Miracle-dz/UniFAR-FTUs huggingface dataset:
Qige Huxin Formula Attenuates Isoprenaline-Induced Cardiac Fibrosis in Mice via Modulating Gut Microbiota and Protecting Intestinal Integrity

Background The composition and metabolic activities of gut microbiota are strongly interconnected with cardiac fibrosis (CF) and heart failure (HF). Qige Huxin formula (QHF), a traditional Chinese medicine (TCM) formulation originating from a classical Fangji Huangqi decoction, has been widely used to clinically treat HF for decades. However, it is still unclear whether QHF alleviates CF by modulating gut microbiota and intestinal integrity. Purpose This study aimed to investigate the cardioprotective effects of QHF in isoprenaline-induced CF through modulating gut microbiota and intestinal integrity. Methods Fifty mice were randomly divided into five groups after one week of acclimatization feeding: control group, model group, 2.56 g/kg/d group (low-dose QHF), 5.12 g/kg/d group (high-dose QHF), and meto group (15 mg/kg/d). The CF model was established by subcutaneously injecting the mice with isoprenaline (10 mg/kg/d for 14 days), followed by QHF treatment. The heart volume, cardiac weight index (CWI), serum myocardial enzymes, serum inflammatory cytokines, serum lipopolysaccharide, histopathology of the heart and colon tissues, ZO-1, and occludin of colon tissues were then measured. Fecal samples from mice were analyzed using 16S rRNA sequencing. Results QHF treatment significantly reduced heart volume, CWI, and serum CK and CK-MB levels, attenuated cardiac histopathological alterations, and alleviated CF. QHF treatment also downregulated TNF-α, IL-1β, and IL-6 in serum. Moreover, QHF treatment decreased the serum level of lipopolysaccharide and maintained intestinal integrity by upregulating ZO-1 and occludin. The 16S rRNA microbiota analysis revealed that QHF treatment increased the relative abundance of Marvinbryantia and Phascolarctobacterium. Conclusions QHF treatment exerts cardioprotective effects through modulating gut microbiota, protecting intestinal integrity, and alleviating inflammation. This study shows that gut microbiota may enhance heart-gut interaction.
A Distributed Collaborative Urban Traffic Big Data System Based on Cloud Computing

With the development and popularity of information technology and ITS, Searching for traffic data and solving traffic problems usually requires collaborative work among a group of people in different geographic locations. A Distributed Collaborative Urban Traffic Big Data system (DCUTBD) is an Internet-based virtual big data environment which provides users with shared resource space and a collaborative platform for publishing multidimensional traffic data, and for visualizing and analyzing complex traffic problems. Cloud Computing technology provides effective solutions for constructing DCUTBD systems because of its ability to provide shared computer processing and storage resources to computers and other devices on demand, and also because of its ability to share programs, data, and software. This paper sums up the urban traffic big data, and analyzes the characteristics of cloud computing technology. The architecture and working mechanism of the DCUTBD system based on cloud services will be elaborated. To demonstrate DCUTBD systems based on cloud computing, we examine a case study of traffic data visualization in Xicheng district, Beijing, China, using a prototype DCUTBD system. The experimental results show that the scheme developed in this paper is efficient and feasible.
Recognition of Drivers’ Hard and Soft Braking Intentions Based on Hybrid Brain-Computer Interfaces

In this paper, we propose simultaneous and sequential hybrid brain-computer interfaces (hBCIs) that incorporate electroencephalography (EEG) and electromyography (EMG) signals to classify drivers’ hard braking, soft braking, and normal driving intentions to better assist driving for the first time. The simultaneous hBCIs adopt a feature-level fusion strategy (hBCI-FL) and classifier-level fusion strategies (hBCIs-CL). The sequential hBCIs include the hBCI-SE1, where EEG signals are prioritized to detect hard braking, and hBCI-SE2, where EMG signals are prioritized to detect hard braking. Experimental results show that the proposed hBCI-SE1 with spectral features and the one-vs-rest classification strategy performs best with an average system accuracy of 96.37% among hBCIs. This work is valuable for developing human-centric intelligent assistant driving systems to improve driving safety and driving comfort and promote the application of BCIs.
The discovery of cathode materials for lithium‐ion batteries from the view of interdisciplinarity

In honor of Professor John B. Goodenough for his 100th birthday, this article tries to find the relationship between the discovery of cathode materials for lithium‐ion batteries and the interdisciplinary research in his career. The original ideas of lithium cobalt oxide, lithium manganese oxide, and LiFePO4 came from his early research in solid state physics and from his strong knowledge of chemical structure and bonding. Some examples are given to demonstrate the importance of interdisciplinary interactions among materials, chemistry, and physics. With the rapid development of rechargeable batteries, such interdisciplinarity is further extended to engineering, information, and even artificial intelligence. Although there are still many challenges like energy density and safety in the batteries, we are confident that a better solution will be soon found.
Characteristics of Transmit Power Allocation for Poor Conditioned End Devices in LPWAN with Peak Detection Based Carrier Sense

This paper investigates characteristics of transmit power allocation technique in low-power wide-area networks (LPWANs) with a carrier sense. Traditionally, we have studied the performance improvement technique for the end devices with high path loss to the gateway in the LPWAN. The technique can improve the performance of such end devices by allocating the transmit power so as to provide the benefit of the capture effect for all end devices. However, the effectiveness of the technique in the LPWAN with the carrier sense has never been verified. In Japan, wireless transceivers in sub-GHz band shall execute the carrier sense based on peak detection before transmitting a packet, and the performance must be verified. Numerical examples are provided to analysis the characteristics of the conventional technique in the LPWAN with the carrier sense based on peak detection.
Efficacy and Safety of Topical Morphine: A Narrative Review

Background. Opioids are the cornerstone of the therapy used in both acute and chronic pain syndromes to treat pain of moderate to severe intensity. The knowledge that opioid receptors also occur in other tissues outside the central nervous system has created a possibility for the topical use of opioids. Thus, local analgesia may be obtained without systemic adverse effects. Methods. A narrative review of scientific papers discussing the topical use of morphine was conducted. For this purpose, the PubMed, Google Scholar, Cochrane Library, and Mendeley databases were searched. Results. The current knowledge on topical morphine does not allow for its recommended use in everyday medical practice, but suggests it may be effective, particularly in the treatment of ulcers and erosions of inflammatory etiology and painful skin lesions including persistent post-mastectomy pain due to breast cancer. Conclusions. Topical morphine has its place beside other analgesics. An important issue is the practical possibility to meet the demand for topical formulations, which is limited by technical difficulties.
Corrosion Barrier Coatings: Progress and Perspectives of the Chemical Route

Improved corrosion barrier coatings (CBCs) to protect metals will allow future metal structures to operate for extended periods, ensuring improved safety by reducing environmental pollution and maintenance costs. Many production methods and design of corrosion barrier coatings (CBCs) have been developed. This review focuses only on CBCs made with chemistry techniques. These CBCs can be passive and active with remarkable performance. Today, most of the work focuses on the discovery and application of “smart nanomaterials,” which, if incorporated into “passive CBCs,” will turn them into “active CBCs,” giving them the phenomenon of “self-healing” that extends their service life. Today, many efforts are focused on developing sensors to diagnose corrosion at an early stage and CBCs that self-diagnose the environment and respond on demand. In addition, recent technological developments are reviewed, and a comprehensive strategy is proposed for the faster development of new CBC materials.
Phenolic Profiling and In-Vitro Bioactivities of Corn (Zea mays L.) Tassel Extracts by Combining Enzyme-Assisted Extraction

In this work, enzyme-assisted extraction (EAE) of phenolic compounds from corn tassel using cellulase, protease, and their combination (1:1) was developed and optimized by central composite response surface methodology. The phenolic profile of obtained corn tassel extracts (CTE) was elucidated by high-performance liquid chromatography–diode array detection (HPLC–DAD) analysis, and their antioxidative, antimicrobial, and cytotoxic properties were evaluated in vitro. The results showed that CTE by EAE with combined enzymes had the highest total phenolic content (TPC). Under optimum enzymatic conditions, the experimental TPC values were 9.78, 8.45, and 10.70 mg/g, respectively, which were significantly higher than that of the non-enzymatic control (6.75 mg/g) (p < 0.05). Fourteen more phenolic compounds (13.80–1694.36 µg/g) were identified in CTE by EAE with the combined enzymes, and thus the antioxidant activity of that extract, determined by DPPH and ABTS radical scavenging method, was demonstrated to be stronger than that of the extracts by EAE with the single and ethanol extraction. Furthermore, this extract also showed remarkably better antimicrobial properties against all tested food-borne pathogenic bacteria and mycotoxigenic fungi than CTE by other extraction methods. CTE by EAE were nontoxic to normal lung fibroblast cell line (Wi-38) but cytotoxic to human colorectal and lung cancer cell lines (Caco-2 and A549), with IC50 values of 392.62–461.98 and 210.66–359.56 µg/mL, respectively, which indicated its potential anticancer properties. In conclusion, CTE by EAE, especially with the combined use of cellulase and protease, seems to hold promising potential for multifunctional application in food and pharma fields.
Revisiting U.S. Nocturnal Tornado Vulnerability and its Influence on Tornado Impacts

This research examines tornadoes and their fatalities by light condition (i.e., daytime and nighttime) for the United States. The study has two primary objectives: 1) catalog and reassess differences in daytime and nighttime, or nocturnal, tornadoes and their fatalities from spatial and temporal perspectives; 2) employ a spatially explicit Monte Carlo simulation technique to calculate differences in daytime and nocturnal tornado-population impact potential by combining climatological tornado risk data with fine-scale, gridded estimates of day and night population density. Results reveal that nocturnal tornadoes remain a substantial impediment to mitigating tornado casualties despite long-term improvements in detection and warning of these events. Nocturnal tornadoes are nearly twice as deadly as daytime events, with fatalities stemming from overnight (i.e., local midnight to sunrise) tornadoes increasing fourfold since the late 19th century. The proportion of all tornado fatalities that occurred during daytime hours has decreased 20% over the last 140 years, while the nocturnal fatality proportion has increased 20%. The stall, or even slight growth, in U.S. tornado mortality rates over the last 30 years has, at least in part, been driven by increasing nocturnal tornado fatalities. Overall, nocturnal tornadoes affect 13% more people on average compared to daytime tornadoes, revealing the importance of time of day in mitigating tornado-population impacts and disasters. Emergency managers, forecasters, first responders, policy makers, and researchers should continue to focus efforts on understanding nocturnal tornadoes, especially regarding how populations receive warnings and respond to these nocturnal threats.
Leadership and governance challenges in delivering place-based transformation through Smart Specialisation

ABSTRACT This paper considers the unfolding of Smart Specialisation Strategy (RIS3) in one of Europe’s innovation-leading metropolitan regions: Stockholm, Sweden. Theoretically, it contributes to debates around change agency and reflects more broadly, which implications arise for metropolitan innovation-leader regions and which are of more generic nature. It argues that actor endowments, dense networks, experience with participatory governance processes and good governance are not sufficient for a successful implementation of RIS3. It finds that transformative regional innovation policy is contingent upon the adequate empowerment of change agents rather than on general regional preconditions.
Empirical basis for car-following theory development

By analyzing data from a car-following experiment, it is shown that drivers control their car by a simple scheme. The acceleration $a(t)$ is held approximately constant for a certain time interval, followed by a jump to a new acceleration. These jumps seem to include a deterministic and a random component; the time $T$ between subsequent jumps is random, too. This leads to a dynamic, that never reaches a fixed-point ($a(t) \to 0$ and velocity difference to the car in front $\Delta v \to 0$) of the car-following dynamics. The existence of such a fixed-point is predicted by most of the existing car-following theories. Nevertheless, the phase-space distribution is clustered strongly at $\Delta v=0$. Here, the probability distribution in $\Delta v$ is (for small and medium distances $\Delta x$ between the cars) described by $p(\Delta v) \propto \exp(-|\Delta v|/\Delta v_0)$ indicating a dynamic that attracts cars to the region with small speed differences. The corresponding distances $\Delta x$ between the cars vary strongly. This variation might be a possible reason for the much-discussed widely scattered states found in highway traffic.
A Design of 10-Bit Asynchronous SAR ADC with an On-Chip Bandgap Reference Voltage Generator

A proposed prototype of a 10-bit 1 MS/s single-ended asynchronous Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) with an on-chip bandgap reference voltage generator is fabricated with 130 nm technology. To optimize the power consumption, static, and dynamic performance, several techniques have been proposed. A dual-path bootstrap switch was proposed to increase the linearity sampling. The Voltage Common Mode (VCM)-based Capacitive Digital-to-Analog Converter (CDAC) switching technique was implemented for the CDAC part to alleviate the switching energy problem of the capacitive DAC. The proposed architecture of the two-stage dynamic latch comparator provides high speed and low power consumption. Moreover, to achieve faster bit conversion with an efficient time sequence, asynchronous SAR logic with an internally generated clock is implemented, which avoids the requirement of a high-frequency external clock, as all conversions are carried out in a single clock cycle. The proposed error amplifier-based bandgap reference voltage generator provides a stable reference voltage to the ADC for practical implementation. The measurement results of the proposed SAR ADC, including an on-chip bandgap reference voltage generator, show an Effective Number of Bits (ENOB) of 9.49 bits and Signal-to-Noise and Distortion Ratio (SNDR) of 58.88 dB with 1.2 V of power supply while operating with a sampling rate of 1 MS/s.
Dexmedetomidine as a rescue agent during intracranial neurosurgery in the setting of opioid tolerance

Dexmedetomidine is a versatile sedative agent widely used both in anaesthesia and intensive care. We present the case of a 32‐year‐old woman with a long‐term history of non‐prescribed intravenous opioid use who underwent elective resection of a skull base tumour. There was difficulty in achieving an adequate depth of anaesthesia despite the high levels of intravenous and volatile anaesthetic agent. Intra‐operatively, a bolus and subsequent infusion of dexmedetomidine helped achieve an adequate depth of anaesthesia. This report highlights some of the benefits of dexmedetomidine for patients who are opioid tolerant, both intra‐ and postoperatively. It also demonstrates the wide range of beneficial effects dexmedetomidine could have when used as a rescue adjunct in neuroanaesthesia.
Exosomes as Crucial Players in Pathogenesis of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that affects multiple systems. Its clinical manifestation varies across patients, from skin mucosa to multiorgan damage to severe central nervous system involvement. The exosome has been shown to play an important role in the pathogenesis of autoimmune diseases, including SLE. We review the recent knowledge of exosomes, including their biology, functions, mechanism, and standardized extraction and purification methods in SLE, to highlight potential therapeutic targets for SLE.
Sparsity-Based Monobit UWB Receiver Under Impulse Noise Environments

In this letter, an ultra-wideband (UWB) non-coherent receiver design is proposed using a monobit analog-to-digital converter (ADC) in an impulsive noise (IN) environment. Sparsity of both the UWB signal and IN are exploited to design a robust digital receiver. A sub-optimal threshold selection of ADC is suggested to enhance system performance in an IN environment. Quasi-static characteristics of the UWB channel are exploited to improve the system’s performance. The proposed monobit digital receiver is analyzed and is shown to have only around 1 dB performance loss in an IN environment as compared to the conventional receiver (IN free). Simulation results provide useful analysis for designing digital UWB receivers both in the absence and in the presence of IN.
A ReRAM-Based Convolutional Neural Network Accelerator Using the Analog Layer Normalization Technique

This article presents a resistive random access memory (ReRAM)-based convolutional neural network (CNN) accelerator with a new analog layer normalization (ALN) technique. The proposed ALN can be used to effectively reduce the effect of the conductance variation in ReRAM devices by normalizing the outputs of the vector-matrix multiplication (VMM) in the charge domain. The ALN achieves high energy and hardware efficiencies because it directly processes the normalization of the VMM outputs without storing their values in memory and is merged into the neuron circuit of the accelerator. To verify the effect of the ALN through experiments, a VMM accelerator that consists of two 25 × 25 sized ReRAM arrays and peripheral circuits with ALN is used for a convolution layer with digital signal processing in a field programmable gate array. The MNIST dataset is used to train and inference a CNN employing two VMM accelerators that work as convolution layers in a pipelined manner. Despite the conductance variation of the ReRAM devices, the ALN successfully stabilizes the output distribution of the convolution layer, which improves the classification accuracy of the network. A final classification accuracy for the MNIST and Fashion-MNIST datasets of 96.2% and 83.1% is achieved, respectively, with an energy efficiency of 9.94 tera-operations per second per Watt.
A New Method for Early Screening of Gastric Cancer (G17 and CA724 Dual-Labeled Time-Resolved Fluorescence Immunoassay)

Gastric carcinoma (GC) is one of the most common malignancies in the world with the great early screening challenges. The study is aimed at establishing a new detection method for early screening GC using time-resolved fluorescence immunoassay (TRFIA) via quantitative detection of gastrin-17 (G-17) and carbohydrate antigen 724 (CA724) in serum. Time-resolved analyzer measured the fluorescence intensity. The standards of G-17/CA724 were used for drawing the standard curve, which is used to calculate the concentration of G-17 and CA724 in serum sample. The sensitivity for G-17 was 0.54 pg/mL and for CA724 was 0.28 U/mL with a wide-range analyze concentration (0.1-1000) pg/mL or U/mL. The average recoveries ranged from 100.52% to 110.30% for G-17 and 103.02% to 116.00% for CA724. All CVs of the intra- and interassay were below 10% with high specificity. There was a high Pearson coefficient between this TRFIA method and the commercially available kits (Pearson r 0.9117 for G-17 and 0.9449 for CA724). Additionally, the cutoff value was 88.41 pg/mL and 5.47 U/mL for CA724 in health subjects. This study established a TRFIA method for simultaneous detection of the concentrations of G-17 and CA724 in serum, which provide a new method for sensitive, accurate, and specific early screening of gastric cancer.
Deep Learning and Power Allocation Analysis in NOMA System

This study shows how the channel estimation based Deep Learning (DL) and a power allocation method are together employed for multi-user detection in a Power domain Non-Orthogonal Multiple Access (PD-NOMA) network. Successive interference cancellation (SIC) procedure is typically employed at receiver side, where numerous users are decoded in a successive approach. Fading channels may scatter transferred signal and initiate dependencies between scattered components, this might influence the channel estimation technique and therefore impact the SIC procedure and signal recognition precision. In our proposed scheme, the influence of Deep Neural Network (DNN) in clearly approximating the channel parameters for users in NOMA cell is inspected. In our scenario, we incorporate the Long Short Term Memory (LSTM) layer with NOMA cell where the LSTM is employed for complex data management to perform training and predication. The DNN is trained online on basis of random channel models and then the trained network is used to approximate the channel taps that will be utilized by the receiver in recovering the desired symbols. Additionally, power factors for user’s devices are optimized to maximize the sum-rate of users where whole power and Quality of service (QoS) restrictions are considered. Simulation outcomes in terms of Bit Error Rate (BER), Outage probability, and sum rate have shown the dominance of the suggested channel estimation using DL over standard estimation approach. Moreover, both fixed power and optimized power schemes are also assessed when DNN is applied.
Cancer-Associated Dysregulation of Sumo Regulators: Proteases and Ligases

SUMOylation is a post-translational modification that has emerged in recent decades as a mechanism involved in controlling diverse physiological processes and that is essential in vertebrates. The SUMO pathway is regulated by several enzymes, proteases and ligases being the main actors involved in the control of sumoylation of specific targets. Dysregulation of the expression, localization and function of these enzymes produces physiological changes that can lead to the appearance of different types of cancer, depending on the enzymes and target proteins involved. Among the most studied proteases and ligases, those of the SENP and PIAS families stand out, respectively. While the proteases involved in this pathway have specific SUMO activity, the ligases may have additional functions unrelated to sumoylation, which makes it more difficult to study their SUMO-associated role in cancer process. In this review we update the knowledge and advances in relation to the impact of dysregulation of SUMO proteases and ligases in cancer initiation and progression.