Search Results (70)

Background: Improving grain yield in wheat remains a top priority, requiring integrated breeding and genetic strategies. This complexity poses a major challenge, driven by quantitative polygenic inheritance, environmental influence, and intricate genetic interactions. We investigated genetic factors and their interactions for agronomic and yield traits in two high-yielding winter wheat cultivars adapted to the US Southern Great Plains. Methods: A bi-parental mapping population consisting of 221 F₇ recombinant inbred lines (RIL) derived from ‘TAM 204’ and ‘Iba’ was evaluated for three years in 11 Texas environments. Both parents and RIL population were genotyped on Illumina NovaSeq 6000 and sequences were aligned to IWGSC RefSeq v1.0 using Bowtie2 for SNP calling. For QTL analyses, each trait was analyzed by individual environment, across multiple environments and mega-environments. Results: A total of 86 QTL were mapped for five traits and among them 32 were consistent in more than one environment or analysis. Among consistent QTL, four were pleiotropic to more than one agronomic or yield traits mapped on chromosomes 2B (57.18, 59.47 Mb) and 2D (29.34, 40.64 Mb). The consistent QTL on chromosome 2D (29.34 Mb) was pleiotropic to GYLD, DTH, TW, TKW and explained maximum phenotypic variation for all traits, representing photoperiod gene (Ppd-D1). Another QTL on chromosome 2D (40.64 Mb) was pleiotropic to GYLD and TW and based on the physical position comparisons it likely reflects a unique locus in Iba. The pleiotropic consistent QTL Qgyld.tamu.2B.59 from TAM 204 represents Ppd-B1 gene. Moreover, it is more likely that Qdth.tamu.5B.575 represents the Vrn-B1 gene in Iba. A total of 23 digenic epistatic interactions involved consistent QTL for all traits. Amongst these, epistatic interactions between the consistent QTL on 2B (57.18 Mb) and 2D (29.34 Mb) were observed for GYLD, DTH and TKW. Conclusions: Our findings revealed key allelic diversity and interaction effects in elite wheat cultivars, paving the way for marker development for identified pleiotropic loci and implementation in marker-assisted selection and recombination breeding. Full article

This paper presents the concept of a 2D m × n waveguide-based power combiner (PC) that is scalable with respect to the operating frequency band and number of input ports. To our knowledge, this work reports the first planar (2D) power combiner, where the input waveguide ports are distributed in two spatial dimensions to form an array, rather than arranged along a single linear (1D) axis as in conventional corporate or cascaded waveguide combiners. The novelty of the approach relies on using H-plane rectangular waveguide T-junctions and low-loss polarization twisters in between vertically stacked T-junctions to facilitate scalability. The work is motivated by the aim to coherently combine the output power of multiple modified uni-traveling carrier (MUTC) terahertz (THz) waveguide photodiodes (PDs) in a 2D array configuration. In the manuscript, the design of a 2 × 2 planar waveguide power combiner for the WR3 band (220–320 GHz) is reported, and it is also shown that this block can be further extended to m × n input ports. Full-wave numerical analysis of the proposed 2 × 2 power combiner shows a return loss of 11 dB at the output port and an average transmission coefficient of about −6.5 dB, i.e., an overall power combining efficiency of ~90%. Furthermore, to enable 2D photodiode array integration, the manuscript presents a new slot-bow tie antenna integrated MUTC photodiode for radiating the optically generated THz power from each PD vertically into the rectangular waveguide. The simulation results of reflection loss and insertion loss for the slot bow-tie antenna are shown to be better than 10 dB and 1.4 dB over the full WR3 band, respectively. To prove scalability of the power combiner concept w.r.t. the number of input ports, a 2 × 4 power combiner is also analyzed. Results reveal a return loss better than 10 dB from 225 to 318 GHz and a transmission coefficient of approximately −9.7 dB at 300 GHz, i.e., a power combining efficiency of ~85%. Full article

Open-sea fishing vessel accidents are difficult to assess systematically because no state holds exclusive jurisdiction, and reporting and investigative duties are not applied consistently. This study analyzed 67 officially reported accidents from the International Maritime Organization (IMO) Global Integrated Shipping Information System (GISIS) using a bow-tie framework combining fault tree analysis (FTA), Firth logistic regression, event tree analysis (ETA), and quantitative risk assessment (QRA). COLREG violations and watchkeeping failures dominated collisions; overload and stability issues caused capsizes; pump capacity, hull leakage, and vessel aging (≥30 years) caused sinkings. Firth regression confirmed older vessels and high beam-to-length ratios (≥0.30) significantly increased sinking likelihood. ETA and QRA estimated probabilities of 0.522 for collisions, 0.090 for capsizes, and 0.388 for sinkings, with risks of R = 0.155, 0.048, and 0.036. Because open-sea accident data rely on limited and voluntary reporting, results are preliminary. However, the bow-tie framework effectively identifies dominant causal factors and high-severity event pathways in open-sea fishing operations. Full article

Maritime accidents are low-probability, high-consequence events, making mechanism analysis crucial for risk mitigation. Existing studies often focus on single scenarios or factors and frequently mix pre-incident observational data with subjective unsafe behavior labels, limiting causal-chain construction for proactive risk prediction. To address these issues, this study proposes a Bow-Tie-based causal-chain Bayesian network, establishing a hierarchical inference chain of “observed parameters–unsafe causes–accident types” to capture causal interactions among multiple factor categories and enable inference from pre-incident data to potential unsafe causes and accident types. Applied to the Bohai Sea region, sensitivity analysis quantified the effects of risk factors under varying conditions on collision, sinking, and grounding probabilities. The results show that the method can infer accident types and unsafe causes using only pre-incident data, achieving over 70% accuracy and closely matching accident investigation findings. Moreover, it reveals layer-by-layer mechanisms of key contributing factors and provides targeted management interventions, supporting quantitative decision-making for maritime regulators and shipping companies, with significant practical applicability. Full article

Bow-tie microwave diodes have proven to be effective sensors of electromagnetic radiation across a wide wavelength range, from centimeter-scale radio waves to micrometer-scale mid-infrared radiation. Their operation is based on electron heating by strong electric fields. However, the experimental data obtained so far remain inconclusive, and the exact nature of the voltage detected by bow-tie diodes is not yet fully understood. In this work, we extend the investigation of the electrical properties of bow-tie diodes based on modulation-doped semiconductor structures with a wide spacer. The analysis focuses on the influence of diode metal contact geometry, illumination conditions, and orientation relative to the crystallographic axes. To elucidate the origin of the voltage detected by bow-tie diodes, we compare theoretical predictions of their electrical parameters—including voltage sensitivity, electrical resistance, asymmetry of the I–V characteristic in weak electric fields, and the nonlinearity coefficient of the I–V characteristic in strong electric fields—with corresponding experimental results. The results of our investigations indicate that, for most diodes, the detected voltage originates from electron heating by the microwave electric field, as evidenced by the polarity of the detected voltage matching the thermoelectric emf of hot carriers. Full article

Ensuring reliability and safety is essential in complex energy systems such as wind turbines, where failures can trigger unexpected downtimes, severe incidents, and significant costs. This study proposes a hybrid BowTie-based reliability framework that integrates Fault Tree Analysis, Reliability Block Diagrams, and BowTie methodology to quantify risk and evaluate the effectiveness of safety barriers. The framework employs key reliability metrics including availability, probability of failure on demand, and probability of failure per hour, and supports scenario-based sensitivity analyses to explore redesign options. A simulation-based case study of a wind turbine generator subsystem is presented, using parameter values drawn from published reliability data. Results highlight that protective relays and automatic trip systems represent critical single points of defence, while improvements such as enhanced oil analysis and redundant dashboards reduce consequence frequency from 2.912 × 10⁻¹⁷ to 8.257 × 10⁻¹⁹ failures/h (a 97.16% reduction, nearly two orders of magnitude). Compared to conventional models, the proposed framework introduces explicit defence in depth modelling, improves computational compactness, and provides a practical decision support tool for asset managers by balancing safety and reliability. At this stage, the study should be regarded as a proof of concept that demonstrates feasibility and sets a foundation for future research and application to larger, more complex infrastructures. Full article

Earle’s balanced salt solution (EBSS) is a classical autophagy inducer that provides a special culture environment lacking amino acids and serum, causing cell starvation. However, the production of relevant omics data surrounding EBSS-induced autophagy is still in the early stage. The objective of this study was to identify new potential functional proteins in the autophagy process through omics analysis. We selected EBSS-induced autophagy as our research object and uncovered autophagy-regulatory proteins using RNA-seq analysis. Western blotting showed that EBSS increased LC3B-II protein levels in NRK cells, reaching the maximum amount at 2 h of culture. Then, we used next-generation sequencing to obtain quantified RNA-seq data from cells incubated with EBSS and the bowtie–tophat–cufflinks flow path to analyze the transcriptome data. Using significant differences in the FPKM values of genes in the treated group compared with those in the control group to indicate differential expression, 470 candidate genes were selected. Subsequently, GO and KEGG analyses of these genes were performed, revealing that most of these signaling pathways were closely associated with autophagy, and to better understand the potential functions and connections of these genes, protein–protein interaction networks were studied. Considering all the conclusions of the analysis, 27 candidate genes were selected for verification, where the knockdown of Txnrd1 decreased LC3B-II protein levels in NRK cells, consistent with the results of confocal experiments. In conclusion, we uncovered autophagy-regulatory proteins using RNA-seq analysis, with our results indicating that TXNRD1 may play a role in regulating EBSS-induced autophagy via an unknown pathway. We hope that our research can provide useful information for further autophagy omics research. Full article

The operational risks of equipment in coalbed methane (CBM) gathering stations exhibit dynamic characteristics. To address this, a dynamic risk assessment method based on Dynamic Bayesian Networks (DBNs) is proposed for CBM station equipment. Additionally, a comprehensive safety management evaluation model is established for gathering station equipment. This approach enables accurate risk assessment and effective implementation of safety management in CBM gathering stations. This method primarily consists of three core components: risk factor identification, dynamic risk analysis, and comprehensive safety management evaluation. First, the Bow-tie model is applied to comprehensively identify risk factors associated with station equipment. Next, a DBN is constructed based on the identified risks, and Markov theory is employed to determine the state transition matrix. Finally, a Comprehensive Safety Management (CSM) evaluation model for gathering station equipment is established. The feasibility of the proposed method is validated through case study applications. The results indicate that during the operation of equipment at CBM gathering stations, priority should be given to strengthening maintenance for medium-hole and enhancing prevention and emergency measures for jet fires. Temperature-controlled spiral-wound heat exchangers, skid-mounted circulating pumps, and pipelines have been identified as critical factors affecting accident occurrence at CBM gathering stations. Enhanced daily inspection and maintenance of this equipment should be implemented. Furthermore, compared to other safety evaluation indicators, the Emergency Preparedness and Response indicator has the most significant impact on the operational safety of CBM gathering station equipment. It requires high-priority attention, thorough implementation of relevant measures, and continuous improvement through targeted actions. Full article

This systematic review explores recent advancements in antenna and rectifier systems for radio frequency (RF) energy harvesting within the gigahertz frequency range, aiming to support the development of sustainable and efficient low-power electronic applications. Conducted under the PRISMA methodology, our review filtered 2465 initial records down to 80 relevant studies, addressing three research questions focused on antenna design, operating frequency bands, and rectifier configurations. Key variables such as antenna type, resonant frequency, gain, efficiency, bandwidth, and physical dimensions were examined. Antenna designs including fractal, spiral, bow-tie, slot, and rectangular structures were analyzed, with fractal antennas showing the highest efficiency, while array antennas exhibited lower performance despite their compact dimensions. Frequency band analysis indicated a predominance of 2.4 GHz and 5.8 GHz applications. Evaluation of substrate materials such as FR4, Rogers, RT Duroid, textiles, and unconventional composites highlighted their impact on performance optimization. Rectifier systems including Schottky, full-wave, half-wave, microwave, multi-step, and single-step designs were assessed, with Schottky rectifiers demonstrating the highest energy conversion efficiency. Additionally, correlation analyses using boxplots explored the relationships among antenna area, efficiency, operating frequency, and gain across design variables. The findings identify current trends and design considerations crucial for enhancing RF energy harvesting technologies. Full article

Poisoning and suffocation accidents occurred frequently in the pre-treatment pool workshops of biogas plants, so this paper provided a multi-dimensional risk analysis model: Bow-Tie-Qualitative Comparative Analysis (QCA)-Bayesian Neural Network-Consequence Simulation. First, the reasons for biogas poisoning and suffocation accidents were clarified through Bow-Tie. Then, the QCA method explored the accident cause combination paths in management. Next, the frequency distribution of biogas poisoning and suffocation accidents in the pre-treatment pool workshop was predicted to be 0.61–0.66 using the Bayesian neural network model, and the uncertainty of the forecast outcome was given. Finally, the ANSYS Fluent 16.0 simulation of biogas diffusion in three different ventilation types and a grid-independent solution of the simulation were conducted. The simulation results showed the distribution of methane, carbon dioxide and hydrogen sulfide gases and the hazards of the three gases to workers were analyzed. In addition, according to the results, this paper discussed the importance and necessity of ventilation in pre-treatment pool workshops and specified the hazard factors in biogas poisoning and suffocation accidents in the pre-treatment pool workshops. Some suggestions on gas alarms were also proposed. Full article

Background: Canine oral melanoma (COM) is an aggressive and often fatal neoplasm in dogs, with clinical and molecular similarities to human melanoma. Despite its relevance as a comparative oncology model, the molecular mechanisms underlying COM remain poorly understood. This study aimed to characterize gene expression profiles in COM to identify differentially expressed genes (DEGs), potential biomarkers, and therapeutic targets. Methods: In this pilot study, we performed RNA sequencing (RNA-seq) on tumor and healthy oral tissue samples from dogs. Two independent analytical pipelines—Bowtie2-DESeq2 and HISAT-StringTie-Ballgown—were used to ensure robustness in DEG detection. We also conducted pathway enrichment and isoform-level analyses to investigate biological processes and alternative splicing events. Results: Both approaches identified a core set of 929 common DEGs. Key oncogenic pathways, including MAPK/ERK and cell cycle regulation, were significantly affected, with notable upregulation of BRAF, NRAS, CDK4, and MITF (log2FC = 2.86, p < 0.001). The transcription factor SOX10 and the cytokine IL-33, both previously implicated in melanoma progression, were consistently overexpressed. Additionally, NF1, a known RAS pathway inhibitor, was also upregulated. Isoform analysis revealed novel transcript variants, suggesting a complex layer of post-transcriptional regulation in COM. Many DEGs remained uncharacterized, and chromosomal distribution analysis highlighted potential genomic influences. Conclusions: Our findings provide new insights into the molecular landscape of COM, reinforcing its utility as a model for human melanoma. The identification of conserved oncogenic pathways and novel transcript variants opens avenues for further functional studies and the development of targeted therapies in both veterinary and human oncology. Full article

DNA and RNA nucleotide sequences are ubiquitous in all biological cells, serving as both a comprehensive library of capabilities for the cells and as an impressive regulatory system to control cellular function. The multi-alignment framework (MAF) provided in this study offers a user-friendly platform for sequence alignment and quantification. It is adaptable to various research needs and can incorporate different tools and parameters for in-depth analysis, especially in low read rate scenarios. This framework can be used to compare results from different alignment programs and algorithms on the same dataset, allowing for a comprehensive analysis of subtle to significant differences. This concept is demonstrated in a small RNA case study. MAF is specifically designed for the Linux platform, commonly used in bioinformatics. Its script structure streamlines processing steps, saving time when repeating procedures with various datasets. While the focus is on microRNA analysis, the templates provided can be adapted for all transcriptomic and genomic analyses. The template structure allows for flexible integration of pre- and post-processing steps. MicroRNA analysis indicates that STAR and Bowtie2 alignment programs are more effective than BBMap. Combining STAR with the Salmon quantifier or, with some limitations, the Samtools quantification, appears to be the most reliable approach. This method is ideal for scientists who want to thoroughly analyze their alignment results to ensure quality. The detailed microRNA analysis demonstrates the quality of three alignment and two quantification methods, offering guidance on assessing result quality and reducing false positives. Full article

This paper presents a comparative analysis of performance for several antenna prototypes using a screen-printing process. This analysis was performed using various bow-tie antenna configurations, including single-band and multi-band antennas with linear or circular polarization over multiple operating frequency ranges. For antenna implementations, three different conductive inks and two resolutions of screen masks were tested. The performance of the fabricated prototypes has then been compared to the copper laser-etched antennas. This study revealed that with the proper selection of ink thinness, screen-printed bow-tie antennas achieve similar performances to copper laser-etched bow-tie antennas up to 6 GHz, even for linearly polarized and circularly polarized antennas. However, the printing resolution should be improved by reducing the ink thickness for bow-tie antennas at higher operating frequencies. The measurement results show a successful agreement after improving the printing resolution of the fabricated 5.8 GHz and 15 GHz bi-band bow-tie antennas. Full article

For gene expression analysis in complex microbiomes, utilizing both metagenomic and metatranscriptomic reads from the same sample enables advanced functional analysis. Due to their diversity, metagenomic contigs are often used as reference sequences instead of complete genomes. However, studies optimizing mapping strategies for both read types remain limited. In addition, although transcripts per million (TPM) is commonly used for normalization, few studies have evaluated the influence of ribosomal RNA (rRNA) in metatranscriptomic reads. This study compared Burrows–Wheeler Aligner–Maximal Exact Match (BWA-MEM) and Bowtie2 as mapping tools for metagenomic contigs. Even after optimizing Bowtie2 parameters, BWA-MEM showed higher efficiency in mapping both metagenomic and metatranscriptomic reads. Further analysis revealed that rRNA sequences contaminate predicted protein-coding regions in metagenomic contigs. When comparing TPM values across samples, contamination by rRNA led to an overestimation of TPM changes. This effect was more pronounced when the difference in rRNA content between samples was larger. These findings suggest that metatranscriptomic reads mapped to rRNA should be excluded before TPM calculations. This study highlights key factors influencing read mapping and quantification in gene expression analysis of complex microbiomes. The findings provide insights for improving analytical accuracy and advancing functional studies using both metagenomic and metatranscriptomic data. Full article

To solve the problems of numerous influencing factors, such as the high uncertainty and leakage risk of gas production pipelines in high-sulfur gas fields, a dynamic analysis of a gas production pipeline’s leakage risk using a dynamic Bayesian network is proposed. By means of Bow-tie model analysis, the primary risk sources of gas pipeline leakage and different accidents are summarized. A temporal dimension was introduced to construct a dynamic Bayesian network model, utilizing the Leaky noisy-OR gate model to rectify and compute conditional probability, thereby facilitating dynamic risk prediction of gas pipeline leakage. Taking the first section of the pipeline of a municipal gas collection station as an example, with the help of GeNIe 4.0 Academic software, the influence degree of each basic event on pipeline gas leakage was revealed. The change curve of gas leakage probability over time was drawn, and the occurrence probability of potential consequences of accidents was computed. The results indicate that the status of flanges, valves, and pipelines are key factors in determining the occurrence of gas leakage accidents, and six risk sources, including medium corrosion in gas leakage accidents, were determined, with these having practical conspicuousness for strengthening the leakage protection of gas pipelines and providing proper support for the formulation of relevant safety measures. Full article