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Triticum militinae (2n = 4X = 28, A t A t GG), belonging to the secondary gene pool of wheat, is known to carry resistance to many diseases. Though some disease resistance genes were reported from T. timopheevii, the closest wild relative of T. militinae, there are no reports from T. militinae. Twenty-one T. militinae Derivatives (TMD lines) developed at the Division of Genetics, IARI, New Delhi, were evaluated for leaf and stripe rusts at seedling and adult plant stages. Eight TMD lines (6–4, 6–5, 11–6, 12–4, 12–8, 12–12, 13–7 and 13–9) showed seedling resistance to both leaf and stripe rusts while six TMD lines (7–5, 7–6, 11–5, 13–1, 13–3 and 13–4) showed seedling resistance to leaf rust but adult plant resistance to stripe rust and three TMD lines (9–1, 9–2 and 15) showed seedling resistance to leaf rust but susceptibility to stripe rust. Three TMD lines (2–7, 2–8 and 6–1) with adult plant resistance to leaf and stripe rusts were found to carry the known gene Lr34/Yr18 . Ten TMD lines (7–5, 7–6, 9–1, 9–2, 11–5, 11–6, 12–12, 12–4, 12–8, and 15) with seedling resistance to leaf rust, showing absence of known genes Lr18 and Lr50 with linked markers requires further confirmation by the test of allelism studies . As not a single stripe rust resistance gene has been reported from T. militinae or its close relative T. timpopheevii , all the 8 TMD lines (6–4, 6–5, 11–6,12–4, 12–8, 12–12, 13–7 and 13–9) identified of carrying seedling resistance to stripe rust and 3 TMD lines (13–1, 13–3 and 13–4) identified of carrying adult plant resistance to stripe rust are expected to carry unknown genes. Also, all the TMD lines were found to be cytologically stable and thus can be used in inheritance and mapping studies.

Reversible data hiding (RDH) techniques recover the original cover image after data extraction. Thus, they have gained popularity in e-healthcare, law forensics, and military applications. However, histogram shifting using a reversible data embedding technique suffers from low embedding capacity and high variability. This work proposes a technique in which the distribution obtained from the cover image determines the pixels that attain a peak or zero distribution. Afterward, adjacent histogram bins of the peak point are shifted, and data embedding is performed using the least significant bit (LSB) technique in the peak pixels. Furthermore, the robustness and embedding capacity are improved using the proposed dynamic block-wise reversible embedding strategy. Besides, the secret data are encrypted before embedding to further strengthen security. The experimental evaluation suggests that the proposed work attains superior stego images with a peak signal-to-noise ratio (PSNR) of more than 58 dB for 0.9 bits per pixel (BPP). Additionally, the results of the two-sample t-test and the Kolmogorov–Smirnov test reveal that the proposed work is resistant to attacks.

The rapid proliferation of misinformation across digital platforms has highlighted the critical need for advanced fake news detection mechanisms. Traditional methods primarily rely on textual analysis, often neglecting the structural patterns of news dissemination, which play a crucial role in determining credibility. To address this limitation, this study proposes a Dual-Stream Graph-Augmented Transformer Model, integrating BERT for deep textual representation and Graph Neural Networks (GNNs) to model the propagation structure of misinformation. The objective is to enhance fake news detection by leveraging both linguistic and network-based features. The proposed method employs Graph Attention Networks (GAT) and Graph Transformers to extract contextual relationships, while an attention-based fusion mechanism effectively integrates textual and graph embeddings for classification. The model is implemented using PyTorch and Hugging Face Transformers, with experiments conducted on the FakeNewsNet dataset, which includes news articles, user interactions, and source metadata. Evaluation metrics such as accuracy, precision, recall, F1-score, and AUC-ROC indicate superior performance, with an accuracy of 99%, outperforming baseline models such as Bi-LSTM and RoBERTa-GCN. The study concludes that incorporating graph-based propagation features significantly improves fake news detection, providing a robust, scalable, and context-aware solution. Future enhancements will focus on refining credibility assessment mechanisms and extending the model to support multilingual and multimodal misinformation detection across diverse digital platforms.

We examine the association between cost of equity and internal control weakness (ICW) for firms that filed first-time Section 404 reports with the SEC. Using several proxies, we find higher implied cost of equity associated with ICW firms than for a control sample of firms that disclosed no ICW. However, the higher cost of equity associated with ICW disappears after controlling for primitive firm characteristics and for analyst forecast bias. Overall, we find that, on average, ICWs are not directly associated with higher cost of equity.

The global production of information continuously increases in quantity and variety. However, the tools and technologies developed to handle such large volumes of data have not adequately met the security and privacy requirements. Existing cloud security systems, often managed by a trusted third party, are susceptible to various security risks. To address these challenges and ensure the protection of personal information, blockchain technology emerges as a crucial solution with substantial potential. This research uses the blockchain-powered attribute-aware encryption method to establish a real-time secure communication approach over the cloud. By employing attribute-based encryption technology, data owners can implement fine-grained search permissions for data users. The proposed solution incorporates accessible encryption technology to enable secure access to encrypted data and facilitate keyword searches on the blockchain. This study provides a functional comparison of recently developed attribute-based encryption algorithms. The access control strategy comprises two access tree types and a linear secret-sharing system, serving as the main components. The elliptic curve’s base field was set to 512b, and the bilinear pairing parameter type used was Type-A. This approach involves storing keywords on a remote server and encrypting them using attribute-based encryption. Furthermore, the encrypted data blockchain and the corresponding ciphertext are stored in the blockchain. Numerical experiments were conducted to evaluate the system’s key generation, trapdoor building, and keyword retrieval capabilities.

Group activity recognition requires a holistic understanding of individual actions, their spatial relationships, and the surrounding environment. Traditional methods that focus solely on isolated movements often fail to capture the complex inter-player and scene-level dependencies inherent in sports and crowd scenarios. In this research work, a model for group activity recognition is developed. The proposed model combines various contextual features through the integration of poses of individual actors in the scene with the pose-aligned spatial scene context for relational reasoning. Pose features of individual actors are extracted using mmPose, while the scene-level context is encoded through pose-conditioned spatial feature aggregation rather than explicit semantic segmentation. These pose and scene context features extracted are combined and used to construct Actor Relation Graphs (ARGs) using Zero Normalized Cross Correlation (ZNCC) which improves robustness to appearance and variations in illumination. Further, Graph Convolutional Networks (GCNs) are modelled using relationships between individual actors in a scene and their group activities. The proposed framework explicitly combines pose-level and scene-level contextual features into a single relational graph, in contrast to previous ARG-GCN approaches that mainly rely on appearance features. The model is evaluated on two benchmark datasets: the Collective Activity dataset (CAD) and the Volleyball dataset (VD). The model exhibits classification accuracies of 95.02% and 94.81% on CAD and VD, respectively. On a TITAN-XP GPU, the average time per video clip with 41 frames is approximately 0.2 s. The results show that the combination of pose and scene contexts features enhances graph-based relational learning and improves recognition accuracy.

The Advisory Committee on the Auditing Profession (ACAP), formed by the U.S. Department of the Treasury, has recommended that all public companies be required to have shareholder ratification of auditor selection. Using data from 1,382 firms for the year ending December 31, 2006, we find that audit fees are higher in firms with shareholder voting on auditor ratification. We also find that firms that started having a shareholder vote pay higher fees than firms that stopped having a shareholder vote. In the second part of our study, we find that in firms with shareholder voting on auditor selection (1) subsequent restatements are less likely and (2) abnormal accruals are lower. Our findings are consistent with the experimental results in Mayhew and Pike (2004), and provide empirical grounding for the debate about mandating shareholder voting on auditor selection.

Issues related to low-balling of initial year audit fees and the resultant impact on audit quality have received significant attention from regulators in many countries. Using 9,684 observations from China during the years 2002–2011, we find that there is a significant initial year audit fee discount following an audit firm change when both of the signing audit partners are different from the prior year. The evidence is mixed if one or both of the signing partners from the prior year also moves with the client to the new audit firm. We find evidence of audit fee discounting in our analysis of fee levels, but not in our analysis of changes in audit fees from the prior year. Sanctions for problem audits and greater earnings management are more likely when there is an audit firm change that involves two new signing partners together with initial year audit fee discounting.

Hybrid development is one of the most promising strategies for boosting crop yields. Parental lines used to create hybrids must have good per se performance and disease resistance for developing superior hybrids. Indian wheat line HD3209 was developed by introducing the rust resistance genes Lr19/Sr25 into the background of popular wheat variety HD2932. The wheat line HD3209 carrying Lr19/Sr25 has been successfully and rapidly converted to the CMS line A-HD3209, with 96.01% background genome recovery, based on selection for agro-morphological traits, rust resistance, pollen sterility, and foreground and background analyses utilizing SSR markers. The converted CMS line A-HD3209 was completely sterile and nearly identical to the recurrent parent HD3209. Based on high per se performance and rust resistance, the study concludes that the derived CMS line A-HD3209 is promising and can be employed successfully in hybrid development.

Section 404 of the Sarbanes-Oxley Act and Auditing Standard No. 2 (PCAOB 2004) require management and the auditor to report on internal controls over financial reporting. Section 404 is arguably the most controversial element of SOX, and much of the debate around the costs of implementing section 404 has focused on auditors' fees (Ernst & Young 2005). In this paper, we examine the association between audit fees and internal control disclosures made pursuant to section 404. Our sample includes 660 manufacturing firms that have a December 31, 2004 fiscal year-end and filed the section 404 report by May 15, 2005. We find that the mean (median) audit fees for the firms in our sample for fiscal 2004 is 86 (128) percent higher than the corresponding fees for fiscal 2003. Audit fees for fiscal 2004 are 43 percent higher for clients with a material weakness disclosure compared to clients without such disclosure; however, audit fees for fiscal 2003 are not associated with an internal control material weakness disclosure (in the 10-K filed following fiscal 2004). We also find that the association between audit fees and the presence of a material weakness disclosure does not vary depending on the type of material weakness (systemic or non-systemic).