bluuebunny/crossref_metadata_2025 huggingface dataset:
Large1
gene transfer in older
myd
mice with severe muscular dystrophy restores muscle function and greatly improves survival
Authors: Yonekawa Takahiro , Rauckhorst Adam J. , El-Hattab Sara , Cuellar Marco A. , Venzke David , Anderson Mary E. , Okuma Hidehiko , Pewa Alvin D. , Taylor Eric B. , Campbell Kevin P.
Published: May 2022

Muscular dystrophy is a progressive and ultimately lethal neuromuscular disease. Although gene editing and gene transfer hold great promise as therapies when administered before the onset of severe clinical symptoms, it is unclear whether these strategies can restore muscle function and improve survival in the late stages of muscular dystrophy.

Large
myd
/Large
myd

(
myd
) mice lack expression of
like-acetylglucosaminyltransferase-1
(
Large1
) and exhibit severe muscle pathophysiology, impaired mobility, and a markedly reduced life span. Here, we show that systemic delivery of AAV2/9 CMV
Large1
(AAV
Large1
) in >34-week-old
myd
mice with advanced disease restores matriglycan expression on dystroglycan, attenuates skeletal muscle pathophysiology, improves motor and respiratory function, and normalizes systemic metabolism, which collectively and markedly extends survival. Our results in a mouse model of muscular dystrophy demonstrate that skeletal muscle function can be restored, illustrating its remarkable plasticity, and that survival can be greatly improved even after the onset of severe muscle pathophysiology.
Aberrant methylmalonylation underlies methylmalonic acidemia and is attenuated by an engineered sirtuin
Authors: Head PamelaSara E. , Myung Sangho , Chen Yong , Schneller Jessica L. , Wang Cindy , Duncan Nicholas , Hoffman Pauline , Chang David , Gebremariam Abigael , Gucek Marjan , Manoli Irini , Venditti Charles P.
Published: May 2022

Organic acidemias such as methylmalonic acidemia (MMA) are a group of inborn errors of metabolism that typically arise from defects in the catabolism of amino and fatty acids. Accretion of acyl-CoA species is postulated to underlie disease pathophysiology, but the mechanism(s) remain unknown. Here, we surveyed hepatic explants from patients with MMA and unaffected donors, in parallel with samples from various mouse models of methylmalonyl-CoA mutase deficiency. We found a widespread posttranslational modification, methylmalonylation, that inhibited enzymes in the urea cycle and glycine cleavage pathway in MMA. Biochemical studies and mouse genetics established that sirtuin 5 (SIRT5) controlled the metabolism of MMA-related posttranslational modifications. SIRT5 was engineered to resist acylation-driven inhibition via lysine to arginine mutagenesis. The modified SIRT5 was used to create an adeno-associated viral 8 (AAV8) vector and systemically delivered to mutant and control mice. Gene therapy ameliorated hyperammonemia and reduced global methylmalonylation in the MMA mice.
Cyclic di-GMP Regulates the Type III Secretion System and Virulence in Bordetella bronchiseptica
Authors: Gutierrez María de la Paz , Wong Ting Y. , Damron Fredrick Heath , Fernández Julieta , Sisti Federico
Published: May 2022

The second messenger cyclic di-GMP (c-di-GMP) is a ubiquitous molecule in bacteria that regulates diverse phenotypes. Among them, motility and biofilm formation are the most studied.
Mast Cell-Derived Proteases Induce Endothelial Permeability and Vascular Damage in Severe Fever with Thrombocytopenia Syndrome
Authors: Wang Yu-Na , Zhang Yun-Fa , Peng Xue-Fang , Ge Hong-Han , Wang Gang , Ding Heng , Li Yue , Li Shuang , Zhang Ling-Yu , Zhang Jing-Tao , Li Hao , Zhang Xiao-Ai , Liu Wei
Published: May 2022

We revealed a pathogenic role for MCs in response to SFTSV infection. The study also identifies potential biomarkers that could differentiate patients at risk of a fatal outcome for SFTS, as well as novel therapeutic targets for the clinical management of SFTS. These findings might shed light on an emerging role for MCs as a potential drug target during infection of other viral hemorrhagic fever diseases with similar host pathology as SFTS.
Supplemental Material: Epidote U-Pb geochronology and H isotope geochemistry trace pre-orogenic hydration of midcrustal granitoids
Authors: Peverelli Veronica , al. et
Published: May 2022

Sample description, methods, and measured U-Pb isotopic data. 
Supplemental Material: Eruptive tempo of Emeishan large igneous province, southwestern China and northern Vietnam: Relations to biotic crises and paleoclimate changes around the Guadalupian-Lopingian boundary
Authors: Huang Hu , al. et
Published: May 2022

Field photographs, photomicrographs, analytical methods and results. 
Experimental investigation of transvenous embolization of arteriovenous malformations using different in vivo models
Authors: Vollherbst Dominik F , Hantz Matthias , Schmitt Niclas , Do Thuy D , Neuberger Ulf , Kauczor Hans U , Bendszus Martin , Sommer Christof M , Möhlenbruch Markus A
Published: May 2022

Background

Transvenous embolization (TVE) is an emerging technique for the endovascular treatment of cerebral arteriovenous malformations (AVMs). The aim of this study was to investigate two in vivo AVM models and to assess TVE techniques using these models.

Methods

Blood flow in the porcine rete mirabile (RM) was modified by either creating a carotid–jugular fistula or by placing a balloon guide catheter in the carotid artery. The RM was embolized with precipitating hydrophobic injectable liquid (PHIL) 25% via transarterial embolization (TAE; control group) and compared with TVE applying the transvenous retrograde pressure cooker technique and TVE using a Woven EndoBridge (WEB) device for flow control (n=6, respectively). The embolization extent (penetration of the RM), the number of events of reflux or embolization distal to the RM and the procedure times were assessed.

Results

The modified RM could be successfully used for embolization in all cases. There were no significant differences regarding the outcome parameters between the two AVM models (fistula or balloon). TVE using the pressure cooker technique led to a higher extent of embolization (median 98.8% vs 63.5%; p=0.008), a lower number of reflux or distal embolization events (p<0.001) and a shorter procedure time (p<0.001) compared with conventional TAE. TVE using a WEB device for flow control was technically feasible and achieved a moderate extent of embolization (median 83.8%).

Conclusion

After surgical or endovascular modification, the porcine RM is a feasible in vivo AVM model for the investigation of TVE techniques. TVE using the pressure cooker technique is superior to conventional TAE in this experimental model.
Explaining lepton-flavor non-universality and self-interacting dark matter with $$L_\mu -L_\tau $$
Authors: Heeck Julian , Thapa Anil
Published: May 2022

Experimental hints for lepton-flavor universality violation in the muon’s magnetic moment as well as neutral- and charged-current B-meson decays require Standard-Model extensions by particles such as leptoquarks that generically lead to unacceptably fast rates of charged lepton flavor violation and proton decay. We propose a model based on a gauged $$U(1)_{L_\mu -L_\tau }$$

U

(
1
)

L
μ

-

L
τ

that eliminates all these unwanted decays by symmetry rather than finetuning and efficiently explains $$(g-2)_\mu $$

(
g
-
2
)

μ

, $$R_{K^{(*)}}$$

R

K

(

∗
)

, $$R_{D^{(*)}}$$

R

D

(

∗
)

, and neutrino masses. The $$U(1)_{L_\mu -L_\tau }$$

U

(
1
)

L
μ

-

L
τ

furthermore acts as a stabilizing symmetry for dark matter and the light $$Z'$$

Z
′

gauge boson mediates velocity-dependent dark-matter self-interactions that resolve the small-scale structure problems. Lastly, even the Hubble tension can be ameliorated via the light $$Z'$$

Z
′

contribution to the relativistic degrees of freedom.
THE ROLE OF THE INFORMATION TECHNOLOGY IN THE INDUSTRIAL STRUCTURE OPTIMIZATION AND UPGRADING IN CHINA
Authors: XU WEICHENG , WANG XIAO , ZHANG ZHENDONG
Published: May 2022

By developing an industrial structure change model, this paper investigates the role of the information technology in explaining the process of industrial structure optimization and upgrading in China from 2001 to 2019. Then, we put forward and discuss the substitution effect and the pervasiveness effect of information technology, and deduce the theoretical propositions from the model. We use the Malmquist index method to estimate the rate of information technology progress, and then choose the genetic algorithm to calibrate the parameters of the model. The research conclusions innovatively explain how the information technology can promote the industrial structure optimization and upgrading in China based on the substitution effect and the pervasiveness effect of information technology in detail. The results point out that when the contribution of information technology to total factor productivity of the tertiary industry is higher than that of the secondary industry, the pervasiveness effect of information technology can promote the upgrading of the industrial structure. Under the comprehensive effect of the pervasiveness effect and substitution effect of information technology, the industrial structure tends to be more optimized. The further heterogeneity analysis shows that the driving effect of information technology on the optimization and upgrading of industrial structure in regions with “servitization” characteristics is more significant. It highlights policy suggestions designed to adopt innovation-driven and technology development strategy, regional industrial structure transformation and economy development strategy.
Moving scene-based video segmentation using fast convolutional neural network integration of VGG-16 net deep learning architecture
Authors: Balachandran G. , Venu Gopala Krishnan J.
Published: May 2022

Video and object segmentation are considered significant research topics in image-video processing. The techniques and mathematical models involved in detecting and segmenting objects employ several modules of different high-level approaches developed for video analysis, object extraction, classification, and recognition. Moving object detection is important in various applications like video surveillance, moving object tracking. This paper proposes video segmentation of moving scene using fast convolutional neural network with VGG-16 net architecture which improves the accuracy. This developed method based on CNN sparsely represents foreground, background, and segmentation mask, which is used in reconstructing the original images. The feed-forward network-trained videos are applied for object detection in a single image with co-segmentation approach where videos or image collections are required as the input. The segmentation is performed through comparative analysis of real-time DAVIS dataset. The results of the experiment show the efficiency of this proposed method which is tested and compared with the existing techniques such as convolution neural network, [Formula: see text]-nearest neighbors, and artificial neural network by the parameters, namely accuracy, precision, recall, and F1-Score. The proposed technique has been improved in terms of accuracy by 97.8%, precision by 94%, recall by 87.9%, and F1-Score by 83.8%.
Workings of science
Authors: Sinha Sharad
Published: May 2022

There is often a debate to differentiate between science and engineering. There is also the view that engineering can be considered applied science. Drawing arguments based on historical developments, this article shows that both science and engineering complement each other. Hence, the question of one being the cause or the effect of the other does not arise.
How to Approach Ambiguous Queries in Conversational Search: A Survey of Techniques, Approaches, Tools, and Challenges
Authors: Keyvan Kimiya , Huang Jimmy Xiangji
Published: May 2022

The advent of recent Natural Language Processing technology has led human and machine interactions more toward conversation. In Conversational Search Systems (CSS) like chatbots and Virtual Personal Assistants such as Apple’s Siri, Amazon Alexa, Microsoft’s Cortana, and Google Assistant, both user and device have a limited platform to communicate through chatting or voice. In the information-seeking process, often users do not know how to properly describe their information need in a machine understandable language. Consequently, it is hard for the assistant agent to predict the user’s intent and yield relevant results by only relying on the original query. Studies have shown many unsatisfactory results can be enhanced with the benefit of CSS, which can dig deeper into the user’s query to reveal the real need. This survey intends to provide a comprehensive and comparative overview ofambiguous query clarificationtask in the context of conversational search technology. We investigate different approaches, their evaluation methods, and future work. We also address the importance of understanding a query for retrieving the most relevant document(s) and satisfying user’s need by predicting their potential request. This work provides an overview of characteristics of ambiguous queries and contributes to better understanding of the existing technologies and challenges in CSS focus on disambiguation of unclear queries from various dimensions.
Discovering Biological Conflict Systems Through Genome Analysis: Evolutionary Principles and Biochemical Novelty
Authors: Aravind L. , Iyer Lakshminarayan M. , Burroughs A. Maxwell
Published: May 2022

Biological replicators, from genes within a genome to whole organisms, are locked in conflicts. Comparative genomics has revealed a staggering diversity of molecular armaments and mechanisms regulating their deployment, collectively termed biological conflict systems. These encompass toxins used in inter- and intraspecific interactions, self/nonself discrimination, antiviral immune mechanisms, and counter-host effectors deployed by viruses and intragenomic selfish elements. These systems possess shared syntactical features in their organizational logic and a set of effectors targeting genetic information flow through the Central Dogma, certain membranes, and key molecules like NAD+. These principles can be exploited to discover new conflict systems through sensitive computational analyses. This has led to significant advances in our understanding of the biology of these systems and furnished new biotechnological reagents for genome editing, sequencing, and beyond. We discuss these advances using specific examples of toxins, restriction-modification, apoptosis, CRISPR/second messenger–regulated systems, and other enigmatic nucleic acid–targeting systems.
Developing and Implementing Predictive Models in a Learning Healthcare System: Traditional and Artificial Intelligence Approaches in the Veterans Health Administration
Authors: Atkins David , Makridis Christos A. , Alterovitz Gil , Ramoni Rachel , Clancy Carolyn
Published: May 2022

Predicting clinical risk is an important part of healthcare and can inform decisions about treatments, preventive interventions, and provision of extra services. The field of predictive models has been revolutionized over the past two decades by electronic health record data; the ability to link such data with other demographic, socioeconomic, and geographic information; the availability of high-capacity computing; and new machine learning and artificial intelligence methods for extracting insights from complex datasets. These advances have produced a new generation of computerized predictive models, but debate continues about their development, reporting, validation, evaluation, and implementation. In this review we reflect on more than 10 years of experience at the Veterans Health Administration, the largest integrated healthcare system in the United States, in developing, testing, and implementing such models at scale. We report lessons from the implementation of national risk prediction models and suggest an agenda for research.
The Role of Telomeres in Human Disease
Authors: Armanios Mary
Published: May 2022

Telomere biology was first studied in maize, ciliates, yeast, and mice, and in recent decades, it has informed understanding of common disease mechanisms with broad implications for patient care. Short telomere syndromes are the most prevalent premature aging disorders, with prominent phenotypes affecting the lung and hematopoietic system. Less understood are a newly recognized group of cancer-prone syndromes that are associated with mutations that lengthen telomeres. A large body of new data from Mendelian genetics and epidemiology now provides an opportunity to reconsider paradigms related to the role of telomeres in human aging and cancer, and in some cases, the findings diverge from what was interpreted from model systems. For example, short telomeres have been considered potent drivers of genome instability, but age-associated solid tumors are rare in individuals with short telomere syndromes, and T cell immunodeficiency explains their spectrum. More commonly, short telomeres promote clonal hematopoiesis, including somatic reversion, providing a new leukemogenesis paradigm that is independent of genome instability. Long telomeres, on the other hand, which extend the cellular life span in vitro, are now appreciated to be the most common shared germline risk factor for cancer in population studies. Through this contemporary lens, I revisit here the role of telomeres in human aging, focusing on how short and long telomeres drive cancer evolution but through distinct mechanisms.
Microbial Interspecies Interactions and Their Impact on the Emergence and Spread of Antimicrobial Resistance
Authors: De Wit Gitta , Svet Luka , Lories Bram , Steenackers Hans P.
Published: May 2022

Bacteria are social organisms that commonly live in dense communities surrounded by a multitude of other species. The competitive and cooperative interactions between these species not only shape the bacterial communities but also influence their susceptibility to antimicrobials. While several studies have shown that mixed-species communities are more tolerant toward antimicrobials than their monospecies counterparts, only limited empirical data are currently available on how interspecies interactions influence resistance development. We here propose a theoretic framework outlining the potential impact of interspecies social behavior on different aspects of resistance development. We identify factors by which interspecies interactions might influence resistance evolution and distinguish between their effect on ( a) the emergence of a resistant mutant and ( b) the spread of this resistance throughout the population. Our analysis indicates that considering the social life of bacteria is imperative to the rational design of more effective antibiotic treatment strategies with a minimal hazard for resistance development.
Sovereign Wealth Funds in Theory and Practice
Authors: James Alexander , Retting Timothy , Shogren Jason F. , Watson Brett , Wills Samuel
Published: May 2022

Are natural resources a curse or a blessing? The answer may depend on how natural wealth is managed. By transforming a temporary windfall into a permanent stock in the form of a sovereign wealth fund, resource-rich economies can avoid volatility and Dutch disease effects, save for future generations, and invest locally. We review the theory behind these resource funds and explore the empirical evidence for their success. Our review is complemented by case studies that highlight some of the more nuanced features, behavior, and effects of resource funds. While the theoretical research highlights the situational success of funds, empirical examinations are minimal. We discuss possible reasons for this gap in the literature and, in doing so, highlight some of the challenges associated with empirical research in this area and discuss possible paths forward.
A Systematic Review of Energy Efficiency Home Retrofit Evaluation Studies
Authors: Giandomenico Lauren , Papineau Maya , Rivers Nicholas
Published: May 2022

We systematically review studies evaluating the energy savings and cost-effectiveness of residential energy efficiency retrofit programs. We review 39 evaluations of 23 residential retrofit programs that were evaluated between 1984 and 2021. Our sample is restricted to program evaluations that used postretrofit household energy billing or consumption data from 140,977 retrofitted households. We report four primary findings. First, none of the studies in our sample reported deep energy savings (e.g., 50% or greater) from retrofit programs. The mean reduction in measured electricity and/or fuel consumption due to energy efficiency retrofits for all programs included in our sample was roughly 7.2%. However, because many households use both fuel and electricity, total household energy savings from the retrofit programs evaluated in our sample are probably smaller. Second, reported program savings decreased as the internal validity of study design increased. Third, as measured by realized savings and cost-effectiveness, the most promising retrofits were insulation and programmable thermostats, whereas the least promising retrofits were storm windows and doors. Fourth, programs with high reported savings and low costs of conserved energy served low-income, fuel-heated households exclusively.
Enhancing Cycling Stability and Specific Capacitance of Vanadium Nitride Electrodes by Tuning Electrolyte Composition
Authors: Haye Emile , Miao Yuanyuan , Pilloud David , Douard Camille , Boukherroub Rabah , Pierson Jean-François , Brousse Thierry , Lucas Stéphane , Houssiau Laurent , Pireaux Jean-Jacques , Achour Amine
Published: May 2022

In this study, the tuning of the KOH electrolyte composition is proposed as a strategy to drastically limit the capacitance fade of vanadium nitride (VN) electrode. We demonstrate that the use of a V5+ (as VO4
3− vanadates anions) containing KOH electrolyte enhances the cycling stability of VN thin film electrode: a loss of 59% of the capacitance is observed for the electrode tested in KOH over 3000 consecutive cycles. After V5+ addition in the electrolyte, the capacitance fade is decreased to 23%. Furthermore, the presence of V5+ species in the solution leads to VN capacitance enhancement from 379 mF cm−2 for V5+ ions free electrolyte up to 577 mF cm−2 at 5 mV s−1 for V5+-containing KOH solution. The enhanced cycling stability is attributed to the stabilization of an oxide/oxynitride layer at the VN surface, instead of its dissolution, thanks to the chemical equilibrium shift of the VN dissolution reaction. This simple and innovative strategy consisting in tuning the electrolyte composition opens new pathways for other systems that suffer from electrode dissolution in the electrolyte while being electrochemically cycled.
Preparation of Ordered Nanohole Arrays with High Aspect Ratios by Anodization of Prepatterned 304 Stainless Steel
Authors: Yanagishita Takashi , Osada Yuga , Masuda Takuya , Masuda Hideki
Published: May 2022

A nanohole array structure with a regular array of cylindrical holes of a high aspect ratio with a period of 63 nm can be obtained by anodizing 304 stainless steel with a concave pattern. It was shown that matching the concave period to the anodization voltage is important to achieving the fabrication of nanohole arrays with a high aspect ratio. This is because the interhole distance of anodic porous oxide obtained by the anodization of 304 stainless steel in ethylene glycol containing 0.1 M ammonium fluoride depends on the anodization voltage. By optimizing the fabrication conditions, it was possible to fabricate highly ordered nanohole arrays with aspect ratios exceeding 100. The nanohole arrays obtained in this study are promising as key materials for fabricating various functional devices.
PEGDA-SN as Both Solid-State Electrolyte and Solid-Solid Interface Material for Li-O2 Battery
Authors: Man Zining , Tian Hao , Zhu Xingbao , Wang Yu , Wu Yuanguo , Wen Xiangyu , Lü Zhe
Published: May 2022

The solid-state batteries have received widespread attention due to their excellent stability and safety, however, the low ionic conductivity and weak interface contact always restricted its performance. In this work, we propose an in situ thermally cross-linked and solidified polymer electrolyte with polyethylene glycol diacrylate (PEGDA) as scaffold in which succinonitrile (SN) and lithium bis-trifluoromethanesulfonimide (LiTFSI) were further introduced to improve the ionic conductivity. Herein, the composite gel was served as not only solid-solid interface material but also solid-state electrolyte. Different with conventional polymer gels, the solvent evaporation could not happen for this composite material during the solidification process, and therefore resulting in good interface contact without inside bubbles. We further present the investigation on transport principle of Li+ in the solid-state electrolyte and the effect of molecular chain on ionic conductivity. The conductivity of the solid-state electrolyte can reach 1.76 × 10−4 S cm−1 at room temperature without any assistance of liquid electrolytes, which is attributed to the short molecular chain of PEGDA. Electrochemical window of the solid-state electrolyte can reach 5.2 V after cross-linking treatment. And the lithium-oxygen battery using this solid-state electrolyte can stably cycle for more than 1100 cycles with a current density of 200 mA g−1 and a limit capacity of 200 mAh g−1 at room temperature.
Study on the Relationship Between Open-Circuit Voltage, Time Constant And Polarization Resistance of Lithium-Ion Batteries
Authors: Yuan Baohe , Zhang Binger , Yuan Xiang , Wang Jingyi , Chen Lulu , Bai Lei , Luo Shijun
Published: May 2022

Battery management system (BMS) is an important role in battery applications. In BMS, the accurate estimation of the state of charge (SOC) of lithium-ion batteries is most important. Open circuit voltage (OCV) is very important for the accurate estimation of SOC. In order to obtain accurate SOC, the relationship between OCV and SOC requires real-time and accuracy. Due to the difference in lithium-ion concentration and battery internal resistance in the lithium-ion battery, OCV has the characteristics of relaxation. It is necessary to study the relaxation behavior of battery OCV. In this paper, the OCV behavior is studied and focuses on the relationship of the time constant and polarization resistance with SOC during relaxation. The results show that, when the SOC is 30%–100%, the time constant and polarization resistance of lithium-ion batteries are the smallest, the performance is the most stable, and the SOC estimation accuracy is the highest. When the battery is overcharged or SOC is low, the performance of the battery is obviously unstable. Finally, it is proposed that the SOC range of the battery can be roughly estimated by calculating the time constant, and the current aging degree of the battery can be judged.
Sodiation-Induced Electrochromism in Carbon Nanofoam–Paper Electrodes
Authors: DeBlock Ryan H. , Carter Rachel , Lefler Matthew J. , Sassin Megan B. , Rolison Debra R. , Long Jeffrey W.
Published: May 2022

Carbon nanofoam papers (CNFPs) serve as device-ready negative electrodes for nonaqueous sodium-ion (Na-ion) batteries, with fast and reversible Na+ storage at the aerogel-like, disordered carbon nanofoam. These binder-free, scalable electrode architectures are not only advantageous for the construction of practical, high-performance Na-ion cells, but are also effective platforms to analyze charge-storage mechanisms. We use in situ optical imaging at the outer surfaces of CNFPs in a Na half-cell to track the distinctive color changes that accompany the multi-stage Na+-storage processes on scanning these electrodes through their active voltage window (0–2 V vs Na∣Na+). We observe that electrochromic transitions ― black in the native (unsodiated) state→blue→red/gold ― occur primarily with deep levels of sodiation at <0.5 V vs Na∣Na+. In situ Raman scattering measurements in the same optical cell show that these color changes correlate with shifts in the characteristic G-band Raman peak that would indicate bulk Na+ insertion into nanoscopic graphitic domains within the aerogel-like carbon. The CNFPs also exhibit appreciable Na-ion storage at higher voltage (0.5–2 V vs Na∣Na+), which can be ascribed to surface-based mechanisms that are accompanied by shifts in the D-band Raman peak, but which do not induce appreciable color change.
Development of a Non-Enzymatic Glucose Sensor Based on Fe2O3 Nanoparticles-Carbon Paste Electrodes
Authors: Hernández-Ramírez D. , Mendoza-Huizar L. H. , Galán-Vidal C. A. , Aguilar-Lira G. Y. , Álvarez-Romero G. A.
Published: May 2022

Fe2O3 nanoparticles have interesting properties such as low production cost, chemical stability, biocompatibility, poor toxicity and high conductivity. In this work, Fe2O3 nanoparticles are used as modifiers to combine its characteristics to those of carbon paste electrodes to enhance the determination of glucose. Differential pulse voltammetry was used as the quantitative analytical technique and then, a Box-Behnken design was used to optimize the its variables in order to maximize the glucose electro-oxidation response signal. The Fe2O3-NPs/CPE sensor showed excellent electro-catalytic performance towards glucose oxidation and three linear ranges: 0.015 μM–1 μM (sensitivity of 51.54 μA/ μM), 1 μM–100 μM (sensitivity of 4.21 μA/μM) and, 30 μM–700 μM (sensitivity of 0.041 μA μM−1) and detection limit of 0.044 μM. The sensor also presented good reproducibility and repeatability, excellent selectivity (in the presence of ascorbic acid, uric acid, lactose, caffeine, and paracetamol), and satisfactory applicability for glucose detection in commercial electrolyte beverages and human urine samples. The improved electrochemical detection capability of Fe2O3-NPs/CPE is attributed to the formation of Fe4+ = O reactive groups at alkaline pH that allowed the oxidization of glucose by a nonenzymatic mechanism.
Posttranslational modifications in GPCR internalization
Authors: Tang Xueqing , Bian Jingwei , Li Zijian
Published: May 2022

G protein-coupled receptors (GPCRs) are the largest family of membrane receptors that serve as the most important drug targets. Classically, GPCR internalization has been considered to lead to receptor desensitization. However, many studies over the past decade have reported that internalized membrane receptors can trigger distinct signal activation. The “internalized activation” provides a completely new understanding for the receptor internalization, the mechanism of physiology/pathology and novel drug targets for precision medicine. GPCR internalization undergoes a series of strict regulations, especially by posttranslational modifications (PTMs). Here, this review summarizes different PTMs in GPCR internalization and analyzes their significance in GPCR internalization dynamics, internalization routes, postinternalization fates, and related diseases, which will offer new insights into the regulatory mechanism of GPCR signaling and novel drug targets for precision medicine.
An increase in force after stretch of diaphragm fibers and myofibrils is accompanied by an increase in sarcomere length nonuniformities and Ca2+ sensitivity
Authors: Contini Massimo , Altman David , Cornachione Anabelle , Rassier Dilson Etcheverry , Bagni Maria Angela
Published: May 2022

When muscle fibers from limb muscles are stretched while activated, the force increases to a steady-state level that is higher than that produced during isometric contractions at a corresponding sarcomere length, a phenomenon known as residual force enhancement (RFE). The mechanisms responsible for the RFE are an increased stiffness of titin molecules that may lead to an increased Ca2+ sensitivity of the contractile apparatus, and the development of sarcomere length nonuniformities. RFE is not observed in cardiac myofibrils, which makes this phenomenon specific to certain preparations. The aim of this study was to investigate whether the RFE is present in the diaphragm, and its potential association with an increased Ca2+ sensitivity and the development of sarcomere length nonuniformities. We used two preparations: single intact fibers and myofibrils isolated from the diaphragm of mice. We investigated RFE in a variety of lengths across the force-length relationship. RFE was observed in both preparations at all lengths investigated and was larger with increasing magnitudes of stretch. RFE was accompanied by an increased Ca2+ sensitivity as shown by a change in the force-pCa2+ curve, and increased sarcomere length nonuniformities. Therefore, RFE is a phenomenon commonly observed in skeletal muscles, with mechanisms that are similar across preparations.
Intensity-dependent modulation of cortical somatosensory processing during external, low-frequency peripheral nerve stimulation in humans
Authors: Hewitt Danielle , Newton-Fenner Alice , Henderson Jessica , Fallon Nicholas B. , Brown Christopher , Stancak Andrej
Published: May 2022

Somatosensory-evoked potentials during low-frequency stimulation of peripheral nerves were examined at graded stimulus intensities. Low-frequency stimulation was associated with decreased responsiveness in the midcingulate cortex and increased responsiveness in primary sensorimotor cortex. Greater intensities were associated with increased midcingulate cortex θ band-power and decreased sensorimotor cortex α band-power. Results further previous evidence of an inhibition of somatosensory processing during and after low-frequency stimulation and point toward a potential augmentation of activity in somatosensory processing regions.
Perfect Fuzzy Soft Tripartite Graphs and Their Complements
Authors: Kalaiarasi Kalaichelvan , Mahalakshmi L. , Kausar Nasreen , Kousar Sajida , Kattel Parameshwari
Published: May 2022

Fuzzy soft graphs are efficient numerical tools for simulating the uncertainty of the real world. A fuzzy soft graph is a perfect fusion of the fuzzy soft set and the graph model that is widely used in a variety of fields. This paper discusses a few unique notions of perfect fuzzy soft tripartite graphs (PFSTG), as well as the concepts of complement of perfect fuzzy soft tripartite graphs (CPFSTGs). Because soft sets are most useful in real‐world applications, the newly developed concepts of perfect soft tripartite fuzzy graphs will lead to many theoretical applications by adding extra fuzziness in analysing. We look at some of their properties and come up with a few results that are related to these concepts. Furthermore, we investigated some fundamental theorems and illustrated an application of size of perfect fuzzy soft tripartite graphs in employee selection for an institution using the perfect fuzzy soft tripartite graph.
Intelligent Performance Evaluation of Urban Subway PPP Project Based on Deep Neural Network Model
Authors: Fan Weizhi , Song Jianmin , Chen Lingmin , Shi Junjiao
Published: May 2022

Neural network refers to an algorithmic mathematical model that imitates the behavioral characteristics of animal neural networks and performs distributed information processing. This kind of network depends on the complexity of the system and needs to adjust the internal node relationship, so as to achieve the purpose of processing information. With the continuous development of the economy, the transportation problem needs to be solved urgently, and the urban subway has emerged at the historic moment. The subway is a fast, large-capacity, electric-driven rail transit built in the city. The advantages of the subway provide conditions for the mitigation of urban traffic, due to the large number of cars, traffic jams, frequent accidents, and serious environmental pollution. In the city center, there are more cars and less space, and the parking lot is not commensurate with the number of cars, making parking difficult. This paper aims to study the intelligent performance evaluation of urban subway PPP projects based on deep neural network models. The subway project has a large investment, a long period, and a wide range, but the development time of the subway in China is relatively short. In order to promote the stable progress of subway projects, it is very necessary to conduct intelligent performance evaluation on subway projects. This paper compares and analyzes the basic characteristics of the PPP model and verifies the applicability and necessity of the PPP model in urban subway transportation projects. Through the investigation of relevant literature, this article puts forward the research content of the social impact assessment of subway projects. The experimental results of this paper show that, from the perspective of whether it is necessary to evaluate the performance of PPP projects, 65% of people think it is very necessary, and 22% think it is more necessary. 3% of people think it is unnecessary, and 10% of people hold an indifferent attitude. These data show that the intelligent performance evaluation of urban subway PPP projects has exploratory significance for urban infrastructure design and construction.
Prediction of Rooftop Photovoltaic Solar Potential Using Machine Learning
Authors: Mukilan K. , Thaiyalnayaki K. , Dwivedi Yagya Dutta , Samson Isaac J. , Poonia Amarjeet , Sharma Arvind , Al-Ammar Essam A. , Wabaidur Saikh Mohammad , Subramanian B. B. , Kassa Adane
Published: May 2022

Solar energy forecasting accuracy is essential for increasing the quantity of renewable energy that can be integrated into the existing electrical grid control systems. The availability of data at unprecedented levels of granularity allows for the development of data-driven algorithms to improve the estimation of solar energy generation and production. In this paper, we develop a prediction of solar potential across large photovoltaic panels from the roof tops using a machine learning method. The Restricted Boltzmann Machine (RBM) is the machine learning method used in the study to predict or forecast the solar potential in rooftops. The machine learning model is supplied with training dataset to get trained with the dataset for conversion into the model and then tested with the test dataset for validating the model. The results of simulation are conducted on R-package over various libraries to predict the rooftop solar potential. The results of simulation shows that the proposed method achieves higher rate of prediction accuracy than the other methods. The results of the simulation show that the proposed method achieves a higher rate of prediction accuracy of 99% than the other methods.
Study on High‐Temperature Behavior of Coal Gangue‐Based Geopolymer Concrete Beams
Authors: Zhang Daming , Xu Jiaqing , Sun Fangjin , Xu Zhonghao
Published: May 2022

A newly coal gangue‐based geopolymer concrete made from alkaline dry powder activator, coal gangue, and fly ash has been proposed by the authors. High‐temperature behavior of the proposed geopolymer concrete beams with different cross sections reinforced with steel bars is investigated in the work here. High‐temperature behavior by numerical simulation is validated by the existing experiment. High‐temperature behavior is investigated by analysing the geopolymer concrete beams with different cross section dimensions. Temperature distribution and deformation of the beams from room temperature to fairly high temperature are studied. The isotherm contours of beams at different temperatures and the thermal stress contours of the beam at different time steps are obtained and analyzed. First, cracking load and ultimate load of the geopolymer beams with different concrete cover thicknesses are analyzed under different high temperature conditions. It is found that the temperature at the cross section centerline of coal gangue‐based geopolymer concrete beam gradually decreases along the vertical direction. The cracking load and ultimate load of the geopolymer concrete beams at high temperature are affected by the thickness of concrete cover. With the increase of temperature, the mid‐span deflection of the beam increases gradually. High temperature is a key factor for analysing the behaviors of coal gangue‐based geopolymer concrete beams.
Clinical Analysis of 137 Cases of Ovarian Tumors in Pregnancy
Authors: Yin Qi , Zhong Min , Wang Zhihui , Sheng XiuJie
Published: May 2022

Ovarian tumors do not really typically occur in association with pregnant; however, once they do, the treatment is critical. It is important to note that around 6% of ovarian tumors in pregnancies are cancerous. The problems induced by ovarian tumors in pregnancy particularly necessitate rapid medical intervention and are much more frequent than cancer. Medication choices and survival of ovary tumor patients could be influenced by varied diagnoses of ovarian masses. So, we present an upgraded logistic regression (ULR) approach in this paper. Initially, the collection of 137 patient datasets was employed in screening test to identify the ovarian tumor as benign-tumor and malignant-tumor by using contrast-enhanced ultrasonography (CEU) method. Then, the screening test images are preprocessed using wavelet transform (WT) approach. The preprocessed data are extracted by using local binary pattern (LBP) and laws’ texture energy (LTE) techniques. Finally, the clinical analysis of the ovarian tumor can be obtained by the proposed ULR approach. The performances were examined and compared with existing approaches to achieve the proposed approach with greatest correctness. The findings are depicted by utilizing the MATLAB tool.
Sports Town Development Strategy Driven by the Sports Industry and Multi-Industry Integration
Authors: Deng Kui
Published: May 2022

Many sports towns have emerged in China in recent years, and the prerequisite for their healthy development requires a suitable investment strategy. Therefore, this article constructs an optimal decision model in which the sports industry is the primary industry, promoting the development of other industries. The results show that subsidies from higher levels of government can incentivize sports towns to invest in sports capital; there is a complementary relationship between the sports capital and other capital investments and sports product marketing efforts; as the subsidy rate increases, profits of the towns and the social benefits created show an inverted U-shape. Choosing the correct subsidy rate is essential for both the towns and their parent government. The research framework and results provide a valuable tool for sports towns and their parent governments to make decisions and adapt their strategies to changing circumstances timely.
Design Optimization of Curved Curtain Wall Based on SPEA II‐GA‐BPNN Algorithm
Authors: Zou YiQuan , Huang HaoZhou , Xia XuYong , Wang Xin
Published: May 2022

The optimization of the design of the curved curtain wall to reduce the construction cost can bring about huge economic benefits to the curtain wall project. This paper breaks through the current practice of cost optimization only in the detailed design stage. Based on the characteristics of optimization objectives in different stages, a composite scheme process is proposed, which uses the combination of SPEA II multiobjective algorithm and GA single‐objective algorithm for design optimization. It predicts and evaluates the optimization scheme by BP neural network. The panel meshing scheme is first optimized in the scheme design stage using the SPEA II multiobjective algorithm. The panel meshing scheme is first optimized in the scheme design stage using the SPEA II multiobjective algorithm. The best optimization results are then screened using the GA single‐objective algorithm to optimize the panel type in the detailed design stage. Afterwards, BP neural network training samples are randomly generated in all the optimization schemes, and the BP neural network is trained. The trained BP neural network model is used to predict and select the optimal solution in the solution set. Finally, the initial solution, existing optimization solution, and compound optimization solution are compared and analyzed. The obtained results show that the proposed composite optimization scheme can effectively reduce the cost of panel and keel materials by almost 10%. It can provide new ideas and methods for the design of curved curtain walls.
Diagnosis of Idiopathic Premature Ovarian Failure by Color Doppler Ultrasound under the Intelligent Segmentation Algorithm
Authors: Yu Lanlan , Qing Xiaofeng
Published: May 2022

The aim of this study was to explore the application value of transvaginal color Doppler ultrasound based on the improved mean shift algorithm in the diagnosis of idiopathic premature ovarian failure (POF). In this study, 80 patients with idiopathic POF were selected and included in the experimental group, and 40 volunteers who underwent health examinations during the same period were selected and included in the control group, who underwent transvaginal Doppler ultrasound examination. At the same time, an improved mean shift algorithm was proposed based on artificial intelligence technology and applied to ultrasound image processing. In addition, the ovarian artery parameters of patients were compared in two groups, including peak systolic flow rate (PSV), diastolic flow rate (EDV), resistance index (RI), and pulsatile index (PI). The results showed that the relative difference degree (RDD) of the segmentation results of the algorithm in this study was significantly lower than that of Snake, Live_wire, and the traditional mean shift algorithm, while the relative overlap degree (ROD) and Dice coefficient were opposite, and the differences were significant (P<0.05). The mediolateral diameter of control group was 2.87±0.31cm, and the anteroposterior diameter was 1.86±0.28 cm; while those were 2.11±0.36 cm and 1.13±0.34 cm, respectively, in the experimental group, showing significant differences between the groups (P<0.05). Of the 80 patients in the experimental group, 132 cases with ovarian arteries were found; among 40 patients in the experimental group, 76 cases were found with ovarian arteries, and the hemodynamic detection rate of the experimental group was significantly lower than that of the control group (P<0.05). The ovarian artery parameters PI, RI, and S/D of the experimental group were significantly higher than those of the control group, and the differences were statistically significant (P<0.05). The results showed that the segmentation results of the improved algorithm in this study were more superior to the segmentation results of other algorithms. The regional information loss of the segmentation results was not serious, and the resolution was higher and the definition was higher. The transvaginal color Doppler ultrasound based on the artificial intelligence segmentation algorithm can clearly show the functional status and hemodynamics of the patient’s ovaries. The ovarian artery parameters PI and RI can be used as specific indicators for evaluating the POF.
Automatic Target Recognition of SAR Images Using Collaborative Representation
Authors: Hu Jinge
Published: May 2022

Synthetic aperture radar (SAR) automatic target recognition (ATR) is one of the key technologies for SAR image interpretation. This paper proposes a SAR target recognition method based on collaborative representation-based classification (CRC). The collaborative coding adopts the global dictionary constructed by training samples of all categories to optimally reconstruct the test samples and determines the target category according to the reconstruction error of each category. Compared with the sparse representation methods, the collaborative representation strategy can improve the representation ability of a small number of training samples for test samples. For SAR target recognition, the resources of training samples are very limited. Therefore, the collaborative representation is more suitable. Based on the MSTAR dataset, the experiments are carried out under a variety of conditions and the proposed method is compared with other classifiers. Experimental results show that the proposed method can achieve superior recognition performance under the standard operating condition (SOC), configuration variances, depression angle variances, and a small number of training samples, which proves its effectiveness.