bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of supervised physiotherapy versus home exercise in subjects with rotator cuff disorders treated surgically: A systematic review and meta‐analysis
Authors: Gutiérrez‐Espinoza Héctor , Araya‐Quintanilla Felipe , Olguín‐Huerta Cristian , Valdés‐Orrego Iván , Sepúlveda‐Osses Oscar 
Published: February 2022

AbstractObjectiveThe aim is to determine the effectiveness of supervised Physiotherapy (PT) versus a home exercise program for functional outcomes in patients with rotator cuff (RC) disorders treated surgically.TypeSystematic review and meta‐analysis of randomized clinical trials.MethodologyAn electronic search was performed in the MEDLINE, CENTRAL, EMBASE, PEDro, LILACS, CINAHL, SPORTDiscus, and Web of Science databases. The eligibility criteria for selecting studies included randomized clinical trials that compared supervised PT versus home exercises in functional outcomes, such as shoulder or upper limb function, pain intensity, and range of motion, in subjects older than 18 years with RC disorders treated surgically.SynthesisSix trials met the eligibility criteria, and for the quantitative synthesis, five studies were included. At 3 months, the mean difference (MD) for the Constant‐Murley questionnaire (0–100 points) was −0.76 points (95% confidence interval (CI) = −15.64 to 14.12, p = 0.92), while the MD for the visual analog scale (0–10 cm) was −0.87 cm (95% CI = −2.8 to 1.06, p = 0.38). These differences were neither clinically nor statistically significant.ConclusionThere was very low quality of evidence towards no better benefits in shoulder pain and function of supervised PT over home exercises programs in patients older than 18 years with RC disorders treated surgically.PROSPERO registrationCRD42020185805.
Quintessence and the Swampland: The Parametrically Controlled Regime of Moduli Space
Authors: Cicoli Michele , Cunillera Francesc , Padilla Antonio , Pedro Francisco G. 
Published: February 2022

AbstractWe provide evidence that slow roll is not possible in any parametrically controlled regime of the moduli space of string theory. This is proven in full generality in the asymptotic limit of the moduli space of type II and heterotic Calabi‐Yau compactifications for the dilaton and any number of Kähler moduli. Our results suggest that in order to build quintessence into string theory one must work in the interior of moduli space where numerical, even if not parametric, control could still be achieved.
A novel natural PPARγ agonist, Gypenoside LXXV, ameliorates cognitive deficits by enhancing brain glucose uptake via the activation of Akt/GLUT4 signaling in db/db mice
Authors: Meng Xiangbao , Zhang Yuan , Li Zongyang , Hu Jinxian , Zhang Di , Cao Weiwei , Li Min , Ma Guoxu , Wang Sicen , Cui Ping , Cai Qian , Huang Guodong 
Published: February 2022

AbstractTargeting the PPARγ might be a potential therapeutic strategy for diabetes‐associated cognitive decline (DACD). In this study, Gypenoside LXXV (GP‐75), a dammarane‐type triterpene compound isolated from Gynostemma pentaphyllum, was found to be a novel PPARγ agonist using a dual‐luciferase reporter assay system. However, whether GP‐75 has protective effects against DACD remains unknown. Interestingly, intragastric administration of GP‐75 (40 mg/kg/day) for 12 weeks significantly attenuated the cognitive deficit in db/db mice. GP‐75 treatment significantly improved the glucose tolerance and lipid metabolism, and suppressed neuroinflammation. Notably, GP‐75 treatment dramatically increased the uptake of glucose by the brain, as detected by 18F‐FDG PET. Incubation of primary cortical neurons with GP‐75 significantly increased 2‐deoxyglucose uptake. In addition, GP‐75 treatment markedly increased the p‐Akt (Ser 473)/total Akt levels and the expression levels of PPARγ and GLUT4, while decreasing the levels of p‐IRS‐1 (Ser 616)/total IRS‐1. Importantly, all of these protective effects mediated by GP‐75 were abolished by cotreatment with the PPARγ antagonist, GW9662. However, GP‐75‐mediated PPARγ upregulation was not affected by coincubation with the phosphatidylinositol 3‐kinase inhibitor, LY294002. Collectively, GP‐75 might be a novel PPARγ agonist that ameliorates cognitive deficit by enhancing brain glucose uptake via the activation of Akt/GLUT4 signaling in db/db mice.
The effects of lycopene supplementation on insulin‐like growth factor‐1 and insulin‐like growth factor binding proteins: A systematic review of randomized controlled trials
Authors: Meshkini Fatemeh , Ramezani‐Jolfaie Nahid , Sargazi Saman , Clark Cain C.T. , Soltani Sepideh 
Published: February 2022

AbstractLycopene has been posited to regulate insulin‐like growth factor‐1 (IGF‐1). We aimed to conduct a systematic review of the effects of lycopene on circulating IGF‐1 and insulin‐like growth factor binding proteins (IGFBPs) in adults. A systematic search was carried out in PubMed, Scopus, ISI Web of Science, and the Cochrane Library databases for randomized controlled trials (RCTs), published from inception until March 2020. A total of 11 studies fulfilled the selection criteria. Eleven studies examined the effect of lycopene supplementation on IGF‐1, one of which reported a significant reduction. Moreover, three, four, and ten studies were found for IGFBP‐1, IGFBP‐2, and IGFBP‐3, respectively; where one study found a significant increase in these proteins. In conclusion, no consistent modifying effect of lycopene supplementation on IGF‐1 and IGFBPs levels are evident in the literature. More research is needed to explore the effect of lycopene on IGF‐1 system.
Challenges encountered during the systematic review of newer and enhanced influenza vaccines and recommendations for the future
Authors: Teljeur Conor , Comber Laura , Jordan Karen , Murchu Eamon O. , Harrington Patricia , O'Neill Michelle , Ryan Máirín 
Published: February 2022

AbstractThere are a variety of challenges in the conduct of systematic reviews of influenza vaccines. We describe our experience of completing four systematic reviews of newer and enhanced inactivated seasonal influenza vaccines. The reporting of the included studies created significant challenges for study identification, data extraction and analysis. Those challenges have implications for the resources required to conduct reviews and, more significantly, for the accuracy of the estimated treatment effect. There is a substantial burden of morbidity and mortality associated with seasonal influenza, and the evidence used to support vaccination strategies requires regular review. An improved review process will facilitate robust decision‐making both nationally and internationally. We recommend the development of reporting guidelines, increased engagement between researchers and decision makers, a database of identified trials, and research into search optimisation.
Consensus tracking control for uncertain non‐strict feedback multi‐agent system under cyber attack via resilient neuroadaptive approach
Authors: Ma Xiaoshan , Yang Lin , Ma Linru , Dong Wenhan , Jin Ming , Zhang Long , Yang Feng , Lin Yan 
Published: February 2022

AbstractMulti‐agent system (MAS) is a common cyber‐physical system (CPS). Due to it often uses a relatively open network platform, it is vulnerable to malicious cyber attacks in the process of system operation, so the control scheme design is critical to ensure the system operation security. In this article, we propose a new resilient neuroadaptive dynamic surface control scheme for non‐linear MASs with potential cyber attacks (false data injection and denial‐of‐service), system uncertainty, unknown control gain, and output constraints which are usually seen on CPSs. In this scheme, the neuroadaptive controller design ensures that all signals of the closed loop system are semi‐globally uniform ultimately bounded when the MAS even exists time‐varying cyber attacks on data links among agents, and the links between controllers, actuators, and sensors. Using Gaussian radial basis function neural network, the system uncertainty, non‐strict feedback terms, unknown control gain, and some cyber attacks are effectively solved and the process of controller design is extremely simplified. Finally, we provide a simulation result to verify the effectiveness and superiority of the proposed control scheme.
The Investigation of Hydrogen Adsorption in MOF NU‐1501 with Different Metal Doping using Molecular Simulations
Authors: Lv Junnan , Wang Ming , Chen Xia , Qin Hongyun , Li Yongjie , Yang Kun , Zhang Hui , Zhang Qicheng , Fu Peng , Fu Qiang , Zhao Zengdian 
Published: February 2022

AbstractMetal‐organic frameworks with high surface areas are currently being widely used for in‐depth studies on hydrogen storage with the aim of discussing the difficulties created by environmental degradation caused by the burning of fossil fuels. Understanding the effect of varied metal ion doping on adsorption position and energy is crucial to understanding the adsorption process. The adsorption behavior of NU‐1501‐Al and NU‐1501‐Fe was investigated using a combination of Grand Canonical Monte Carlo and Density Functional Theory in this study. The calculations reveal that aluminum has a larger charge than iron and higher adsorption energy. As the loading increases, hydrogen is primarily adsorbed by metal atoms and the carbon atoms of the metal‐benzene ring are connected to metal‐oxygen atoms. The research hopes to provide molecular‐level insights into the adsorption behavior of porous materials doped with different metals, which could be used to screen materials that improve gas adsorption, separation, and other expansion characteristics.
Mild and Metal‐Free Cross‐Dehydrogenative Coupling of Nitrogen Heteroarenes with Aldehydes Enabled by Structural Hybridization of Promoting Reagents
Authors: Zhao Jianhong , Qian Kun , Tong Mengchao , Yuan Qiyang , Zhang Yongqiang 
Published: February 2022

AbstractA mild and metal‐free cross‐dehydrogenative coupling reaction of nitrogen heteroarenes with aldehydes has been developed by the structural hybridization of promoting reagents. The procedure is environmentally benign, cost‐effective and industrially scalable, which allows the direct acylation of electron‐deficient nitrogen heteroarenes in moderate to good yields. Furthermore, the synthetic utility of this new method in the synthesis of a variety of pharmaceutically relevant isoquinoline alkaloids has been also demonstrated.
The role of resilience in depression and anxiety symptoms: A three‐wave cross‐lagged study
Authors: Lau Way K. W. 
Published: February 2022

AbstractCultivation of resilience is believed to ameliorate mental health problems. The impact of mental health problems on resilience is however rarely discussed. This study investigated the reciprocal relationship of resilience with depression and anxiety symptoms using a three‐wave cross‐lagged design. Resilience level, depression, and anxiety symptoms were assessed at baseline, the third and the sixth month in 125 university students without psychiatric disorders (62 females). No significant changes in resilience levels were observed across the 6 months. Depressive symptoms, but not anxiety symptoms significantly increased at the third and sixth months compared with baseline. The three‐wave cross‐lagged models revealed an unstable reciprocal relationship of resilience with depression and a stable reciprocal relationship between resilience and anxiety symptoms over time. The reciprocal relationship between resilience and mental health problems indicates the importance of cultivating resilience for the prevention of mental illness as well as the importance of managing mental health symptoms at non‐clinical levels for monitoring resilience. The unstable reciprocal relationship between resilience and depression symptoms across time suggests the existence of potential moderators that impact the relationship between resilience and depression. Our findings further support the notion that resilience is conceptualized as a dynamic process.
Structure Engineering of Vanadium Tetrasulfides for High‐Capacity and High‐Rate Sodium Storage
Authors: Yang Dan , Zhang Shipeng , Yu Pei , Cheng Siling , Yuan Zishun , Jiang Yu , Sun Wenping , Pan Hongge , Feng Yuezhan , Rui Xianhong , Yu Yan 
Published: February 2022

AbstractStructure engineering of electrode materials can significantly improve the life cycle and rate capability of the sodium‐ion battery (SIB), yet remains a challenging task due to the lack of an effective synthetic strategy. Herein, the microstructure of VS4 hollow spheres is successfully engineered through a facile hydrothermal method. The hollow VS4 microspheres possess rich porosity and are covered with 2D ultrathin nanosheets on the surface. The finite element simulation (FES) reveals that such heterostructures can effectively relieve the stress induced by the sodiation and thereby enhance the structural integrity. The SIB with the hollow VS4 microspheres as anode displays impressively high specific capacity, excellent stability upon ultra‐long cycling, and extraordinary rate capacity, e.g., a reversible capacity of ≈378 mA h g−1 at ultra‐high 10 A g−1, while retaining 73.2% capacity after 1000 cycles. The Na storage mechanism is also elucidated through in situ/ex situ characterizations. Moreover, the hollow VS4 microspheres demonstrate reliable rate performance at a low temperature of −40 °C (e.g., the capacity is ≈163 mA h g−1 at 2 A g−1). This work provides novel insights toward high‐performance SIBs.
Carrageenan‐Based Hybrids with Biopolymers and Nano‐Structured Materials for Biomimetic Applications
Authors: Qamar Sarmad Ahmad , Junaid Muhammad , Riasat Areej , Jahangeer Muhammad , Bilal Muhammad , Mu Bo‐Zhong 
Published: February 2022

AbstractCarrageenan is an algal‐originated group of polysaccharides with unusual structural and functional capabilities, desired for different biomimetic applications due to their renewable, biocompatible, and biodegradable nature. Carrageenan‐based hybrids (nano‐/biocomposites) with different biopolymers and nano‐structured materials have been widely reported as potential candidates for bone/cartilage tissue engineering, delivery of drugs/bioactive ingredients, wound healing, and 3D bioprinting applications. Owning to the broad‐scale biomimetic applications of carrageenan‐based materials, this review aims to summarize carrageenan chemistry and distinct physicochemical features of biopolymeric and/or nanostructured materials‐based on carrageenans in a detailed manner. Herein, different biopolymers (such as chitosan, cellulose, starch, and alginates), and nano‐structured materials (such as silica nanoparticles, magnetic/non‐magnetic nanocarriers, graphene oxide nanoparticles, carbon nanotubes/nanorods, metal oxide nanoparticles) are comprehensively described in combination with carrageenan. However, carrageenan toxicity studies have presented major challenges that need to be addressed when using carrageenan‐based materials for biomedical and therapeutic purposes. Several existing challenges, prospects, and research recommendations are described at the end of this review.
Diosmetin alleviates cerebral ischemia‐reperfusion injury through Keap1‐mediated Nrf2/ARE signaling pathway activation and NLRP3 inflammasome inhibition
Authors: Shi Min , Wang Jianqiang , Bi Fangfang , Bai Zhangyong 
Published: February 2022

AbstractDiosmetin was found to exert protective effect on renal and myocardial ischemia‐reperfusion (IR) injury. This study aimed to investigate the role of diosmetin in cerebral IR (CIR) injury. PC12 neurons were exposed to oxygen–glucose deprivation/reoxygenation (OGD/R) to establish CIR injury model in vitro and then incubated with diosmetin, and we found that diosmetin alleviated OGD/R‐induced viability inhibition, LDH release, apoptosis, and oxidative stress in PC12 cells. Then our results showed that diosmetin downregulated kelch like ECH‐associated protein 1 (Keap1) expression, and upregulated nuclear factor E2‐related factor 2 (Nrf2) expression, antioxidant response element (ARE) activity and the mRNA and protein expression of heme oxygenase 1 (HO‐1) and NAD(P)H: quinone oxidoreductase 1 (NQO1). Keap1 overexpression or Nrf2 silencing both attenuated the neuroprotective effect of diosmetin on PC12 cells. Moreover, diosmetin inhibited the levels of nucleotide‐binding oligomerization domain (NOD)‐like receptor (NLR) pyrin domain containing 3 (NLRP3) inflammasome pathway related proteins and inflammatory cytokines interleukin (IL)‐1β and IL‐18. Additionally, a middle cerebral artery occlusion (MCAO) rat model was established and diosmetin was injected for treatment. Diosmetin alleviated CIR‐induced neurological deficits, cerebral infarction, brain edema and histopathological damage, and neuronal apoptosis and oxidative stress in MCAO rats. In conclusion, diosmetin attenuated OGD/R‐induced PC12 cell viability inhibition, apoptosis, oxidative stress and inflammation through Keap1‐mediated Nrf2/ARE signaling activation and NLRP3 inflammasome inhibition, and alleviated CIR‐induced neurological injury in MCAO rat model. Our study may provide a novel therapeutic strategy for CIR injury.
Improvement of biomass aggregation in sludge bulking by magnetic field application
Authors: Zaidi Nur Syamimi , Zhan Loh Zhang , Bahrodin Muhammad Burhanuddin , Hussein Norelyza , Awang Nik Azimatolakma , Kadier Abudukeremu 
Published: February 2022

AbstractHigh biomass aggregation is commonly associated with good solid–liquid separation that can inhibit the occurrence of sludge bulking. The application of magnetic fields in the removal of pollutants has been studied previously but the relation between a magnetic field with biomass aggregation and its effect on pollutant removal efficiency receives very little attention. This present study was conducted to analyze the effect of the magnetic field toward biomass aggregation that can eventually contribute to the good removal performance of the pollutants. Two continuous laboratory‐scale sequencing batch reactors known as Reactor A and Reactor B were set up. Reactor A was equipped with an 88 mT magnetic field while Reactor B acted as the control. Reactor A recorded higher biomass aggregation with the range of 75.0–95.2% compared to Reactor B which possessed mostly medium aggregation with an average of 65.5%. As a result, lower sludge volume index (SVI) was recorded in Reactor A (25.8 ml/g) compared to Reactor B (73.1 ml/g). Likewise, Reactor A showed significantly higher chemical oxygen demand (COD) and ammonia‐nitrogen removal compared to Reactor B. These findings imply that the magnetic field successfully improves biomass aggregation, therefore improving the removal performance under the sludge bulking occurrence.
Boundary stabilization for axially moving Kirchhoff string under fractional PI control
Authors: Cheng Yi , Guo Bao‐Zhu , Wu Yuhu 
Published: February 2022

AbstractIn this paper, we investigate vibration control for an axially moving Kirchhoff string. A fractional PI boundary control is applied transversally to the right boundary and the transverse vibration of the system is shown to be suppressed. By constructing an auxiliary equivalent system (PDE‐ODE) and a novel energy like function, the well‐posedness and exponential stability of the closed‐loop system are established by means of the Faedo‐Galerkin method and the Lyapunov method. The effectiveness of the proposed controller is verified by a numerical simulation using finite element method.
Introduction
Authors: Brazdil Pavel , van Rijn Jan N. , Soares Carlos , Vanschoren Joaquin 
Published: February 2022

SummaryThis chapter starts by describing the organization of the book, which consists of three parts. Part I discusses some basic concepts, including, for instance, what metalearning is and how it is related to automatic machine learning (AutoML). This continues with a presentation of the basic architecture of metalearning/AutoML systems, discussion of systems that exploit algorithm selection using prior metadata, methodology used in their evaluation, and different types of meta-level models, while mentioning the respective chapters where more details can be found. This part also includes discussion of methods used for hyperparameter optimization and workflow design. Part II includes the discussion of more advanced techniques and methods. The first chapter discusses the problem of setting up configuration spaces and conducting experiments. Subsequent chapters discuss different types of ensembles, metalearning in ensemble methods, algorithms used for data streams and transfer of meta-models across tasks. One chapter is dedicated to metalearning for deep neural networks. The last two chapters discuss the problem of automating various data science tasks and trying to design systems that are more complex. Part III is relatively short. It discusses repositories of metadata (including experimental results) and exemplifies what can be learned from this metadata by giving illustrative examples. The final chapter presents concluding remarks.
Metalearning in Ensemble Methods
Authors: Brazdil Pavel , van Rijn Jan N. , Soares Carlos , Vanschoren Joaquin 
Published: February 2022

AbstractThis chapter discusses some approaches that exploit metalearning methods in ensemble learning. It starts by presenting a set of issues, such as the ensemble method used, which affect the process of ensemble learning and the resulting ensemble. In this chapter we discuss various lines of research that were followed. Some approaches seek an ensemble-based solution for the whole dataset, others for individual instances. Regarding the first group, we focus on metalearning in the construction, pruning and integration phase. Modeling the interdependence of models plays an important part in this process. In the second group, the dynamic selection of models is carried out for each instance. A separate section is dedicated to hierarchical ensembles and some methods used in their design. As this area involves potentially very large configuration spaces, recourse to advanced methods, including metalearning, is advantageous. It can be exploited to define the competence regions of different models and the dependencies between them.
Concluding Remarks
Authors: Brazdil Pavel , van Rijn Jan N. , Soares Carlos , Vanschoren Joaquin 
Published: February 2022

SummaryAs metaknowledge has a central role in many approaches discussed in this book, we address the issue of what kind of metaknowledge is used in different metalearning/AutoML tasks, such as algorithm selection, hypeparameter optimization, and workflow generation. We draw attention to the fact that some metaknowledge is acquired (learned) by the systems, while other is given (e.g., different aspects of the given configuration space). This chapter continues by discussing future challenges, such as how to achieve better integration of metalearning and AutoML approaches, and what kind of guidance could be provided by the system when configuring metalearning/AutoML systems to new settings. This task may involve (semi-)automatic reduction of configuration spaces to make the search more effective. The last part of this chapter discusses various challenges encountered when trying to automate different steps of data science.