Search Results (686)

Food loss and waste from the European Union’s dairy supply chain, particularly in the management of fresh milk, imposes significant environmental burdens. This study demonstrates that implementing Radio Frequency Identification (RFID)-enabled digital decision-support tools can substantially reduce these impacts across the region. A cradle-to-grave life cycle assessment (LCA) was used to quantify both the additional environmental burdens from RFID (tag production, usage, and disposal) and the avoided burdens due to reduced milk losses in the farm, processing, and distribution stages. Within the EU’s fresh milk supply chain, the implementation of digital tools could result in annual net reductions of up to 80,000 tonnes of CO₂-equivalent greenhouse gas emissions, 81,083 tonnes of PM_2.5-equivalent particulate matter, 84,326 tonnes of land use–related carbon deficit, and 80,000 cubic meters of freshwater-equivalent consumption. Spatial analysis indicates that regions with historically high spoilage rates, particularly in Southern and Eastern Europe, see the greatest benefits from RFID enabled digital-decision support tools. These environmental savings are most pronounced during the peak months of milk production. Overall, the study demonstrates that despite the environmental footprint of RFID systems, their integration into the EU’S dairy supply chain enhances transparency, reduces waste, and improves resource efficiency—supporting their strategic value. Full article

Radio Frequency Identification (RFID) technology is widely applied in various scenarios, including logistics tracking, supply chain management, and target monitoring. In these contexts, the malicious cloning of legitimate tag information can lead to sensitive data leakage and disrupt the normal acquisition of tag information by readers, thereby threatening personal privacy and corporate security and incurring significant economic losses. Although some efforts have been made to detect cloning attacks, the presence of missing tags in RFID systems can obscure cloned ones, resulting in a significant reduction in identification efficiency and accuracy. To address these problems, we propose the block-based cloned tag identification (BCTI) protocol for identifying cloning attacks in the presence of missing tags. First, we introduce a block indicator to sort all tags systematically and design a block mechanism that enables tags to respond repeatedly within a block with minimal time overhead. Then, we design a superposition strategy to further reduce the number of verification times, thereby decreasing the execution overhead. Through an in-depth analysis of potential tag response patterns, we develop a precise method to identify cloning attacks and mitigate interference from missing tags in probabilistic cloning attack scenarios. Moreover, we perform parameter optimization of the BCTI protocol and validate its performance across diverse operational scenarios. Extensive simulation results demonstrate that the BCTI protocol meets the required identification reliability threshold and achieves an average improvement of $24.01\%$ in identification efficiency compared to state-of-the-art solutions. Full article

The global coffee supply chain is a complex multi-stakeholder ecosystem plagued by fragmented records, unverifiable origin claims, and limited real-time visibility. These limitations pose risks to ethical sourcing, product quality, and consumer trust. To address these issues, this paper proposes a blockchain and IoT-enabled framework for secure and transparent coffee supply chain management. The system integrates simulated IoT sensor data such as Radio-Frequency Identification (RFID) identity tags, Global Positioning System (GPS) logs, weight measurements, environmental readings, and mobile validations with Ethereum smart contracts to establish traceability and automate supply chain logic. A Solidity-based Ethereum smart contract is developed and deployed on the Sepolia testnet to register users and log batches and to handle ownership transfers. The Internet of Things (IoT) data stream is simulated using structured datasets to mimic real-world device behavior, ensuring that the system is tested under realistic conditions. Our performance evaluation on 1000 transactions shows that the model incurs low transaction costs and demonstrates predictable efficiency behavior of the smart contract in decentralized conditions. Over 95% of the 1000 simulated transactions incurred a gas fee of less than ETH 0.001. The proposed architecture is also scalable and modular, providing a foundation for future deployment with live IoT integrations and off-chain data storage. Overall, the results highlight the system’s ability to improve transparency and auditability, automate enforcement, and enhance consumer confidence in the origin and handling of coffee products. Full article

Background: Cochlear implantation is widely used to provide auditory rehabilitation to individuals with severe-to-profound sensorineural hearing loss. However, electrode insertion during cochlear implantation leads to inner ear trauma, damage to sensory structures, and consequently, loss of residual hearing. There is very limited information regarding the target proteins involved in electrode insertion trauma (EIT) following cochlear implantation. Methods: The aim of our study was to identify target proteins and host molecular pathways involved in cochlear damage following EIT utilizing the iTRAQ™ (isobaric tags for relative and absolute quantification) technique using our ex vivo model. The organ of Corti (OC) explants were dissected from postnatal day 3 rats and subjected to EIT or left untreated (control). The proteins were extracted, labelled, and subjected to ultra-high performance liquid chromatography–tandem mass spectrometry. Results: We identified distinct molecular pathways involved in EIT-induced cochlear damage. Confocal microscopy confirmed the expression of these identified proteins in OC explants subjected to EIT. By separating the apical, middle, and basal cochlear turns, we deciphered a topographic array of host molecular pathways that extend from the base to the apex of the cochlea, which are activated post-trauma following cochlear implantation. Conclusions: The identification of target proteins involved in cochlear damage will provide novel therapeutic targets for the development of effective treatment modalities for the preservation of residual hearing in implanted individuals. Full article

Paeoniflorin (PF), a monomeric compound extracted from the dry roots of Paeonia lactiflora, has been widely used in the treatment of nervous system diseases, marking it as a critical formula in Parkinson’s disease (PD). However, the action of PF against PD and its molecular mechanism are still unclear. In this study, tandem mass tags quantitative proteomics was performed to systematically clarify the underlying mechanism of action of PF against PD and to confirm it using in vivo and in vitro studies. The results showed that PF notably enhanced the viability of PC12 cells and mitigated MPP⁺-induced mitochondrial dysfunction, oxidative stress, and apoptosis. Tandem mass tag-based quantitative proteome analysis revealed the identification of 6405 proteins, of which 92 were downregulated and 190 were upregulated. Among them, the levels of PI3K, AKT, CREB, and BDNF in the MPP⁺-induced PC12 cell and MPTP mice were considerably lower than in the control group, indicating the role of the BDNF/CREB pathway in the pathogenesis of neuroprotection. The related DEP (PI3K, AKT, CREB, and BDNF) expression levels were verified by Western blot. PF effectively restored the altered expression of the four DEPs induced by MPP⁺ and MPTP. Summarily, PF exerted remarkable neuroprotective effects in MPP⁺-induced PC12 cell and MPTP-induced mice. Further, our research may provide proteomics insights that contribute to the further exploration of PF as a potential treatment for PD. Full article

Hydropower infrastructure has profoundly altered riverine connectivity, posing challenges to the migratory behavior of aquatic species. This study examined the post-passage migration efficiency of Schizothorax wangchiachii in a regulated river system, focusing on upstream and downstream reaches of the Songxin Hydropower Station on the Heishui River, a tributary of the Jinsha River. We used radio-frequency identification (RFID) tagging to track individuals after fishway passage and coupled this with environmental monitoring data. A Cox proportional hazards model was applied to identify key abiotic drivers of migration success and to develop a predictive framework. The upstream success rate was notably low (15.6%), with a mean passage time of 438 h, while downstream success reached 81.1%, with an average of 142 h. Fish exhibited distinct diel migration patterns; upstream movements were largely nocturnal, whereas downstream migration mainly occurred during daylight. Water temperature (HR = 0.535, p = 0.028), discharge (HR = 0.801, p = 0.050), water level (HR = 0.922, p = 0.040), and diel timing (HR = 0.445, p = 0.088) emerged as significant factors shaping the upstream movement. Our findings highlight that fishways alone may not ensure functional connectivity restoration. Instead, coordinated habitat interventions in upstream tributaries, alongside improved passage infrastructure, are crucial. A combined telemetry and modeling approach offers valuable insights for river management in fragmented systems. Full article

Interactions between chemical drugs and their target proteins are fundamental to drug screening and precision therapy in modern clinical medicine. However, elucidating these interactions within living cells remains challenging due to the limited availability of efficient detection methods. Despite substantial efforts, technical limitations still impede the identification of direct interactors. In this study, we present a simple method to detect the binding between a chemical drug and its target proteins in live cells. This approach utilizes a self-labeling protein (SLP) tag system, specifically HaloTag which is a modified haloalkane dehalogenase, combined with spatially localized expression of the SLP. To implement this system, dasatinib was conjugated to a HaloTag ligand, and the HaloTag protein was expressed in specific intracellular compartments, such as endosomes or F-actin structures. Upon treatment of cells with the HaloTag ligand-conjugated dasatinib, green fluorescent protein (GFP)-fused cytoplasmic dasatinib target proteins were observed to co-localize with the HaloTag at these subcellular structures, thereby indicating direct drug–target binding. This method provides a good spatial resolution with a high signal-to-noise ratio and low false-positive signals across a high background and false-positive/false-negative signals from endogenous proteins and/or non-specific binding. In this context, we believe that our method is a useful platform for visualizing the binding between chemical drugs and their cytoplasmic targets within living systems. Full article

Coccidiosis, caused by Eimeria spp., significantly reduces poultry productivity and causes major economic losses. Traditional control methods are limited by drug resistance and high production costs. Recent genomic and bioinformatic advances have enabled the identification of novel antigens, making recombinant subunit vaccines a promising next-generation strategy by eliciting robust cellular and humoral immune responses. This study investigates the E. necatrix gametocyte protein 56 (EnGAM56) as a potential candidate for recombinant subunit vaccines. The full-length E. necatrix gametocyte gam56 gene (Engam56-F) was amplified, expressed in vitro, and characterized via SDS-PAGE and Western blot. Immunofluorescence assays revealed that EnGAM56-F is specifically localized in gametocytes and unsporulated oocysts. Chickens immunized with recombinant proteins (rEnGAM56-F and rEnGAM56-T) were evaluated for immunoprotection against E. necatrix infection through lesion scores, weight gain, oocyst production, anticoccidial index (ACI), and antibody and cytokine levels. The synergistic effects were evaluated by employing various combinations of recombinant proteins, including rEtGAM22, rEtGAM56-T, and rEtGAM59. Results showed that EnGAM56-F encodes a 468-amino acid protein with distinct tyrosine-serine-rich and proline-methionine-rich regions. rEnGAM56-F was specifically recognized by both anti-6 × His tag antibodies and convalescent serum from chickens infected with E. necatrix. Both rEnGAM56-F and rEnGAM56-T provided immune protection, with rEnGAM56-T showing superior efficacy. The combination of rEnGAM (22 + 59 + 56-T) yielded the strongest immune response, followed by rEnGAM (22 + 56-T). These findings highlight the potential of EnGAM56 as a candidate for recombinant subunit anticoccidial vaccines. Full article

Identifying the source camera of a digital image is a critical task for ensuring image authenticity. In this paper, we propose a novel privacy-preserving distributed source camera identification scheme that jointly exploits both physical-layer fingerprint features and a carefully designed artificial tag. Specifically, we build a hybrid fingerprint model by combining sensor level hardware fingerprints with artificial tag features to characterize the unique identity of the camera in a digital image. To address privacy concerns, the proposed scheme incorporates a privacy-preserving strategy that encrypts not only the hybrid fingerprint parameters, but also the image content itself. Furthermore, within the distributed framework, the identification task performed by a single secondary user is formulated as a binary hypothesis testing problem. Experimental results demonstrated the effectiveness of the proposed scheme in accurately identifying source cameras, particularly under complex conditions such as those involving images processed by social media platforms. Notably, for social media platform identification, our method achieved average accuracy improvements of 7.19% on the Vision dataset and 8.87% on the Forchheim dataset compared to a representative baseline. Full article

This paper presents a Virtualized Computational Radio Frequency Identification (VCRFID) solution that utilizes far-field UHF RF for sensing, computing, and self-powering at the edge. A standard UHF RFID system is asymmetric as it consists of a relatively large, complex “reader”, which acts as an RF transmitter and controller for a number of small simple battery-less “tags”, which work in passive mode as they communicate and harvest RF energy from the reader. Previously proposed Computational RFID (CRFID) solutions enhance the standard RFID tags with microcontrollers and sensors in order to gain enhanced functionality, but they end up requiring a relatively high level of power, and thus ultimately reduced range, which limits their use for many Internet-of-Things (IoT) application scenarios. Our VCRFID solution instead keeps the functionality of the tags minimalistic by only providing a sensor interface to be able to capture desired environmental data (temperature, humidity, vibration, etc.), and then transmit it to the RFID reader, which then performs all the computational load usually carried out by a microcontroller on the tag in prior work. This virtualization of functions enables the design of a circuit without a microcontroller, providing greater flexibility and allowing for wireless reconfiguration of tag functions over RF for a 97% reduction in energy consumption compared to prior energy-harvesting RFID tags with microcontrollers. The target application is Industry 4.0 where our VCRFID solution enables battery-less fine-grain monitoring of vibration and temperature data for pumps and motors for predictive maintenance scenarios. Full article

Proteins regulate various cellular processes and are of great biological interest. The protein search engine is a crucial tool in proteomics research, used to analyze high-throughput tandem mass spectrometry data and to identify protein sequence information. A core step in protein search engines is constructing sequence tag indexes and performing the rapid retrieval of protein databases. However, as the scale of protein sequence data continues to grow, traditional protein search engines face the dual challenges of the high storage cost of sequence tag indexes and low retrieval efficiency. To address these issues, we propose a sequence tag index scheme named STIP, which is based on an inverted index and compression techniques. Based on STIP, we design a peptide retrieval algorithm named STIP-Search. This algorithm utilizes the sequence tag index constructed by STIP for peptide sequence retrieval. STIP uses the greedy algorithm to partition the tag index into blocks; in this way, STIP can generate tag indexes for very large protein databases, such as NCBI-nr. Compared to the current four mainstream tag index generation algorithms used in Open-pFind, MODplus, TIIP and PIPI2, STIP has the lowest storage and time consumption. It utilizes delta encoding, index reduction, and dynamic bit width encoding to compress the tag index, reducing the storage cost by 76.2%. Compared to TIIP, which is currently the algorithm with the lowest time complexity, the time cost of the peptide sequence retrieval of STIP-Search is reduced by 8.94% to 23.31%. Full article

The last few years have seen the introduction of new technologies in beekeeping, including RFID. Using readers and miniaturized tags, RFID systems work in the UHF frequency band, allowing reading distances to reach tens of centimeters. This work analyzes the propagation inside a full beehive, composed of 10 frames supported by a wooden structure. Each frame contains a layer of beeswax supported by metallic wires. The methodology employed involves measuring Received Signal Strength Indicator (RSSI) values and simulating the environment using CST Studio. The results show that tags located along the frame’s wires have more coverage than tags in the center positions, revealing coupling of the microtag antenna with the wire. Furthermore, obtaining coverage through simulations represents a more restrictive approach than through measurements. Frame selectivity is also observed, as most of the coverage is found within the three frames closest to the reader antenna. This result shows that RFID systems can find application in the identification and location of the queen bee in a hive. Full article

In this work, a precursor-driven tailoring of strontium aluminate phosphors doped with Eu²⁺ and Dy³⁺ to generate unique, batch-specific luminescent signatures suitable for smartphone-detectable anti-counterfeiting tags was developed. A microwave-assisted hydrothermal synthesis approach was employed to explore the impact of a wide range of alkaline hydroxide and carbonate precursors on the structure of strontium aluminate. The resulting materials exhibited distinct differences in crystalline phase composition, morphology, and trap depth distribution. A smartphone-based detection system was developed, enabling rapid identification of spectral fingerprints. This study demonstrates a viable strategy for embedding unique luminescent identifiers, offering a scalable solution for robust, low-cost anti-counterfeiting applications in both the spectral and the time domain. Full article

Rice (Oryza sativa L.) is a stable food for over half of the world population, contributing 50–80% of the daily calorie intake. The completion of rice genome sequencing marks a significant milestone in understanding functional genomics, yet the systematic identification of gene functions remains a bottleneck for rice improvement. Large-scale mutant libraries in which the functions of genes are lost or gained (e.g., through chemical/physical treatments, T-DNA, transposons, RNAi, CRISPR/Cas9) have proven to be powerful tools for the systematic linking of genotypes to phenotypes. So far, using different mutagenesis approaches, a million mutant lines have been established and about 5–10% of the predicted rice gene functions have been identified due to the high demands of labor and low-throughput utilization. DNA-barcoding-based large-scale mutagenesis offers unprecedented precision and scalability in functional genomics. This review summarizes large-scale loss-of-function and gain-of-function mutant library development approaches and emphasizes the integration of DNA barcoding for pooled analysis. Unique DNA barcodes can be tagged to transposons/retrotransposons, DNA constructs, miRNA/siRNA, gRNA, and cDNA, allowing for pooling analysis and the assignment of functions to genes that cause phenotype alterations. In addition, the integration of high-throughput phenotyping and OMICS technologies can accelerate the identification of gene functions. Full article

This paper presents a dual circularly polarized encoding terahertz tag utilizing linked-semi-ellipses elements. The proposed design achieves broadband 2-bit polarization encoding in terahertz frequency bands through independently controlling dual circularly polarized phases with linked-semi-ellipses elements. The tag simultaneously possesses two key functionalities: circular polarization conversion and circular polarization encoding, which enhance its resilience to environmental influences. Simulations demonstrated the polarization conversion rates exceeding 80% across 0.42–0.53 THz with reflected RCS from tag achieved −51.7 dB·m² and a 3 dB beamwidth of ±22°. The tag achieves broadband 2-bit circular polarization encoding and attains a 23.6% relative bandwidth. The circular polarization encoding method enhances stability in metal-rich environments and offers substantial potential for diverse practical applications, including indoor positioning, logistics tracking, and object identification. Full article