Search Results (591)

Remote-access virtual private networks (VPNs) are a key component of enterprise security infrastructures. In practice, the effectiveness of a remote-access VPN is determined not only by cryptographic mechanisms but also by its ability to remain available and recover quickly under realistic operating conditions, which directly affects the operational security guarantees provided by the underlying cryptographic protocols. Enterprise deployments are characterized by heterogeneous client platforms, wireless access networks, and frequent endpoint and network disruptions. In this paper, we execute an exploratory case study of the operation of remote-access VPNs in enterprise environments through an empirical evaluation of WireGuard, OpenVPN, and IPsec. Using a controlled but realistic testbed with a cloud-hosted gateway and heterogeneous client platforms, we evaluate baseline performance as well as behavior under endpoint CPU stress, network impairments, MTU variation, and mobility-related disruptions, reflecting constrained and dynamically changing deployment conditions. The results suggest that VPN operational characteristics are influenced by both protocol design and execution environment. Within the evaluated deployment scenarios, kernel-based implementations generally exhibited higher resilience under endpoint resource contention and faster recovery after disruptions, while layered and virtualized environments exhibited increased variability and sensitivity to network imperfections. These findings underline that resilience in remote-access VPNs should be interpreted as a system-level property emerging from the interaction of implementation architecture, endpoint characteristics, and deployment conditions. Full article

In recent years, aquaculture, a critical pillar of global food security, has faced challenges including germplasm resource degradation, frequent disease outbreaks, and insufficient environmental adaptability. To address these issues, omics technologies—centered on genomics, transcriptomics, and related fields—are driving the transformation of aquaculture toward precision and intelligence by establishing a three-dimensional “genotype–phenotype–environment” knowledge network. In this review, we outline foundational applications of omics in aquaculture and highlight the characteristics and current applications of distinct omics approaches. Furthermore, we summarize three core application domains of omics in aquaculture: (1) genetic breeding via genomic selection (GS), gene editing, and multi-omics molecular dissection of economic traits; (2) disease prevention through host–pathogen interaction studies and microbial engineering; and (3) environmental assessment through multi-omics characterization of biological and ecological responses. Additionally, we identify challenges in applying omics technologies to aquatic breeding and database development. Overall, this review aims to provide aquaculture practitioners with actionable insights by enhancing understanding of omics-driven innovations in sustainable aquaculture advancement. Full article

The European Union’s REPowerEU Plan (2022) targets 10 million tonnes of renewable hydrogen imports by 2030, catalyzing an unprecedented cascade of bilateral green hydrogen partnerships with countries across the Middle East and North Africa (MENA) and Sub-Saharan Africa (SSA). Despite the strategic and developmental significance of these partnerships, the literature has treated hydrogen largely as a techno-economic or single-country problem, leaving the diplomatic architecture and equity dimensions of EU–MENA–SSA hydrogen diplomacy under-theorized and unmeasured. This study addresses these gaps by integrating energy-security realism, regime-complex theory, and critical political ecology into a synthetic framework, and by introducing two novel empirical instruments: a hand-coded dataset of 26 in-scope bilateral hydrogen agreements (2020–2024) and a fully specified protocol for a Green Hydrogen Diplomacy Equity Index (GHD-EI). A longitudinal dyad-year panel skeleton (27 EU importers × 36 MENA/SSA exporters, 2015–2026, 11,664 dyad-year cells) has been constructed to host a planned multi-method quantitative sequence, structural gravity PPML, staggered difference-in-differences, synthetic control, exponential random graph models, and causal forests whose execution against fully populated covariates is reserved for a subsequent paper. This paper is accordingly framed as a data descriptor and specified analytical protocol, reporting descriptive and structural findings from the 26 in-scope agreements: a 2022 inflection synchronized with REPowerEU and COP27; importer-side concentration on Germany (34.6% of agreements) and EU-level framework partnerships (34.6%)—two distinct actors jointly accounting for 69.2%—and a small, statistically non-significant difference in mean partnership depth between MENA (n = 18, M = 3.22) and SSA (n = 8, M = 3.25) exporters (Welch t = −0.08, p = 0.94; Cohen’s d = −0.04). The comparison is likely under-powered (power ≈ 0.20–0.44) given the small SSA cell and reported here as a tentative pattern. At this stage, the study contributes a cross-regional agreement dataset, a fully specified equity-indicator protocol, and a theoretical framework for subsequently evaluating whether the green hydrogen transition advances just internationalism or reproduces green-extractivist patterns. Full article

Five studies are frequently cited as experimental evidence that photobiomodulation (PBM) may stimulate tumour growth or produce phototoxicity, contributing to a documented barrier to clinical adoption in oncology. We reappraise these studies against their own reported dosimetry. None characterised the spatial power distribution of its beam. Each was assessed for arithmetic consistency, beam profile, device category, and biological-model appropriateness, and re-examined against the Arrhenius framework for thermal damage. In four of the five, the exposures delivered lay outside the therapeutic photobiological window on the authors’ own stated parameters: surface temperatures of 55 °C and, in places, 71 °C, with injury the original authors describe as coagulation and necrosis extending to paralysis and death; irradiances approximately 25 times those used clinically; and, in one case, parameters the authors themselves describe as high. The fifth, a xenograft study, used a dose within the therapeutic range, but its immunodeficient host cannot express the immune-mediated response at issue. A sixth study, from the same group and using the same device as one of the five but operated at a therapeutic irradiance, is included as an internal control and reported therapeutic benefit. Injury in these regimes is best understood as oxygen-dependent, with temperature acting as a sensitising variable and as a marker of the regime rather than as the proximate cause, a reading supported by the original authors’ own helium-substitution, cooling and heated-probe controls. We outline a two-tier mechanistic framework, in which correctly dosed PBM may engage systemic anti-tumour immunity, as a hypothesis for prospective testing rather than as a finding of this analysis. None of these studies provides dosimetrically secure evidence of a hazard from therapeutic-range PBM; equally, the absence of such evidence is not a demonstration of safety. Beam-profile reporting should become standard in PBM oncology research. Full article

Cloud-integrated sensor and Internet of Things (IoT) systems enable scalable data storage, processing, and intelligent monitoring, but their distributed nature exposes network-flow and host-level data to unauthorized access, tampering, and cyberattacks. This study proposes a Weighted Symmetric Hashed Blockchain (WSHB) framework that integrates mutual-information-based feature weighting, deep-learning-based attack classification, AES-256-GCM authenticated encryption, cryptographic hashing, and permissioned-ledger logging. The framework was evaluated independently using HIKARI-2021 for network-based intrusion detection and ADFA-LD for host-based intrusion detection. A transparent comparative evaluation was conducted against LSTM and CNN–RNN baselines using identical data splits, preprocessing settings, input representations, hyperparameter-search budget, and repeated initialization seeds. The proposed WSHB-DNN classifier achieved macro-F1 scores of $0.6837$ on HIKARI-2021 and $0.7914$ on ADFA-LD, showing the strongest overall classification performance among the evaluated models. The cryptographic and permissioned-ledger components provide confidentiality protection, record-level authentication, integrity verification, and tamper-evident logging for confirmed attack-event records. These results demonstrate the potential of WSHB as a reproducible framework for attack classification and secure event logging in cloud-integrated sensor environments. Full article

Plant diseases impose major constraints on global crop productivity and pose a major threat to food security. Here, we review transcription factors (TFs) as central orchestrators of plant defense, consolidating recent advances in how these regulators connect pathogen perception to immune signaling, transcriptional reprogramming, and durable defense responses. Initially, we combined a literature-based synthesis with a natural language processing (NLP) analysis of 1647 PubMed abstracts published between 2021 and 2026 to map dominant and underexplored TF families associated with plant immunity. WRKY, MYB, AP2/ERF, bHLH/MYC, and NAC dominated the recent literature, whereas families such as NF-Y, Trihelix, PLATZ, TCP, and GRAS represent emerging regulatory actors. Across these and other families, TFs integrate pattern- and effector-triggered immunity, hormone crosstalk, chromatin dynamics, non-coding RNA regulation, post-translational modifications, and metabolic remodeling, in addition to cell-type-specific expression. Further evidence indicates that pathogens frequently manipulate TFs to weaken host defense, underscoring their central position in plant molecular physiology and plant-pathogen coevolution. The data emphasize that TF function is context-dependent and influenced by multilayered regulation, cell type, pathogen lifestyle, and host genetic background. This review provides a framework for understanding TFs in plant immune control and highlights TF-centered strategies for engineering durable crop resistance, along with future challenges. Full article

Aquaculture is central to global food security, but intensification of production has increased disease risk and environmental pressure. The gut microbiome of aquatic organisms is now recognized as a key mediator of host physiology, nutrition, immunity, and pathogen resistance, making it a promising alternative to antimicrobial-based disease control. This review summarizes current knowledge on the composition, assembly, and functional roles of the gut microbiome in fish and crustaceans of aquacultural importance. Major bacterial phyla include Proteobacteria, Firmicutes, Bacteroidetes, Fusobacteria, Actinobacteria, and Verrucomicrobia. Community structure is shaped by environment, diet, host age, genetics, stress, and stochastic processes, with differences between marine and freshwater systems. The microbiome contributes to immune defense through short-chain fatty acid production, Toll-like receptor signaling, cytokine regulation, mucosal immunoglobulin responses, antimicrobial peptide and bacteriocin production, and competitive exclusion of pathogens. It also supports productivity by improving nutrient assimilation, vitamin and enzyme synthesis, and feed conversion. Probiotics, prebiotics, and synbiotics are discussed as strategies for targeted microbiome modulation, although unstable colonization and the lack of standardized protocols remain major challenges. Overall, targeted microbiome manipulation offers a promising route toward sustainable, antimicrobial-reduced aquaculture. Full article

This paper presents findings from a comprehensive assessment aimed at identifying deep geological storage formations suitable for the secure isolation of chemically active gases, including anthropogenic CO₂. Although Kazakhstan currently lacks operational industrial-scale CO₂ storage sites, high annual emissions exceeding 2 million tonnes are concentrated in its southern region, specifically Almaty city and the surrounding Almaty Region. Despite this pressing need, the precise location, availability, and capacity of potential storage sites in this area remain poorly understood. By synthesizing legacy geological, geophysical, and hydrogeological datasets compiled within the eastern Ili Depression, this study evaluates regional deep saline aquifers for potential CO₂ geological storage under favorable techno-economic conditions. It must be clearly emphasized that this study focuses exclusively on deep groundwater aquifers (saline aquifers). Leveraging historical seismic, drilling, and well-logging data originally acquired for petroleum and water resource exploration, we constrain the stratigraphic architecture and structural framework of prospective storage units. The lithostratigraphic framework of the sedimentary cover in the Ili Basin is established, identifying key reservoir intervals and effective sealing formations. The results indicate that the eastern Ili Depression offers highly favorable conditions for geologic storage, with Permian, Triassic, and Jurassic sedimentary successions reaching thicknesses of up to 1200 m. Reservoir intervals are identified across major stratigraphic units, with potential storage formations accounting for up to 60% of the stratigraphic volume. Specifically, the Miocene–Paleogene and Jurassic intervals host sandstone reservoirs exceeding 10 m in thickness, with porosities reaching up to 30%. Upper Jurassic clayey successions function as effective intraformational seals for Middle Jurassic reservoirs, while Upper Cretaceous clay sequences provide regional caprock integrity for the overlying Neogene–Paleogene sandy intervals. These geological settings satisfy rigorous containment criteria required for secure gas sequestration. These insights into the deep architecture of the Ili Depression elucidate key geological controls governing prospective storage sites, paving the way for future carbon capture and storage (CCS) initiatives in one of Kazakhstan’s most vital economic regions. Full article

This study examines how immigrants build the everyday foundations of life in the host society through food provisioning practices. Many previous studies have explored immigrant adaptation from organizational or cultural perspectives. By contrast, this study focuses on the daily procurement of familiar food. It views food provisioning as part of the ongoing process of home in the making, through which home gradually takes shape in everyday life by linking material access, social relations, and cultural continuity. The desire for familiar food is common among immigrants and reflects the habitus embodied through everyday food practices. As migrants enter a new social and material field, this habitus is continuously negotiated and adapted, giving rise to new food provisioning practices. Against this theoretical background, this study examines how these everyday practices shape immigrants’ lives in the host society. This study takes Chinese residents in Japan as research subjects. Based on a questionnaire survey of 317 Chinese residents, this study shows that fresh vegetables and fruits are perceived as particularly difficult to obtain. Some Chinese residents therefore use diverse provisioning practices, including home gardening, sharing, exchange, and small-scale sales. The study then examines cases of Chinese residents’ home gardens and small-scale commercial gardens as sites of food provisioning. The qualitative cases reveal that crop choices, cultivation methods, circulation routes, and garden scale are flexibly adjusted according to family needs, customer demand, land access, labor capacity, and seasonality. These practices enable Chinese residents to secure familiar food, organize everyday life, and develop social relations with co-ethnic residents and members of the wider local society. The findings suggest that garden-based food provisioning represents an informal, everyday pathway of integration shaped by the material and social conditions of life in Japan. Full article

To address the renewable energy hosting capacity problem in regional power grids under security, stability, and power supply adequacy constraints, this paper proposes an energy storage configuration method that coordinates demand–response, synchronous condensers, grid-forming renewable energy retrofits, and storage. First, wind and photovoltaic output scenarios are generated by clustering historical data while considering wind–solar correlations, and a time-of-use-price-based demand–response model is established to improve the net-load profile. Second, a three-layer optimization framework is constructed. The upper layer determines the rated power and energy capacity of the storage system and minimizes storage investment and operation and maintenance costs. The middle layer performs source–grid–load–storage coordinated dispatch under the storage boundary provided by the upper layer and minimizes the total operating costs while embedding node voltage and short-circuit ratio security checks. The lower layer maximizes renewable energy hosting capacity through incremental capacity iteration and determines the maximum admissible renewable capacity subject to reliability, security, and stability constraints. A normalized normal constraint (NNC) method is adopted to solve the multi-objective three-layer model. Case studies based on an improved IEEE 118-bus system show that the coordinated measures can significantly increase hosting capacity, reduce storage demand, and improve voltage and frequency security. Full article

Software-Defined Networking (SDN) separates the control and data planes, introducing a logically centralized controller that is itself a high-value attack target. Despite growing interest in SDN intrusion detection, publicly available datasets either restrict evaluation to binary normal-vs-DDoS classification or lack control-plane telemetry, leaving multi-class detection of SDN-architectural attacks without a dedicated benchmark. This work presents LAN-SDN-NIDS, a publicly available, multi-class flow-level dataset of 1,125,059 records generated in a fully containerized Containernet/OpenDaylight testbed across five standard network topologies. Each flow record combines 29 traffic-level features with 11 control-plane-aware metrics—including Packet-In and Flow-Mod counts and first-seen delay. The dataset covers five attack classes in two categories: three that exploit SDN control-plane mechanisms (link fabrication, host injection, and port hijack) alongside DDoS and port scan, plus normal traffic. An XGBoost classifier trained on the full feature set achieved a macro F1 of 0.94; an ablation study showed that removing OpenFlow features causes link fabrication F1 to collapse from 0.97 to 0.19, indicating that control-plane telemetry is decisive for detecting SDN-architectural attacks under the conditions evaluated. A UMAP embedding is consistent with class separability, except for a structural overlap between host injection and normal traffic attributable to their shared ARP protocol. Full article

The fall armyworm (FAW), Spodoptera frugiperda, is a highly polyphagous pest that has rapidly expanded across Africa, Asia, and Oceania, threatening food security and agricultural productivity. Reliance on synthetic insecticides for FAW management is increasingly challenged by insecticide resistance, environmental contamination, and adverse effects on non-target organisms and human health. This review synthesizes current knowledge on the potential of endophytic fungi as a sustainable strategy for FAW management. Following a systematic literature search, 59 original research articles published over the past 41 years were evaluated. These studies investigated 44 fungal species across 37 host crops, with Zea mays representing the most extensively studied system. The fungal species most frequently assessed were Beauveria bassiana, Metarhizium anisopliae sensu lato (s.l.), and Epichloe coenophialum. Overall, several fungal species successfully colonized plant tissues and reduced FAW performance through increased larval mortality, delayed development, and reduced feeding. These effects were associated with the production of bioactive secondary metabolites, induction of plant defense responses, and alteration of volatile organic compound emissions. Despite these promising findings, important knowledge gaps remain. Studies assessing effects on non-target organisms and natural enemies are scarce, and field validation remains limited. Research efforts are also geographically biased, with relatively few studies conducted in Africa despite the continent experiencing some of the highest FAW-related losses. Future research should prioritize field evaluations, multitrophic interaction studies, investigations in underrepresented regions, and socio-economic analyses to support farmer adoption. Addressing these gaps will be critical for determining the practical role of endophytic fungi in sustainable FAW management. Full article

Large Language Model (LLM)-based agents automate complex tasks by integrating external tools such as web browsers, e-mail clients, file readers, and APIs, but this same integration exposes them to indirect prompt injection (IPI) attacks, in which malicious instructions hidden in tool content hijack the agent. A central but often overlooked question is how defending against such attacks affects the LLM and its own task performance and computational efficiency. In this study, we design a comprehensive testbed and a layered defense, Spotlight-Guard, that combines spotlighting-based input isolation, an LLM detection-and-quarantine pipeline, and instruction integrity based on a Hash-based Message Authentication Code (HMAC) into a single framework, and we evaluate it jointly along two axes: security and LLM performance. Experiments on locally hosted 7B-class open-weight models (Qwen-2.5-7B, Mistral-7B, and DeepSeek-Coder) use Attack Success Rate (ASR) for security and benign-task success rate together with confusion-matrix-based metrics (precision, recall, and F1) for task performance, all with bootstrap 95% confidence intervals. Across a stratified, fixed-seed benchmark of 250 adversarial and 250 benign cases per configuration, the full system reduces the ASR from 36.0% to 17.2% while preserving a 97.2% benign-task success rate and raising the detection F1 from 0.749 to 0.892, demonstrating that strong protection need not degrade the model’s task performance. A component ablation isolates each layer’s contribution, an adaptive-attack evaluation confirms a low ASR (6.7%) under attacks crafted to target the pipeline, and an analysis of computational cost (model invocations per request) quantifies the efficiency overhead, characterizing the security–performance trade-off of layered defenses on open-weight LLMs. Full article

Security datasets are central to the evaluation of intrusion detection and prevention systems, but their suitability differs substantially across domains, data sources, attack scenarios, labeling practices, and reproducibility conditions. This study presents a structured evidence-mapping review of security datasets reported in intrusion detection and prevention research between 2018 and 2025. The final evidence map includes 42 primary dataset-use publication records, 82 dataset or evidence-source mentions, and 69 unique datasets, corpora, or evidence sources after duplicate, retracted, and irrelevant records were removed. The review organizes datasets across network-based IDS, IPS, firewall, VPN, WAF, endpoint, email filtering, IAM, DDoS, Windows, Linux-Apache, NetFlow, cloud, and IoT/IIoT security settings. In addition to adoption-frequency analysis, the study assesses representative dataset families in terms of documentation, labeling information, feature representation, class balance, public availability, reproducibility, and practical usability limitations. The findings show that established benchmarks remain widely reused, but recent studies increasingly rely on domain-specific datasets for IoT/IIoT, DDoS, cloud, edge, host, and cyber-physical environments. The review also proposes and illustrates a dataset-selection framework that links dataset choice to security objectives, operational context, telemetry requirements, attack coverage, and evaluation protocol. The results support more transparent, context-aware, and reproducible dataset selection for intrusion detection and prevention research. Full article

Agricultural outward foreign direct investment (OFDI) is an important mechanism for strengthening food security, enhancing agricultural capacity, and advancing sustainable development through greater supply-chain resilience and resource-use efficiency. This study applies social network analysis to characterize the global agricultural OFDI network and uses a temporal exponential random graph model (TERGM) to examine its drivers. The results show that the network remains sparse but has become more efficiently connected, reciprocal, and clustered, while retaining a pronounced core–periphery structure. Developed economies, led by the United States, occupy the network core, whereas the positions of emerging Asian economies, including China, have strengthened over time. Both endogenous network dependencies and exogenous attributes jointly shape tie formation. The post-2018 estimates indicate weaker network persistence, stronger resource-endowment effects, and greater investment attraction in host economies with less restrictive institutional environments. Across development groups, agricultural capital from high-income economies follows a predominantly unidirectional core–periphery pattern, whereas developing economies exhibit more frequent reciprocal and cyclical investment ties. Full article