bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding Twenty Years of Inequality and Poverty Trends in Russia
Authors: Lisina Anastasiya , Van Kerm Philippe
Published: February 2022

The distribution of income in Russia changed significantly over the past 25 years. This paper examines the factors that have been driving the fall in inequality and poverty over two recent decades in the Russian Federation. Changes in earnings from public and private sectors and pensions have been the main sources of changes in the income distribution between 1994 and 2015. Falling inequality and poverty were the result of a decrease in the dispersion of private sector earnings and an increase in the levels of pensions and public sector earnings. Neither the evolution of socio‐demographic characteristics nor the level or structure of employment alone had big impacts.
Co‐worker peer effects on parental leave take‐up
Authors: Carlsson Magnus , Reshid Abdulaziz Abrar
Published: February 2022

We investigate co‐worker peer effects in the use of parental leave in Sweden. We use an instrumental variable approach called “peers of peers”, in which the parental leave taken by family peers (siblings and cousins) of co‐workers is used as an instrument for co‐workers’ use of parental leave. For fathers, we find that a 10‐day increase in the average parental leave taken by co‐workers increases their use of parental leave by approximately one and a half days, while, for mothers, the increase is approximately one day. The results are robust to alternative model specifications. We explore possible mechanisms and discuss policy implications.
REVIEW: ISCHEMIC HEART DISEASE AND THE POTENTIAL ROLE OF FENUGREEK (TRIGONELLA FOENUM GRAECUM LINN.) IN CARDIOPROTECTION
Authors: Hanafi Noorul Izzati , Saidan Noor Hafizoh , Mohamed Maizan , Sirajudeen KNS , Gan Siew Hua , A. K. Pahirulzaman Khomaizon , Pasupuleti Visweswara Rao
Published: February 2022

Ischemic heart disease, often known as coronary heart disease (CHD), is a term for heart disorders caused by narrowing heart arteries (coronary arteries) that provide blood to the heart's muscles. The body is prone to heart attacks when there is less oxygen supply (hypoxia) to the heart resulting a major cell death in the heart tissues. Cardiovascular disease (CVD) is the leading cause of death worldwide. Over the last few decades, the potential therapeutic effects of herbs and other types of complementary medicines for managing risk factors for CVD have gotten a lot of attention. Fenugreek (Trigonella foenum graecum Linn.) is a very important spice in most Asian dishes. In Malaysia, fenugreek, locally known as ‘halba’, is used in the preparation of popular dishes; ‘nasi dagang’ for breakfast, and ‘putu halba’ as snacks for hi-tea and sometimes applied in drinks. Although, to date, the effect of fenugreek against diabetes and heart diseases is well investigated, most studies do not focus on its the effects at molecular levels. This review gives an insight on the ischemic heart disease and the nutritional values of fenugreek as functional food in protecting the heart.
High magnesium mitigates the vasoconstriction mediated by different types of calcium influx from monocrotaline‐induced pulmonary hypertensive rats
Authors: Zhuang Xiao‐Ling , Zhu Zhuang‐Li , Huang Qiu‐Hong , Yan Fu‐Rong , Zheng Si‐Yi , Lai Su‐Mei , Jiao Hai‐Xia , Lin Mo‐Jun
Published: February 2022

New Findings

What is the central question of this study?

What is the involvement of Mg2+ in mitigating the vasoconstriction in pulmonary arteries and smaller pulmonary arteries in the monocrotaline‐induced pulmonary arterial hypertension (MCT‐PAH) rat model?

What are the main finding and its importance?

Both store‐operated Ca2+ entry‐ and receptor‐operated Ca2+ entry‐mediated vasoconstriction were enhanced in the MCT‐PAH model. High magnesium inhibited vasoconstriction by directly antagonizing Ca2+ and increasing NO release, and this was more notable in smaller pulmonary arteries.

Increased extracellular magnesium concentration has been shown to attenuate the endothelin‐1‐induced contractile response via the release of nitric oxide (NO) from the endothelium in proximal pulmonary arteries (PAs) of chronic hypoxic mice. Here, we further examined the involvement of Mg2+ in the inhibition of vasoconstriction in PAs and distal smaller pulmonary arteries (sPAs) in a monocrotaline‐induced pulmonary arterial hypertension (MCT‐PAH) rat model. The data showed that in control rats vasoconstriction in sPAs is more intense than that in PAs. In MCT‐PAH rats, store‐operated Ca2+ entry (SOCE)‐ and receptor‐operated Ca2+ entry (ROCE)‐mediated contraction were significantly strengthened. However, there was no upregulation of the vasoconstriction mediated by voltage‐dependent calcium entry (VDCE). Furthermore, high magnesium greatly inhibited VDCE‐mediated contraction in PAs rather than sPAs, which was the opposite of the ROCE‐mediated contraction. Moreover, monocrotaline pretreatment partly eliminated the endothelium‐dependent vasodilatation in PAs, which in sPAs, however, was still promoted by magnesium due to the increased NO release in pulmonary microvascular endothelial cells (PMVECs). In conclusion, the findings suggest that both SOCE‐ and ROCE‐mediated vasoconstriction in the MCT‐PAH model are enhanced, especially in sPAs. The inhibitory effect of high magnesium on vasoconstriction can be achieved partly by its direct role as a Ca2+ antagonist and partly by increasing NO release in PMVECs.
A machine learning tutorial for spatial auditory display using head-related transfer functions
Authors: McMullen Kyla , Wan Yunhao
Published: February 2022

This review presents a high-level overview of the uses of machine learning (ML) to address several challenges in spatial auditory display research, primarily using head-related transfer functions. This survey also reviews and compares several categories of ML techniques and their application to virtual auditory reality research. This work addresses the use of ML techniques such as dimensionality reduction, unsupervised learning, supervised learning, reinforcement learning, and deep learning algorithms. The paper concludes with a discussion of the usage of ML algorithms to address specific spatial auditory display research challenges.
Axion dark matter: What is it and why now?
Authors: Chadha-Day Francesca , Ellis John , Marsh David J. E.
Published: February 2022

The axion has emerged in recent years as a leading particle candidate to provide the mysterious dark matter in the cosmos, as we review here for a general scientific audience. We describe first the historical roots of the axion in the Standard Model of particle physics and the problem of charge-parity invariance of the strong nuclear force. We then discuss how the axion emerges as a dark matter candidate and how it is produced in the early universe. The symmetry properties of the axion dictate the form of its interactions with ordinary matter. Astrophysical considerations restrict the particle mass and interaction strengths to a limited range, which facilitates the planning of experiments to detect the axion. A companion review discusses the exciting prospect that the axion could be detected in the near term in the laboratory.
Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer
Authors: Zhang Kaiyang , Erkan Erdogan Pekcan , Jamalzadeh Sanaz , Dai Jun , Andersson Noora , Kaipio Katja , Lamminen Tarja , Mansuri Naziha , Huhtinen Kaisa , Carpén Olli , Hietanen Sakari , Oikkonen Jaana , Hynninen Johanna , Virtanen Anni , Häkkinen Antti , Hautaniemi Sampsa , Vähärautio Anna
Published: February 2022

Chemotherapy resistance is a critical contributor to cancer mortality and thus an urgent unmet challenge in oncology. To characterize chemotherapy resistance processes in high-grade serous ovarian cancer, we prospectively collected tissue samples before and after chemotherapy and analyzed their transcriptomic profiles at a single-cell resolution. After removing patient-specific signals by a novel analysis approach, PRIMUS, we found a consistent increase in stress-associated cell state during chemotherapy, which was validated by RNA in situ hybridization and bulk RNA sequencing. The stress-associated state exists before chemotherapy, is subclonally enriched during the treatment, and associates with poor progression-free survival. Co-occurrence with an inflammatory cancer–associated fibroblast subtype in tumors implies that chemotherapy is associated with stress response in both cancer cells and stroma, driving a paracrine feed-forward loop. In summary, we have found a resistant state that integrates stromal signaling and subclonal evolution and offers targets to overcome chemotherapy resistance.
Field-induced reagent concentration and sulfur adsorption enable efficient electrocatalytic semihydrogenation of alkynes
Authors: Gao Ying , Yang Rong , Wang Changhong , Liu Cuibo , Wu Yongmeng , Li Huizhi , Zhang Bin
Published: February 2022

Efficient electrocatalytic alkyne semihydrogenation with potential/time-independent selectivity and Faradaic efficiency (FE) is vital for industrial alkene productions. Here, sulfur-tuned effects and field-induced reagent concentration are proposed to promote electrocatalytic alkyne semihydrogenation. Density functional theory calculations reveal that bulk sulfur anions intrinsically weaken alkene adsorption, and surface thiolates lower the activation energy of water and the Gibbs free energy for H* formation. The finite element method shows high-curvature structured catalyst concentrates K
+
by enhancing electric field at the tips, accelerating more H* formation from water electrolysis via sulfur anion–hydrated cation networks, and promoting alkyne transformations. So, self-supported Pd nanotips with sulfur modifiers are developed for electrochemical alkyne semihydrogenation with up to 97% conversion yield, 96% selectivity, 75% FE, and a reaction rate of 465.6 mmol m
−2
hour
−1
. Wide potential window and time irrelevance for high alkene selectivity, good universality, and easy access to deuterated alkenes highlight the promising potential.
Lighting the way to personalized mRNA immune cell therapies
Authors: Metzloff Ann E. , Billingsley Margaret M. , Mitchell Michael J.
Published: February 2022

Nanoparticles, mRNA, and ultraviolet light combine to reprogram specific immune cells directly in the body.
Hematopoietic cell transplantation donor-derived memory-like NK cells functionally persist after transfer into patients with leukemia
Authors: Berrien-Elliott Melissa M. , Foltz Jennifer A. , Russler-Germain David A. , Neal Carly C. , Tran Jennifer , Gang Margery , Wong Pamela , Fisk Bryan , Cubitt Celia C. , Marin Nancy D. , Zhou Alice Y. , Jacobs Miriam T. , Foster Mark , Schappe Timothy , McClain Ethan , Kersting-Schadek Samantha , Desai Sweta , Pence Patrick , Becker-Hapak Michelle , Eisele Jeremy , Mosior Matthew , Marsala Lynne , Griffith Obi L. , Griffith Malachi , Khan Saad M. , Spencer David H. , DiPersio John F. , Romee Rizwan , Uy Geoffrey L. , Abboud Camille N. , Ghobadi Armin , Westervelt Peter , Stockerl-Goldstein Keith , Schroeder Mark A. , Wan Fei , Lie Wen-Rong , Soon-Shiong Patrick , Petti Allegra A. , Cashen Amanda F. , Fehniger Todd A.
Published: February 2022

Natural killer (NK) cells are innate lymphoid cells that eliminate cancer cells, produce cytokines, and are being investigated as a nascent cellular immunotherapy. Impaired NK cell function, expansion, and persistence remain key challenges for optimal clinical translation. One promising strategy to overcome these challenges is cytokine-induced memory-like (ML) differentiation, whereby NK cells acquire enhanced antitumor function after stimulation with interleukin-12 (IL-12), IL-15, and IL-18. Here, reduced-intensity conditioning (RIC) for
HLA
-haploidentical hematopoietic cell transplantation (HCT) was augmented with same-donor ML NK cells on day +7 and 3 weeks of N-803 (IL-15 superagonist) to treat patients with relapsed/refractory acute myeloid leukemia (AML) in a clinical trial (NCT02782546). In 15 patients, donor ML NK cells were well tolerated, and 87% of patients achieved a composite complete response at day +28, which corresponded with clearing high-risk mutations, including
TP53
variants. NK cells were the major blood lymphocytes for 2 months after HCT with 1104-fold expansion (over 1 to 2 weeks). Phenotypic and transcriptional analyses identified donor ML NK cells as distinct from conventional NK cells and showed that ML NK cells persisted for over 2 months. ML NK cells expressed CD16, CD57, and high granzyme B and perforin, along with a unique transcription factor profile. ML NK cells differentiated in patients had enhanced ex vivo function compared to conventional NK cells from both patients and healthy donors. Overall, same-donor ML NK cell therapy with 3 weeks of N-803 support safely augmented RIC haplo-HCT for AML.
Closed Genome Sequence of an Environmental Aeromonas veronii Strain from California, United States, with an IncA/C Plasmid Carrying an Extended-Spectrum β-Lactamase Gene,
bla
VEB-3
Authors: Lovero Karissa G. , Mota-Bravo Luis
Published: February 2022

We describe the extended-spectrum β-lactamase
bla
VEB-3
gene found in an IncA/C plasmid in
Aeromonas veronii
strain SW3814, which was collected from a freshwater lake in southern California, United States.
Bbvac: A Live Vaccine Candidate That Provides Long-Lasting Anamnestic and Th17-Mediated Immunity against the Three Classical
Bordetella
spp.
Authors: Gestal Monica C. , Howard Laura K. , Dewan Kalyan K. , Harvill Eric T.
Published: February 2022

Infectious diseases are a major cause of morbidity and mortality in the United States, accounting for over 40 million hospitalizations since 1998. Therefore, novel vaccine strategies are imperative, which can be improved with a better understanding of the mechanisms that bacteria utilize to suppress host immunity, a key mechanism for establishing colonization.
Bordetella
spp., the causative agents of whooping cough, suppress host immunity, which allows for persistent colonization.
Comparative Genomic Analysis Reveals Preserved Features in Organohalide-Respiring
Sulfurospirillum
Strains
Authors: Yang Yi , Schubert Torsten , Lv Yan , Li Xiuying , Yan Jun
Published: February 2022

Organohalide-respiring bacteria (OHRB) play critical roles in the detoxification of chlorinated pollutants and bioremediation of subsurface environments (e.g., groundwater and sediment) impacted by anthropogenic chlorinated solvents. The majority of known OHRB cannot perform reductive dechlorination below neutral pH, hampering the applications of OHRB for remediating acidified groundwater due to fermentation and reductive dechlorination (
1
,
2
).
Implementation and Extended Evaluation of the Euroimmun Anti-SARS-CoV-2 IgG Assay and Its Contribution to the United Kingdom’s COVID-19 Public Health Response
Authors: Otter Ashley David , Bown Abbie , D’Arcangelo Silvia , Bailey Daniel , Semper Amanda , Hewson Jacqueline , Catton Matthew , Perumal Prem , Sweed Angela , McKee Deborah Fox , Jones Jessica , Harvala Heli , Lamikanra Abigail , Zambon Maria , Andrews Nick , Whitaker Heather , Linley Ezra , Mentzer Alexander J. , Skelly Donal , Knight Julian C. , Klenerman Paul ,   UKHSA Porton Euroimmun testing group, Amirthalingam Gayatri , Taylor Stephen , Rowe Cathy , Vipond Richard , Brooks Tim
Published: February 2022

Serology assays have been useful in determining those with previous SARS-CoV-2 infection in a wide range of research and serosurveillance projects. However, assays vary in their sensitivity at detecting SARS-CoV-2 antibodies. Here, we detail an extended evaluation and characterization of the Euroimmun anti-SARS-CoV-2 IgG assay, one that has been widely used within the United Kingdom on over 160,000 samples.
High Prevalence of Klebsiella pneumoniae in European Food Products: a Multicentric Study Comparing Culture and Molecular Detection Methods
Authors: Rodrigues Carla , Hauser Kathrin , Cahill Niamh , Ligowska-Marzęta Małgorzata , Centorotola Gabriella , Cornacchia Alessandra , Garcia Fierro Raquel , Haenni Marisa , Nielsen Eva Møller , Piveteau Pascal , Barbier Elodie , Morris Dearbháile , Pomilio Francesco , Brisse Sylvain
Published: February 2022

Bacteria of the
Klebsiella pneumoniae
species complex (KpSC) are ubiquitous, and
K. pneumoniae
is a leading cause of antibiotic-resistant infections in humans. Despite the urgent public health threat represented by
K. pneumoniae
, there is a lack of knowledge of the contribution of food sources to colonization and subsequent infection in humans.
Development of a Test Card Based on Colloidal Gold Immunochromatographic Strips for Rapid Detection of Antibodies against Theileria equi and Babesia caballi
Authors: Yang Guangpu , Chen Kewei , Guo Wei , Hu Zhe , Qi Ting , Liu Diqiu , Wang Yaoxin , Du Cheng , Wang Xiaojun
Published: February 2022

Equine piroplasmosis (EP), caused by
Theileria equi
and
Babesia caballi
, is an important tick-borne disease of equines that is prevalent in most parts of the world. EP is considered a reportable disease by the World Organization for Animal Health (OIE).
Firearms: the leading cause of years of potential life lost
Authors: Klein Joshua , Prabhakaran Kartik , Latifi Rifat , Rhee Peter
Published: February 2022

Objectives

Data from the Centers for Disease Control and Prevention (CDC) show that firearm deaths are increasing in the USA. The aims of this study were to determine the magnitude of potential years of life lost due to firearms and to examine the evolution of firearm deaths on the basis of sex, race, and geographical location within the USA.

Methods

Data was extracted (2009–2018) from the National Vital Statistics Reports from the CDC and the Web-based Injury Statistics Query and Reporting System database. Years of potential life lost was calculated by the CDC standard of subtracting the age at death from the standard year of 80, and then summing the individual years of potential life lost (YPLL) across each cause of death.

Results

The YPLL in 2017 and 2018 was higher for firearms than motor vehicle crashes (MVCs). In 2018, the YPLL for firearms was 1.42 million and 1.34 million for MVC. Males comprised the majority (85.4%) of the 38 929 firearm deaths. White males had the most YPLL due to suicide, with 4.95 million YPLL during the course of the 10-year period; black males had the most YPLL due to homicide with 3.2 million YPLL during the same time period. The largest number of suicides by firearms was in older white males. Firearm-related injury deaths were highest in the South, followed by the West, Midwest, and Northeast, respectively.

Conclusion

Firearms are now the leading cause of YPLL in trauma. Firearm deaths have overtaken MVC as the mechanism for the main cause of potential years of life lost since 2017. Suicide in white males accounts for more YPLL than homicides. Deaths related to firearms are potentially preventable causes of death and prevention efforts should be redirected.

Level of evidence

Level III—Descriptive Study.
AAC Excellence oat
Authors: Yan Weikai , Fregeau-Reid Judith , deHaan Brad , Thomas Steve , Hayes Matt , Martin Richard , Cummiskey Allan , Pageau Denis , Morasse Isabelle , Orozovic Savka , Mitchell-Fetch Jennifer , Menzies Jim , Xue Allen , Mountain Nathan
Published: February 2022

AAC Excellence is a covered, spring oat (Avena sativa L.) cultivar developed by the Ottawa Research and Development Center (ORDC), Agriculture and Agri-Food Canada (AAFC). It was derived from a four-way cross, OA1250-1/MN07205//Rigodon/HiFi, made in 2009. It has been tested in the Quebec provincial Oat Registration and Recommendation (QCORR) trials since 2017. Based on orthogonal data from the 2018–2021 QCORR trials, AAC Excellence yielded 6% higher than the mean of official checks (AAC Dieter, Canmore, and CS Camden) and its yield was more stable across years than the checks and other cultivars. AAC Excellence had similar levels of test weight and kernel weight to those of the checks, a β-glucan level similar to Akina and better than AAC Nicolas and all checks, and a groat content level similar to AAC Nicolas and AC Dieter and better than Akina and other checks. It had a superior package of yield and quality and is most adapted to Quebec, the Maritimes, and northern Ontario.
Least-Distance Range Adjusted Measure in DEA: Efficiency Evaluation and Benchmarking for Japanese Banks
Authors: Wang Xu , Hasuike Takashi
Published: February 2022

This study aims to formulate the least-distance range adjusted measure (LRAM) in data envelopment analysis (DEA) and apply it to evaluate the relative efficiency and provide the benchmarking information for Japanese banks. In DEA, the conventional range adjusted measure (RAM) acts as a well-defined model that satisfies a set of desirable properties. However, because of the practicality of the least-distance measure, we formulate the LRAM and propose the use of an effective mixed integer programming (MIP) approach to compute it in this study. The formulated LRAM (1) satisfies the same desirable properties as the conventional RAM, (2) provides the least-distance benchmarking information for inefficient decision-making units (DMUs), and (3) can be computed easily by using the proposed MIP approach. Here, we apply the LRAM to a Japanese banking data set corresponding to the period 2017–2019. Based on the results, the LRAM generates higher efficiency scores and allows inefficient banks to improve their efficiency with a smaller extent of input–output modification than that required by the RAM, thereby indicating that the LRAM can provide more easy-to-achieve benchmarking information for inefficient banks. Therefore, from the perspective of the managers of DMUs, this study provides a valuable LRAM for efficiency evaluation and benchmarking analysis.
Calculations in induced gravity from higher-derivative field theories
Authors: Kan Nahomi , Shiraishi Kiyoshi
Published: February 2022

In this paper, we investigate Einstein’s gravity induced from higher-derivative scalar field theories. We develop an approach utilizing an effective theory of multiple fields for the higher-derivative theory. The expressions for induced cosmological constant and the induced gravitational constant are obtained in the present scenario of induced gravity in [Formula: see text] dimensions. We also show that finite values for the induced constants can be extracted in certain infinite-derivative theories.
Kosambi–Cartan–Chern Stability in the Intermediate Nonequilibrium Region of the Brusselator Model
Authors: Yamasaki Kazuhito , Yajima Takahiro
Published: February 2022

This study applies the Kosambi–Cartan–Chern (KCC) theory to the Brusselator model to derive differential geometric quantities related to bifurcation phenomena. Based on these geometric quantities, the KCC stability of the Brusselator model is analyzed in linear and nonlinear cases to determine the extent to which nonequilibrium affects bifurcation and stability. The geometric quantities of the Brusselator model have a constant value in the linear case, and are functions of spatial variables with parameter dependence in the nonlinear case. Therefore, the KCC stability of the nonlinear case shows various distribution patterns, depending on the distance from the equilibrium point (EQP), as follows: in the regions near or far enough from the EQP, the distribution of KCC stability is uniform and regular; and in the intermediate nonequilibrium region, the distribution varies and shows complex patterns with parameter dependence. These results indicate that stability in the intermediate nonequilibrium region plays an important role in the dynamic complex patterns in the Brusselator model.
65 competencies
Authors: Weiser Orli , Kalman Yoram M. , Kent Carmel , Ravid Gilad
Published: February 2022

Delphi study sets out to identify essential cognitive, interpersonal, and intrapersonal competencies needed for success in data analytics.
Underwater Sensor Multi-Parameter Scheduling for Heterogenous Computing Nodes
Authors: Elhoseny Mohamed , Lakhan Abdullah , Rashid Ahmed , Mohammed Mazin , Abdulkareem Karrar
Published: February 2022

Sensor-aware distributed workflow applications are becoming increasingly popular underwater. The apps are marine operations that generate data and process it based on its characteristics. Mobile-fog-cloud paradigms, as well as computing such as sensor nodes, have emerged. As previously stated, the nodes can be combined into a single system to achieve several goals. Many factors are considered, including network contents, workload fluctuation, variable execution durations, deadlines, and bandwidth. As a result, scheduling mobile workflow systems with multiple parameters might be challenging. The study suggests a novel content-efficient decision-aware task scheduling (CATSA) method for defining and adapting to complicated environmental changes. The CATSA consists of several components that work together to perform various benchmarks in the system, including a decision planner, sequencing, and scheduling. As evidenced by test findings during evaluation, the suggested architecture outperforms current studies regarding workflow execution quality of services and improved the makespan 30% and deadline meeting 40% in the study.
Towards Revenue Maximization with Popular and Profitable Products
Authors: Gan Wensheng , Chen Guoting , Yin Hongzhi , Fournier-Viger Philippe , Chen Chien-Ming , Yu Philip S.
Published: February 2022

Economic-wise, a common goal for companies conducting marketing is to maximize the return revenue/profit by utilizing the various effective marketing strategies. Consumer behavior is crucially important in economy and targeted marketing, in which behavioral economics can provide valuable insights to identify the biases and profit from customers. Finding credible and reliable information on products’ profitability is, however, quite difficult since most products tend to peak at certain times w.r.t. seasonal sales cycles in a year.
On-Shelf Availability (OSA)
plays a key factor for performance evaluation. Besides, staying ahead of hot product trends means we can increase marketing efforts without selling out the inventory. To fulfill this gap, in this paper, we first propose a general profit-oriented framework to address the problem of revenue maximization based on economic behavior, and compute the

O
n-shelf
P
opular and most
P
rofitable
P
roducts (OPPPs)

for the targeted marketing. To tackle the revenue maximization problem, we model the k-satisfiable product concept and propose an algorithmic framework for searching OPPP and its variants. Extensive experiments are conducted on several real-world datasets to evaluate the effectiveness and efficiency of the proposed algorithm.
QIRO: A Static Single Assignment-based Quantum Program Representation for Optimization
Authors: Ittah David , Häner Thomas , Kliuchnikov Vadym , Hoefler Torsten
Published: February 2022

We propose an IR for quantum computing that directly exposes quantum and classical data dependencies for the purpose of optimization. The

Quantum Intermediate Representation for Optimization

(QIRO)
consists of two dialects, one input dialect and one that is specifically tailored to enable quantum-classical co-optimization. While the first employs a perhaps more intuitive memory-semantics (quantum operations act on qubits via side-effects), the latter uses value-semantics (operations consume and produce states) to integrate quantum dataflow in the IR’s
Static Single Assignment (SSA)
graph. Crucially, this allows for a host of optimizations that leverage dataflow analysis. We discuss how to map existing quantum programming languages to the input dialect and how to lower the resulting IR to the optimization dialect. We present a prototype implementation based on MLIR that includes several quantum-specific optimization passes. Our benchmarks show that significant improvements in resource requirements are possible even through static optimization. In contrast to circuit optimization at run time, this is achieved while incurring only a small constant overhead in compilation time, making this a compelling approach for quantum program optimization at application scale.
On the Global Maximization of Network Lifetime in Wireless Rechargeable Sensor Networks
Authors: Van Quan La , Nguyen Minh Hieu , Nguyen Thanh Hung , Nguyen Kien , Le Nguyen Phi
Published: February 2022

In a Wireless Rechargeable Sensor Network (WRSN), a mobile charger (MC) moves and supplies energy for sensor nodes to maintain the network operation. Hence, optimizing the charging schedule of MC is essential to maximize the network lifetime in WRSNs. The existing works only target the local optimization of network lifetime limited to MC’s subsequent charging round. The network lifetime has been normally reflected in a different metric that is not directly related to the final charging round period. To the best of our knowledge, this work is the first to address the global maximization of network lifetime in WRSNs, which optimizes not only the subsequent charging round but all charging rounds over the entire network lifetime. Another uniqueness is the joint consideration of both the charging path and charging time optimization problems. As a solution, we propose a genetic algorithm (GA)-based global optimization scheme that considers all the possible charging rounds. The GA has a novel mutation operation that mutates gene sizes for representing charging schedules with a varying number of charging rounds. The experiment results show that our algorithm can extend the network lifetime by 35.1 times on average and 38.6 times in the best case compared to existing ones.
A group effort
Authors: Edwards Chris
Published: February 2022

Researchers look for new insights in the world of hypergraphs.
Algorithmic hiring needs a human face
Authors: Marks Paul
Published: February 2022

Artificial intelligence may be an unstoppable force, but in the recruitment market it has met an immovable object: humans. Something has to give.
A call to action
Authors: Baecker Ronald M.
Published: February 2022

Digital dreams have become nightmares: What we must do.
Improving the Dilation of a Metric Graph by Adding Edges
Authors: Gudmundsson Joachim , Wong Sampson
Published: February 2022

Most of the literature on spanners focuses on building the graph from scratch. This article instead focuses on adding edges to improve an existing graph. A major open problem in this field is: Given a graph embedded in a metric space, and a budget of 
k
edges, which 
k
edges do we add to produce a minimum-dilation graph? The special case where
k=1
has been studied in the past, but no major breakthroughs have been made for
k > 1
. We provide the first positive result, an
O(k)
-approximation algorithm that runs in
O(n
3
log
n
) time.
Modeling of PEMFC and Analysis of Multiple Influencing Factors on Output Characteristics
Authors: Yang Yang , Zhu Wen-Chao , Li Yang , Zhao Bo , Zhang Lei-Qi , Song Jie , Deng Zhan-Feng , Shi Ying , Xie Chang-Jun
Published: February 2022

The output characteristics of the Proton-Exchange Membrane Fuel Cells (PEMFCs) are affected by multiple factors, but quantitatively describing the relationships is challenging. In this paper, a semi-empirical dynamic model of PEMFC is established firstly. The influence of a single factor on the output characteristics of PEMFC is analyzed longitudinally. Then, a derivative significance weight analysis based on support vector regression (SVR-DSWA) algorithm is proposed to analyze the influence weights of multi-factors on the output characteristics, and the optimal parameters combinations in different current density regions are obtained by maximizing the output voltage values based on formulated SVR model. The Root-Mean-Square Error (RMSE) of output voltage prediction results based on the SVR algorithm is less than 0.0458, and the accuracy of weight analysis results by using the SVR-DSWA algorithm and the optimal parameters combinations analysis method are verified by 4-factor 3-level orthogonal experiments in low, medium, and high current density regions. The SVR-DSWA algorithm and optimal parameters combinations analysis method can replace the orthogonal experiment to analyze the influence weights and optimal combinations of input factors on the output characteristics within the full current density range rapidly, and has much higher efficiency than the orthogonal experiment. The analysis results can provide theoretical support for improving fuel cell performance and formulating a control strategy.
Effect of Chloride on the Pitting Corrosion of Carbon Steel in Alkaline Solutions
Authors: Qiu Jie , Zhu Yakun , Xu Yi , Li Yanhui , Mao Feixiong , Wu Angjian , Macdonald Digby D
Published: February 2022

The effect of chloride concentration on the passivity breakdown of carbon steel in deaerated pH = 13.5 alkaline solution was investigated. The results show that chloride plays an important role for the pitting corrosion of carbon steel. When NaCl

≤

1

M
,

the carbon steel is passive but for

1

M
<

NaCl < 2

M
,

the carbon steel transfers from passive to passivity breakdown. When NaCl

≥

2

M
,

passive film breakdown occurs and the passivity breakdown potential (E

b
) of carbon steel is linearly-dependent on the logarithm of the chloride activity in the alkaline solution. As predicted by the PDM, the near-normal distribution of

E

b

is well indicated by the near straight line in the cumulative distribution probability. The analysis in this study gives us a method to calculate the

E

b

of carbon steel in alkaline solution and its distribution for any given chloride concentration.
An Innovative Framework for Dynamic Traffic Lights Management Based on the Combined Use of Fuzzy Logic and Several Network Architectures
Authors: Arena Fabio , Pau Giovanni , Ralescu Anca , Severino Alessandro , You Ilsun
Published: February 2022

The development of Information and Communication Technologies (ICT) has now reached some entirely unexpected domains. Many applications in modern cities lead to novelties, resulting in new habits of the citizens of tomorrow’s smart cities. These innovations include Intelligent Transportation Systems (ITS). An important application domain of ITS is undoubtedly represented by the dynamic and optimized management of traffic-lighted road intersections. Although several works have already been presented in the literature over the years, many have not considered the new perspectives regarding the source of data to manage traffic lights, i.e., not only Wireless Sensor Networks (WSNs), but, mainly, the vehicular communications. This paper introduces an innovative approach to dynamically regulating traffic light cycles and phases in an isolated intersection. The suggested method can fit data management from WSNs and vehicular communications through IEEE 802.11p and LTE-V2V, employing various Fuzzy Logic Controllers (FLCs) that manage vehicles turning movements for dynamic controls of both the phase and the green time of traffic lights. The results obtained will allow us to observe that the proposed application is better than the others. Each of the implemented configurations will bring advantages and disadvantages that allow choosing one configuration or another based on specific project requirements.
Nanohydroxyapatite‐Blasted Bioactive Surface Drives Shear‐Stressed Endothelial Cell Growth and Angiogenesis
Authors: Pinto T. S. , Martins B. R. , Ferreira M. R. , Bezerra F. , Zambuzzi W. F.
Published: February 2022

Nanosized crystalline hydroxyapatite coating (HAnano®) accelerates the osteointegration of dental implants which is hypothesized to drive angiogenesis. In order to test this hypothesis, we have subjected shear‐stressed human umbilical vein endothelial cells (HUVECs) to a HAnano®‐enriched medium, as well as to surface presenting dual acid etching (DAE) as a control. To note, the titanium implants were coated with 10 nm in diameter HA particles using the Promimic HAnano method. Our data reveals that HAnano® modulates higher expression of genes related with endothelial cell performance and viability, such as VEGF, eNOS, and AKT, and further angiogenesis in vitro by promoting endothelial cell migration. Additionally, the data shows a significant extracellular matrix (ECM) remodeling, and this finding seems developing a dual role in promoting the expression of VEGF and control endothelial cell growth during angiogenesis. Altogether, these data prompted us to further validate this phenomenon by exploring genes related with the control of cell cycle and in fact our data shows that HAnano® promotes higher expression of CDK4 gene, while p21 and p15 genes (suppressor genes) were significantly lower. In conjunction, our data shows for the first time that HAnano®‐coated surfaces drive angiogenesis by stimulating a proliferative and migration phenotype of endothelial cells, and this finding opens novel comprehension about osseointegration mechanism considering nanosized hydroxyapatite coating dental implants.
A Hemolysis Image Detection Method Based on GAN-CNN-ELM
Authors: Shi Xiaonan , Deng Yong , Fang Yige , Chen Yajuan , Zeng Ni , Fu Limei
Published: February 2022

Since manual hemolysis test methods are given priority with practical experience and its cost is high, the characteristics of hemolysis images are studied. A hemolysis image detection method based on generative adversarial networks (GANs) and convolutional neural networks (CNNs) with extreme learning machine (ELM) is proposed. First, the image enhancement and data enhancement are performed on a sample set, and GAN is used to expand the sample data volume. Second, CNN is used to extract the feature vectors of the processed images and label eigenvectors with one-hot encoding. Third, the feature matrix is input to the map in the ELM network to minimize the error and obtain the optimal weight by training. Finally, the image to be detected is input to the trained model, and the image with the greatest probability is selected as the final category. Through model comparison experiments, the results show that the hemolysis image detection method based on the GAN-CNN-ELM model is better than GAN-CNN, GAN-ELM, GAN-ELM-L1, GAN-SVM, GAN-CNN-SVM, and CNN-ELM in accuracy and speed, and the accuracy rate is 98.91%.
Expletive ta in Mandarin Chinese: A Quantitative Study
Authors: Yu Yue , Zhao Qiurong
Published: February 2022

Expletive pronouns have posed significant challenges to both linguistic studies and natural language processing in Chinese. Based on the data from the Chinese corpus at the Center for Chinese Linguistics of Peking University (CCL), this paper investigates the automatic dependency parsing errors of expletive ta (“it/he”) and relative constructions and provides a detailed quantitative analysis of the characteristics of the constructions in question. The findings not only provide evidence to show that even in radical pro‐drop languages such as Mandarin, pleonastics can occur in both object and subject positions but also offer important insights for Chinese natural language processing.
Study on the Influence of Borehole Water Content on Bolt Anchoring Force in Soft Surrounding Rock
Authors: Zhang Pandong , Gao Lin , Liu Pengze , Wang Yongyin , Liu Ping , Kang Xiangtao
Published: February 2022

In order to further reveal the influence mechanism of borehole water content on anchoring force in soft surrounding rock, three different research methods are used. Firstly, through theoretical analysis, it reveals that borehole water content will affect the cohesion of anchoring agent and then leads to the decrease of anchoring force. Secondly, through experimental analysis and numerical simulation of the influence of different boreholes water content on the anchoring force, it indicates that the borehole water content has a weakening effect on the mechanics characteristics of bolts significantly. When the borehole water content is less than 15 mL, the influence of borehole water content on anchoring force is weak for a given borehole length. When the borehole water content is greater than 15 mL, the anchoring force decreases greatly with the increase of borehole water content for a given borehole length and the decline of anchorage force is more than 30%. At the same time, through the experimental analysis, it reveals that the failure type of bolt in weak surrounding rock is the typical failure of anchorage force where the fracture goes far into the surrounding rock. Thus, in practical operation, reasonably controlling the borehole water content (rate) within the critical value can improve the bolt support effect and reduce the support cost.
Intravitreal Administration Effect of Adipose-Derived Mesenchymal Stromal Cells Combined with Anti-VEGF Nanocarriers, in a Pharmaceutically Induced Animal Model of Retinal Vein Occlusion
Authors: Gounari Eleni , Komnenou Anastasia , Kofidou Evangelia , Nanaki Stavroula , Bikiaris Dimitrios , Almpanidou Stavroula , Kouzi Kokkona , Karampatakis Vasileios , Koliakos George
Published: February 2022

Antiangiogenic therapeutic agents (anti-VEGF) have contributed to the treatment of retinal vein occlusion (RVO) while mesenchymal stromal cell- (MSCs-) mediated therapies limit eye degeneration. The aim of the present study is to determine the effect of adipose-derived MSCs (ASCs) combination with nanocarriers of anti-VEGF in a pharmaceutically induced animal model of RVO. Nanoparticles (NPs) of thiolated chitosan (ThioCHI) with encapsulated anti-VEGF antibody were prepared. ASCs were isolated and genetically modified to secrete the green fluorescence GFP. Twenty-four New Zealand rabbits were divided into the I-IV equal following groups: ASCs, ASCs + nanoThioCHI-anti-VEGF, RVO, and control. For the RVO induction, groups I-III received intravitreal (iv) injections of MEK kinase inhibitor, PD0325901. Twelve days later, therapeutic regiments were administered at groups I-II while groups III-IV received BSS. Two weeks later, the retinal damage evaluated via detailed ophthalmic examinations, histological analysis of fixed retinal sections, ELISA for secreted cytokines in peripheral blood or vitreous fluid, and Q-PCR for the expression of related to the occlusion and inflammatory genes. Mild retinal edema and hemorrhages, limited retinal detachment, and vasculature attenuation were observed in groups I and II compared with the pathological symptoms of group III which presented a totally disorganized retinal structure, following of positive immunostaining for neovascularization and related to RVO markers. Important reduction of the high secreted levels of inflammatory cytokines was quantified in groups I and II vitreous fluid, while the expression of the RVO-related and inflammatory genes has been significantly decreased especially in group II. GFP+ ASCs, capable of being differentiated towards neural progenitors, detected in dissociated retina tissues of group II presenting their attachment to damaged area. Conclusively, a stem cell-based therapy for RVO is proposed, accompanied by sustained release of anti-VEGF, in order to combine the paracrine action of ASCs and the progressive reduction of neovascularization.
An Energy Detection-Based Spectrum-Sensing Method for Cognitive Radio
Authors: Luo Jun , Zhang Guoping , Yan Chiyu
Published: February 2022

Energy detection (ED) method is one of the most commonly used signal-sensing methods in spectrum sensing due to its low implementation complexity. ED can achieve good detection performance when the noise variance is known. However, in most cases, the noise variance is estimated, which may result in the uncertainty in noise variance. In the presence of noise variance uncertainty, the detection performance of the ED method may degrade significantly. To reduce the impact of uncertainty in noise variance, an ED-based sensing method is proposed in this paper. This method combines these signal samples sampled by multiple antennas to obtain the decision statistic as ED does. A novel technique is proposed to construct the decision threshold so that it is independent of the noise variance. As a consequence, the proposed method is free of the effect of noise variance uncertainty, and the noise variance estimation is not need. The simulation results show that the detection probability of this method can approach to 1 even when the SNR is −15 dB while the detection probability of ED is below 0.8, which means the detection performance of the proposed method can outperform the ED method without the noise variance estimation when the number of antennas is greater than two.
English Teaching Evaluation Combined with End-User Computing and Neural Network
Authors: Tan Qingyan
Published: February 2022

A neural network model and English teaching evaluation of university with end-user computing are the focus of this paper. The main research contributions are as follows: (1) Propose an ADA-BP neural network. It applies the adaptive learning rate as well as the momentum term to promote the BP network. Experiments show that the model solves the problems of the existing methods and models such as difficulty in determining weights, prone to overfitting, slow convergence, and prone to local minimums, which verifies the effectiveness in evaluating college English teaching. (2) Propose the DA-SVR network. The model has multiple hidden layers and performs multiple feature conversions to optimize the network. The output layer of the model uses SVR as a predictor to achieve evaluation. (3) Deploy the designed evaluation network on the server, and end users can use the API interface to directly access and test the model functions. Massive experiments have verified the effectiveness of the designed method.
Finite-Time Attitude Cooperative Control of Multiple Unmanned Aerial Vehicles via Fast Nonsingular Terminal Sliding Mode Control
Authors: Han Qiang , Tuo Xianguo , Tang Yuxin , He Ping
Published: February 2022

This paper discusses the attitude cooperative control of multiple unmanned aerial vehicle systems (MUAVs) with unknown dynamics and external disturbances. Distributed fast nonsingular terminal sliding mode control (FNTSMC) is used with quaternion-description dynamical systems. The dynamics and external disturbances are changed into lumped disturbances by formula transformation. A robust nonlinear disturbance observer is proposed to estimate the lumped disturbances in finite time. Then, combining the fast terminal sliding mode control, distributed FNTSMC controllers are designed under the directed topology. Based on the Lyapunov stability theory and graph theory, convergence stability of the nonlinear systems is strictly proved, and the tracking errors between the leader and the followers approach to a small residual set. Finally, the simulation example is presented to illustrate the effectiveness and advantage of the proposed controllers.
Construction of Relationship Model between College Students’ Psychological Status and Epidemic Situation Based on BP Neural Network
Authors: Yao Shuguang
Published: February 2022

In view of the impact of COVID-19 on the mental health of college students, this paper proposes a study on the relationship between psychological status and epidemic situation of university students based on BP neural network, so as to provide theoretical basis for universities to take targeted mental health education. This paper investigates the effects of COVID-19 on the psychological emotions of college students. According to the behavior and psychological characteristics of college students, the relevant investigation results are obtained through event monitoring, early warning, and usual performance, and a relationship model between college students’ psychological status and epidemic situation based on BP neural network is constructed. This paper studies several factors through the relationship model and uses the principal component analysis method to analyze the impact of various factors on college students’ psychology. According to the model prediction and result analysis, it concluded that the influence of COVID-19 should focus on improving the professional quality, physical quality, humanistic quality, and moral quality of university students, so as to improve the stability of colleges and universities in the event of public health emergencies. The model constructed in this paper can provide reference for carrying out mental health education and formulating effective intervention programs.