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Reconfigurable computing (RC) theory aims to take advantage of the flexibility of general‐purpose processors (GPPs) alongside the performance of application specific integrated circuits (ASICs). Numerous RC architectures have been proposed since the 1960s, but all are struggling to become mainstream. The main factor that prevents RC to be used in general‐purpose CPUs, GPUs, and mobile devices is that it requires extensive knowledge of digital circuit design which is lacked in most software programmers. In an RC development, a processor cooperates with a reconfigurable hardware accelerator (HA) which is usually implemented on a field‐programmable gate arrays (FPGAs) chip and can be reconfigured dynamically. It implements crucial portions of software (kernels) in hardware to increase overall performance, and its design requires substantial knowledge of digital circuit design. In this paper, a novel RC architecture is proposed that provides the exact same instruction set that a standard general‐purpose RISC microprocessor (e.g., ARM Cortex‐M0) has while automating the generation of a tightly coupled RC component to improve system performance. This approach keeps the decades‐old assemblers, compilers, debuggers and library components, and programming practices intact while utilizing the advantages of RC. The proposed architecture employs the LLVM compiler infrastructure to translate an algorithm written in a high‐level language (e.g., C/C++) to machine code. It then finds the most frequent instruction pairs and generates an equivalent RC circuit that is called miniature accelerator (MA). Execution of the instruction pairs is performed by the MA in parallel with consecutive instructions. Several kernel algorithms alongside EEMBC CoreMark are used to assess the performance of the proposed architecture. Performance improvement from 4.09% to 14.17% is recorded when HA is turned on. There is a trade‐off between core performance and combination of compilation time, die area, and program startup load time which includes the time required to partially reconfigure an FPGA chip.

Proteins, RNA, DNA, lipids, and carbohydrates are only some of the molecular components found in exosomes released by tumor cells. They play an essential role in healthy and diseased cells as messengers of short- and long-distance intercellular communication. However, since exosomes are released by every kind of cell and may be found in blood and other bodily fluids, they may one day serve as biomarkers for a wide range of disorders. In many pathological conditions, including cancer, inflammation, and infection, they play a role. It has been shown that the biogenesis of exosomes is analogous to that of viruses and that the exosomal cargo plays an essential role in the propagation, dissemination, and infection of several viruses. Bidirectional modulation of the immune response is achieved by the ability of exosomes associated with viruses to facilitate immunological escape and stimulate the body's antiviral immune response. Recently, exosomes have received a lot of interest due to their potential therapeutic use as biomarkers for viral infections such as human immunodeficiency virus (HIV), Hepatitis B virus (HBV), Hepatitis C virus (HCV), Epstein–Barr virus (EBV), and SARS-CoV-2. This article discusses the purification procedures and detection techniques for exosomes and examines the research on exosomes as a biomarker of viral infection. Graphical abstract

With the large scale operation of electric buses (EBs), the arrangement of their charging optimization will have a significant impact on the operation and dispatch of EBs as well as the charging costs of EB companies. Thus, an accurate grasp of how external factors, such as the weather and policy, affect the electric consumption is of great importance. Especially in recent years, haze is becoming increasingly serious in some areas, which has a prominent impact on driving conditions and resident travel modes. Firstly, the grey relational analysis (GRA) method is used to analyze the various external factors that affect the power consumption of EBs, then a characteristic library of EBs concerning similar days is established. Then, the wavelet neural network (WNN) is used to train the power consumption factors together with power consumption data in the feature library, to establish the power consumption prediction model with multiple factors. In addition, the optimal charging model of EBs is put forward, and the reasonable charging time for the EB is used to achieve the minimum operating cost of the EB company. Finally, taking the electricity consumption data of EBs in Baoding and the data of relevant factors as an example, the power consumption prediction model and the charging optimization model of the EB are verified, which provides an important reference for the optimal charging of the EB, the trip arrangement of the EB, and the maximum profit of the electric public buses.

Proper regulation of energy metabolism in the brain is crucial for maintaining brain activity in physiological and different pathophysiological conditions. Ischemic stroke has a complex pathophysiology which includes perturbations in the brain energy metabolism processes which can contribute to worsening of brain injury and stroke outcome. Smoking and diabetes are common risk factors and comorbid conditions for ischemic stroke which have also been associated with disruptions in brain energy metabolism. Simultaneous presence of these conditions may further alter energy metabolism in the brain leading to a poor clinical prognosis after an ischemic stroke event. In this review, we discuss the possible effects of smoking and/or diabetes on brain glucose utilization and mitochondrial energy metabolism which, when present concurrently, may exacerbate energy metabolism in the ischemic brain. More research is needed to investigate brain glucose utilization and mitochondrial oxidative metabolism in ischemic stroke in the presence of smoking and/or diabetes, which would provide further insights on the pathophysiology of these comorbid conditions and facilitate the development of therapeutic interventions.

The rising penetration of intermittent renewable distributed generation leads to uncertainties in the planning of electric distribution networks. Fully considering the uncertainties pertinent to wind power generation, photovoltaic power generation and load demand, this paper proposes a scenario-based model for the planning of active distribution systems. The solution obtains the optimal capacities and locations of wind and photovoltaic based distributed generators in the distribution system, whilst minimizing the active and reactive power losses as well as voltage deviation. A scenario matrix is generated using the heuristic moment matching technique that captures the stochastic moments and correlation among historical wind and photovoltaic power, and electricity demand. The scenario matrix is then incorporated to propose a stochastic planning model that considers a multi-objective index for minimizing power losses and voltage deviation. Finally, the effectiveness of the proposed planning model is confirmed using case-studies in 53-bus and IEEE 123-bus distribution systems.

Nicotinamide mononucleotide (NMN) is a nucleotide that is most recognized for its role as an intermediate of nicotinamide adenine dinucleotide (NAD+) biosynthesis. Although the biosynthetic pathway of NMN varies between eukaryote and prokaryote, two pathways are mainly followed in case of eukaryotic human—one is through the salvage pathway using nicotinamide while the other follows phosphorylation of nicotinamide riboside. Due to the unavailability of a suitable transporter, NMN enters inside the mammalian cell in the form of nicotinamide riboside followed by its subsequent conversion to NMN and NAD+. This particular molecule has demonstrated several beneficial pharmacological activities in preclinical studies, which suggest its potential therapeutic use. Mostly mediated by its involvement in NAD+ biosynthesis, the pharmacological activities of NMN include its role in cellular biochemical functions, cardioprotection, diabetes, Alzheimer’s disease, and complications associated with obesity. The recent groundbreaking discovery of anti-ageing activities of this chemical moiety has added a valuable essence in the research involving this molecule. This review focuses on the biosynthesis of NMN in mammalian and prokaryotic cells and mechanism of absorption along with the reported pharmacological activities in murine model.

Severe acute respiratory syndrome (SARS-CoV-2), the causative agent of the global pandemic, which has resulted in more than one million deaths with tens of millions reported cases, requires a fast, accurate, and portable testing mechanism operable in the field environment. Electrochemical sensors, based on paper substrates with portable electrochemical devices, can prove an excellent alternative in mitigating the economic and public health effects of the disease. Herein, we present an impedance biosensor for the detection of the SARS-CoV-2 spike protein utilizing the IgG anti-SARS-CoV-2 spike antibody. This label-free platform utilizing screen-printed electrodes works on the principle of redox reaction impedance of a probe and can detect antigen spikes directly in nasopharyngeal fluid as well as virus samples collected in the universal transport medium (UTM). High conductivity graphene/carbon ink is used for this purpose so as to have a small background impedance that leads to a wider dynamic range of detection. Antibody immobilization onto the electrode surface was conducted through a chemical entity or a biological entity to see their effect; where a biological immobilization can enhance the antibody loading and thereby the sensitivity. In both cases, we were able to have a very low limit of quantification (i.e., 0.25 fg/mL), however, the linear range was 3 orders of magnitude wider for the biological entity-based immobilization. The specificity of the sensor was also tested against high concentrations of H1N1 flu antigens with no appreciable response. The most optimized sensors are used to identify negative and positive COVID-19 samples with great accuracy and precision.

Electronic nicotine delivery systems (ENDS), also commonly known as electronic cigarettes (e-cigs) are considered in most cases as a safer alternative to tobacco smoking and therefore have become extremely popular among all age groups and sex. It is estimated that up to 15% of pregnant women are now using e-cigs in the US which keeps increasing at an alarming rate. Harmful effects of tobacco smoking during pregnancy are well documented for both pregnancy and postnatal health, however limited preclinical and clinical studies exist to evaluate the long-term effects of prenatal e-cig exposure on postnatal health. Therefore, the aim of our study is to evaluate the effect of maternal e-cig use on postnatal blood-brain barrier (BBB) integrity and behavioral outcomes of mice of varying age and sex. In this study, pregnant CD1 mice (E5) were exposed to e‐Cig vapor (2.4% nicotine) until postnatal day (PD) 7. Weight of the offspring was measured at PD0, PD7, PD15, PD30, PD45, PD60 and PD90. The expression of structural elements of the BBB, tight junction proteins (ZO-1, claudin-5, occludin), astrocytes (GFAP), pericytes (PDGFRβ) and the basement membrane (laminin α1, laminin α4), neuron specific marker (NeuN), water channel protein (AQP4) and glucose transporter (GLUT1) were analyzed in both male and female offspring using western blot and immunofluorescence. Estrous cycle was recorded by vaginal cytology method. Long‐term motor and cognitive functions were evaluated using open field test (OFT), novel object recognition test (NORT) and morris water maze test (MWMT) at adolescence (PD 40–45) and adult (PD 90–95) age. In our study, significantly reduced expression of tight junction proteins and astrocyte marker were observed in male and female offspring until PD 90 (P < 0.05). Additionally, prenatally e-cig exposed adolescent and adult offspring showed impaired locomotor, learning, and memory function compared to control offspring (P < 0.05). Our findings suggest that prenatal e-cig exposure induces long-term neurovascular changes of neonates by disrupting postnatal BBB integrity and worsening behavioral outcomes.

The multiple contamination of pesticides are common in farmland soil. However, there is a noteworthy knowledge gap regarding the ecophysiological response of co-exposure of pesticides on non-target crops under such conditions. Silicon (Si) was chosen to alleviate pesticides phytotoxicity due to its ability to improve plant growth and adaptive responses against xenobiotics exposure. This study explores the mechanisms of combined effects of lambda-cyhalothrin (CM), a synthetic pyrethroid insecticide and difenoconazole (DIF), a systemic triazole fungicide induced phytotoxicity and the potential of Si to alleviate CM + DIF toxicity by regulating growth, redox homeostasis, and antioxidant defense in tomato ( Solanum lycopersicum L.) seedlings. The results showed that tomato growth and chlorophyll biosynthesis was significantly inhibited by individual and combined stress of CM and DIF, possibly due to induced oxidative stress. Interestingly, the extent of lipid peroxidation was much higher under CM and DIF co-exposure than under CM and DIF only, as indicated by MDA level, thus indicating the synergistic effect of pesticide on oxidative damage. Moreover, pesticide exposure significantly improved ascorbate peroxidase, peroxidase, glutathione S-transferase, reduced glutathione, and proline in tomato seedlings compared to control. Our study demonstrates that Si improves tomato seedling’s tolerance to CM + DIF toxicity by enhancing pesticides metabolism through GSH-GST detoxification enzymes. Si supply also enhanced PAL activity and stimulated reactions in the phenylpropanoid pathway to produce phenolic and flavonoids in tomato seedlings under CM + DIF stress. Si promotes chlorophyll biosynthesis and reinforces the antioxidative system, thereby maintaining redox homeostasis and overall seedling growth under CM and DIF co-exposure. The findings provide valuable information about the underlying mechanisms of Si-mediated CM and DIF co-exposure response with potential use as effective bio-stimulants in agriculture to address pesticides phytotoxicity issues.

Background Pharmaceutical companies spend more than one-third of their sales revenue on marketing and promotion directed toward healthcare professionals. There has been a focus on the relationship between healthcare professionals and the pharmaceutical industry in recent years. This study aims to explore the attitude toward and acceptability of medical promotional tools and their influence on physicians’ prescribing practices in Jordan and Iraq. Methods A cross-sectional survey study was conducted to explore the influence of visits by medical representatives (MRs) and medical promotions on physicians’ prescribing practices between June and October 2020 in Jordan and Iraq. Previously validated questionnaires were used. Results A total of 801 physicians completed the questionnaires. Face-to-face visits, followed by the dispensing of medical samples, were the two most common promotional methods used by MRs. 48% of participating physicians reported that they would accept the promotional marketing tools offered to them. MRs focused on the key selling points of their product during medical promotions, and 39.6% of the physicians reported that MRs had a negative attitude toward their competitors’ products. 69.9% of the physicians reported that they would change their practice after participating in conferences or meetings. Conclusion Medical promotional tools have a clear influence on physicians’ prescribing practices in Jordan and Iraq. Therefore, medical promotion should be controlled and guided by clear and country-specific ethical guidelines. This will ensure safe medical promotion to physicians and optimise the healthcare practices provided to patients.