Miracle-dz/UniFAR-FTUs huggingface dataset:
Casein kinase 2 attenuates brain injury induced by intracerebral hemorrhage via regulation of NR2B phosphorylation

Objective Intracerebral hemorrhage (ICH) is a common cerebrovascular disease with high incidence, disability, and mortality. Casein kinase 2 (CK2) is a serine/threonine kinase with hundreds of identified substrates and plays an important role in many diseases. This study aimed to explore whether CK2 plays protective roles in ICH-induced neuronal apoptosis, inflammation, and oxidative stress through regulation NR2B phosphorylation. Methods CK2 expression level of brain tissues taken from ICH patients was determined by immunoblotting. Neurons from embryonic rat and astrocytes from newborn rats were cultured and treated by Hemoglobin chloride (Hemin). The proliferation of astrocytes, the apoptosis and oxidative stress of neurons and the inflammatory factors of astrocytes were detected. CK2 expression was determined in ICH model rats. The effects of CK2 overexpression plasmid (pc-CK2) on neurobehavioral defects and brain water content in ICH rats were observed. Results CK2 expression in ICH patients was down-regulated. Overexpression of CK2 promoted the astrocyte proliferation, inhibited neuronal apoptosis, and reduced astrocyte-mediated inflammation. N-methyl-D-aspartate receptor 2B (NR2B) reversed the effects of pc-CK2 on neurons and astrocytes. CK2 phosphorylated NR2B at the S1480 site, down-regulated the expression of NR2B and interfered with the interaction between NR2B and postsynaptic density protein 95 (PSD95). In vivo experiments showed that the expression of CK2 decreased and the expression of NR2B increased in ICH rats. Furthermore, pc-CK2 attenuated neurobehavioral defects, brain water content and neuronal damage in ICH rats. Conclusion CK2 phosphorylated NR2B, down-regulated the expression of NR2B, interfered with the interaction between NR2B and PSD95, alleviated inflammatory reactions, inhibited neuronal apoptosis and oxidative stress after ICH. CK2 and NR2B may be new potential therapeutic targets for the treatment of ICH. However, the limitation of this study is that we only investigated the regulation of NR2B by CK2.
Dual‐band antenna with improved gain for WLAN and ISM applications

In this Letter, a dual-band antenna with an improved gain is proposed. The structure features 9.7 and 10.4 dBi gain within 2.4 GHz to 2.5 GHz and 5 GHz to 6 GHz bands, respectively. This makes it suitable for WLAN and ISM applications. The structure comprises an asymmetrical pair of radiators and slots suspended over a reflector. The antenna is optimised in a two-stage process using a trust-region-based gradient search algorithm. The design is compared to the state-of-the-art radiators reported in the literature. The numerical results are validated through measurements of the fabricated antenna prototype.
The EP energy function and minimization schemes

j fj(x)τj) (3) The ti(x) must be positive but they do not have to be proper densities. However p(x), which is not being approximated, does need to be a proper density. It doesn’t have to be the actual “prior” in the problem; you could choose it to be 1, for example, if x has finite domain. p(x) does not have to be in an exponential family, but it will make your life easier if it is. The EP (dual) energy function is min ν max λ (n− 1) log ∫
Virulence Factors and Antimicrobial Resistance Profile of Escherichia Coli Isolated from Laying Hens in Italy

Simple Summary Colibacillosis is a disease of great importance in the poultry industry, but many of its features and characteristics still need to be identified. This survey on avian Escherichia coli investigated the correlation between the presence of specific virulence genes, antimicrobial resistance features and serogroups. The results highlighted that half of the tested strains were avian pathogenic Escherichia coli (APEC). Moreover, a high prevalence of two specific serogroups was detected, namely, O2 and O88. Finally, antimicrobial resistance was lower than in other studies. Further investigations of APEC strains’ antimicrobial resistance features would support farmers, veterinarians and local authorities in planning actions for a better control of colibacillosis in poultry production. Abstract Colibacillosis is the most common bacterial disease in the poultry industry. The isolation of Escherichia coli (E. coli) strains with multiple resistance to various classes of antimicrobials has been increasing in recent years. In this study, antimicrobial resistance features, serotyping and the presence of avian pathogenic Escherichia coli (APEC) virulence genes were investigated on a total of 71 E. coli strains isolated during outbreaks of colibacillosis in laying hens. The correlation between these features was evaluated. The most frequently isolated serogroups were O2 and O88. Resistance was often detected with nalidixic acid (49%) and ampicillin (38%), while all strains were sensitive to ceftiofur and florfenicol. Overall, 25% of the isolates showed resistance to at least three or more antimicrobial classes (multidrug-resistant strains), and 56% of the isolates were defined as APEC strains (due to the presence of at least five virulence genes). Correlation between the different parameters (virulence genes, serogroup and antimicrobial resistance) did not reveal relevant associations. The comparison of the obtained results with those of similar studies highlighted the importance of continuous monitoring in order to have a better understanding of colibacillosis. An evaluation of the national epidemiological situation would allow, especially with regard to antimicrobial resistance, to focus on the right measures in order to prioritize the available resources for effective disease control.
Motivations of User Engagement in eWOM of Chinese Microblog Motivations of User Engagement in eWOM of Chinese Microblog

This study examined the motivations of user engagement in electronic word-of-mouth behavior through a netnography. The sample includes more than 2,000 posts from the Chinese microblog-Sina Weibo and 20 follow-up interviews about film reviews. 5 types of motivations were examined, including egoistic motivations, motivations for the reward, reciprocal motivations, altruistic motivations, and motivations in the sense of community. Results confirmed the effect of egoistic motivations, reciprocal motivations, and motivations in the sense of community for the increasing volume of eWOM. However, motivations for the reward and altruistic motivations were found less powerful. Hence, the reward was found to decrease the generation of eWOM.The findings would give implications for marketers to plan and leverage eWoM and help scholars understand eWoM in a microblog context.
Two-stage framework for corner case stimuli generation Using Transformer and Reinforcement Learning

- Constrained-Random Verification (CRV) is a common method to achieve full function coverage by generating test cases randomly with some meaningful constrained setting. Some corner cases verification relies on a deep understanding of the DUT and component design from experts. The constrained creation and tuning are usually the time-consuming tasks. Furthermore, some of the corner cases are the “difficult” corner cases, which means the targets are hard to be hit even if experts tune the constraints many times. We deal with the difficult corner case verification of FIFO full condition in this paper. The two-stage process was introduced. The framework combines the concept of CRV and machine learning, including attention mechanism and Reinforcement Learning (RL). Our experiment results demonstrate that we improve the hit rate up to 380x of corner case for FIFO verification.
METHODS OF ALGEBRAIC GEOMETRY IN THE THEORY OF NON-LINEAR EQUATIONS

CONTENTSIntroduction § 1. The Akhiezer function and the Zakharov-Shabat equations § 2. Commutative rings of differential operators § 3. The two-dimensional Schrodinger operator and the algebras associated with it § 4. The problem of multi-dimensional -algebraic operators Appendix 1. The Hamiltonian formalism in equations of Lax and Novikov types Appendix 2. Elliptic and rational solutions of the K-dV equations and systems of many particles Concluding Remarks References
A Low Maintenance Infrastructure to Jumpstart CPU Regression and Performance Correlation

- Surge is a low-maintenance RTL jumpstart mechanism that works on any architectural boundary for CPU simulation. Surge's design makes it resilient to frequent RTL rewrites and design changes. It has a small code base to maintain, supports multicore, and is compatible with all soft IP configurations. Legacy RTL jumpstart mechanisms relied on a specialized SVTB module with a detailed mapping of every architectural state to its microarchitectural (µArch) counterpart. The legacy jumpstart module must understand every relevant signal path, register shadow copy, and array configuration; this results in monolithic code that frequently breaks due to µArch changes. Surge utilizes the CPU's functional high-level model and legacy CPU power state feature to abstract out the µArch dependencies. Under Surge, any test will first run very fast under E-core’s [1] (formerly known as Intel Atom) functional model to the point of interest then seamlessly migrate to RTL simulation. As a result, Intel E-core validation skips the RTL simulation cycles spent on test setup and E-core performance team can more reliably complete performance correlation simulation.
Maximizing Formal ROI through Accelerated IP Verification Sign-off

- Over the past few years, formal verification (FV) has become an essential piece of our verification sign-off methodology. We have successfully used FV to sign off several critical design blocks with zero escapes and have also set up a mature FV sign-off flow that is well integrated into our mainstream verification process. However, despite all the great return on investment (ROI) generated on each block signed off using FV, the overall impact to previous projects was somehow limited due to the scope of FV adoption. To unleash the full power of FV, we believe that 1) FV should be considered as a primary method to achieve block-level verification sign-off and 2) FV should also be leveraged at the system level to uncover "superbugs" which are beyond the reach of the traditional simulation approach. This idea is supported by our management team. As a result, we started to deploy FV on a much larger scale to accelerate the verification sign-off of a brand-new IP. This paper shares our recent experience on how we upscale FV usage to maximize formal ROI.
Frequency domain decomposition‐based multisensor data fusion for assessment of progressive damage in structures

In this paper, we focused on the development and verification of a solid and robust framework for structural condition assessment of real‐life structures using measured vibration responses, with the presence of multiple progressive damages occurring within the inspected structures. A self‐tuning learning method for structural condition assessment was proposed. Damage sensitive features were extracted using a frequency domain decomposition (FDD) approach to fuse all the measured responses, followed by random projection algorithm for dimensionality reduction. An automatic parameter selection method called Appropriate Distance to the Enclosing Surface (ADES) was used for tuning the classifier parameter. The effect of operational conditions on the robustness of the proposed method was also investigated, and it was realized that application of FDD to extract damage sensitive feature reduces the variation in the results. Promising results in the assessment of damage were obtained based on two comprehensive case studies, which included single and multiple damage scenarios. The contributions of the work are threefold. First, through two comprehensive case studies, we demonstrate that the frequency‐based feature from a single sensor might not be adequate enough to detect the progress of damage, even if the sensor is in the vicinity of damage. Second, we show that data fusion using FDD can reliably assess the severity of damage, and finally, we propose a new automated approach for tuning the classifier parameter.
A Technique for Skew Correction and Text Localization in Natural Scene Images

-The image processing is the technique which is used to process the digital information. The text extraction is the major challenge due to robust image information. The images which are natural scene has not the equal contrast and also has the skewness due to which it is difficult to extract the text from the image. In this research work, the PCA algorithm is applied for the extraction and also threshold based technique is applied for the skew removal. The proposed algorithm is implemented in MATLAB and results in terms of certain parameters
Automatic Investigation of Power Inefficiency

- This work presents an automatic method to identify and suggest to designers missed power optimization opportunities by finding useless activities in the design during simulation, where useless activities are defined as toggling events that do not contribute to a given task. The proposed method leverages functional regression test suites and coverage collection mechanisms, which are both common in modern verification methodologies hence the method can be seamlessly integrated into existing environments. We present the evaluation of this method on a commercial low-power SoC design with details on the achieved results which include two power-inefficiency issues
Mixed-abstraction Modeling Approach with Fault Injection for Hardware-Firmware Co-design and Functional Co-verification of an Automotive Airbag System on Chip Product

—In modern automotive and consumer electronic industry, the number of functionalities and complexity is increasing. Additionally, there is pressure to produce reduced time-to-market and first-time-right design products, which pose great challenges for all chip designers. An effective utilization of modeling and simulation facilitates the design process so that these challenges can be met. This paper proposes a mixed-abstraction modeling strategy for chip top-level functional verification which significantly improves the simulation performance but still achieves high accuracy for a complex hardware-firmware co-verification. The digital content of the chip (consists of digital logic core and digital functional modules) is implemented with RTL format while the analog content of the chip is modeled using VHDL behavior modeling with support of real signal. Hence, a chip top-level simulation (hardware-firmware co-simulation) is achievable with event-based simulation technology. Additionally, the mixed-abstraction modeling strategy and method saves a considerable amount of effort in modeling, thus helps the project to gain time. For demonstration, a complete airbag system on chip (SoC) product was successfully modeled using this modeling approach. At an early stage of the design phase, the model is used in the chip top-level functional verification, and in parallel, supports optimization as well as errors debugging of hardware and firmware design activities.
Design and Performance analysis of Adaptive-XY over N-XY and DO Routing on FPGA Platform

— Network on Chip (NoC) is an attractive alternative to bus-based technology in communication networks. The research Article proposes the NoC-based Router architectures with adaptive routing algorithm. The Normal-XY (N-XY) and Dimension order (DO) Routing are also designed for performance analysis purpose. It consists of the input register, priority encoder, packet formation, and different routing algorithms. The input registers store the data information from IP Cores via a Network interface (NI); then the priority encoder provides the select line to the corresponding input. Packet formation is done based on the packets received through the encoder. The Adaptive-XY (A-XY) Routing algorithm is based on the adaptive nature of XY Flow direction. The two dimensions are in X, and Y flow with less number of routing nodes are processed, and packets are assists to the destination with less congestion. The performance analysis of proposed router and 2X2 Mesh NOC with Adaptive –XY Routing algorithm over Normal-XY (N-XY) and Dimension order (DO) Routing is improved with hardware constraints which include Chip area, Operating Frequency, and Power consumption on FPGA platform. Factors for further improvements have been suggested.
IEEE 1801 Assisted Custom IP Development and Low Power Checks Using Cadence Virtuoso Power Manager

— Defining and verifying power requirements across analog and digital boundaries involves manual task. The power intent defined at concept level must be considered for development at the IP block level, no matter if these are analog or digital blocks. This makes defining and checking of power intent across these analog and digital hierarchies complicated. Also, the power related checks stop at the analog block boundaries. In order to ease the design process, we applied a new methodology for defining and checking of power intent through nested analog and digital hierarchies. The approach depends on the IEEE 1801 format to define the power intent for both analog and digital sub-blocks.
Molecular Features in Lymphatic Metastases Reflect the Metastasis Mechanism of Lymph Nodes With Non-Small-Cell Lung Cancers

Lymphatic metastasis influences clinical treatment and prognosis of patients with non-small-cell lung cancer (NSCLC). There is an urgency to understand the molecular features and mechanisms of lymph node metastasis. We analyzed the molecular features on pairs of the primary tumor and lymphatic metastasis tissue samples from 15 NSCLC patients using targeted next-generation sequencing. The potential metastasis-related genes were screened from our cohort based on cancer cell fraction. After filtering with gene functions, candidate metastasis-related events were validated in the MSK cohort with Fisher’s exact test. The molecular signature and tumor mutational burden were similar in paired samples, and the average mutational concordance was 42.0% ± 28.9%. Its metastatic mechanism is potentially a linear progression based on the metastatic seeding theory. Furthermore, mutated ataxia telangiectasia mutated and Rad3-related (ATR) and tet methylcytosine dioxygenase 2 (TET2) genes were significantly enriched in lymphatic metastases (p ≤ 0.05). Alterations in these two genes could be considered metastasis-related driving events. Mutated ATR and TET2 might play an active role in the metastasis of lymph nodes with NSCLC. More case enrollment and long-term follow-up will further verify the clinical significance of these two genes.
Traditional Chinese Medicine in the Treatment of Chronic Kidney Diseases: Theories, Applications, and Mechanisms

Chronic kidney disease (CKD) is a common and progressive disease that has become a major public health problem on a global scale. Renal fibrosis is a common feature in the pathogenesis of CKD, which is mainly related to the excessive accumulation and deposition of extracellular matrix caused by various inflammatory factors. No ideal treatment has yet been established. In recent years, based on the traditional Chinese medicine (TCM) theory of CKD and its molecular mechanism, clinical evidence or experimental studies have confirmed that a variety of Chinese materia medica (CMM) and their effective components can delay the progress of CKD. TCM believes that the pathogenesis of CKD is the deficiency in the root and excess in the branch, and the deficiency and excess are always accompanied by the disease. The strategies of TCM in treating CKD are mainly based on invigorating Qi, tonifying the kidneys, promoting blood circulation, removing stasis, eliminating heat and dampness, removing turbidity, and eliminating edema, and these effects are multitargeted and multifunctional. This review attempts to summarize the theories and treatment strategies of TCM in the treatment of CKD and presents the efficacy and mechanisms of several CMMs supported by clinical evidence or experimental studies. In addition, the relationship between the macroscopic of TCM and the microscopic of modern medicine and the problems faced in further research were also discussed.
Molecular docking supported investigation of antioxidant, analgesic and diuretic effects of Costus speciosus rhizome

ABSTRACT. The aim of the current study was to analyze the polyphenols and determines the antioxidant, analgesic and diuretic properties of the methanolic extract of C.speciosus rhizome. DPPH and ferric reducing antioxidant power (FRAP) assays were used to determine the antioxidant activity. Acetic acid-induced writhing and formalin-induced licking experiments were used to assess the analgesic effect. The total phenolic, flavonoid and flavonol contents were found 51.73± 0.25 mg GAE/g dry weight, 3.41± 0.07mg QE/g dry weights and 44.19± 2.24 mg QE/g dry weight, respectively. The plant extract exhibited weak antioxidant activity in the DPPH and FRAP assays, with an IC50 value of 1699±62 μg/mL and an EC50 value of 125±2 μg/mL, respectively. The extract significantly reduced the number of writhes at both doses (200 and 400 mg/kg body weight) as compared to the control. The extract (400 mg/kg) also significantly reduced the percent inhibition of licking by 31.96 and 62.69% compared to the control in the early and late phase, respectively. Compared to the standard drug furosemide, the plant extract also showed a weak diuretic effect. The docking study supported the analgesic activity of rhizome extract. The potent analgesic activity of the plant extract justifies the traditional and medicinal aspects. KEY WORDS: Costus speciosus, Analgesic activity, Diuretic effect, Molecular docking Bull. Chem. Soc. Ethiop. 2022, 36(3), 627-640. DOI: https://dx.doi. org/10.4314/bcse.v36i3. 12