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The fully quantum reverse Shannon theorem establishes the optimal rate of noiseless classical communication required for simulating the action of many instances of a noisy quantum channel on an arbitrary input state, while also allowing for an arbitrary amount of shared entanglement of an arbitrary form. Turning this theorem around establishes a strong converse for the entanglement-assisted classical capacity of any quantum channel. This paper proves the strong converse for entanglement-assisted capacity by a completely different approach and identifies a bound on the strong converse exponent for this task. Namely, we exploit the recent entanglement-assisted “meta-converse” theorem of Matthews and Wehner, several properties of the recently established sandwiched Rényi relative entropy (also referred to as the quantum Rényi divergence), and the multiplicativity of completely bounded p -norms due to Devetak et al. The proof here demonstrates the extent to which the Arimoto approach can be helpful in proving strong converse theorems, it provides an operational relevance for the multiplicativity result of Devetak et al., and it adds to the growing body of evidence that the sandwiched Rényi relative entropy is the correct quantum generalization of the classical concept for all α > 1.

The emerging and reemerging forms of fungal infections encountered in the course of allogeneic bone marrow transplantations, cancer therapy, and organ transplants have necessitated the discovery of antifungal compounds with enhanced efficacy and better compatibility. A very limited number of antifungal compounds are in practice against the various forms of topical and systemic fungal infections. The trends of new antifungals being introduced into the market have remained insignificant while resistance towards the introduced drug has apparently increased, specifically in patients undergoing long-term treatment. Considering the immense potential of natural microbial products for the isolation and screening of novel antibiotics for different pharmaceutical applications as an alternative source has remained largely unexplored. Endophytes are one such microbial community that resides inside all plants without showing any symptoms with the promise of producing diverse bioactive molecules and novel metabolites which have application in medicine, agriculture, and industrial set ups. This review substantially covers the antifungal compounds, including volatile organic compounds, isolated from fungal endophytes of medicinal plants during 2013–2018. Some of the methods for the activation of silent biosynthetic genes are also covered. As such, the compounds described here possess diverse configurations which can be a step towards the development of new antifungal agents directly or precursor molecules after the required modification.

There has been a sudden boom in the technical industry and an increase in the number of good startups. Keeping track of various appropriate job openings in top industry names has become increasingly troublesome. This leads to deadlines and hence important opportunities being missed. Through this research paper, the aim is to automate this process to eliminate this problem. To achieve this, Puppeteer and Representational State Transfer (REST) APIs for web crawling have been used. A hybrid system of Content-Based Filtering and Collaborative Filtering is implemented to recommend these jobs. The intention is to aggregate and recommend appropriate jobs to job seekers, especially in the engineering domain. The entire process of accessing numerous company websites hoping to find a relevant job opening listed on their career portals is simplified. The proposed recommendation system is tested on an array of test cases with a fully functioning user interface in the form of a web application. It has shown satisfactory results, outperforming the existing systems. It thus testifies to the agenda of quality over quantity.

The Cocktail party problem, which is tracing and identifying a specific speaker’s speech while numerous speakers communicate concurrently is one of the crucial problems still to be addressed for automated speech recognition (ASR) and speaker recognition. In this study, we attempt to thoroughly explore traditional methods for speech separation in a cocktail party environment and further analyze traditional single-channel methods for example source-driven methods like Computational Auditory Scene Analysis (CASA), data-driven methods like non-negative matrix factorization (NMF), model-driven methods, customary multi-channel methods such as beamforming, blind source separation for multi-channel and the newly developed deep learning approaches such as meta-learning based methods, self-supervised learning. This paper further accentuates numerous datasets and evaluation metrics in the domain of speech processing & brings out the comparison between traditional methods and methods based on deep learning for speech separation. This study provides a basic understanding and comprehensive knowledge of state-of-the-art researches in the area of speech separation and serves as a brief overview to new researchers.

The application of natural carbohydrate polysaccharides for antigen delivery and its adjuvanation potential has garnered interest in the scientific community in the recent years. These biomaterials are considered favorable candidates for adjuvant development due to their desirable properties like enormous bioavailability, non-toxicity, biodegradability, stability, affordability, and immunostimulating ability. Chitosan is the one such extensively studied natural polymer which has been appreciated for its excellent applications in pharmaceuticals. Trimethyl chitosan (TMC), a derivative of chitosan, possesses these properties. In addition it has the properties of high aqueous solubility, high charge density, mucoadhesive, permeation enhancing (ability to cross tight junction), and stability over a range of ionic conditions which makes the spectrum of its applicability much broader. It has also been seen to perform analogously to alum, complete Freund's adjuvant, incomplete Freund's adjuvant, and cyclic guanosine monophosphate adjuvanation, which justifies its role as a potent adjuvant. Although many review articles detailing the applications of chitosan in vaccine delivery are available, a comprehensive review of the applications of TMC as an adjuvant is not available to date. This article provides a comprehensive overview of structural and chemical properties of TMC which affect its adjuvant characteristics; the efficacy of various delivery routes for TMC antigen combination; and the recent advances in the elucidation of its mechanism of action.

A prevalent long-term medical condition in children that is rarely understood and acknowledged in educational contexts is developmental coordination disorder (DCD), which is one of the most prevalent conditions in school-aged children. Mild-to-severe abnormalities in muscle tone, posture, movement, and the learning of motor skills are associated with motor disorders. Early detection of developmental abnormalities in children is crucial as delayed motor milestones during infancy might indicate a delay in both physical and neurological development. To overcome the current condition of motor impairment, obstructing their risk factors is important to prevent the development of disability, which is already determined in the prenatal and perinatal period. Concerning the relationship with gestational age, the majority of the studies reported a relationship between DCD and preterm children. However, the entire range of gestational age, including post-term birth, has not been studied. The risk of developmental consequences such as cognitive impairments, major mental diseases, attention-deficit/hyperactivity disorder, autism spectrum disorder, and other behavioral and emotional problems increases in post-term birth, according to prior studies. Thus, this review aims to provide an overview of information linking post-term birth to children's motor impairment, with a focus on DCD. A thorough systemic review was conducted on online databases, and only a few studies were found on the association with post-term children. Insufficient evidence made it necessary to examine more post-term cohorts in adolescence to fully determine the long-term health concerns and develop therapies to mitigate the detrimental effects of post-term deliveries.

Internet of Things (IoT) fog nodes are distributed near end-user devices to mitigate the impacts of low delay, position awareness, and spatial spread, which aren't permitted by numerous IoT apps. Fog computing (FC) also speeds up reaction times by decreasing the quantity of data sent to the cloud. Despite these advantages, FC still has a lot of work to do to fulfill security and privacy standards. The constraints of the FC resources are the cause of these difficulties. In reality, FC could raise fresh concerns about privacy and security. Although the Fog security and privacy problems have been covered in several articles recently, most of these studies just touched the surface of these difficulties. This paper provides a unique solution for the authentication of data by using hyperledger fabric. The fog layer store data transferred by the IoT layer and calculate the hash value. These hash values are now stored in hyperledger fabric for authentication purposes. The proposed model results compared with lewako’s and Fan’s scheme and found that the proposed model has 25.00 % less encryption time, 09.3 % less decryption time, 17.48 % less storage overhead, and 23.38 % less computation cost as compared to Fan’s scheme.

Despite the availability of various diagnostic procedures, a tissue biopsy is still indispensable for the routine diagnosis of lung cancer. However, inaccurate diagnoses can occur, leading to inefficient cancer management. In this context, use of circulating microRNAs (miRNAs) may serve as diagnostic tools as liquid biopsies, and as biomarkers to better understand the molecular mechanisms involved in the progression of cancer. We identified miR‐590‐5p as a potential prognostic marker in the progression of non‐small cell lung cancer (NSCLC). We were able to detect this miRNA in blood plasma samples of NSCLC patients through quantitative real‐time PCR. Our data showed an ~7.5‐fold downregulation of miR‐590‐5p in NSCLC patients compared to healthy controls, which correlated with several clinicopathological features. Further, overexpression of miR‐590‐5p led to decreased cell viability, proliferation, colony formation, migration, and invasion potential of lung cancer cells, whereas its knockdown showed the opposite effect. In addition, the levels of several proteins involved in the epithelial‐to‐mesenchymal transition negatively correlated with miR‐590‐5p levels in lung adenocarcinoma cells and tumors of NSCLC patients. Further, dual‐luciferase reporter assays identified STAT3 as a direct target of miR‐590‐5p, which negatively regulated STAT3 activation and its downstream signaling molecules (eg, Cyclin D1, c‐Myc, Vimentin, and β‐catenin) involved in tumorigenesis. Taken together, our study suggests that miR‐590‐5p functions as a tumor suppressor in NSCLC through regulating the STAT3 pathway, and may serve as a useful biomarker for the diagnosis/prognosis of NSCLC, and as a potential therapeutic target for the treatment of NSCLC. This study shows that circulating miR‐590‐5p functions as a tumor suppressor in NSCLC. In the future, it may be used as a potential liquid biopsy biomarker for the diagnosis/prognosis of NSCLC.

A strategy to halt dissolution of particle-coated air bubbles in water based on interfacial rheology design is presented. Whereas previously a dense monolayer was believed to be required for such an “armored bubble” to resist dissolution, in fact engineering a 2D yield stress interface suffices to achieve such performance at submonolayer particle coverages. We use a suite of interfacial rheology techniques to characterize spherical and ellipsoidal particles at an air–water interface as a function of surface coverage. Bubbles with varying particle coverages are made and their resistance to dissolution evaluated using a microfluidic technique. Whereas a bare bubble only has a single pressure at which a given radius is stable, we find a range of pressures over which bubble dissolution is arrested for armored bubbles. The link between interfacial rheology and macroscopic dissolution of ∼100 μm bubbles coated with ∼1 μm particles is presented and discussed. The generic design rationale is confirmed by using nonspherical particles, which develop significant yield stress at even lower surface coverages. Hence, it can be applied to successfully inhibit Ostwald ripening in a multitude of foam and emulsion applications.

HIV-associated cardiovascular diseases remain a leading cause of death in people living with HIV/AIDS (PLWHA). Although antiretroviral drugs suppress the viral load, they fail to remove the virus entirely. HIV-1 Nef protein is known to play a role in viral virulence and HIV latency. Expression of Nef protein can be detected in different organs, including cardiac tissue. Despite the established role of Nef protein in HIV-1 replication, its impact on organ function inside the human body is not clear. To understand the effect of Nef at the organ level, we created a new Nef-transgenic (Nef-TG) mouse that expresses Nef protein in the heart. Our study found that Nef expression caused inhibition of cardiac function and pathological changes in the heart with increased fibrosis, leading to heart failure and early mortality. Further, we found that cellular autophagy is significantly inhibited in the cardiac tissue of Nef-TG mice. Mechanistically, we found that Nef protein causes the accumulation of Bcl2 and Beclin-1 proteins in the tissue, which may affect the cellular autophagy system. Additionally, we found Nef expression causes upregulation of the cellular senescence marker p21 and senescence-associated β-galactosidase expression. Our findings suggest that the Nef-mediated inhibition of autophagy and induction of senescence markers may promote aging in PLWHA. Our mouse model could help us to understand the effect of Nef protein on organ function during latent HIV infection.