bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of surface electromyography controlled prosthetics limb based on recurrent neural network
Authors: Bittibssi Tarek M. , Zekry Abdelhalim , Genedy Mohamed A. , Maged Shady A. 
Published: January 2022

AbstractLow‐cost traditional prosthetic legs, available worldwide, can make walking and stair climbing possible but still difficult. This article presents the hardware implementation of the surface electromyography (sEMG) powered prosthesis actuation (PPA) system using a learned neural network algorithm based on recurrent neural network (RNN), which is used to train sEMG benchmark databases, and predict joint angle. This implementation was created based on sEMG signal measurements. The data were collected from three benchmark datasets describing different subjects during performance, and analyzing various gait patterns were used to construct the neural network and reduce significant model errors in a real‐time setting. Processing circuits, interfacing the output with the controller board, signal amplification, motor driving circuits, and single‐board computer programming are included in the implementation.
Optimization and hardware implementation of noise reduction algorithm for low‐power audio chip
Authors: Wang Ang , Yu Lina , Lan Yuyan , Zhou Weixin , Xiao Wan'ang 
Published: January 2022

AbstractIn order to improve the voice quality and decrease the power consumption of the audio electronic products, the noise reduction algorithm and its low‐power hardware implementation are studied. Several types of common noise reduction algorithms are analyzed and simulated, and the log‐minimum mean square error algorithm with statistical‐model‐based voice activity detection noise estimator is selected, which can achieve best signal‐to‐noise ratio improvement of 5.56 dB. The ability of the algorithm to track nonstationary noise is analyzed, and the failure of noise reduction caused by an extreme situation is prevented, and the amount of calculation is reduced by multiplex at the algorithm level. In hardware implementation, look‐up tables are used to implement special operations. High‐significant‐bits search is used to simplify the look‐up table to reduce power consumption, and the speed of the search circuit is optimized by parallel design. The exponential integral and exponential operation are combined as one operation with lower precision requirements, leading to lower power consumption. The design presented in this article passed FPGA verification and taped out with a digital hearing aids chip on SMIC 0.13 μm process. The area and the power consumption of the noise reduction module is 0.206 mm2 and 15.3 μW, respectively, which makes the design suitable for low‐power audio chip applications.
Electrochemically Mediated Direct CO2 Capture by a Stackable Bipolar Cell
Authors: Hemmatifar Ali , Kang Jin Soo , Ozbek Nil , Tan Kai‐Jher , Hatton T. Alan 
Published: January 2022

AbstractThe unprecedented increase in atmospheric CO2 concentration calls for effective carbon capture technologies. With distributed sources contributing to about half of the overall emission, CO2 capture from the atmosphere [direct air capture, (DAC)] is more relevant than ever. Herein, an electrochemically mediated DAC system is reported which utilizes affinity of redox‐active quinone moieties towards CO2 molecules, and unlike incumbent chemisorption technologies which require temperature or pH swing, relies solely on the electrochemical voltage for CO2 capture and release. The design and operation of a DAC system is demonstrated with stackable bipolar cells using quinone chemistry. Specifically, poly(vinylanthraquinone) (PVAQ) negative electrode undergoes a two‐electron reduction reaction and reversibly complexes with CO2, leading to CO2 sequestration from the feed stream. The subsequent PVAQ oxidation, conversely, results in release of CO2. The performance of both small‐ and meso‐scale cells for DAC are evaluated with feed CO2 concentrations as low as 400 ppm (0.04 %), and energy consumption is demonstrated as low as 113 kJ per mole of CO2 captured. Notably, the bipolar cell construct is modular and expandable, equally suitable for small and large plants. Moving forward, this work presents a viable and highly customizable electrochemical method for DAC.
Saturated hydraulic conductivity of boreal peat and its relationships with peat properties and sampling depth
Authors: Paat Raul , Kohv Marko , Jõeleht Argo 
Published: January 2022

AbstractThe boreal region is a significant peat‐forming area. With peat, there lie other natural resources, including mineral ores and fossil fuels needed by our economy. However, mining for mineral resources or any other activity that leads to large‐scale groundwater extraction in the near vicinity or underneath the mires can alter the water levels in the overlaying ecosystems and thus have a damaging effect on them, raising concerns about the mires' preservation. Peat itself may isolate surface vegetation from drainage caused by nearby mining when its hydraulic conductivity is sufficiently low. More is known about the hydraulic properties of the uppermost layers of the peat column, but there is very little data about deeper, generally more decomposed peat layers that may potentially act as drainage barriers. Carrying out in situ hydraulic conductivity tests in less conductive peat can be laborious and time‐consuming, and not always practical. This research aims to study and verify statistical relationships between easy‐to‐measure peat properties and hydraulic conductivity over the entire peat column, covering the knowledge deficit that is important in the context of indirect drainage effects related to mining or any other large‐scale groundwater extraction. For that, we sampled peat and conducted in situ saturated hydraulic conductivity tests in several mires in northeast Estonia to gather information about the hydraulic properties of boreal peat. Collected data were fitted with linear mixed‐effects models to link hydraulic conductivity with the degree of decomposition, dry bulk density, depth of measurement, and peatland growth phase. The results indicate that these parameters are strongly correlated with saturated hydraulic conductivity and can serve as predictors of this parameter. Constructed statistical models exhibit relatively high explanatory power and show potential usage for characterizing the hydraulic conductivity of peat. The findings of this study may be helpful in the efforts of mire conservation.
Hydrolysis of dimethyl terephthalate to terephthalic acid on Nb‐modified HZSM‐5 zeolite catalysts
Authors: Guo Bao , Liu Jidong , Tang Shixiong , Liu Yida , Tian Zenan , Lv Jianhua 
Published: January 2022

AbstractBACKGROUNDWhether waste polyethylene terephthalate (PET) can be effectively recycled is one of the main challenges of the current environmental problems. The hydrolysis of dimethyl terephthalate (DMT) to terephthalic acid (TPA) over Nb‐modified HZSM‐5 zeolite was studied. Nb/HZSM‐5 zeolites with different loadings were prepared and characterized by X‐ray diffraction, X‐ray photoelectron spectroscopy, scanning electron microscopy, NH3‐temperature programmed desorption and pyridine adsorption infrared spectroscopy. The effects of different reaction conditions on the conversion of DMT and TPA yield were investigated.RESULTSThe yield of TPA strongly depends on the reaction conditions and the loading of Nb. The niobium phase exists in the form of Nb2O5 on the zeolite and interacts with the surface of HZSM‐5 to produce the active site of Brønsted acid. The yield of TPA is closely related to the concentration of Brønsted acid sites. On 0.6Nb/HZSM‐5 catalyst, the yield of TPA is highest, at about 94%.CONCLUSIONNb/HZSM‐5 catalyst has excellent catalytic activity and high stability for DMT hydrolysis. In addition, the product TPA prepared in this study can be directly applied to the current PET production supply chain, providing a promising catalytic route. © 2022 Society of Chemical Industry (SCI).
Compassion practice as an antidote for compassion fatigue in the era of COVID‐19
Authors: Bentley Paige G. 
Published: January 2022

AbstractEmpathy is a critical factor in counseling, yet the process of empathizing with suffering can have a detrimental impact on counselor well‐being. In the wake of coronavirus disease 2019 (COVID‐19), the need for strategies to ameliorate this potential negative impact is even more apparent. This article explores compassion practices to meet that need.
Scholarly journal publishing in Australia
Authors: Jamali Hamid R. , Wakeling Simon , Abbasi Alireza 
Published: January 2022

AbstractThis article describes the nature and extent of scholarly journal publishing in Australia. Australian journals are defined as journals that belong to or are affiliated with an Australian entity. There are currently 651 active Australian journals. The oldest started in the 19th century, and the 1990s was the top decade in terms of starting new journals. Australian journals mostly belong to or are affiliated with non‐profit organizations (e.g., learned societies) (364, 55.9%), or educational institutions (168, 25.8%). While most of the journals (426, 65.4%) are published by their owners (self‐publish), the publication of 162 journals has been outsourced to international commercial publishers, with most of these linked to non‐profit organizations. About 39.8% of Australian journals are open access and most of them do not charge author‐processing charges. Half of the Australian journals (326) are indexed in Scopus and slightly less than half (301) are included in Web of Science (WoS). Arts, Humanities and Social Sciences are well represented in the disciplinary focus of journals, although journals indexed in Scopus and WoS are more likely to be in health, life and physical science disciplines.
Efficacy of dual sublingual immunotherapy with Japanese cedar pollen and house dust mite allergens in patients with allergic rhinitis sensitized to multiple allergens
Authors: Fujii Tatsuya , Kitamura Yoshiaki , Kamimura Seiichiro , Ishitani Keisuke , Takeda Noriaki 
Published: January 2022

AbstractObjectiveIn the present study, we examined the effects of dual sublingual immunotherapy (SLIT) with Japanese cedar pollen (JCP) and house dust mite (HDM) allergens on nasal symptoms during the peak pollen period (PPP) and in late fall (LF) in patients with allergic rhinitis (AR) sensitized to both JCP and HDM. We then compared the efficacy of dual‐SLIT with JCP and HDM to that of mono‐SLIT with JCP at PPP.MethodsTwenty‐five bisensitized patients with AR who showed positive serum specific immunoglobulin E (IgE) against both JCP and HDM were enrolled. In dual‐SLIT, 16 patients received JCP drops/tablets and HDM tablets concurrently. In mono‐SLIT with JCP, nine patients received JCP drops/tablets. Nasal symptoms were scored on a 0–4 point scale.ResultsThe nasal scores at PPP and in LF in the bisensitized patients with AR who received dual‐SLIT with JCP and HDM in 2019 were significantly lower than those in the same patients who received antihistamines only in 2018. The decrease in scores of nasal obstruction at PPP from 2018 to 2019 in patients who received dual‐SLIT was significantly greater than those in patients who received mono‐SLIT with JCP. Dual‐SLIT was well tolerated and only had mild adverse effects.ConclusionThese findings suggest that dual‐SLIT suppressed both JCP‐induced seasonal and HDM‐induced perennial nasal symptoms in bisensitized patients with AR. Dual‐SLIT was more effective in suppressing nasal obstruction at PPP than mono‐SLIT with JCP with limitation of baseline characteristics not to be controlled between the two groups, suggesting that dual‐SLIT suppressed HDM‐induced priming effects, thus resulting in further suppression of nasal obstruction at PPP.Level of Evidence3b, a case‐controlled study
Competition is on the rise: To what extent does traditional fundraising performance research apply in competitive environments?
Authors: Walk Marlene , Curley Cali , Levine Daniel Jamie 
Published: January 2022

AbstractResearch on fundraising performance links organizational size, professional donor engagement, and legitimacy with fundraising outcomes. But can we assume the same factors will positively impact fundraising performance in light of increasing competition among nonprofits? This study explores whether and how traditional factors known to impact fundraising performance perform in the context of online fundraising tournaments: an environment that is explicitly competitive as those who lose drop out. Our analysis draws on data from 596 US nonprofits that participated in such tournaments. This inquiry addresses increasing competitive pressures placed on nonprofits as they likely cannot avoid competition in the future.
An empirical evaluation of deep learning‐based source code vulnerability detection: Representation versus models
Authors: Semasaba Abubakar Omari Abdallah , Zheng Wei , Wu Xiaoxue , Agyemang Samuel Akwasi , Liu Tao , Ge Yuan 
Published: January 2022

AbstractVulnerabilities in the source code of the software are critical issues in the realm of software engineering. Coping with vulnerabilities in software source code is becoming more challenging due to several aspects such as complexity and volume. Deep learning has gained popularity throughout the years as a means of addressing such issues. This paper proposes an evaluation of vulnerability detection performance on source code representations and evaluates how machine learning (ML) strategies can improve them. The structure of our experiment consists of three deep neural networks (DNNs) in conjunction with five different source code representations: abstract syntax trees (ASTs), code gadgets (CGs), semantics‐based vulnerability candidates (SeVCs), lexed code representations (LCRs), and composite code representations (CCRs). Experimental results show that employing different ML strategies in conjunction with the base model structure influences the performance results to a varying degree. However, ML‐based techniques suffer from poor performance on class imbalance handling and dimensionality reduction when used in conjunction with source code representations.
A Review of Machine Learning Algorithms for Text Classification
Authors: Li Ruiguang , Liu Ming , Xu Dawei , Gao Jiaqi , Wu Fudong , Zhu Liehuang 
Published: January 2022

AbstractText classification is a basic task in the field of natural language processing, and it is a basic technology for information retrieval, questioning and answering system, emotion analysis and other advanced tasks. It is one of the earliest application of machine learning algorithm, and has achieved good results. In this paper, we made a review of the traditional and state-of-the-art machine learning algorithms for text classification, such as Naive Bayes, Supporting Vector Machine, Decision Tree, K Nearest Neighbor, Random Forest and neural networks. Then, we discussed the advantages and disadvantages of all kinds of machine learning algorithms in depth. Finally, we made a summary that neural networks and deep learning will become the main research topic in the future.
Analysis of Address Linkability in Tornado Cash on Ethereum
Authors: Tang Yujia , Xu Chang , Zhang Can , Wu Yan , Zhu Liehuang 
Published: January 2022

AbstractTornado Cash, the most popular non-custodial coin mixer on Ethereum, is widely used to protect the privacy of addresses. However, some inappropriate transaction behaviors in Tornado Cash mixing mechanism lead to the risk of privacy leakage. More specifically, the malicious attackers can link multiple addresses of the same users according to the transaction data. Motivated by the above problem, this paper systematically analyzes the privacy issues of Tornado Cash for the first time. In this paper, we give the macroscopic analysis of Tornado Cash based on the on-chain data and formalize two types of transaction patterns. Focus on the presented transaction patterns, we propose three heuristic clustering rules to link the users’ addresses, which reduce the size of users’ anonymity set. Finally, we perform the experiment on real Tornado Cash transaction data to describe the effectiveness of the proposed clustering rules.
FPFlow: Detect and Prevent Browser Fingerprinting with Dynamic Taint Analysis
Authors: Li Tianyi , Zheng Xiaofeng , Shen Kaiwen , Han Xinhui 
Published: January 2022

AbstractBrowser fingerprinting is a practical user tracking technology widely adopted by many real-world websites to potentially track users’ browsing behaviors. By collecting information such as screen resolution, user agent, and WebGL rendered data, the tracker can generate a unique identifier for users without their knowledge, leading to a severe violation of user privacy. Therefore, an effective detection and defense technology for browser fingerprinting is needed to protect user privacy. In this paper, we proposed FPFlow, a dynamic JavaScript taint analysis framework to detect and prevent browser fingerprinting. FPFlow monitors the whole process of browser fingerprinting, including collecting information, generating fingerprinting, and sending it to the remote server. We evaluated FPFlow on TRANCO top 10,000 websites. Our experiments showed that our framework could effectively detect browser fingerprints. We found 66.6% of the websites performing fingerprinting and revealed how browser fingerprinting is applied in real-world websites. We also showed that FPFlow could prevent browser fingerprinting with an acceptable overhead.
Research and Application of Security Situation Awareness Platform for Large Enterprises
Authors: Wang Zhanyu 
Published: January 2022

AbstractThis paper analyzes the international and domestic security situation and major security threats, including those faced by large enterprises. In order to improve the security management level of large enterprises, the construction of safety management system which takes the safety situation awareness platform as the command core is puts forward. The technical framework, evolution route, main functions, core technologies and three-stage models of detection, perception and prediction, closed-loop rectification, and threat information sharing are discussed. At the same time, the author analyzes the organization mechanism, the research and development guarantee, the sustainable application, the introduction of ecology and so on, and puts forward the solution.
CP asymmetry in the angular distributions of τ → KSπντ decays. Part II. General effective field theory analysis
Authors: Chen Feng-Zhi , Li Xin-Qiang , Peng Shi-Can , Yang Ya-Dong , Zhang Hong-Hao 
Published: January 2022

Abstract
In this work, we proceed to study the CP asymmetry in the angular distributions of τ → KSπντ decays within a general effective field theory framework including four-fermion operators up to dimension-six. It is found that, besides the commonly considered scalar-vector interference, the tensor-scalar interference can also produce a non-zero CP asymmetry in the angular distributions, in the presence of complex couplings. Using the dispersive representations of the Kπ form factors as inputs, and taking into account the detector efficiencies of the Belle measurement, we firstly update our previous SM predictions for the CP asymmetries in the same four Kπ invariant-mass bins as set by the Belle collaboration. Bounds on the effective couplings of the non-standard scalar and tensor interactions are then obtained under the combined constraints from the CP asymmetries measured in the four bins and the branching ratio of τ−→ KSπ−ντ decay, with the numerical results given respectively by $$ \operatorname{Im}\left[{\hat{\upepsilon}}_S\right] $$
Im

ϵ
̂

S

= −0.008 ± 0.027 and $$ \operatorname{Im}\left[{\hat{\upepsilon}}_T\right] $$
Im

ϵ
̂

T

= 0.03 ± 0.12, at the renormalization scale μτ = 2 GeV in the $$ \overline{\mathrm{MS}} $$

MS
¯

scheme. Using the best-fit values, we also find that the distributions of the CP asymmetries can deviate significantly from the SM expectation in almost the whole Kπ invariant-mass region. Nevertheless, the current bounds on $$ \operatorname{Im}\left[{\hat{\upepsilon}}_S\right] $$
Im

ϵ
̂

S

and $$ \operatorname{Im}\left[{\hat{\upepsilon}}_T\right] $$
Im

ϵ
̂

T

are still plagued by large experimental uncertainties, but will be improved with more precise measurements from the Belle II experiment as well as the proposed Tera-Z and STCF facilities. Assuming further that the non-standard scalar and tensor interactions originate from a weakly-coupled heavy new physics well above the electroweak scale, the SU(2)L invariance of the resulting SMEFT Lagrangian would indicate that very strong limits on $$ \operatorname{Im}\left[{\hat{\upepsilon}}_S\right] $$
Im

ϵ
̂

S

and $$ \operatorname{Im}\left[{\hat{\upepsilon}}_T\right] $$
Im

ϵ
̂

T

could also be obtained from the neutron electric dipole moment and the $$ {D}^0-{\overline{D}}^0 $$

D
0

−

D
¯

0

mixing. With the bounds from these processes taken into account, it is then found that, unless there exist extraordinary cancellations between the new physics contributions, neither the scalar nor the tensor interaction can produce any significant effects on the CP asymmetries (relative to the SM predictions) in the processes considered, especially under the “single coefficient dominance” assumption.
Women’s Economic Contribution, Relationship Status and Risky Sexual Behaviours: A Cross-Sectional Analysis from a Microfinance-Plus Programme in Rural South Africa
Authors: Tolmay Janke , Knight Louise , Muvhango Lufuno , Polzer-Ngwato Tara , Stöckl Heidi , Ranganathan Meghna 
Published: January 2022

AbstractIn sub-Saharan Africa, women bear a disproportionate burden of HIV/AIDS while also facing economic and gender inequalities. To explore the association of women’s economic contribution and relationship status with risky sexual behaviour, this study analysed cross-sectional data from 626 women aged 22 to 84 in rural South Africa. All women were enrolled in a microfinance plus gender training programme (Intervention with Microfinance for AIDS and Gender Equity (IMAGE)). We used univariable and multivariable logistic regression to explore the associations of relationship status and women’s household income contribution with inconsistent condom use, multiple sexual partners and transactional sex, respectively. We found that married, older women had the highest odds of inconsistent condom use, while those contributing all the household income had higher odds of multiple sexual partnerships, but lower odds of transactional sex compared to those with no contribution. Income contribution and relationship status have a nuanced relationship with sexual risk behaviours. Thus, economic strengthening interventions should target relevant vulnerable women while also addressing the broader social and economic drivers of risky sexual behaviour.