bluuebunny/crossref_metadata_2025 huggingface dataset:
Reducing Overestimating and Underestimating Volatility via the Augmented Blending-ARCH Model
Authors: Lu Jun , Yi Shao
Published: April 2022

SVR-GARCH model tends to “backward eavesdrop” when forecasting the financial time series volatility in which case it tends to simply produce the prediction by deviating the previous volatility. Though the SVR-GARCH model has achieved good performance in terms of various performance measurements, trading opportunities, peak or trough behaviors in the time series are all hampered by underestimating or overestimating the volatility. We propose a blending ARCH (BARCH) and an augmented BARCH (aBARCH) model to overcome this kind of problem and make the prediction towards better peak or trough behaviors.The method is illustrated using real data sets including SH300 and S&P500. The empirical results obtained suggest that the augmented and blending models improve the volatility forecasting ability.
Gobernanza urbana y resolución de problemas urbanísticos: algunas evidencias a partir del caso de Puerto Montt (Chile)
Authors: Burgdorf Annika , Prada Trigo José
Published: April 2022

El fuerte crecimiento urbano en las últimas décadas en varias ciudades chilenas, junto con la aparición de nuevos problemas de origen diverso, ponen en cuestión la relevancia de la contribución de la gobernanza en este contexto. Con ese trasfondo, el presente estudio se plantea como un análisis del caso de Puerto Montt, especialmente sensible por haber vivido un auge de la salmonicultura desde la década de los 80, que junto con el crecimiento urbano habría generado una serie de externalidades negativas. Éstas, aparecen junto con un Plan Regulador Comunal obsoleto y un modelo político muy centralista. A través de una metodología mediante entrevistas en profundidad a actores clave, se analiza e interpreta la capacidad de la gobernanza urbana para resolver los principales temas críticos identificados. Los resultados, señalan al modelo político fuertemente centralista como principal limitador de la capacidad para establecer soluciones colectivas.
Introduction to the special issue on ocean acoustics in the changing arctic
Authors: Worcester Peter F. , Badiey Mohsen , Sagen Hanne
Published: April 2022

This paper introduces the Special Issue of The Journal of the Acoustical Society of America on Ocean Acoustics in the Changing Arctic. The special issue includes papers on ocean (and in one case atmospheric) acoustics. Changes in both the ice cover and ocean stratification have significant implications for acoustic propagation and ambient sound. The Arctic is not done changing, and papers in this special issue, therefore, represent a snapshot of current acoustic conditions in the Arctic.
Nonlinear rheology of entangled wormlike micellar solutions predicted by a micelle-slip-spring model
Authors: Sato Takeshi , Larson Ronald G.
Published: April 2022

We examine linear and nonlinear shear and extensional rheological properties using a “micelle-slip-spring model” [T. Sato et al., J. Rheol. 64, 1045–1061 (2020)] that incorporates breakage and rejoining events into the slip-spring model originally developed by Likhtman [Macromolecules 38, 6128–6139 (2005)] for unbreakable polymers. We here employ the Fraenkel potential for main chain springs and slip-springs to address the effect of finite extensibility. Moreover, to improve extensional properties under a strong extensional flow, stress-induced micelle breakage (SIMB) is incorporated into the micelle-slip-spring model. Thus, this model is the first model that includes the entanglement constraint, Rouse modes, finite extensibility, breakage and rejoining events, and stress-induced micelle breakage. Computational expense currently limits the model to micellar solutions with moderate numbers of entanglements (≲7), but for such solutions, nearly quantitative agreement is attained for the start-up of the shearing flow. The model in the extensional flow cannot yet be tested owing to the lack of data for this entanglement level. The transient and steady shear properties predicted by the micelle-slip-spring model for a moderate shear rate region without significant chain stretch are fit well by the Giesekus model but not by the Phan–Thien/Tanner (PTT) model, which is consistent with the ability of the Giesekus model to match experimental shear data. The extensional viscosities obtained by the micelle-slip-spring model with SIMB show thickening followed by thinning, which is in qualitative agreement with experimental trends. Additionally, the extensional rheological properties of the micelle-slip-spring model with or without SIMB are poorly predicted by both the Giesekus and the PTT models using a single nonlinear parameter. Thus, future work should seek a constitutive model able to capture the behavior of the slip-spring model in shear and extensional flows and so provide an accurate, efficient model of micellar solution rheology.
Children’s Motivation Profiles in Sports and Physical Activities: A Latent Profile Analysis and Self-Determination Theory Approach
Authors: Lohbeck Annette , Hohmann Andreas , von Keitz Philipp , Daseking Monika
Published: April 2022

Using latent profile analysis and self-determination theory, the present study aimed to examine younger children’s motivation profiles in sports and physical activities and the relations of those profiles to various predictors and achievement outcomes. A total of 1,116 German children from Grade 2 participated in this study. Latent-profile-analysis solutions based on five behavioral-regulation types covered in self-determination theory (i.e., intrinsic, identified, introjected, external, amotivation) were tested. Results favored a three-profile solution, showing three theoretically meaningful and distinct motivation profiles labeled “amotivated,” “non-self-determined,” and “self-determined.” Older children and children with a lower physical self-concept were more likely to be members of the amotivated profile relative to the other profiles than younger children and children with a higher physical self-concept. Furthermore, children of the self-determined profile demonstrated the best physical performance in various motor-skills tests.
Engineering a living cardiac pump on a chip using high-precision fabrication
Authors: Michas Christos , Karakan M. Çağatay , Nautiyal Pranjal , Seidman Jonathan G. , Seidman Christine E. , Agarwal Arvind , Ekinci Kamil , Eyckmans Jeroen , White Alice E. , Chen Christopher S.
Published: April 2022

Biomimetic on-chip tissue models serve as a powerful tool for studying human physiology and developing therapeutics; however, their modeling power is hindered by our inability to develop highly ordered functional structures in small length scales. Here, we demonstrate how high-precision fabrication can enable scaled-down modeling of organ-level cardiac mechanical function. We use two-photon direct laser writing (TPDLW) to fabricate a nanoscale-resolution metamaterial scaffold with fine-tuned mechanical properties to support the formation and cyclic contraction of a miniaturized, induced pluripotent stem cell–derived ventricular chamber. Furthermore, we fabricate microfluidic valves with extreme sensitivity to rectify the flow generated by the ventricular chamber. The integrated microfluidic system recapitulates the ventricular fluidic function and exhibits a complete pressure-volume loop with isovolumetric phases. Together, our results demonstrate a previously unexplored application of high-precision fabrication that can be generalized to expand the accessible spectrum of organ-on-a-chip models toward structurally and biomechanically sophisticated tissue systems.
Nanoalloy libraries from laser-induced thermionic emission reduction
Authors: Jiang Haoqing , Liu Xingtao , Zhu Meng-Nan , Xu Jin , An Licong , Sui Peng-Fei , Luo Jing-Li , Cheng Gary J.
Published: April 2022

Nanoalloys, especially high-entropy nanoalloys (HENAs) that contain equal stoichiometric metallic elements in each nanoparticle, are widely used in vast applications. Currently, the synthesis of HENAs is challenged by slow reaction kinetics that leads to phase segregation, sophisticated pretreatment of precursors, and inert conditions that preclude scalable fabrication of HENAs. Here, we report direct conversion of metal salts to ultrafine HENAs on carbonaceous support by nanosecond pulsed laser under atmospheric conditions. Because of the unique laser-induced thermionic emission and etch on carbon, the reduced metal elements were gathered to ultrafine HENAs and stabilized by defective carbon support. This scalable, facile, and low-cost method overcomes the immiscible issue and can produce various HENAs uniformly with a size of 1 to 3 nanometers and metal elements up to 11 with productivity up to 7 grams per hour. One of the senary HENAs exhibited excellent catalytic performance in oxygen reduction reaction, manifesting great potential in practical applications.
Ultrahigh strength, modulus, and conductivity of graphitic fibers by macromolecular coalescence
Authors: Lee Dongju , Kim Seo Gyun , Hong Seungki , Madrona Cristina , Oh Yuna , Park Min , Komatsu Natsumi , Taylor Lauren W. , Chung Bongjin , Kim Jungwon , Hwang Jun Yeon , Yu Jaesang , Lee Dong Su , Jeong Hyeon Su , You Nam Ho , Kim Nam Dong , Kim Dae-Yoon , Lee Heon Sang , Lee Kun-Hong , Kono Junichiro , Wehmeyer Geoff , Pasquali Matteo , Vilatela Juan J. , Ryu Seongwoo , Ku Bon-Cheol
Published: April 2022

Theoretical considerations suggest that the strength of carbon nanotube (CNT) fibers be exceptional; however, their mechanical performance values are much lower than the theoretical values. To achieve macroscopic fibers with ultrahigh performance, we developed a method to form multidimensional nanostructures by coalescence of individual nanotubes. The highly aligned wet-spun fibers of single- or double-walled nanotube bundles were graphitized to induce nanotube collapse and multi-inner walled structures. These advanced nanostructures formed a network of interconnected, close-packed graphitic domains. Their near-perfect alignment and high longitudinal crystallinity that increased the shear strength between CNTs while retaining notable flexibility. The resulting fibers have an exceptional combination of high tensile strength (6.57 GPa), modulus (629 GPa), thermal conductivity (482 W/m·K), and electrical conductivity (2.2 MS/m), thereby overcoming the limits associated with conventional synthetic fibers.
Growth performance and heamatobiochemical parameters of broilers fed diets containing Artemisia afra essential oil
Authors: Zvarivadza William , Marume Upenyu
Published: April 2022

The study was conducted to determine the effects of Artemisia afra Jacq. ex Willd. essential oil inclusion in diets on growth performance and blood parameters in broiler chickens. Four hundred day-old Cobb 500 chicks were randomly allotted to four treatments: NC – negative control (commercial broiler diet without antibiotics), PC – positive control (commercial broiler diet), AA1 – commercial diet + 0.1% A. afra essential oil, and AA2 – commercial diet + 0.3 % A. afra essential oil. Each treatment was replicated 10 times. From the results, birds fed the PC diet had the highest average daily feed intake (105.60 g ± 3.18) and average daily gain (ADG) in the grower phase. The highest ADG in the finisher phase was obtained in the AAI treatment (170.23 g·d−1 ± 2.00), whereas the feed conversion ratio was lower in the essential-oil-containing diets. Diet significantly improved protein utilization efficiency in both grower and finisher phases. Birds fed AA1 had the highest values for neutrophils, monocytes, and eosinophils, whereas those fed the NC diet had the highest alkaline phosphatase levels (102.00 IU·L−1 ± 7.61). The findings of the study suggest the use of A. afra essential oil in broiler diets can positively improve growth and flock health.
Response of alewife abundance to the bacterial kidney disease outbreak in the Chinook salmon population of Lake Michigan: importance of predation
Authors: Madenjian Charles P.
Published: April 2022

Prey fish abundance can be influenced by predation (top-down) and food limitation (bottom-up) effects. I characterized temporal trends in yearling and older (YAO) alewife (Alosa pseudoharengus) biomass density, as estimated by a long-term bottom trawl survey, in Lake Michigan during 1973–2019. Special attention was given to the bacterial kidney disease (BKD) outbreak in the population of Chinook salmon (Oncorhynchus tshawytscha), the predominant predator on alewives in the lake. YAO alewife biomass density exhibited a steep and significant decline during 1973–1985, but then partially rebounded with a significant increase between the 1983–1985 and 1986–2003 (BKD years) periods, followed by a significant decrease between the 1986–2003 and 2004–2006 periods. YAO alewife biomass density showed another significant decline during 2004–2019. The BKD outbreak led to a partial relaxation of predation on the YAO alewife population, and YAO alewife biomass density responded by showing a moderate increase in 1986 and then fluctuating about this moderately higher level for more than 15 years. Overall, temporal trends in YAO alewife biomass density were primarily driven by predation.
Insight into the microscopic structure of a quintessential black hole from the quantization concept
Authors: Aounallah H. , El Moumni H. , Khalloufi J. , Masmar K.
Published: April 2022

In this work, based on [D.-Q. Sun, J.-B. Deng, P. Li and X.-R. Hu, Class. Quantum Grav. 37, 015008 (2020)], we examine the effect of the quintessence field on the microscopic structure of a charged anti-de Sitter (AdS) black hole from the quantization perspective. Indeed, the impact of the state parameter and the quintessence intensity on “energy quantum” is illustrated. Furthermore, we extend the relationship between the number of quanta of the area and the microscopic degrees of freedom of the black hole to the quintessential background. We express the latent heat in terms of the number of quanta of the area of the large black hole (LBH) and the number of quanta of the area of the small black hole (SBH). Besides that, we explore the connection between the microscopic structure and Ruppeiner geothermodynamics in the (mass, pressure)-plane through the number of quanta of area perspective and the quintessence parameters. Finally, we interpret our result in terms of repulsive/attractive interactions amongst the black hole constituents.
An Energy- and Reliability-Aware Task Scheduling in Real-Time MPSoC Systems
Authors: Saberikia Mohammad Reza , Beitollahi Hakem
Published: April 2022

Reliability and energy efficiency are two hostile objectives considered in designing task scheduling in most real-time multiprocessor systems on chip (MPSoC). Addressing and improving one of them may affect and degrade the efficiency of the other one and vice versa. In this paper, we intend to examine these challenges and ultimately achieve an optimal energy consumption and reliability state. This paper presents a novel scheduling technique that can adapt to the limitations of real-time systems and have optimal energy consumption and reliability. This is done by minimizing the overlap of tasks, adjusting the speed of processors and the number of backups of each task. The proposed scheme reduces energy consumption on average by 11% to 42% compared to the previous state-of-the-art techniques and keeps the reliability at a high level.
A COMPREHENSIVE REVIEW ON MINIMUM QUANTITY LUBRICATION IN TURNING PROCESS
Authors: BALASUADHAKAR A. , KUMARAN S. THIRUMALAI , KURNIAWAN RENDI , AHMED FAROOQ
Published: April 2022

The physical health of human beings and the environment will be negatively influenced by the improper use of cutting fluid, which is an important factor for achieving sustainable machining. Turning is a basic process of all machining operations. Using a minimum quantity lubrication (MQL) system is the best way for achieving sustainable turning process. Improvements made in the MQL system to achieve better performance of the turning process have been discussed in this paper. Search categories that have been used to carry out the study are MQL system with the conventional cutting fluid, MQL system with nano-fluid, MQL system with cryogenics and restructured MQL system. The advancements in MQL turning process published over a span of four most recent years from 2018 to 2021 have been chosen for this review. In this study, the details of experimentation such as materials used for the workpiece, cutting tool materials, environments for lubrication, machining parameters, MQL fluids and performance parameters such as surface roughness, tool wear, cutting force, cutting temperature, etc. have been critically considered. Results investigated from various articles mostly show that advanced MQL systems such as MQL system with nano-fluid, MQL system with cryogenics and restructured MQL system are better than the conventional MQL system in terms of producing better output performance.
Quantitative structure–activity relationship modeling reveals the minimal sequence requirement and amino acid preference of sirtuin-1’s deacetylation substrates in diabetes mellitus
Authors: Shao X. , Kong W. , Li Y. , Zhang S.
Published: April 2022

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide ([Formula: see text]-dependent deacetylase involved in multiple glucose metabolism pathways and plays an important role in the pathogenesis of diabetes mellitus (DM). The enzyme specifically recognizes its deacetylation substrates’ peptide segments containing a central acetyl-lysine residue as well as a number of amino acids flanking the central residue. In this study, we attempted to ascertain the minimal sequence requirement (MSR) around the central acetyl-lysine residue of SIRT1 substrate-recognition sites as well as the amino acid preference (AAP) at different residues of the MSR window through quantitative structure–activity relationship (QSAR) strategy, which would benefit our understanding of SIRT1 substrate specificity at the molecular level and is also helpful to rationally design substrate-mimicking peptidic agents against DM by competitively targeting SIRT1 active site. In this procedure, a large-scale dataset containing 6801 13-mer acetyl-lysine peptides (and their SIRT1-catalyized deacetylation activities) were compiled to train 10 QSAR regression models developed by systematic combination of machine learning methods (PLS and SVM) and five amino acids descriptors (DPPS, T-scale, MolSurf, [Formula: see text]-score, and FASGAI). The two best QSAR models (PLS+FASGAI and SVM+DPPS) were then employed to statistically examine the contribution of residue positions to the deacetylation activity of acetyl-lysine peptide substrates, revealing that the MSR can be represented by 5-mer acetyl-lysine peptides that meet a consensus motif [Formula: see text][Formula: see text][Formula: see text](AcK)0[Formula: see text]. Structural analysis found that the [Formula: see text] and (AcK)0residues are tightly packed against the enzyme active site and confer both stability and specificity for the enzyme–substrate complex, whereas the [Formula: see text], [Formula: see text] and [Formula: see text] residues are partially exposed to solvent but can also effectively stabilize the complex system. Subsequently, a systematic deacetylation activity change profile (SDACP) was created based on QSAR modeling, from which the AAP for each residue position of MSR was depicted. With the profile, we were able to rationally design an SDACP combinatorial library with promising deacetylation activity, from which nine MSR acetyl-lysine peptides as well as two known SIRT1 acetyl-lysine peptide substrates were tested by using SIRT1 deacetylation assay. It is revealed that the designed peptides exhibit a comparable or even higher activity than the controls, although the former is considerably shorter than the latter.
Bond Slip in Reinforced Concrete Beam–Column Joints — A Semi-Empirical Implicit Modeling and Possible Influence of Design Standard Compliance
Authors: Basu Dhiman , Lakhani Mohit
Published: April 2022

Bond slip in RC beam–column joints may affect the seismic response or performance assessment of structures considerably. Explicit macroscopic models that satisfy the joint kinematics can be incorporated within a frame model to numerically account for the effect of bond slip. Seismic performance assessment of buildings generally rules out the explicit modeling owing to the associated computational cost. Simplified implicit models are instead preferred owing to the ease of implementation in a commercial finite element (FE) provided the model parameters are calibrated experimentally. Extrapolation of the calibration is generally not valid in other cases with different geometry, sizes and even loading protocols. Most commercial software do not offer the features to explicitly modeling the bond slip. Numerical modeling of bond slip is proposed in this paper that can be conveniently implemented in a commercial software such as Seismostruct. Unlike the prior art, the slip parameter can be extracted using a semiempirical approach preceded by the generation of a numerical database. The proposed framework is also validated against the experimental results of one exterior and one interior beam–column joints. Sample illustration on an example building designed against the same seismic hazard level but following the recommendations per IS 13920, ACI 318 and EC8 is considered for monotonic (without bond slip) and cyclic (with bond slip) pushover analyses. Consideration of bond slip initiates early yielding and results in reduction of secant stiffness at the onset of yielding. The extent of influence depends on the compliance of design standards. For example, relatively higher percentage of reinforcement when designed per IS 13920 (as compared to ACI 318 and EC8) leads to a somewhat lower slip parameter resulting in lesser yield displacement and reduction of secant stiffness at the onset of yielding.
Modeling and analysis of SEIRS epidemic models using homotopy perturbation method: A special outlook to 2019-nCoV in India
Authors: Thomas Reetha , Jose Sayooj Aby , Raja R. , Alzabut J. , Cao Jinde , Balas Valentina E.
Published: April 2022

Considering the prevailing situations, the mathematical modeling and dynamics of novel coronavirus (2019-nCoV) particularly in India are studied in this paper. The goal of this work is to create an effective SEIRS model to study about the epidemic. Four different SEIRS models are considered and solved in this paper using an efficient homotopy perturbation method. A clear picture of disease spreading can be obtained from the solutions derived using this method. We parametrized the model by considering the number of infection cases from 1 April 2020 to 30 June 2020. Finally, numerical analysis and graphical representations are provided to interpret the spread of virus.
Optimal control of combined antiretroviral therapies in an HIV infection model with cure rate and fusion effect
Authors: Nath Bhagya Jyoti , Dehingia Kaushik , Sadri Khadijeh , Sarmah Hemanta Kumar , Hosseini Kamyar , Park Choonkil
Published: April 2022

This paper mainly targets to deduce an optimal treatment strategy for combined antiretroviral drugs, which can maximize healthy CD4+ T cells level with minimum side effects and cost. For this purpose, we consider a within-host treatment model for the HIV infection with two controls incorporating full logistic proliferation of healthy CD4+ T cells, cure rate and fusion effect. These two controls represent the effects of reverse transcriptase inhibitors (RTIs) and protease inhibitors (PIs), respectively. The model analysis begins with proving different basic properties like non-negativity, boundedness of the model solutions and calculation of the basic reproduction number of the model under consideration. Then, stability results are obtained for HIV infection-free equilibrium point and also, a critical efficacy for the combined therapies is calculated. After that, the optimal control problem is proposed and solved numerically using a forward–backward iterative method. Finally, we obtain an optimal treatment strategy that can maximize healthy CD4+ T cells count and control the viral load, and HIV-infected CD4+ T cells count to an undetectable level resulting in improved health conditions of infected individuals.
Structural, Elastic, Electronic, Magnetic, and Thermoelectric Properties of the IrFeSi Half-Heusler Compound: A First-Principles Study
Authors: Zair Asma , Nabil Brahmi Badr-Eddine , Ouahrani Tarik , Nabila Niama Koudjeti , Bekhechi Smaine
Published: April 2022

The emerging need for new functional materials has recently been engaged in a large quest to predict the alternative green and low-cost energy industry. To this end, thermoelectric as well as spintronic applications remain challenging. In this study, we present, for the first time, a density functional calculation on the IrFeSi half-Heusler compound. The calculation gives a deep analysis of the stability within the calculation of phonon spectra and elastic constants as well as Gibbs energy. The electronic and magnetic properties show that the investigated compound is a half-metallic ferromagnetic material. We show that IrFeSi has an integer magnetic moment of 3[Formula: see text][Formula: see text] in good agreement with the Slater–Pauling (SP) rule. By means of the Boltzman theory, we find that the investigated compound exhibits an interesting thermoelectric performance at room temperature.
Warehouse Inspection with an Autonomous Micro Air Vehicle
Authors: Martinez-Carranza Jose , Rojas-Perez Leticia Oyuki
Published: April 2022

In this work, we present an approach to address the problem of warehouse inspection using a MicroAir Vehicle (MAV) that performs autonomous flight by following a set of waypoints in a GPS-denied environment. During the navigation, a second onboard camera is used to observe the inspection area where it is expected to observe QR codes attached to packages placed on shelves. To this end, we use a metric monocular simultaneous localization And Mapping (SLAM) system to estimate the MAVs position in metres, avoiding the need for an external positioning system. The onboard computer executes the detection and decoding of QR codes and the SLAM system. The MAV can also communicate with a Ground Control Station (GCS) to display telemetry, the MAVs position, images from the inspection camera with detected QR codes, and a list of the found packages. This approach was used to compete in the indoors competition of the International Micro Air Vehicle Competition (IMAV) 2019, where we received the special award: Best Flight Performance.
Targets-Attackers-Defenders Game via Pairwise Outcomes
Authors: Liang Li , Wang Jianan , Deng Fang
Published: April 2022

Decision algorithms are one of the key areas of focus in cluster confrontation research. In this paper, a Targets-Attackers-Defenders (TADs) game that includes an attacking team with [Formula: see text] Attackers, a target team with [Formula: see text] targets and a defending team with [Formula: see text] Defenders is considered. In this game, the players within each team cooperate with each other, and both cooperation and confrontation between the teams ensue. The defending team cooperates with the target team against the attacking team. The attacking team aims to capture [Formula: see text] Targets. The defending team protects [Formula: see text] Targets by intercepting Attackers or rendezvousing with Targets. We present a maximum matching algorithm considering both confrontation and cooperation by using relative distance and velocity parameters, and transform the TADs problem into a real-time target-assignment problem with strong confrontation. Finally, we propose an improved basic variable neighborhood search algorithm to solve the target-assignment problem and give the optimal dynamical strategy for each player.
FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction
Authors: Damaskinos Georgios , Guerraoui Rachid , Kermarrec Anne-Marie , Nitu Vlad , Patra Rhicheek , Taiani Francois
Published: April 2022

Federated learning (FL) is very appealing for its privacy benefits: essentially, a global model is trained with updates computed on mobile devices while keeping the data of users local. Standard FL infrastructures are however designed to have no energy or performance impact on mobile devices, and are therefore not suitable for applications that require frequent (
online
) model updates, such as news recommenders.

This article presents
FLeet
, the first
Online FL
system, acting as a middleware between the Android operating system and the machine learning application.
FLeet
combines the privacy of Standard FL with the precision of online learning thanks to two core components: (1)
I-Prof
, a new lightweight profiler that predicts and controls the impact of learning tasks on mobile devices, and (2)
AdaSGD
, a new adaptive learning algorithm that is resilient to delayed updates.

Our extensive evaluation shows that Online FL, as implemented by
FLeet
, can deliver a 2.3× quality boost compared to Standard FL while only consuming 0.036% of the battery per day.
I-Prof
can accurately control the impact of learning tasks by improving the prediction accuracy by up to 3.6× in terms of computation time, and by up to 19× in terms of energy.
AdaSGD
outperforms alternative FL approaches by 18.4% in terms of convergence speed on heterogeneous data.
CAFE and SOUP: Toward Adaptive VDI Workload Prediction
Authors: Zhang Yao , Fan Wenping , Hao Qichen , Wu Xinya , Zhang Min-Ling
Published: April 2022

For Virtual Desktop Infrastructure (VDI) system, effective resource management is rather important where turning off spare virtual machines would help save running cost while maintaining sufficient virtual machines is essential to secure satisfactory user experience. Current VDI resource management strategy works in apassivemanner by either reactively driving available capacity based on user demands or following manually configured schedules, which may lead to unnecessary running costs or unsatisfactory user experience. In this article, we propose a first attempt toward proactive VDI resource management, where two adaptive learning approaches for VDI workload prediction are proposed by learning from multi-grained historical features. Fornon-persistentdesktop pool, based on the aggregation session count of pool-sharing users, theCAFEapproach induces a pool-level workload predictive model by utilizing coarse-to-fine historical features extracted from aggregation workload data. Forpersistentdesktop pool, based on the session connection status of individual users within the same pool, theSOUPapproach induces user-level workload predictive model by incorporating encoded multi-grained features extracted from the logon behavior of individual users into an aggregation pool-level model. Extensive experiments on datasets of real VDI customers and electricity load evidently verify the effectiveness of the proposed adaptive approaches for VDI workload prediction as well as other workload prediction tasks.
Data Mining on Smartphones: An Introduction and Survey
Authors: Yates Darren , Islam Md Zahidul
Published: April 2022

Data mining is the science of extracting information or “knowledge” from data. It is a task commonly executed on cloud computing resources, personal computers and laptops. However, what about smartphones? Despite the fact that these ubiquitous mobile devices now offer levels of hardware and performance approaching that of laptops, locally executed model-training using data mining methods on smartphones is still notably rare. On-device model-training offers a number of advantages. It largely mitigates issues of data security and privacy, since no data is required to leave the device. It also ensures a self-contained, fully portable data mining solution requiring no cloud computing or network resources and able to operate in any location. In this article, we focus on the intersection of smartphones and data mining. We investigate the growth in smartphone performance, survey smartphone usage models in previous research, and look at recent developments in locally executed data mining on smartphones.
PRShare: A Framework for Privacy-preserving, Interorganizational Data Sharing
Authors: Idan Lihi , Feigenbaum Joan
Published: April 2022

We consider the task of interorganizational data sharing, in which data owners, data clients, and data subjects have different and sometimes competing privacy concerns. One real-world scenario in which this problem arises concerns law-enforcement use of phone-call metadata: The data owner is a phone company, the data clients are law-enforcement agencies, and the data subjects are individuals who make phone calls. A key challenge in this type of scenario is that each organization uses its own set of proprietary intraorganizational attributes to describe the shared data; such attributes cannot be shared with other organizations. Moreover, data-access policies are determined by multiple parties and may be specified using attributes that are not directly comparable with the ones used by the owner to specify the data.

We propose a system architecture and a suite of protocols that facilitate dynamic and efficient interorganizational data sharing, while allowing each party to use its own set of proprietary attributes to describe the shared data and preserving the confidentiality of both data records and proprietary intraorganizational attributes. We introduce the novel technique of
Attribute-Based Encryption with Oblivious Attribute Translation (OTABE)
, which plays a crucial role in our solution. This extension of attribute-based encryption uses semi-trusted proxies to enable dynamic and oblivious translation between proprietary attributes that belong to different organizations; it supports hidden access policies, direct revocation, and fine-grained, data-centric keys and queries. We prove that our OTABE-based framework is secure in the standard model and provide two real-world use cases.
Electrolyzer Performance Loss from Accelerated Stress Tests and Corresponding Changes to Catalyst Layers and Interfaces
Authors: Alia Shaun M. , Reeves Kimberly S. , Yu Haoran , Park Jaehyung , Kariuki Nancy , Kropf A. Jeremy , Myers Deborah J. , Cullen David A.
Published: April 2022

Stress tests are developed for proton exchange membrane electrolyzers that utilize low catalyst loading, elevated potential, and frequent cycling with square- and triangle-waves to accelerate anode catalyst layer degradation during intermittent operation. Kinetics drive performance losses (ohmic/transport secondary) and are accompanied by decreasing exchange current density, decreasing cyclic voltammetric capacitance, and increasing polarization resistance. Decreased kinetics are likely due to a combination of iridium (Ir) migration into electrochemically inaccessible locations in the anode or membrane, Ir particle growth (supported by X-ray scattering), changes in the extent of the Ir oxidation state (supported by X-ray absorption spectroscopy), and anode catalyst layer reordering. Decreasing catalyst/transport layer contact and catalyst/membrane interfacial tearing may add contact resistances and account for increasing ohmic losses. Performance losses for low and moderate catalyst loading, as well as from accelerated and model wind/solar cycling protocols, were likewise dominated by kinetics but vary in severity. Accelerated cycling (1 cycle per minute) appears to reasonably accelerate relevant loss mechanisms and can be used to project electrolyzer lifetime from anode deterioration. Ongoing accelerated stress test development and studies into performance loss mechanisms will continue to be critical as electrolysis shifts to intermittent power and low-cost applications.
Synthesis of Porous Carbon-Supported Copper-Based Electrocatalysts Derived from IRMOF: A Non-Noble Metal Electrocatalyst with Optimized Active Sites for the Oxygen Evolution Reaction
Authors: Parkash Anand , Solangi Nizamuddin , Solangi Sorath , Almani Sikandar , Soomro Suhail Ahmed
Published: April 2022

Metal-organic frameworks (MOFs) are a type of porous material that offers a highly flexible medium for future broad application due to their crystallinity, structural diversity, and permanent porosity. Herein, by doping copper with Isoreticular metal-organic framework-3 (IRMOF-3) as a precursor, an effective electrocatalyst with x%Cu/IRMOF-3 (x = 1%–10%) porous carbon spheres were prepared and characterized. The oxygen evolution reaction (OER) electrocatalytic properties of x%Cu/IRMOF-3 were investigated. According to the findings, 5%Cu/IRMOF-3–900 has a superior performance with a low overpotential of 265 mV and strong long-term stability in alkaline solution. With a porous structure and high nitrogen content, 5%Cu doped IRMOF-3 is superior to several reported precious metal-free electrocatalysts developed of MOFs. In this research, MOF has been utilized as a template to design a new approach for developing non-noble metal OER catalysts.
Effect of Skin Layer on Brush Loading, Cross-Contamination, and Cleaning Performance during Post-CMP Cleaning
Authors: Sahir Samrina , Cho Hwi-Won , Jalalzai Palwasha , Peter Jerome , Singh Randeep , Hamada Satomi , Kim Tae-Gon , Park Jin-Goo
Published: April 2022

The use of polyvinyl acetal (PVA) brushes is one of the most effective and prominent techniques applied for the removal of chemical mechanical planarization (CMP) contaminants. However, the brush can be a source of defects by entrapping the abrasives inside its porous structure during brush scrubbing. In this study, the effect of brush top skin layer was extensively studied on contamination, cross-contamination, and cleaning performance by comparing brushes with and without skin layer. The presence of a dense top skin layer resulted in larger contact areas and high ceria particle adsorption on the skin layer. This leads to higher cross-contamination of the wafers during scrubbing along with high cleaning performances. Conversely, the brushes without skin layer showed lower contamination and negligible cross-contamination with a reduced cleaning performance (removal of ceria particles from oxide surface). Therefore, the role of the brush skin layer is significant and needs to be considered while designing a post-CMP cleaning process.
Ultralow Contact Resistivity on Ga-Doped Ge with Contact Co-Implantation of Ge and B
Authors: Mao Shujuan , Liu Jinbiao , Wang Yao , Liu Weibin , Yao Jiaxin , Hu Yanpeng , Cui Hengwei , Kong Zhenzhen , Zhang Ran , Liu Haochen , Wang Zhenxing , Li Tingting , Zhou Na , Zhang Yongkui , Gao Jianfeng , Wu Zhenhua , Li Yongliang , Li Junfeng , Luo Jun , Wang Wenwu , Yin Huaxiang
Published: April 2022

In this work, a comparative study of Ga, Ge+B, and Ga+B ion-implantation (I/I) is reported to improve the specific contact resistivity (ρ
c) on p-type Ge. It is found that Ga I/I shows superiority for shallow source/drain (S/D) junctions doping over Ge+B I/I and Ga+B I/I in terms of activation (Na), junction depth (Xj), and ρ
c; whereas for contact surface doping, Ge+B I/I and Ga+B I/I demonstrate advantage over Ga I/I owing to less dose loss in NiGe and more robust B segregation at the NiGe/Ge interface. Using a combination of Ga I/I and Ge+B I/I for shallow S/D junctions and contact surface doping respectively, an ultralow ρ
c of 2.7 × 10−9 Ω-cm2 is achieved on p-type Ge.
Progress of Proprioceptive Training in the Treatment of Traumatic Shoulder Instability
Authors: Lv Shi , Chen Yang , Liu Mingliang , Qin Lei , Liu Ziyuan , Liu Wenxin , Cui Mengmeng , Zhang Xinlei , Yan Han , Ning Fangli , Zhang Hanlin , Xu Yuzhen
Published: April 2022

In individuals with traumatic shoulder instability, there is a loss of proprioception. This paper reviews the academic literature on shoulder instability and functional impairment in recent years and combines it with clinical practice experience to summarize several techniques of proprioceptive regeneration following traumatic shoulder instability. Many issues were discovered, including a lack of literature on the role of sensory input, a lack of basic proprioceptive research, insufficient sample size in proprioceptive research, and a lack of systematic and standardized standards for the evaluation and training of proprioception in clinical practice, among others. In the future, we will need to better understand the mechanism of proprioception and conduct research on various groups of people, with a focus on discussing the optimal intensity, frequency, and duration of various training methods, as well as implementing proprioceptive training in stages throughout the rehabilitation process. The reestablishment of shoulder joint function, the restoration of proprioception, and the enhancement of daily activities are all critical.
Communication Audio and Video Coding and Decoding Methods in Wireless Cooperative Communication Network
Authors: Li Shenghui , Wang Wenmin
Published: April 2022

Wireless communication is ubiquitous in people’s daily life. As people’s requirements for wireless communication continue to increase, how to improve system performance has become a core issue that communication researchers pay attention to. Wireless cooperative communication is considered to be a key technology in the future communication system because it can provide better communication quality, higher system capacity, wider communication coverage, richer services, and high spectrum utilization efficiency. The proposed network coding can effectively eliminate the transmission bottleneck problem faced by wireless cooperative communication. The development of audio and video communication coding technology has increased the demand for audio and video communication services. The goal of audio and video coding is shifting from traditional storage applications to network transmission. Therefore, the audio and video coding technology for network transmission is being affected by academia and industry. The purpose of this paper is to study the communication audio and video codec methods in wireless cooperative communication networks and to understand the development status of audio and video codec by reading a large number of related documents. On the basis of the problem, relevant experiments are designed to conduct in-depth research. Experimental results show that this scheme can simplify the implementation of scalable coding, improve the coding efficiency of the enhancement layer, and improve the quality of the reconstructed video when the audio and video streams are truncated.
Mortality and Years of Life Lost in Diabetes Mellitus and Its Subcategories in China and Its Provinces, 2005–2020
Authors: Wang Feixue , Wang Wei , Yin Peng , Liu Yunning , Liu Jiangmei , Wang Lijun , Qi Jinlei , You Jinlin , Lin Lin , Zhou Maigeng
Published: April 2022

Objectives. To analyze diabetes mellitus (DM) mortality and years of life lost (YLL) in different years and different subgroups at the national and regional levels in China from 2005 to 2020. Methods. We estimated mortality and YLL of DM and its subcategories for 31 provinces in China during 2005–2020 using multisource data from the National Mortality Surveillance System (NMSS). Results. The age standardized mortality rate (ASMR) of DM increased from 12.18 per 100,000 in 2005 to 13.62 per 100,000 in 2020, which was an increase of 11.86%. The ASMR of type 2 diabetes mellitus (T2DM) was much higher than that of type 1 diabetes mellitus (T1DM). The ASMR of T1DM remained stable, but the rate of T2DM increased, and the increase in male patients was higher than that in their female counterparts. At the same time, the burden of premature death was highest in the

group
≥
80

years old, and ASMR increased from 236.02 per 100,000 in 2005 to 358.86 per 100,000 in 2020. In 2005, the eastern region had the highest ASMR of DM, but the western region’s ASMR grew faster and eventually became the highest in 2020. In addition, the YLL rate in the eastern region showed a downward trend; however, in the middle and western regions the YLL rate continued to rise, with that of the western region rapidly increasing. Conclusion. A dramatically upward trend in DM deaths can be seen in China from 2005 to 2020. DM remains a chronic disease in urgent need of prevention and control, especially in the elderly and people in less-affluent provinces. We must put forward more targeted policies to effectively allocate medical resources and focus on high-risk groups to reduce the premature-mortality burden of DM and its subcategories.
Tax Incentive Policy and Enterprise Innovation: From Enterprise Heterogeneous Perspective
Authors: Yu Yabin , Xu Qian
Published: April 2022

In the study, data of Chinese listed companies in city Hangzhou, Ningbo and Wenzhou from 2012 to 2019 are used for detailed analysis. According to the data analysis, we have got several results: (1) the tax incentive policy has a significant promoting effect on the innovation activities of enterprises. (2) For such microlevel data, we also can get more detailed conclusion by enterprise heterogeneity. Heterogeneous factors do affect the effect of tax incentives on enterprise innovation input. Based on these findings, we can provide well‐directed suggestions for future actions of enterprises and policy makers.
Design and Application of BP Neural Network Optimization Method Based on SIWSPSO Algorithm
Authors: Chu Lina
Published: April 2022

BP neural network method can deal with nonlinear and uncertain problems well and is widely used in the construction of classification, clustering, prediction, and other models. However, BP neural network method has some limitations in fitting nonlinear functions, such as slow convergence speed and easy local optimal convergence rather than global optimal convergence. In order to solve the insufficiency, the optimization approach applying BP neural networks is discussed. This paper proposes a simplified PSO algorithm based on stochastic inertia weight (SIWSPSO) algorithm to optimize BP neural network. In order to test the effect and applicability of the method, this paper established a quality safety risk warning based on SIWSPSO-BP network and selected the detection data of intelligent door lock products for risk warning experiment. The experimental results show that the convergence speed of SIWSPSO-BP model was increased by two times and the accuracy of product quality risk warning reached 85%, which significantly improves the accuracy and learning efficiency of risk warning.
Attribute Control Charts Based on TLT for Length‐Biased Weighted Lomax Distribution
Authors: Gadde Srinivasa Rao , Al-Omari Amer Ibrahim
Published: April 2022

The length‐biased weighted Lomax distribution (LBWD) is a novel continuous of two parameters lifetime distribution. In this article, we introduced an attribute control chart (CC) for the lifetime of a product that follows the LBWD in terms of the number of failure items before a fixed time period is investigated. The performance of the suggested charts is investigated using in term of the average run length (ARL). The necessary tables of shift sizes and various sample sizes are offered for numerous values of the distribution parameters as well as specified ARL and shift constants. Some numerical examples are discussed for various scheme parameters to study the performance of the new LBWD attribute control charts.
Laparoscopic Release for Median Arcuate Ligament Compression Syndrome Associated with a Celiac-Mesenteric Trunk
Authors: Cawich Shamir O. , Harnanan Dave , Pran Lemuel
Published: April 2022

The median arcuate ligament compression syndrome is a rare entity that occurs in 2 per 100,000 unselected individuals. We present a case where the median arcuate ligament compression syndrome was associated with an equally uncommon anatomic variation—a celiac-mesenteric trunk, which occurs in 0.42-2.7% of unselected individuals. We could find no prior report of a celiac-mesenteric trunk being associated with the median arcuate ligament compression syndrome. This report also adds to the literature to show that a laparoscopic approach to median arcuate ligament release is feasible.