bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zinc‐ion hybrid supercapacitors: Design strategies, challenges, and perspectives
Authors: Chen Xiudong , Zhang Hang , Gao Yun , Liu Jin‐Hang , Cao Xiaohua , Zhan Changchao , Wang Shitao , Wang Jiazhao , Dou Shi‐Xue , Cao Dapeng 
Published: September 2022

AbstractZinc‐ion hybrid supercapacitors (ZHSCs) may be the most promising energy storage device alternatives for portable and large‐scale electronic devices in the future, as they combine the benefits of both supercapacitors and zinc‐ion batteries. Even though many surprise outcomes have been accomplished with ZHSCs, the creation of suitable cathode materials and electrolytes, as well as the enhancement of zinc anodes, continue to be the most difficult obstacles in the development of high‐performance ZHSCs. The low capacitance of the cathode material, poor stability, and low utilization rate of the zinc anode seriously affect the electrochemical performance and application of ZHSCs. Furthermore, parasitic processes in aqueous electrolytes, such as the hydrogen and oxygen evolution reactions might result in low‐voltage windows and unsatisfied cycling performance of the ZHSCs. This review provides a concise summary of the most recent developments and energy storage mechanisms in ZHSCs. Meanwhile, the cathode material design strategy (structural engineering, hybrid‐composite design, heteroatom doping, and so on), the zinc anode design strategy (zinc foil improvement, zinc‐free metal composites, and so on), and the structure–activity relationship of the electrochemical performance of ZHSCs are discussed. Additionally, a summary of the impact of modifications in electrolyte composition on the electrochemical performance of ZHSCs is provided. Finally, this review also discusses the future development direction of ZHSCs. It is anticipated that this evaluation will serve as a helpful reference for the creation of high‐performance ZHSCs, which will hasten the development of these devices.
A security hybrid mechanism using fuzzy with adaptive ElGamal approach in cloud
Authors: Kavitha Ravichandran , Valarmathi AngaThevar 
Published: September 2022

SummaryDue to the increasing number of people accessing their personal medical information online, it has raised concerns about the security of their data. Unauthorized access to patient's records can lead to disclosure of their privacy. There are various types of frauds that can affect the integrity of a patient's records such as theft of identity and tax fraud. It is therefore necessary to implement a secure data access and retrieval system in order to prevent these types of crimes. Security passwords are often the only barrier between hackers and users. Many of us often use the same ones for multiple accounts. Biometric passwords are more secure than traditional ones due to their ability to be created by observing a person's eyes. They can also be created with a secret key that's stored in an encrypted format. Proposed method combines a secure key with an optimized fuzzy extraction algorithm to provide high‐level security. The file is then encrypted using adaptive ElGamal and its digital signature is uploaded in cloud. Data recovery services are also introduced to help users keep their data secure using seed block algorithm (SBA). These services can be utilized to recover files once they get lost or get destroyed. The proposed security approach for back‐up files (SBA) can be used to minimize the time it takes for the recovery process. It also addresses the issue of unauthorized access to the data stored on remote servers.
Efficient exact algorithms for continuous bi‐objective performance‐energy optimization of applications with linear energy and monotonically increasing performance profiles on heterogeneous high performance computing platforms
Authors: Khaleghzadeh Hamidreza , Reddy Manumachu Ravi , Lastovetsky Alexey 
Published: September 2022

AbstractPerformance and energy are the two most important objectives for optimization on heterogeneous high performance computing platforms. This work studies a mathematical problem motivated by the bi‐objective optimization of data‐parallel applications on such platforms for performance and energy. First, we formulate the problem and present an exact algorithm of polynomial complexity solving the problem where all the application profiles of objective type one are continuous and strictly increasing, and all the application profiles of objective type two are linear increasing. We then apply the algorithm to develop solutions for two related optimization problems of parallel applications on heterogeneous hybrid platforms, one for performance and dynamic energy and the other for performance and total energy. Our proposed solution methods are then employed to solve the two bi‐objective optimization problems for two data‐parallel applications, matrix multiplication and gene sequencing, on a hybrid platform employing five heterogeneous processors, namely, two different Intel multicore CPUs, an Nvidia K40c GPU, an Nvidia P100 PCIe GPU, and an Intel Xeon Phi.
Deep learning: A taxonomy of modern weapons to combat Covid‐19 similar pandemics in smart cities
Authors: Saeedvand Saeed , Jafari Masoumeh , Aghdasi Hadi S. , Baltes Jacky , Rahmani Amir Masoud 
Published: September 2022

SummaryThe Covid‐19 pandemic has affected many lives over the past year. In addition to the enormous health cost, the necessary lockdowns and government‐mandated suspension to prevent the spread of the virus had a huge economic impact. The new challenges in 2021 were combating new virus mutations and providing effective vaccines globally. Artificial intelligent (AI) and machine learning have made significant improvements in many different applications during the last decades. One of the advanced and robust technologies in machine learning is deep learning (DL), which can be employed to help prevent initial infections and detect and monitor their progress and side effects. Fast and accurate Covid‐19 infection detection and treatment of suspected patients is essential to make better decisions, ensure treatment, and even save patients' lives. Modern technologies are required to achieve these objectives and create a sustainable society. This article presents a taxonomy in DL algorithms to cover both the technical novelties and empirical results techniques for Covid‐19 in smart cities. In this regard, (i) we demonstrate possible DL algorithms capable of combating Covid‐19; (ii) we propose an up‐to‐date perspective of DL algorithms in social prevention and medical treatment; and (iii) we identify the challenges in combating Covid‐19 outbreaks.
Agility, innovation, environmental management and competitiveness in the hotel industry
Authors: López‐Gamero María D. , Molina‐Azorín José F. , Pereira‐Moliner Jorge , Pertusa‐Ortega Eva M. 
Published: September 2022

AbstractThe hotel industry is characterized by operating in a global, dynamic and uncertain environment where stakeholders' concerns on sustainable development are growing. However, there is limited research on whether hotels have flexibility and capacity for change, to develop environmental practices that meet stakeholder demands and improve their competitiveness. Through the dynamic capabilities theory, the resource‐based view and the stakeholder theory, this paper develops a model that considers agility and innovation as antecedents of environmental management and competitive advantages as consequences. A Partial Least Squares analysis is carried out based on data from Spanish hotels. The results indicate that agility and innovation influence environmental management positively; agility influences innovation positively; and agility influences environmental management indirectly through innovation. Moreover, environmental management positively influences cost and differentiation competitive advantages. This study contributes to the literature by examining the role of two important dynamic capabilities and their impact on environmental management and showing how the interaction and mediation between these capabilities favors competitive advantages.
A novel step‐up topology for multilevel power conversion
Authors: Jain Anekant , Gupta Krishna Kumar , Jain Sanjay K. 
Published: September 2022

AbstractRenewable energy sources employ a power conditioning unit for injecting power into the grid. Such resources of small capacity are characterized by low generated voltage and thus require a high voltage boost at the inversion stage. This paper proposes a novel transformer‐less, single‐phase grid‐connected, 13‐level inverter to yield the voltage boost. The presented topology is realized through 12 unidirectional switches, 2 diodes, and 3 capacitors. A single‐stage circuit synthesizes 13 levels with a single input source and yielding an overall voltage gain of six. The adapted modulation technique is robust enough to keep the capacitors self‐balanced for all values of the modulation index. The proposed topology is modular and cost‐effective in comparison to other similar typologies due to reduced device count and space requirement. The presented topology is validated experimentally with satisfactory operation in yielding input voltage boost by a factor of six.
Dynamic winter weather moderates movement and resource selection of wild turkeys at high‐latitude range limits
Authors: Gonnerman Matthew , Shea Stephanie A. , Sullivan Kelsey , Kamath Pauline , Overturf Kaj , Blomberg Erik 
Published: September 2022

AbstractFor wide‐ranging species in temperate environments, populations at high‐latitude range limits are subject to more extreme conditions, colder temperatures, and greater snow accumulation compared with their core range. As climate change progresses, these bounding pressures may become more moderate on average, while extreme weather occurs more frequently. Individuals can mitigate temporarily extreme conditions by changing daily activity budgets and exhibiting plasticity in resource selection, both of which facilitate existence at and expansion of high‐latitude range boundaries. However, relatively little work has explored how animals moderate movement and vary resource selection with changing weather, and a general framework for such investigations is lacking. We applied hidden Markov models and step selection functions to GPS data from wintering wild turkeys (Meleagris gallopavo) near their northern range limit to identify how weather influenced transition among discrete movement states, as well as state‐specific resource selection. We found that turkeys were more likely to spend time in a stationary state as wind chill temperatures decreased and snow depth increased. Both stationary and roosting turkeys selected conifer forests and avoided land covers associated with foraging, such as agriculture and residential areas, while shifting their strength of selection for these features during poor weather. In contrast, mobile turkeys showed relatively weak resource selection, with less response in selection coefficients during poor weather. Our findings illustrate that behavioral plasticity in response to weather was context dependent, but movement behaviors most associated with poor weather were also those in which resource selection was most plastic. Given our results, the potential for wild turkey range expansion will partly be determined by the availability of habitat that allows them to withstand periodic inclement weather. Combining hidden Markov models with step selection functions is broadly applicable for evaluating plasticity in animal behavior and dynamic resource selection in response to changing weather. We studied turkeys at northern range limits, but this approach is applicable for any system expected to experience significant changes in the coming decade, and may be particularly relevant to populations existing at range peripheries.
Guidelines for the digestive enzymes inhibition assay
Authors: Wang Jing , Zhao Minjie , Liu Tao , Feng Fengqin , Zhou Aicun 
Published: September 2022

AbstractAs digestive enzymes play a key role in the digestion and absorption of nutrients, more and more studies have focused on the inhibitory effect of various biochemicals on digestive enzymes, such as amylase, glucosidases, lipases, and proteases, etc. Presently, assays were developed to evaluate the inhibitory activity of digestive enzymes vary. Therefore, to facilitate the study of digestive enzyme inhibitory activity, it is critical to select an adequate assay. In this guideline, assays used recently were selected for extended discussion, including the reaction systems of each assay as well as the practice of digestive enzymes inhibition assessment.
Identification of Adulterated Evening Primrose Oil Based on GC‐MS and FT‐IR Combined with Chemometrics
Authors: Pan Fengguang , Yang Enqi , Chen Xianmao , Li Peizhi , Wu Xinling , Zhang Mingdi 
Published: September 2022

AbstractEvening primrose oil has a high market value due to its rich unsaturated fatty acids, so it is likely to be adulterated under the drive of economic interests. In this study, evening primrose oil's fatty acid and physicochemical properties are systematically determined, and the characteristic fatty acids are screened out. The feasibilities of GC‐MS and FT‐IR in identifying oil adulteration are also evaluated. Evening primrose oil's major fatty acids are linoleic acid (C18:2), γ‐linolenic acid (C18:3n6), palmitic acid (C16:0), oleic acid (C18:1), and stearic acid (C18:0). In addition, palmitoleic acid (C16:1), hexadecadienoic acid (C16:2), nonadecanoic acid (C19:0), eicosatrienoic acid (C20:3), erucic acid (C22:1), tricosanoic acid (C23:0) and lignoceric acid (C24:0) are rarely detected in other related studies on the evening primrose oil. This study uses fatty acids as indicators, hierarchical cluster analysis, and cosine similarity analysis to identify the evening primrose oil mixed with >5% peanut oil and >10% sunflower oil. Besides, the principal component analysis also distinguishes evening primrose oil blended with different proportions of peanut and sunflower oils. In summary, this study confirms that fatty acids can be characteristic indexes to identify adulterated evening primrose oil by GC‐MS and FT‐IR combined with chemometrics.Practical Applications: This study further clarifies the major and characteristic fatty acids of evening primrose oil. On this basis, the adulteration of evening primrose oil (taking peanut oil and sunflower oil as an example) is identified. Therefore, it is helpful to assess the quality and identify the authenticity of the evening primrose oil, which is vital for the stability of the evening primrose oil market and the interests of consumers. These methods combined with chemometrics can also be extended to ensure the certification of other oils and to classify oils into different classes. The improvements in vegetable oil quality will also benefit the vegetable oil industry and control bodies.
A shared mucosal gut microbiota signature in primary sclerosing cholangitis before and after liver transplantation
Authors: Hole Mikal Jacob , Jørgensen Kristin Kaasen , Holm Kristian , Braadland Peder R. , Meyer‐Myklestad Malin Holm , Medhus Asle Wilhelm , Reikvam Dag Henrik , Götz Alexandra , Grzyb Krzysztof , Boberg Kirsten Muri , Karlsen Tom Hemming , Kummen Martin , Hov Johannes R. 
Published: September 2022

Background and Aims:
Several characteristic features of the fecal microbiota have been described in primary sclerosing cholangitis (PSC), whereas data on mucosal microbiota are less consistent. We aimed to use a large colonoscopy cohort to investigate key knowledge gaps, including the role of gut microbiota in PSC with inflammatory bowel disease (IBD), the effect of liver transplantation (LT), and whether recurrent PSC (rPSC) may be used to define consistent microbiota features in PSC irrespective of LT.

Approach and Results:
We included 84 PSC and 51 liver transplanted PSC patients (PSC‐LT) and 40 healthy controls (HCs) and performed sequencing of the 16S ribosomal RNA gene (V3–V4) from ileocolonic biopsies. Intraindividual microbial diversity was reduced in both PSC and PSC‐LT versus HCs. An expansion of Proteobacteria was more pronounced in PSC‐LT (up to 19% relative abundance) than in PSC (up to 11%) and HCs (up to 8%; QFDR < 0.05). When investigating PSC before (PSC vs. HC) and after LT (rPSC vs. no‐rPSC), increased variability (dispersion) in the PSC group was found. Five genera were associated with PSC before and after LT. A dysbiosis index calculated from the five genera, and the presence of the potential pathobiont, Klebsiella, were associated with reduced LT‐free survival. Concomitant IBD was associated with reduced Akkermansia.

Conclusions:
Consistent mucosal microbiota features associated with PSC, PSC‐IBD, and disease severity, irrespective of LT status, highlight the usefulness of investigating PSC and rPSC in parallel, and suggest that the impact of gut microbiota on posttransplant liver health should be investigated further.
Glucagon‐like peptide‐1 receptor differentially controls mossy cell activity across the dentate gyrus longitudinal axis
Authors: Steiner Alex , Owen Benjamin M. , Bauer James P. , Seanez Leann , Kwon Sam , Biddinger Jessica E. , Huffman Ragan , Ayala Julio E. , Nobis William P. , Lewis Alan S. 
Published: September 2022

AbstractUnderstanding the role of dentate gyrus (DG) mossy cells (MCs) in learning and memory has rapidly evolved due to increasingly precise methods for targeting MCs and for in vivo recording and activity manipulation in rodents. These studies have shown MCs are highly active in vivo, strongly remap to contextual manipulation, and that their inhibition or hyperactivation impairs pattern separation and location or context discrimination. Less well understood is how MC activity is modulated by neurohormonal mechanisms, which might differentially control the participation of MCs in cognitive functions during discrete states, such as hunger or satiety. In this study, we demonstrate that glucagon‐like peptide‐1 (GLP‐1), a neuropeptide produced in the gut and the brain that regulates food consumption and hippocampal‐dependent mnemonic function, might regulate MC function through expression of its receptor, GLP‐1R. RNA‐seq demonstrated that most, though not all, Glp1r in hippocampal principal neurons is expressed in MCs, and in situ hybridization revealed strong expression of Glp1r in hilar neurons. Glp1r‐ires‐Cre mice crossed with Ai14D reporter mice followed by co‐labeling for the MC marker GluR2/3 revealed that almost all MCs in the ventral DG expressed Glp1r and that almost all Glp1r‐expressing hilar neurons were MCs. However, only ~60% of dorsal DG MCs expressed Glp1r, and Glp1r was also expressed in small hilar neurons that were not MCs. Consistent with this expression pattern, peripheral administration of the GLP‐1R agonist exendin‐4 (5 μg/kg) increased cFos expression in ventral but not dorsal DG hilar neurons. Finally, whole‐cell patch‐clamp recordings from ventral MCs showed that bath application of exendin‐4 (200 nM) depolarized MCs and increased action potential firing. Taken together, this study adds to known MC activity modulators a neurohormonal mechanism that may preferentially affect ventral DG physiology and may potentially be targetable by several GLP‐1R pharmacotherapies already in clinical use.
Spatial and temporal dynamics of water isotopes in the riverine‐marine mixing zone along the German Baltic Sea coast
Authors: Aichner Bernhard , Rittweg Timo , Schumann Rhena , Dahlke Sven , Duggen Svend , Dubbert David 
Published: September 2022

AbstractRiver estuaries are characterized by mixing processes between freshwater discharge and marine water masses. Since the first are depleted in heavier stable isotopes compared with the marine realm, estuaries often show a linear correlation between salinity and water stable isotopes (δ18O and δ2H values). In this study, we evaluated spatial and seasonal isotope dynamics along three estuarine lagoon transects, located at the northern German Baltic Sea coast. The data show strong seasonality of isotope values, even at locations located furthest from the river mouths. They further reveal a positive and linear salinity‐isotope correlation in spring, but ‐in two of the three studied transects‐ hyperbolic and partially reverse correlations in summers. We conclude that additional hydrological processes partially overprint the two‐phase mixing correlation during summers: aside from the isotope seasonality of the riverine inflows, the shallow inner lagoons in the studied estuaries are influenced by evaporation processes. In contrast the estuarine outflow regions are under impact of significant salinity and isotope fluctuations of the Baltic Sea. Deciphering those processes is crucial for the understanding of water isotope and salinity dynamics. This is also of relevance in context of ecological studies, for example, when interpreting oxygen and hydrogen isotope data in aquatic organisms that depend on ambient estuarine waters.
Prostate cancer incidence in men with prostate‐specific antigen below 3 ng/mL: The Finnish Randomized Study of Screening for Prostate Cancer
Authors: Ola Idris Olasunmbo , Talala Kirsi , Tammela Teuvo , Taari Kimmo , Murtola Teemu , Kujala Paula , Raitanen Jani , Auvinen Anssi 
Published: September 2022

AbstractProstate‐specific antigen (PSA)‐based screening for prostate cancer (PCa) can reduce PCa mortality, but also involves overdetection of low‐risk disease with potential adverse effects. We evaluated PCa incidence among men with PSA below 3 ng/mL and no PCa diagnosis at the first screening round of the Finnish Randomized Study of Screening for PCa. Follow‐up started at the first screening attendance and ended at PCa diagnosis, emigration, death or the common closing date (December 2016), whichever came first. Cox regression analysis was used to estimate hazard ratios and their confidence intervals (CI). Among men with PSA <3 ng/mL, cumulative PCa incidence was 9.1% after 17.6 years median follow‐up. Cumulative incidence was 3.6% among men with baseline PSA 0 to 0.99 ng/mL, 11.5% in those with PSA 1.0 to 1.99 ng/mL and 25.7% among men with PSA 2 to 2.99 ng/mL (hazard ratio 9.0, 95% CI: 7.9‐10.2 for the latter). The differences by PSA level were most striking for low‐risk disease based on Gleason score and EAU risk group. PSA values <1 ng/mL indicate a very low 20‐year risk, while at PSA 2 to 2.99 ng/mL risks are materially higher, with 4‐ to 5‐fold risk for aggressive disease. Using risk‐stratification and appropriate rescreening intervals will reduce screening intensity and overdetection. Using cumulative incidence of clinically significant PCa (csPCa) as the criterion, rescreening intervals could range from approximately 3 years for men with initial PSA 2 to 2.99 ng/mL, 6 years for men with PSA 1 to 1.99 ng/mL to 10 years for men with PSA <1 ng/mL.