Miracle-dz/UniFAR-FTUs huggingface dataset:
Step-up approach in emphysematous hepatitis: A case report

BACKGROUND Emphysematous hepatitis (EH) is a rare, rapidly progressive fulminant gas-forming infection of the liver parenchyma. It is often fatal and mostly affects diabetes patients. CASE SUMMARY We report a case of EH successfully managed by a step-up approach consisting of aggressive hemodynamic support, intravenous antibiotics, and percutaneous drainage, ultimately followed by laparoscopic deroofing. Of 11 documented cases worldwide, only 1 of the patients survived, treated by urgent laparotomy and surgical debridement. CONCLUSION EH is a life-threatening infection. Its high mortality rate makes timely diagnosis essential, in order to navigate treatment accordingly.
A Novel Method for Intelligibility Assessment of Nonlinearly Processed Speech in Spaces Characterized by Long Reverberation Times

Objective assessment of speech intelligibility is a complex task that requires taking into account a number of factors such as different perception of each speech sub-bands by the human hearing sense or different physical properties of each frequency band of a speech signal. Currently, the state-of-the-art method used for assessing the quality of speech transmission is the speech transmission index (STI). It is a standardized way of objectively measuring the quality of, e.g., an acoustical adaptation of conference rooms or public address systems. The wide use of this measure and implementation of this method on numerous measurement devices make STI a popular choice when the speech-related quality of rooms has to be estimated. However, the STI measure has a significant drawback which excludes it from some particular use cases. For instance, if one would like to enhance speech intelligibility by employing a nonlinear digital processing algorithm, the STI method is not suitable to measure the impact of such an algorithm, as it requires that the measurement signal should not be altered in a nonlinear way. Consequently, if a nonlinear speech enhancing algorithm has to be tested, the STI—a standard way of estimating speech transmission cannot be used. In this work, we would like to propose a method based on the STI method but modified in such a way that it makes it possible to employ it for the estimation of the performance of the nonlinear speech intelligibility enhancement method. The proposed approach is based upon a broadband comparison of cumulated energy of the transmitted envelope modulation and the received modulation, so we called it broadband STI (bSTI). Its credibility with regard to signals altered by the environment or nonlinear speech changed by a DSP algorithm is checked by performing a comparative analysis of ten selected impulse responses for which a baseline value of STI was known.
Long-Term Sequelae of COVID-19: A Systematic Review and Meta-Analysis of One-Year Follow-Up Studies on Post-COVID Symptoms

Emerging evidence has shown that COVID-19 survivors could suffer from persistent symptoms. However, it remains unclear whether these symptoms persist over the longer term. This study aimed to systematically synthesise evidence on post-COVID symptoms persisting for at least 12 months. We searched PubMed and Embase for papers reporting at least one-year follow-up results of COVID-19 survivors published by 6 November 2021. Random-effects meta-analyses were conducted to estimate pooled prevalence of specific post-COVID symptoms. Eighteen papers that reported one-year follow-up data from 8591 COVID-19 survivors were included. Fatigue/weakness (28%, 95% CI: 18–39), dyspnoea (18%, 95% CI: 13–24), arthromyalgia (26%, 95% CI: 8–44), depression (23%, 95% CI: 12–34), anxiety (22%, 95% CI: 15–29), memory loss (19%, 95% CI: 7–31), concentration difficulties (18%, 95% CI: 2–35), and insomnia (12%, 95% CI: 7–17) were the most prevalent symptoms at one-year follow-up. Existing evidence suggested that female patients and those with more severe initial illness were more likely to suffer from the sequelae after one year. This study demonstrated that a sizeable proportion of COVID-19 survivors still experience residual symptoms involving various body systems one year later. There is an urgent need for elucidating the pathophysiologic mechanisms and developing and testing targeted interventions for long-COVID patients.
Mapping Uncertainties of Soft-Sensors Based on Deep Feedforward Neural Networks through a Novel Monte Carlo Uncertainties Training Process

Data-driven sensors are techniques capable of providing real-time information of unmeasured variables based on instrument measurements. They are valuable tools in several engineering fields, from car automation to chemical processes. However, they are subject to several sources of uncertainty, and in this way, they need to be able to deal with uncertainties. A way to deal with this problem is by using soft sensors and evaluating their uncertainties. On the other hand, the advent of deep learning (DL) has been providing a powerful tool for the field of data-driven modeling. The DL presents a potential to improve the soft sensor reliability. However, the uncertainty identification of the soft sensors model is a known issue in the literature. In this scenario, this work presents a strategy to identify the uncertainty of DL models prediction based on a novel Monte Carlo uncertainties training strategy. The proposed methodology is applied to identify a Soft Sensor to provide a real-time prediction of the productivity of a chemical process. The results demonstrate that the proposed methodology can yield a soft sensor based on DL that provides reliable predictions, with precision being proven by its corresponding coverage region.
Deep Reinforcement Learning Based Optical and Acoustic Dual Channel Multiple Access in Heterogeneous Underwater Sensor Networks

In this paper, we investigate how to efficiently utilize channel bandwidth in heterogeneous hybrid optical and acoustic underwater sensor networks, where sensor nodes adopt different Media Access Control (MAC) protocols to transmit data packets to a common relay node on optical or acoustic channels. We propose a new MAC protocol based on deep reinforcement learning (DRL), referred to as optical and acoustic dual-channel deep-reinforcement learning multiple access (OA-DLMA), in which the sensor nodes utilizing the OA-DLMA protocol are called agents, and the remainder are non-agents. The agents can learn the transmission patterns of coexisting non-agents and find an optimal channel access strategy without any prior information. Moreover, in order to further enhance network performance, we develop a differentiated reward policy that rewards specific actions over optical and acoustic channels differently, with priority compensation being given to the optical channel to achieve greater data transmission. Furthermore, we have derived the optimal short-term sum throughput and channel utilization analytically and conducted extensive simulations to evaluate the OA-DLMA protocol. Simulation results show that our protocol performs with near-optimal performance and significantly outperforms other existing protocols in terms of short-term sum throughput and channel utilization.
Disrupted Resting State Attentional Network Connectivity in Adolescent and Young Adult Cannabis Users following Two-Weeks of Monitored Abstinence

Background. Numerous neuropsychological studies have shown that cannabis use during adolescence and young adulthood led to deficits in sustained and selective attention. However, few studies have examined functional connectivity in attentional networks among young cannabis users, nor have characterized relationships with cannabis use patterns following abstinence. Methods. Differences in resting state functional connectivity (RSFC) within the dorsal (DAN) and ventral (VAN) attention networks were examined in 36 adolescent and young adult cannabis users and 39 non-substance using controls following two weeks of monitored abstinence. Observed connectivity differences were then correlated with past-year and lifetime cannabis use, length of abstinence, age of regular use onset, and Cannabis Use Disorder symptoms (CUD). Results. After controlling for alcohol and nicotine use, cannabis users had lower RSFC within the DAN network, specifically between right inferior parietal sulcus and right anterior insula, as well as white matter, relative to controls. This region was associated with more severe cannabis use measures, including increased lifetime cannabis use, shorter length of abstinence, and more severe CUD symptoms. Conclusions. Findings demonstrate that regular cannabis use by adolescents and young adults is associated with subtle differences in resting state connectivity within the DAN, even after two weeks of monitored abstinence. Notably, more severe cannabis use markers (greater lifetime use, CUD symptoms, and shorter abstinence) were linked with this reduced connectivity. Thus, findings support public policy aimed at reducing and delaying cannabis use and treatments to assist with sustained abstinence. Future longitudinal studies are needed to investigate causation.
COVID‐19 crisis and risk spillovers to developing economies: Evidence from Africa

Abstract This study provides new evidence on how risk spillovers occur from the United States to developing economies in Africa during the COVID‐19 pandemic. The results show that downside risk exposures of African markets, financial firms and banks particularly increased during Phase I (30 January to 30 April 2020). The nature and magnitude of downside risk exposures of African financial markets were similar to those of the United States. Our results also reveal that the United States is a net transmitter of risk spillovers while Nigeria, South Africa, Egypt and Morocco are net recipients. Our conclusions offer guidance to risk managers, policymakers and investors.
Reinforcement Effect Evaluation for Arch Bridge Based on Dynamic Characteristics

Due to imperfect method for reinforcement effect evaluation,strengthening effect evaluation for arch bridge was proposed according to the second load for the strengthening treatment of arch bridge,rigidity evaluation of overall deflection change rate and characteristics of dynamic frequency.According to specific projects,advantages of the evaluation method based on the frequency of dynamic characteristics were confirmed through MIDAS/CIVIL for calculation;it was demonstrated that this method could provide useful guidances for strengthening effect evaluation of other bridges.
Intriguing Chloride: Involvement of Chloride Ions in Proton Transfers

The proton transfer from carbon to a chloride ion and the proton transfer to a molecule of water promoted by chloride ions in the acid-catalyzed formation of hydroxamic acids from aldehydes and substituted nitrosobenzenes in mixed solvents have been proposed based on experimental and theoretical investigations. The formation of uncommon contact ion pairs consisting of the nitrosocarbinolic cation intermediate and a chloride anion, followed by the proton transfer from a C-H moiety of the cation intermediate, has been proposed. The influence of chloride on the proton transfer to a water molecule of the solvent-separated nitrosocarbinolic-cation–chloride ion pair was investigated too. The insights are based on the obtained kinetic and other evidence with regard to (1) influences of chloride anions on the observed reaction rates and primary kinetic isotope effects (PKIE) in the reaction; (2) the observed variation of the PKIE-s and rates of the reaction when perchlorate anions are present along with the chloride ions; and (3) the consideration of a model of the nitrosocarbinolic-cation-intermediate—chloride ion pair and transition structure for the proposed proton transfers based on the ab initio calculations.
Aryl Hydrocarbon Receptor Activation by Benzo[a]pyrene Prevents Development of Septic Shock and Fatal Outcome in a Mouse Model of Systemic Salmonella enterica Infection

This study focused on immunomodulatory effects of aryl hydrocarbon receptor (AhR) activation through benzo[a]pyrene (BaP) during systemic bacterial infection. Using a well-established mouse model of systemic Salmonella enterica (S.E.) infection, we studied the influence of BaP on the cellular and humoral immune response and the outcome of disease. BaP exposure significantly reduced mortality, which is mainly caused by septic shock. Surprisingly, the bacterial burden in BaP-exposed surviving mice was significantly higher compared to non-exposed mice. During the early phase of infection (days 1–3 post-infection (p.i.)), the transcription of proinflammatory factors (i.e., IL-12, IFN-γ, TNF-α, IL-1β, IL-6, IL-18) was induced faster under BaP exposure. Moreover, BaP supported the activity of antigen-presenting cells (i.e., CD64 (FcγRI), MHC II, NO radicals, phagocytosis) at the site of infection. However, early in infection, the anti-inflammatory cytokines IL-10 and IL-22 were also locally and systemically upregulated in BaP-exposed S.E. -infected mice. BaP-exposure resulted in long-term persistence of salmonellae up to day 90 p.i. , which was accompanied by significantly elevated S.E. -specific antibody responses (i.e., IgG1, IgG2c). In summary, these data suggest that BaP-induced AhR activation is capable of preventing a fatal outcome of systemic S.E. infection, but may result in long-term bacterial persistence, which, in turn, may support the development of chronic inflammation.
Stakeholder-Oriented Firms Have Feelings and Moral Standing Too

A central claim in stakeholder theory is that, if we see stakeholders as human beings, we will attribute higher moral standing or show more moral consideration to stakeholders. But would the same hold for firms? In this paper, I apply the concepts of humanization and moral standing to firms, and I predict that (1) individuals attribute higher moral standing to stakeholder-oriented than to profit-oriented firms, because (2) individuals attribute more experience (such as feelings) to stakeholder-oriented than to profit-oriented firms. Five experiments support these predictions across different operationalizations of stakeholder and profit orientations. The analyses show that moral standing attributions are not fully explained by attributions of agency (such as thinking) to firms, or by attributions of experience or agency to human stakeholders (instead of firms). By unearthing the importance of experience attributions for moral standing attributions to firms, this work provides novel insights in ongoing legal, philosophical and public debates related to firms’ moral standing. The findings also bring the debate about firms’ moral standing to the heart of stakeholder theory, and lead to new normative and descriptive research questions about the interests of firms and their stakeholders.
To Study the Effect of Different Substrate Materials on Rectangular Microstrip Patch Antenna Parameters Using HFSS

The study of microstrip patch antennas has made great progress in recent years. Compared with conventional antennas, microstrip patch antennas have more advantages and better prospects. They are lighter in weight, low volume, low cost, low profile, smaller in dimension and ease of fabrication and conformity. Moreover, the microstrip patch antennas can provide dual and circular polarizations, dual-frequency operation, frequency agility, broad band-width, feedline flexibility, beam scanning omnidirectional patterning. In this paper we will discuss the effect of different substrate materials on rectangular microstrip patch antenna parameters at 6.6 GHz. Rectangular MPA is simulated using HFSS which is based on FEM.
Optical, morphological, electrical properties and white light photoresponse of CdSe nanoparticles

ABSTRACT II–VI nanocrystalline semiconductors offer a wide range of applications in electronics, optoelectronics, and photonics. The study of the morphological, electrical, and optical properties of Cadmium selenide (CdSe) nanoparticles prepared with tri ethanolamine (TEA) as a complex agent is reported in the paper. Cadmium acetate as a Cd source and (Na2SeO3) as a Se precursor. Transmission electron microscope (TEM), field emission scanning electron microscope (FESEM), energy dispersive x-ray (EDX), and ultraviolet-visible spectroscopy (UV-VIS) were used to characterise the synthesised nanoparticles for their optical, compositional, morphological, and electrical properties. The film of CdSe was deposited on the glass substrate. The electrical characterisation of CdSe thin films at various temperatures dark electrical conductivity and photoconductivity reveal that the films were semiconducting in nature, indicating the suitability of these films for photo sensor applications.
Applicability of the new standard of city-size classification in China

: The new standard of city-size classification in China that divides all cities into five categories and seven subcategories, which was published in 2014, has gained popular attention. However ， there have been various results of city- size classification due to different interpretations of the new standard. This article compares the new standard with the old standard and analyzes the city- size hierarchy of China in 2010 to evaluate the applicability and limitations of the new standard. The results show that the new standard has improved significantly over the old standard by changing the definition of population statistics, definition of urban space statistics, and the classification standard. Comparing the classification results based on the new and the old standards as well as other methods, the number of megacities and big cities reduced significantly while the number of small cities increased. The new result shows a clear pyramid structure of city sizes, which conforms to the central place theory and the rank-size rule. Thus, the new standard provides better guidelines to city management. According to the 6th census data in 2010, China has 12 megacities, 58 big cities, 93 medium-size cities, and 493 small cities. The majority of the higher rank cities are located in national- level urban agglomerations in southeastern China. However, the new standard also has some limitations. Urban resident population statistics that is a key in the new standard are often unavailable in non- census years, and the classification result is affected by adjustments of urban administrative boundaries. Further research on urban area identification and data sharing is urgently needed.
Throughput performance of a non‐linear energy‐harvesting cognitive radio‐enabled device‐to‐device network

In cellular networks, device‐to‐device (D2D) communication is a new paradigm. In this paper, the performance of a non‐linear energy‐harvesting D2D communication network underlaying a cellular network is studied under a channel quality constraint. To make the study more realistic, spectrum sensing is incorporated with the D2D communication. Thus, the user equipments (UEs), that is, D2D devices, are enabled with cognitive radio (CR) technology. Since the UEs are battery powered, there exists an energy constraint. Thus, each UE is also equipped with an energy‐harvesting circuit and harvest energy from radio frequency (RF) signal of power transfer units (PTUs) and cellular users (CUs). Each UE uses its harvested energy for transmission. A D2D transmitter uses sensing information to decide its mode of transmission over a CU channel and is shared in hybrid mode. An algorithm is proposed based on threshold‐based censoring to maximize the throughput. In the proposed scheme, D2D users associated with the bad quality of channels are eliminated from the transmission process. Analytical expressions of throughput and improvement in spectrum utilization (ISU) are developed. The impact of the interference threshold to CU, the censoring threshold and the saturation level of the energy harvester on throughput is studied. The network performance is also investigated for several types of channels. It is found that the amount of fading has a significant impact on throughput performance. It is observed that the proposed scheme outperforms the conventional scheme.
Formulation and Evaluation of Topical Nano-Lipid-Based Delivery of Butenafine: In Vitro Characterization and Antifungal Activity

The present research work was designed to prepare butenafine (BN)-loaded bilosomes (BSs) by the thin-film hydration method. BN is a sparingly water-soluble drug having low permeability and bioavailability. BSs are lipid-based nanovesicles used to entrap water-insoluble drugs for enhanced permeation across the skin. BSs were prepared by the thin-film hydration method and optimized by the Box–Behnken design (BBD) using lipid (A), span 60 (B), and sodium deoxycholate (C) as independent variables. The selected formulation (BN-BSo) was converted into the gel using Carbopol 940 as a gelling agent. The prepared optimized gel (BN-BS-og) was further evaluated for the gel characterization, drug release, drug permeation, irritation, and anti-fungal study. The optimized bilosomes (BN-BSo) showed a mean vesicle size of 215 ± 6.5 nm and an entrapment efficiency of 89.2 ± 1.5%. The DSC study showed that BN was completely encapsulated in the BS lipid matrix. BN-BSog showed good viscosity, consistency, spreadability, and pH. A significantly (p < 0.05) high release (81.09 ± 4.01%) was achieved from BN-BSo compared to BN-BSog (65.85 ± 4.87%) and pure BN (17.54 ± 1.37 %). The permeation study results revealed that BN-BSo, BN-BSog, and pure BN exhibited 56.2 ± 2.7%, 39.2 ± 2.9%, and 16.6 ± 2.3%. The enhancement ratio of permeation flux was found to be 1.4-fold and 3.4-fold for the BN-BS-og and pure BN dispersion. The HET-CAM study showed that BN-BSog was found to be nonirritant as the score was found within the limit. The antifungal study revealed a significant (p < 0.05) enhanced antifungal activity against C. albicans and A. niger. The findings of the study revealed that BS is an important drug delivery system for transdermal delivery.
Characterisation of Particle Size and Viability of SARS-CoV-2 Aerosols from a Range of Nebuliser Types Using a Novel Sampling Technique

Little is understood about the impact of nebulisation on the viability of SARS-CoV-2. In this study, a range of nebulisers with differing methods of aerosol generation were evaluated to determine SARS-CoV-2 viability following aerosolization. The aerosol particle size distribution was assessed using an aerosol particle sizer (APS) and SARS-CoV-2 viability was determined after collection into liquid media using All-Glass Impingers (AGI). Viable particles of SARS-CoV-2 were further characterised using the Collison 6-jet nebuliser in conjunction with novel sample techniques in an Andersen size-fractioning sampler to predict lung deposition profiles. Results demonstrate that all the tested nebulisers can generate stable, polydisperse aerosols (Geometric standard deviation (GSD) circa 1.8) in the respirable range (1.2 to 2.2 µm). Viable fractions (VF, units PFU/particle, the virus viability as a function of total particles produced) were circa 5 × 10−3. VF and spray factors were not significantly affected by relative humidity, within this system where aerosols were in the spray tube an extremely short time. The novel Andersen sample collection methods successfully captured viable virus particles across all sizes; with most particle sizes below 3.3 µm. Particle sizes, in MMAD (Mass Median Aerodynamic Diameters), were calculated from linear regression of log10-log10 transformed cumulative PFU data, and calculated MMADs accorded well with APS measurements and did not differ across collection method types. These data will be vital in informing animal aerosol challenge models, and infection prevention and control policies.