² s⁻¹/mmol m⁻² s⁻¹), and contributed a higher seed yield (626–746 g/m²) compared to other genotypes. However, a larger seed test weight (>60 g/100 seed) was observed for AVTCPK#24, AVTCPK#8, and AVTCPK#3. Similarly, a high proportion (45%) of larger seeds (>10–11 mm) was recorded for AVTCPK#24. Furthermore, a higher %Ndfa in AVTCPK#6 (71%) followed by AVTCPK#19 (63%) indicated greater symbiotic nitrogen fixation in high-yielding genotypes. Positive correlation was observed between %Ndfa and seed protein, as well as between seed yield and plant height, primary shoots, leaf count, leaf area index, leaf photosynthesis, stomatal conductance, transpiration rate at pod filling stage, biomass, and harvest index. An inverse correlation between (Δ¹³C) and iWUE, particularly in AVTCPK#6 and AVTCPK#19, indicates greater heat and drought tolerance, required for high-yielding Kabuli chickpea production in northern Australia. Full article

It is unknown how recurring flooding impacts household diet in Central Java. We aimed to assess how recurrent flooding influenced household food access over 22 years in Central Java by linking the Global Surface Water dataset (GSW) to the Indonesian Family Life Survey. We examined linear and nonlinear relationships and joint effects with indicators of adaptive capacity. We measured recurrent flooding as the fraction of district raster cells with episodic flooding from 1984–2015 using GSW. Food access outcomes were household food expenditure share (FES) and dietary diversity score (DDS). We fit generalized linear mixed models and random forest regression models. We detected joint effects with flooding and adaptive capacity. Wealth and access to credit were associated with improved FES and DDS. The effect of wealth on FES was stronger in households in more flood-affected districts, while access to credit was associated with reduced odds of DDS in more flood-affected districts. Flooding had more predictive importance for FES than for DDS. Access to credit, a factor that ordinarily improves food access, may not be effective in flood-prone areas. Wealthier households may be better able to adapt in terms of food access. Future research should incorporate land use data to understand how different locales are affected and further understand the complexity of these relationships. Full article

Breeding high-photosynthetic-efficiency wheat varieties is a crucial link in safeguarding national food security. Traditional identification methods necessitate laborious on-site observation and measurement, consuming time and effort. Leveraging unmanned aerial vehicle (UAV) remote sensing technology to forecast photosynthetic indices opens up the potential for swiftly discerning high-photosynthetic-efficiency wheat varieties. The objective of this research is to develop a multi-stage predictive model encompassing nine photosynthetic indicators at the field scale for wheat breeding. These indices include soil and plant analyzer development (SPAD), leaf area index (LAI), net photosynthetic rate (Pn), transpiration rate (Tr), intercellular CO₂ concentration (Ci), stomatal conductance (Gsw), photochemical quantum efficiency (PhiPS2), PSII reaction center excitation energy capture efficiency (Fv’/Fm’), and photochemical quenching coefficient (qP). The ultimate goal is to differentiate high-photosynthetic-efficiency wheat varieties through model-based predictions. This research gathered red, green, and blue spectrum (RGB) and multispectral (MS) images of eleven wheat varieties at the stages of jointing, heading, flowering, and filling. Vegetation indices (VIs) and texture features (TFs) were extracted as input variables. Three machine learning regression models (Support Vector Machine Regression (SVR), Random Forest (RF), and BP Neural Network (BPNN)) were employed to construct predictive models for nine photosynthetic indices across multiple growth stages. Furthermore, the research conducted principal component analysis (PCA) and membership function analysis on the predicted values of the optimal models for each indicator, established a comprehensive evaluation index for high photosynthetic efficiency, and employed cluster analysis to screen the test materials. The cluster analysis categorized the eleven varieties into three groups, with SH06144 and Yannong 188 demonstrating higher photosynthetic efficiency. The moderately efficient group comprises Liangxing 19, SH05604, SH06085, Chaomai 777, SH05292, Jimai 22, and Guigu 820, totaling seven varieties. Xinmai 916 and Jinong 114 fall into the category of lower photosynthetic efficiency, aligning closely with the results of the clustering analysis based on actual measurements. The findings suggest that employing UAV-based multi-source remote sensing technology to identify wheat varieties with high photosynthetic efficiency is feasible. The study results provide a theoretical basis for winter wheat phenotypic monitoring at the breeding field scale using UAV-based multi-source remote sensing, offering valuable insights for the advancement of smart breeding practices for high-photosynthetic-efficiency wheat varieties. Full article