Exploration and Setup of Power Delivery System Attacks

Especially with the rise of AI/ML, graphics processing units (GPUs) are becoming increasingly important in personal and enterprise computing. As a result, GPU hardware and software security has never been more important. This paper will focus on the hardware security of the NVIDIA Jetson Nano’s GPU. Because high clock frequency has been known to induce faults in computer systems, this paper will serve as a guide supplement explaining how to overclock the NVIDIA Jetson Nano’s CPU and GPU. This will provide an attack environment for future security researchers. The viability of future NVIDIA Jetson Nano hardware security research will be addressed. Finally, this report will include a recommendation for a discrete graphics card to purchase, providing another avenue for GPU hardware security research

Effects of Drynariae Rhizoma Total Flavonoids on Smad1 and Smad5 mRNA Expression in Osteoporotic Rats

Abstract: This study aimed to investigate effects of the total flavonoids in Drynariae Rhizoma on the Smad1 and Smad5 mRNA expression in ovariectomized rats. A total of 60 SD rats were divided into the normal, blank control, and premarin-treated groups as well as three Drynariae Rhizoma total flavonoid-treated groups (with n = 10 per group). The flavonoid-treated groups received high, moderate, and low doses of Drynariae Rhizoma. All rats were ovariectomized, except for those in the normal group. The normal and blank control groups were fed with standard feed for 24 weeks. The flavonoid-treated groups were ovariectomized at 12 weeks and fed with Drynariae Rhizoma in three different concentrations for the remaining 12 weeks. The premarin-treated group was similarly ovariectomized at 12 weeks but fed with premarin for the remaining 12 weeks. All rats were sacrificed, and their right femur bones were collected for detecting Smad1 and Smad5. The Smad1 and Smad5 expression of the blank control group was 40% and 59.5%, respectively, of the normal levels (P < 0.05 for both). By contrast, all Smad1 and Smad5 expression was significantly increased by Drynariae Rhizoma treatment, regardless of the dose, as compared with the blank control group (P < 0.05). Smad5 gene expression was significantly increased by the moderate dose of Drynariae Rhizoma (P < 0.01). The total flavonoids in Drynariae Rhizoma promoted Smad1 and Smad5 gene expression in the bone marrow of ovariectomized rats, particularly the moderate dose of Drynariae Rhizoma total flavonoids

PDNPulse: Sensing PCB Anomaly with the Intrinsic Power Delivery Network

The ubiquitous presence of printed circuit boards (PCBs) in modern electronic systems and embedded devices makes their integrity a top security concern. To take advantage of the economies of scale, today's PCB design and manufacturing are often performed by suppliers around the globe, exposing them to many security vulnerabilities along the segmented PCB supply chain. Moreover, the increasing complexity of the PCB designs also leaves ample room for numerous sneaky board-level attacks to be implemented throughout each stage of a PCB's lifetime, threatening many electronic devices. In this paper, we propose PDNPulse, a power delivery network (PDN) based PCB anomaly detection framework that can identify a wide spectrum of board-level malicious modifications. PDNPulse leverages the fact that the PDN's characteristics are inevitably affected by modifications to the PCB, no matter how minuscule. By detecting changes to the PDN impedance profile and using the Frechet distance-based anomaly detection algorithms, PDNPulse can robustly and successfully discern malicious modifications across the system. Using PDNPulse, we conduct extensive experiments on seven commercial-off-the-shelf PCBs, covering different design scales, different threat models, and seven different anomaly types. The results confirm that PDNPulse creates an effective security asymmetry between attack and defense

Discussion on tunnel bottom excavation method and lining deformation monitoring scheme of operating tunnel

In order to analyze the degree of disturbance to the lining by the full-width excavation and reinforcement of the tunnel bottom, and determine the length of the excavation unit, and the excavation interval and improve the monitoring measurement plan. Through field observation and numerical simulation comparative analysis and verification, it is determined that the deformation of the lining equals mainly the deformation of the side wall, the influence range of the settlement of the side wall is greater than that of the convergence, the maximum value of the maximum principal stress of the lining is mainly distributed from the side wall of the excavation area to the arch line, the side wall of the excavation area produces shear yield when the length of the excavation unit reaches 5m, and the influence area will cross influence when the excavation interval is less than twice the influence area. Based on the distribution law of lining deformation, principal stress and elastoplastic area, it is recommended that the length of the excavation unit should be less than 5m, the excavation interval should be greater than twice the influence range of the side wall settlement; and the monitoring section should be arranged at the central section of the excavation area, the interval of the monitoring section should be determined according to the location of the excavation unit, the monitoring scope may not extend to the unreinforced section, and the settlement of the side walls should be increased

Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation

Click-Through Rate (CTR) prediction is a fundamental technique in recommendation and advertising systems. Recent studies have shown that implementing multi-scenario recommendations contributes to strengthening information sharing and improving overall performance. However, existing multi-scenario models only consider coarse-grained explicit scenario modeling that depends on pre-defined scenario identification from manual prior rules, which is biased and sub-optimal. To address these limitations, we propose a Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendations (HierRec), which perceives implicit patterns adaptively and conducts explicit and implicit scenario modeling jointly. In particular, HierRec designs a basic scenario-oriented module based on the dynamic weight to capture scenario-specific information. Then the hierarchical explicit and implicit scenario-aware modules are proposed to model hybrid-grained scenario information. The multi-head implicit modeling design contributes to perceiving distinctive patterns from different perspectives. Our experiments on two public datasets and real-world industrial applications on a mainstream online advertising platform demonstrate that our HierRec outperforms existing models significantly

How Can Recommender Systems Benefit from Large Language Models: A Survey

Recommender systems (RS) play important roles to match users' information needs for Internet applications. In natural language processing (NLP) domains, large language model (LLM) has shown astonishing emergent abilities (e.g., instruction following, reasoning), thus giving rise to the promising research direction of adapting LLM to RS for performance enhancements and user experience improvements. In this paper, we conduct a comprehensive survey on this research direction from an application-oriented view. We first summarize existing research works from two orthogonal perspectives: where and how to adapt LLM to RS. For the "WHERE" question, we discuss the roles that LLM could play in different stages of the recommendation pipeline, i.e., feature engineering, feature encoder, scoring/ranking function, and pipeline controller. For the "HOW" question, we investigate the training and inference strategies, resulting in two fine-grained taxonomy criteria, i.e., whether to tune LLMs or not, and whether to involve conventional recommendation model (CRM) for inference. Detailed analysis and general development trajectories are provided for both questions, respectively. Then, we highlight key challenges in adapting LLM to RS from three aspects, i.e., efficiency, effectiveness, and ethics. Finally, we summarize the survey and discuss the future prospects. We also actively maintain a GitHub repository for papers and other related resources in this rising direction: https://github.com/CHIANGEL/Awesome-LLM-for-RecSys.Comment: 15 pages; 3 figures; summarization table in appendi

Identification of differentially expressed miRNAs in chicken lung and trachea with avian influenza virus infection by a deep sequencing approach

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play critical roles in a wide spectrum of biological processes and have been shown to be important effectors in the intricate host-pathogen interaction networks. Avian influenza virus (AIV) not only causes significant economic losses in poultry production, but also is of great concern to human health. The objective of this study was to identify miRNAs associated with AIV infections in chickens.</p> <p>Results</p> <p>Total RNAs were isolated from lung and trachea of low pathogenic H5N3 infected and non-infected SPF chickens at 4 days post-infection. A total of 278,398 and 340,726 reads were obtained from lung and trachea, respectively. And 377 miRNAs were detected in lungs and 149 in tracheae from a total of 474 distinct chicken miRNAs available at the miRBase, respectively. Seventy-three and thirty-six miRNAs were differentially expressed between infected and non-infected chickens in lungs and tracheae, respectively. There were more miRNAs highly expressed in non-infected tissues than in infected tissues. Interestingly, some of these differentially expressed miRNAs, including miR-146, have been previously reported to be associated with immune-related signal pathways in mammals.</p> <p>Conclusion</p> <p>To our knowledge, this is the first study on miRNA gene expression in AIV infected chickens using a deep sequencing approach. During AIV infection, many host miRNAs were differentially regulated, supporting the hypothesis that certain miRNAs might be essential in the host-pathogen interactions. Elucidation of the mechanism of these miRNAs on the regulation of host-AIV interaction will lead to the development of new control strategies to prevent or treat AIV infections in poultry.</p

GASZ Is Essential for Male Meiosis and Suppression of Retrotransposon Expression in the Male Germline

Nuage are amorphous ultrastructural granules in the cytoplasm of male germ cells as divergent as Drosophila, Xenopus, and Homo sapiens. Most nuage are cytoplasmic ribonucleoprotein structures implicated in diverse RNA metabolism including the regulation of PIWI-interacting RNA (piRNA) synthesis by the PIWI family (i.e., MILI, MIWI2, and MIWI). MILI is prominent in embryonic and early post-natal germ cells in nuage also called germinal granules that are often associated with mitochondria and called intermitochondrial cement. We find that GASZ (Germ cell protein with Ankyrin repeats, Sterile alpha motif, and leucine Zipper) co-localizes with MILI in intermitochondrial cement. Knockout of Gasz in mice results in a dramatic downregulation of MILI, and phenocopies the zygotene–pachytene spermatocyte block and male sterility defect observed in MILI null mice. In Gasz null testes, we observe increased hypomethylation and expression of retrotransposons similar to MILI null testes. We also find global shifts in the small RNAome, including down-regulation of repeat-associated, known, and novel piRNAs. These studies provide the first evidence for an essential structural role for GASZ in male fertility and epigenetic and post-transcriptional silencing of retrotransposons by stabilizing MILI in nuage

Discovery of Novel MicroRNAs in Female Reproductive Tract Using Next Generation Sequencing

MicroRNAs (miRNAs) are small non-coding RNAs that mediate post-transcriptional gene silencing. Over 700 human miRNAs have currently been identified, many of which are mutated or de-regulated in diseases. Here we report the identification of novel miRNAs through deep sequencing the small RNAome (<30 nt) of over 100 tissues or cell lines derived from human female reproductive organs in both normal and disease states. These specimens include ovarian epithelium and ovarian cancer, endometrium and endometriomas, and uterine myometrium and uterine smooth muscle tumors. Sequence reads not aligning with known miRNAs were each mapped to the genome to extract flanking sequences. These extended sequence regions were folded in silico to identify RNA hairpins. Sequences demonstrating the ability to form a stem loop structure with low minimum free energy (<−25 kcal) and predicted Drosha and Dicer cut sites yielding a mature miRNA sequence matching the actual sequence were considered putative novel miRNAs. Additional confidence was achieved when putative novel hairpins assembled a collection of sequences highly similar to the putative mature miRNA but with heterogeneous 3′-ends. A confirmed novel miRNA fulfilled these criteria and had its “star” sequence in our collection. We found 7 distinct confirmed novel miRNAs, and 51 additional novel miRNAs that represented highly confident predictions but without detectable star sequences. Our novel miRNAs were detectable in multiple samples, but expressed at low levels and not specific to any one tissue or cell type. To date, this study represents the largest set of samples analyzed together to identify novel miRNAs