bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of Physical Activity at 90 Days After Acute Stroke or Transient Ischemic Attack in Patients With Home Discharge: A Pilot Study
Authors: Yokota Chiaki , Ohta Sachiko , Fujimoto Yasuyuki
Published: October 2021

The aim was to identify the barriers to achieving premorbid physical activity in patients with home discharge after acute minor stroke or transient ischemic attack. Fifty-six patients (median age, 72 years) were analyzed. We assessed total physical activity in the premorbid condition and at 90 days after onset using the International Physical Activity Questionnaire. The patients were divided into two groups according to changes in total physical activity until 90 days after onset: decreased activity (n = 16) and nondecreased activity (n = 40) groups. Outcome measures were examined at discharge. The decreased activity group took significantly longer to perform the timed up and go test (median, 7.19 vs. 6.52 s) and contained more apathetic patients (44% vs. 15%). Apathy at discharge (relative risk 6.05, 95% confidence interval [1.33, 27.6]) was a significant determinant of decreased physical activity. Apathy is a barrier to the restoration of premorbid physical activity in stroke survivors.
Europe's Science Powerhouses Face Limits to Growth
Authors: Kahn Patricia , Balter Michael
Published: October 2021

Universities in Germany and France are facing similar problems: Reforms launched in the 1960s and 1970s have led to a big increase in student numbers, but spending on higher education has not kept pace. The result in both countries is overcrowding and alienation among students. Both also face a major constraint on reform at the local level: Decisions on university policy are made by the central government. The two countries are beginning to take different paths out of these difficulties, however. These are discussed more fully in separate articles.
Poland: Teachers Struggle With Low Funds and Morale
Authors: Koenig Robert
Published: October 2021

Warsaw—Science education in Poland is still haunted by the ghosts of the old system, in which research was largely conducted in academy institutes while teaching was conducted in the universities. University courses also tend to be narrow and inflexible. Efforts to bridge this gap have been hampered by lack of funds in the past few years, although there have been exceptions, such as a new biology program at Gdansk and interdisciplinary programs at Warsaw University and Krakow's Jagiellonian University. Without more government support, however, one leading academic says education is likely to move backward.
Czech Republic: Grad School Bridges Old Divisions
Authors: Kahn Patricia
Published: October 2021

Prague—Charles University, one of Europe's oldest universities, is undergoing a transformation as it struggles to regain its place in international science. The university had become deeply divided into individual faculties, providing specialized education. In an attempt to link these factions, a new Postgraduate School in Biomedicine was formed 3 years ago with representatives of different faculties and academy institutes where students could earn Ph.D.s based on original research. One big problem remains, however: science's sinking attractiveness as a career.
Nonlinear Simulations of Jupiter's 5-Micron Hot Spots
Authors: Showman Adam P. , Dowling Timothy E.
Published: October 2021

Large-scale nonlinear simulations of Jupiter's 5-micron hot spots produce long-lived coherent structures that cause subsidence in local regions, explaining the low cloudiness and the dryness measured by the Galileo probe inside a hot spot. Like observed hot spots, the simulated coherent structures are equatorially confined, have periodic spacing, propagate west relative to the flow, are generally confined to one hemisphere, and have an anticyclonic gyre on their equatorward side. The southern edge of the simulated hot spots develops vertical shear of up to 70 meters per second in the eastward wind, which can explain the results of the Galileo probe Doppler wind experiment.
CRISPR patent fight revived
Authors: Cohen Jon
Published: October 2021

U.S. patent office issues new interference declaration
Technology Feature | Small images, big picture: Artificial intelligence to revolutionize microscopy
Authors: O'Meara Sarah
Published: October 2021

Researchers hope that bringing deep learning techniques to cell imaging and analysis could turn messy biological problems into solvable computations.
NASA set to announce Earth system observatory
Authors: Voosen Paul
Published: October 2021

Climate-monitoring satellites mark resurgence for agency's earth science division.
Interfer’n with antibody responses
Authors: Laidlaw Brian J. , Cyster Jason G.
Published: October 2021

Type I interferon blocks the generation of neutralizing antibodies in response to chronic infection.

See related Research Articles by

Fallet
et al.

,

Moseman
et al.

, and

Sammicheli
et al.
Placental chorioangioma: an unusual cause of neonatal cardiomyopathy
Authors: Solan Tom , Thomas Niranjan , Kee Penny
Published: October 2021

A late preterm baby presented with clinical and echocardiographic features of cardiomyopathy and cardiac failure soon after birth. After extensive metabolic, infective and genetic investigations, the likely cause was established to be due to multiple small placental chorioangiomas. While large placental chorioangiomas are associated with maternal, fetal and neonatal complications, small chorioangiomas are usually asymptomatic and diagnosed incidentally on placental histology. Our case demonstrates that multiple small chorioangiomas might behave like a giant chorioangioma, causing significant neonatal morbidity. This report also highlights the importance of assessing the placental histology where no identifiable cause for neonatal cardiomyopathy can be found.
Thrombotic thrombocytopenic purpura after ChAdOx1 nCoV-19 vaccine
Authors: Lee Hui Ping , Selvaratnam Veena , Rajasuriar Jay Suriar
Published: October 2021

A 50-year-old Indian woman presented with acute dysphasia, left upper limb numbness and thrombocytopenia 12 days after receiving the ChAdOx1 nCoV-19 vaccine (AstraZeneca/Vaxzevria). MRI of the brain was unremarkable. Microangiopathic haemolytic anaemia with thrombocytopenia was noted on her peripheral blood film. A diagnosis of thrombotic thrombocytopenic purpura (TTP) was confirmed through the findings of absent ADAMTS13 (a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13) activity and markedly raised titre of ADAMTS13 autoantibodies. Prompt treatment with plasma exchange, adjunctive steroids and rituximab was commenced. A remission of TTP was achieved and she was discharged 3 weeks after admission. While other immune-mediated conditions have been documented after receipt of the vaccine, this report highlights the first case of immune-mediated TTP diagnosed after administration of the ChAdOx1 nCoV-19 vaccine.
COVID-19: responding to a pandemic on Operation TORAL
Authors: Webster Stacey , Gough A , Riley M R , Makin S
Published: October 2021

Operation TORAL was the UK’s contribution to NATO’s Operation RESOLUTE SUPPORT in Kabul, Afghanistan. Approximately 1000 British troops were deployed in Kabul when the arrival of the COVID-19 pandemic in Afghanistan was declared. This article will describe the challenges faced due to COVID-19 in Kabul.

Medical planning considerations, occupational health issues, implementation of behaviour change and operating as part of a multinational organisation are all discussed, with challenges encountered detailed and potential solutions offered. The use of a suggested framework for ensuring the medical estimate process covered all areas relevant to an emerging viral pandemic —the 4Ds and 4Cs approach—proved particularly useful in the early stages of the pandemic in Afghanistan.
Is there a role for physical activity when treating patients with cancer with immune checkpoint inhibitors? Protocol for a scoping review
Authors: Chen Miaoqi , Rai Ridesh , Fox Louis , Moss Charlotte Louise , George Gincy , Karagiannis Sophia N , Enting Deborah , Joseph Magdalene , Peat Nicola , Russell Beth , Van Hemelrijck Mieke
Published: October 2021

Introduction

For patients with cancer, immune checkpoint inhibitors (ICIs) produce superior long-term responses compared with alternative treatments, although at the cost of manifesting adverse immune-related events. There are many hypotheses of the impacts of physical activities in immunotherapy, but little is known about the oncological outcomes and the underlying mechanisms. This scoping review aims to identify possible physical activity interventions, their efficacy and feasibility and the potential underlying biological mechanisms responsible for their effects.

Method and analysis

The Levac methodology framework was used along with guidance from the Joanna Briggs Institute Manual for Evidence Synthesis to inform development of this protocol. Abstracts and titles followed by full-text screening will be performed by two independent reviewers for inclusion. All studies describing the impact of physical activities and exercise interventions on cancer ICIs, with particular focus on oncological outcomes, quality of life or underling biological mechanisms, will be included. After extracting qualitative and quantitative data, they will be evaluated and summarised, respectively. Subsequently, a further consultation step with other scientists and healthcare professionals will be performed.

Ethics and dissemination

The research findings will be published through an open-access peer-reviewed journal. The results of this scoping review will be used to inform further studies on physical impacts on immunotherapy. All data included will be from open resources, therefore, no ethical clearances are required.
A critical state constitutive model for gassy clay
Authors: Gao Zhiwei , Cai Hongjian , Hong Yi , Lu Dechun
Published: October 2021

Fine-grained marine sediments often contain gas bubbles that can cause many geotechnical problems. This soil has a composite structure with gas bubbles fitting within the saturated soil matrix. The gas cavity has a detrimental effect on the soil stiffness and strength when they are filled with undissolved gas only. The gas cavity can be filled with gas and pore water due to “bubble flooding”. Bubble flooding has a beneficial effect on the soil stiffness and undrained shear strength because it makes the saturated soil matrix partially drained under a globally undrained condition. A critical state constitutive model for gassy clay is presented that accounts for the composite structure of the soil and bubble flooding. The gas cavity is assumed to have a detrimental effect on the plastic hardening of the saturated soil matrix. Some of the bubbles can be flooded by pore water from the saturated soil matrix, which leads to higher mean effective stress of the saturated soil matrix. Consequently, both soil stiffness and strength increase. Only one new parameter is introduced to model the detrimental effect of gas bubbles on plastic hardening. The model has been validated by the results of three gassy clays.
Physics potential for the H$$\rightarrow \hbox {ZZ}^{*}$$ decay at the CEPC
Authors: Kiuchi Ryuta , Gu Yanxi , Zhong Min , Kong Lingteng , Schuy Alex , Hsu Shih-Chieh , Shi Xin , Zhang Kaili
Published: October 2021

The precision of the yield measurement of the Higgs boson decaying into a pair of Z bosons process at the Circular Electron Positron Collider is evaluated. Including the recoil Z boson associated with the Higgs production (Higgsstrahlung) a total of three Z bosons are involved for this channel, from which final states characterized by the presence of a pair of leptons, quarks, and neutrinos are chosen for the signal. Two analysis approaches are compared and the final statistical precision of $${\sigma }_{\mathrm {ZH}}{\cdot }$$

σ
ZH

·

BR($$H \rightarrow ZZ^{*}$$

H
→
Z

Z

∗

) is estimated to be 6.9% using a multivariate analysis technique, based on boosted decision trees. The relative precision of the Higgs boson width, using this $$H \rightarrow ZZ^{*}$$

H
→
Z

Z

∗

decay topology, is estimated by combining the obtained result with the precision of the inclusive ZH cross section measurement.
Metrizability of spaces of valuation domains associated to pseudo-convergent sequences
Authors: Peruginelli G. , Spirito D.
Published: October 2021

Let V be a valuation domain of rank one with quotient field K. We study the set of extensions of V to the field of rational functions K(X) induced by pseudo-convergent sequences of K from a topological point of view, endowing this set either with the Zariski or with the constructible topology. In particular, we consider the two subspaces induced by sequences with a prescribed breadth or with a prescribed pseudo-limit. We give some necessary conditions for the Zariski space to be metrizable (under the constructible topology) in terms of the value group and the residue field of V.
On split equality equilibrium, monotone variational inclusion and fixed point problems in Banach spaces
Authors: Godwin Emeka Chigaemezu , Abass Hammed Anuoluwapo , Izuchukwu Chinedu , Mewomo Oluwatosin Temitope
Published: October 2021

In this paper, we propose and study a new algorithm for finding a common element of the sets of solutions of split equality pseudomonotone equilibrium, split equality monotone variational inclusion and fixed point problems for Bregman relatively nonexpansive mappings in [Formula: see text]-uniformly convex and uniformly smooth Banach spaces. Our iterative method uses stepsizes which do not require prior knowledge of the operator norm. We apply our result to solve split equality variational inequality and split equality convex minimization problems. The result present in this paper unifies and extends several existing results in the literature.
A note on matrix domains of Copson matrix of order α and compact operators
Authors: Ayman Mursaleen Mohammad
Published: October 2021

Roopaei [J. Inequal. Appl. 2020 (2020) 120] introduced the sequence space [Formula: see text] which is a matrix domain of Copson matrix in the space [Formula: see text] [Formula: see text] In this paper, we characterize the matrix classes [Formula: see text], [Formula: see text] and [Formula: see text] [Formula: see text]. Moreover, we characterize compact operators associated with matrices belonging to these classes via the techniques of measures of noncompactness.
On the derivations of BiHom-Poisson superalgebras
Authors: Khalili Valiollah , Asif Sania
Published: October 2021

In this paper, our objective is to study numerous fundamental properties of the algebra of generalized derivations on a multiplicative BiHom-Poisson superalgebra [Formula: see text]. First, we present a description of some generalized derivations, central derivations, quasiderivations, centroid and quasicentroid of the multiplicative BiHom-Poisson superalgebra [Formula: see text] More specifically, we obtain some important connections and properties of these derivations. We prove that in a larger multiplicative BiHom-Poisson superalgebra, [Formula: see text] can be embedded as a derivations algebra. Finally, we show that when [Formula: see text] is centerless, the derivations of the larger multiplicative BiHom-Poisson superalgebras have direct sum decompositions.
EXPLORING FAIR AND AMBITIOUS MITIGATION CONTRIBUTIONS OF ASIAN ECONOMIES FOR THE GLOBAL WARMING LIMIT UNDER THE PARIS AGREEMENT
Authors: LI XINRU , JIANG XUEMEI , XIA YAN
Published: October 2021

Focusing on the mitigation responsibilities and efforts, this paper provides a unified estimation of allowable emission quotas for a number of Asian economies to limit the global temperature rise well below 2°C based on a range of effort-sharing approaches. The study also explores the inconsistency between their planned emission pathways under the Nationally Determined Contributions (NDCs) and the allowable emissions to achieve the 2°C target. The results show that most of the Asian developing economies would be in favor of the Equal-Per-Capita and Grandfather criteria, for which they would obtain more allowable emissions quota. However, even with the most favorable criterion, official mitigation pledges represented by NDCs are far less enough for these developing Asian economies such as China, India, Vietnam, Thailand and Pakistan, as their emission pathways under NDCs significantly exceed the ideal pathways under all effort-sharing approaches. In contrast, most of the Asian developed economies have already planned reductions of annual CO2 emissions under NDCs, in line with their ideal pathways under the most favorable effort-sharing approach. However, their reductions of emissions require deep strengthening of deployment in low-carbon, zero-carbon and negative-carbon techniques, given the current growing trend of emissions for these economies.
The Model Counting Competition 2020
Authors: Fichte Johannes K. , Hecher Markus , Hamiti Florim
Published: October 2021

Many computational problems in modern society account to probabilistic reasoning, statistics, and combinatorics. A variety of these real-world questions can be solved by representing the question in (Boolean) formulas and associating the number of models of the formula directly with the answer to the question. Since there has been an increasing interest in practical problem solving for model counting over the past years, the Model Counting Competition was conceived in fall 2019. The competition aims to foster applications, identify new challenging benchmarks, and promote new solvers and improve established solvers for the model counting problem and versions thereof. We hope that the results can be a good indicator of the current feasibility of model counting and spark many new applications. In this article, we report on details of the Model Counting Competition 2020, about carrying out the competition, and the results. The competition encompassed three versions of the model counting problem, which we evaluated in separate tracks. The first track featured the model counting problem, which asks for the number of models of a given Boolean formula. On the second track, we challenged developers to submit programs that solve the weighted model counting problem. The last track was dedicated to projected model counting. In total, we received a surprising number of nine solvers in 34 versions from eight groups.
An Updated Experimental Evaluation of Graph Bipartization Methods
Authors: Goodrich Timothy D. , Horton Eric , Sullivan Blair D.
Published: October 2021

We experimentally evaluate the practical state-of-the-art in graph bipartization (Odd Cycle Transversal (OCT)), motivated by the need for good algorithms for embedding problems into near-term quantum computing hardware. We assemble a preprocessing suite of fast input reduction routines from the OCT and Vertex Cover (VC) literature and compare algorithm implementations using Quadratic Unconstrained Binary Optimization problems from the quantum literature. We also generate a corpus of frustrated cluster loop graphs, which have previously been used to benchmark quantum annealing hardware. The diversity of these graphs leads to harder OCT instances than in existing benchmarks.

In addition to combinatorial branching algorithms for solving OCT directly, we study various reformulations into other NP-hard problems such as VC and Integer Linear Programming (ILP), enabling the use of solvers such as CPLEX. We find that for heuristic solutions with time constraints under a second, iterative compression routines jump-started with a heuristic solution perform best, after which point using a highly tuned solver like CPLEX is worthwhile. Results on exact solvers are split between using ILP formulations on CPLEX and solving VC formulations with a branch-and-reduce solver. We extend our results with a large corpus of synthetic graphs, establishing robustness and potential to generalize to other domain data. In total, over 8,000 graph instances are evaluated, compared to the previous canonical corpus of 100 graphs.

Finally, we provide all code and data in an open source suite, including a Python API for accessing reduction routines and branching algorithms, along with scripts for fully replicating our results.
Tailored Reality: Perception-aware Scene Restructuring for Adaptive VR Navigation
Authors: Dong Zhi-Chao , Wu Wenming , Xu Zenghao , Sun Qi , Yuan Guanjie , Liu Ligang , Fu Xiao-Ming
Published: October 2021

In virtual reality (VR), the virtual scenes are pre-designed by creators. Our physical surroundings, however, comprise significantly varied sizes, layouts, and components. To bridge the gap and further enable natural navigation, recent solutions have been proposed to redirect users or recreate the virtual content. However, they suffer from either interrupted experience or distorted appearances. We present a novel VR-oriented algorithm that automatically restructures a given virtual scene for a user’s physical environment. Different from the previous methods, we introduce neither interrupted walking experience nor curved appearances. Instead, a perception-aware function optimizes our retargeting technique to preserve the fidelity of the virtual scene that appears in VR head-mounted displays. Besides geometric and topological properties, it emphasizes the unique first-person view perceptual factors in VR, such as dynamic visibility and objectwise relationships. We conduct both analytical experiments and subjective studies. The results demonstrate our system’s versatile capability and practicability for natural navigation in VR: It reduces the virtual space by 40% without statistical loss of perceptual identicality.
Locating Identities in Time: An Examination of the Formation and Impact of Temporality on Presentations of the Self through Location-Based Social Networks
Authors: Papangelis Konstantinos , Lykourentzou Ioanna , Khan Vassilis-Javed , Chamberlain Alan , Cao Ting , Saker Michael , Lalone Nicolas
Published: October 2021

Studies of identity and location-based social networks (LBSN) have tended to focus on the performative aspects associated with marking one's location. Yet these studies often present this practice as being an
a priori
aspect of locative media. What is missing from this research is a more granular understanding of how this process develops over time. Accordingly, we focus on the first 6 weeks of 42 users beginning to use an LBSN we designed and named
GeoMoments
. Through our analysis of our users' activities, we contribute to understanding identity and LBSN in two distinct ways. First, we show how LBSN users develop and perform self-identity over time. Second, we highlight the extent these temporal processes reshape the behaviors of users. Overall, our results illustrate that although a performative use of GeoMoments does evolve, this development does not occur in a vacuum. Rather, it occurs within the dynamic context of everyday life, which is prompted, conditioned, and mediated by the way the affordances of GeoMoments digitally organize and archive past locational traces.
On Social Contagion in Gamification
Authors: Loria Enrica , Nacke Lennart E. , Marconi Annapaola
Published: October 2021

Social connections shape our behaviour because of peer pressure and social contagion. This phenomenon is amplified in online networks by particularly influential individuals: influencers. Although this concept originated in social media, recent research shows how influencers can also exist in games and affect players' long-term retention. Prolonged retention caused by influencers could benefit gameful systems, especially if the system's goal is positive behavioural change. Retention is desirable because it can aid in internalizing new habits. Therefore, we investigated retention influencers' presence within a location-based persuasive gamified system (Play&Go) and their influence on other behaviours (i.e., the pursuit of a gamification goal), via social network analysis techniques. Results show how retention influencers exist in Play&Go and how studying different influence types (which push the systems' goals) may lead to different influencer groups. Our findings emphasize the importance of social mechanics in location-based gamification and discuss the value of understanding a player community to improve game design.
The Pandemic as a Catalyst for Reimagining the Foundations of Location-Based Games
Authors: Bhattacharya Arpita , Windleharth Travis W. , Lee Cassandra , Paramasivam Amulya , Kientz Julie A. , Yip Jason C. , Lee Jin Ha
Published: October 2021

Mainstream location-based games (LBGs) highlight three foundations-exercise, exploration, and social interaction-which were hugely disrupted by the COVID-19 pandemic. This genre has already had access issues depending on the player's region, identity, ability, and technology, which the pandemic also amplified. Thus, the pandemic provided a unique opportunity to re-imagine the design of LBGs to preserve player benefits while challenging these foundations. We conducted a two-week diary study with 11 LBG players coping with difficult life circumstances, followed by remote co-design sessions. Participants continued to play primarily to maintain community connection while adjusting the mode of socialization, finding meaning through virtual exploration, and support mental health and personal growth. Participants discussed ways to enhance the experience by expanding the range of physical activities during social distancing, reimagining proximity-based social interactions, and exploring via social construction of places while expanding beyond how the three foundations are currently supported in LBGs.
Players' Stories and Secrets in Animal Crossing
Authors: Tong Xin , Gromala Diane , Neustaedter Carman , Fracchia F. David , Dai Yisen , Lu Zhicong
Published: October 2021

Animal Crossing is an online multiplayer game that supports social communication and collaboration. Its recent version, New Horizons, is immensely popular having sold over 32 million copies worldwide, with many players attracted to the opportunities it provides to remotely socialize during the COVID-19 pandemic. To understand players' increased positive emotions and social interactions, we surveyed 119 of them betweenMay and December 2020 and conducted remote interviews with 25 respondents. We identified the social dynamics among players and with non-player characters (NPCs), and analyzed how positive social interactions were facilitated under player-generated narratives and game-determined narratives. Based on our empirical analyses, we have extended our understanding of how to create positive, safe, and friendly interactions: (1)the design of mood-improving game worlds with flexible game tasks, (2) implementation of game-determined activities with social implications, (3) provision of player rewards to reinforce their social interactions, and (4)creation of opportunities to integrate NPCs' game-determined narratives into player-generated narratives.
Computing Blindfolded on Data Homomorphically Encrypted under Multiple Keys: A Survey
Authors: Aloufi Asma , Hu Peizhao , Song Yongsoo , Lauter Kristin
Published: October 2021

With capability of performing computations on encrypted data without needing the secret key, homomorphic encryption (HE) is a promising cryptographic technique that makes outsourced computations secure and privacy-preserving. A decade after Gentry’s breakthrough discovery of how we might support arbitrary computations on encrypted data, many studies followed and improved various aspects of HE, such as faster bootstrapping and ciphertext packing. However, the topic of how to support secure computations on ciphertexts encrypted under multiple keys does not receive enough attention. This capability is crucial in many application scenarios where data owners want to engage in joint computations and are preferred to protect their sensitive data under their own secret keys. Enabling this capability is a non-trivial task. In this article, we present a comprehensive survey of the state-of-the-art multi-key techniques and schemes that target different systems and threat models. In particular, we review recent constructions based on Threshold Homomorphic Encryption (ThHE) and Multi-Key Homomorphic Encryption (MKHE). We analyze these cryptographic techniques and schemes based on a new secure outsourced computation model and examine their complexities. We share lessons learned and draw observations for designing better schemes with reduced overheads.
A Survey on Uncertainty Estimation in Deep Learning Classification Systems from a Bayesian Perspective
Authors: Mena José , Pujol Oriol , Vitrià Jordi
Published: October 2021

Decision-making based on machine learning systems, especially when this decision-making can affect human lives, is a subject of maximum interest in the Machine Learning community. It is, therefore, necessary to equip these systems with a means of estimating uncertainty in the predictions they emit in order to help practitioners make more informed decisions. In the present work, we introduce the topic of uncertainty estimation, and we analyze the peculiarities of such estimation when applied to classification systems. We analyze different methods that have been designed to provide classification systems based on deep learning with mechanisms for measuring the uncertainty of their predictions. We will take a look at how this uncertainty can be modeled and measured using different approaches, as well as practical considerations of different applications of uncertainty. Moreover, we review some of the properties that should be borne in mind when developing such metrics. All in all, the present survey aims at providing a pragmatic overview of the estimation of uncertainty in classification systems that can be very useful for both academic research and deep learning practitioners.
Faster Support Vector Machines
Authors: Schlag Sebastian , Schmitt Matthias , Schulz Christian
Published: October 2021

The time complexity of support vector machines (SVMs) prohibits training on huge datasets with millions of data points. Recently, multilevel approaches to train SVMs have been developed to allow for time-efficient training on huge datasets. While regular SVMs perform the entire training in one—time-consuming—optimization step, multilevel SVMs first build a hierarchy of problems decreasing in size that resemble the original problem and then train an SVM model for each hierarchy level, benefiting from the solved models of previous levels. We present a faster multilevel support vector machine that uses a label propagation algorithm to construct the problem hierarchy. Extensive experiments indicate that our approach is up to orders of magnitude faster than the previous fastest algorithm while having comparable classification quality. For example, already one of our sequential solvers is on average a factor 15 faster than the parallel ThunderSVM algorithm, while having similar classification quality.
1
Cellular Adaptations to Cytoplasmic Mg2+ Limitation
Authors: Groisman Eduardo A. , Chan Carissa
Published: October 2021

Mg2+ is the most abundant divalent cation in living cells. It is essential for charge neutralization, macromolecule stabilization, and the assembly and activity of ribosomes and as a cofactor for enzymatic reactions. When experiencing low cytoplasmic Mg2+, bacteria adopt two main strategies: They increase the abundance and activity of Mg2+ importers and decrease the abundance of Mg2+-chelating ATP and rRNA. These changes reduce regulated proteolysis by ATP-dependent proteases and protein synthesis in a systemic fashion. In many bacterial species, the transcriptional regulator PhoP controls expression of proteins mediating these changes. The 5′ leader region of some mRNAs responds to low cytoplasmic Mg2+ or to disruptions in translation of open reading frames in the leader regions by furthering expression of the associated coding regions, which specify proteins mediating survival when the cytoplasmic Mg2+ concentration is low. Microbial species often utilize similar adaptation strategies to cope with low cytoplasmic Mg2+ despite relying on different genes to do so.
Recollecting What We Once Knew: My Life in Psycholinguistics
Authors: Gleitman Lila R. , Gleitman Claire
Published: October 2021

The mid-twentieth century brought a radical change in how the linguistics community formulated its major goal, moving from a largely taxonomic science to Chomsky's revolution, which conceptualized language as a higher-order cognitive function. This article reviews the paths (not always direct) that brought Lila Gleitman into contact with that revolution, her contributions to it, and the evolution in her thinking about how language is learned by every child, regardless of extreme variation in the input received. To understand how that occurs, we need to discover what must be learned by the child and what is already there to guide that learning—what must be, in Plato's terms, “recollected.” The growing picture shows a learner equipped with information-processing mechanisms that extract evidence about word meanings using various evidential sources. Chief among these are the observational and linguistic-syntactic contexts in which words occur. The former is supported by a mechanism Gleitman and her collaborators call “propose but verify,” and the latter by a mechanism known as “syntactic boot-strapping.”
Big Data and Deep Learning‐Based Video Classification Model for Sports
Authors: Wang Lin , Zhang Haiyan , Yuan Guoliang
Published: October 2021

Information technologies such as deep learning, big data, cloud computing, and the Internet of Things provide key technical tools to drive the rapid development of integrated manufacturing. In recent years, breakthroughs have been made in big data analysis using deep learning. The research on the sports video high‐precision classification model in this paper, more specifically, is the automatic understanding of human movements in free gymnastics videos. This paper will combine knowledge related to big data‐based computer vision and deep learning to achieve intelligent labeling and representation of specific human movements present in video sequences. This paper mainly implements an automatic narrative based on long‐ and short‐term memory networks to achieve the classification of sports videos. In the classical video description model S2VT, long‐ and short‐term memory networks are used to learn the mapping relationship between word sequences and video frame sequences. In this paper, we introduce an attention mechanism to highlight the importance of keyframes that determine freestyle gymnastic movements. In this paper, a dataset of freestyle gymnastics breakdown movements for professional events is built. Experiments are conducted on the data and the self‐constructed dataset, and the planned sampling method is applied to eliminate the differences between the training decoder and the prediction decoder. The experimental results show that the improved method in this paper can improve the accuracy of sports video classification. The video classification model based on big data and deep learning is to provide users with a better user experience and improve the accuracy of video classification. Also, in the experiments of this paper, the effect of extracting features for the classification of different lifting sports models is compared, and the effect of feature extraction network on the automatic description of free gymnastic movements is analyzed.
Study on a Class of Piecewise Nonlinear Systems with Fractional Delay
Authors: Wang Meiqi , Ma Wenli , Chen Enli , Chang Yujian
Published: October 2021

In this paper, a dynamic model of piecewise nonlinear system with fractional‐order time delay is simplified. The amplitude frequency response equation of the dynamic model of piecewise nonlinear system with fractional‐order time delay under periodic excitation is obtained by using the average method. It is found that the amplitude of the system changes when the external excitation frequency changes. At the same time, the amplitude frequency response characteristics of the system under different time delay parameters, different fractional‐order parameters, and coefficient are studied. By analyzing the amplitude frequency response characteristics, the influence of time delay and fractional‐order parameters on the stability of the system is analyzed in this paper, and the bifurcation equations of the system are studied by using the theory of continuity. The transition sets under different piecewise states and the constrained bifurcation behaviors under the corresponding unfolding parameters are obtained. The variation of the bifurcation topology of the system with the change of system parameters is given.
[Retracted] BP Neural Network Based on Simulated Annealing Algorithm Optimization for Financial Crisis Dynamic Early Warning Model
Authors: Chen Ying
Published: October 2021

Financial early warning mechanism is of great significance to the long‐term healthy development and stable operation of listed enterprises. This paper adopts the logistic regression early warning model and BP neural network early warning model. Based on the BP neural network t early warning model optimized by the simulated annealing algorithm, the prediction effects of the model are compared from the perspectives of model accuracy and variable importance. Through the comparative analysis of the empirical results of the three methods, it can be seen that the simulated annealing algorithm has many advantages. The combination of the simulated annealing algorithm with multithreading, data compression, and segmentation greatly improves the efficiency of the algorithm and shortens the running time. Using the logistic regression early warning model and BP neural network early warning model and based on the BP neural network t early warning model optimized by the simulated annealing algorithm, the prediction effects of the model are compared from the perspective of model accuracy and variable importance. The results show that the three index dimensions of the BP neural network optimized by the simulated annealing algorithm have good discrimination ability to financial status. The BP neural network early warning model optimized based on the simulated annealing algorithm has good prediction accuracy and good practical significance.
Pressure-Relief Mechanism and Application of Large-Diameter Boreholes in Coal Seams with Rockburst Hazard
Authors: Hao Zhen , Sun Guangzhong , Wei Haihang , Liu Jiayu , Tian Maolin , Liu Shuaiyi , Xu Yikun
Published: October 2021

Drilling of large-diameter boreholes is regarded as an effective measure for rockburst prevention. By investigating the morphological characteristic and evolution of plastic zone in borehole surrounding rock, the pressure-relief mechanism of large-diameter borehole was ascertained, and the engineering application of large-diameter boreholes was assessed in the 13230 working face of Gengcun Coal Mine, Henan Province, China. The results showed that (1) the plastic zone in surrounding rock of borehole appear as circular, elliptical, and butterfly shapes, in which the maximum size of the butterfly wings of the plastic zone is several times larger than the borehole diameter; (2) under certain stress conditions, multiple large-diameter boreholes distributed in coal seam with rockburst risk lead to the generation and coalescence of large-range butterfly-shape plastic zone. They reduce the stress concentration and capacity for storing elastic energy of coal seam, thus reducing the rockburst risk of the coal seam; (3) large-diameter boreholes significantly decrease the stress concentration in front of the 13230 working face and improve the stress environment in the head entry, promoting the safe mining of the working face.
High Level of Inflammatory Cytokines in the Tears: A Bridge of Patients with Concomitant Exotropia and Dry Eye
Authors: Gao Feng , Hong Xiaoping , Ding Fadian , Huang Shirong , Lian Wei , Wang Hanjun , Zheng Weidong , Ni Jun , Chen Min , Liu Qicai
Published: October 2021

Concomitant exotropia have obvious symptoms of eye discomfort in adults, and the presence of ocular surface inflammation in patients may be important mediators between concomitant exotropia and dry eye. Oculus Keratograph eye comprehensive analyzer was performed to detect noninvasive tear break time, noninvasive tear height, and eye red index, while the ocular surface disease index and schirmer I testing were made. The levels of IL‐6, IL‐10, IL‐17A, IL‐12P70, INF‐γ, and TNF‐α were detected in tears in patients with concomitant exotropia and healthy controls matched by age and gender through the Simoa technology. IL‐6 was significantly higher in patients with concomitant exotropia (4.683 ± 1.329) pg/mL than that in normal group (1.455 ± 0.391) pg/mL, p = 0.0304. TNF‐α was also significantly higher in patients (0.2095 ± 0.0703) pg/mL than normal group (0.0513 ± 0.0149) pg/mL, p = 0.0397. The levels of inflammatory factors in strabismic patients vs. normal controls were as follows: IL‐17A (0.1551 pg/mL︰0.0793 pg/mL), IL‐10 (0.3358 pg/mL︰0.0513 pg/mL), IL‐12p70 (0.0253 pg/mL︰0.0099 pg/mL), and INF‐γ (0.0284 pg/mL︰0.009 pg/mL) were detected, and the median of them in concomitant strabismus was 1.96‐6.55‐fold as much as the control group. High levels of inflammatory cytokines in tears of patients with concomitant exotropia, which may be a potentially factor promoted the occurrence of dry eye in the patients with concomitant exotropia.
Total Organic Carbon Content Prediction in Lacustrine Shale Using Extreme Gradient Boosting Machine Learning Based on Bayesian Optimization
Authors: Liu Xingzhou , Tian Zhi , Chen Chang
Published: October 2021

The total organic carbon (TOC) content is a critical parameter for estimating shale oil resources. However, common TOC prediction methods rely on empirical formulas, and their applicability varies widely from region to region. In this study, a novel data-driven Bayesian optimization extreme gradient boosting (XGBoost) model was proposed to predict the TOC content using wireline log data. The lacustrine shale in the Damintun Sag, Bohai Bay Basin, China, was used as a case study. Firstly, correlation analysis was used to analyze the relationship between the well logs and the core-measured TOC data. Based on the degree of correlation, six logging curves reflecting TOC content were selected to construct training dataset for machine learning. Then, the performance of the XGBoost model was tested using

K

-fold cross-validation, and the hyperparameters of the model were determined using a Bayesian optimization method to improve the search efficiency and reduce the uncertainty caused by the rule of thumb. Next, through the analysis of prediction errors, the coefficient of determination (

R

2

) of the TOC content predicted by the XGBoost model and the core-measured TOC content reached 0.9135. The root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were 0.63, 0.77, and 12.55%, respectively. In addition, five commonly used methods, namely,

Δ
log
R

method, random forest, support vector machine,

K

-nearest neighbors, and multiple linear regression, were used to predict the TOC content to confirm that the XGBoost model has higher prediction accuracy and better robustness. Finally, the proposed approach was applied to predict the TOC curves of 20 exploration wells in the Damintun Sag. We obtained quantitative contour maps of the TOC content of this block for the first time. The results of this study facilitate the rapid detection of the sweet spots of the lacustrine shale oil.
Technical and Energy Efficiency of Urban Logistics in China: Empirical Analysis of 216 Prefecture-Level Cities
Authors: Wang Dongfang , Li Jinfeng , Tarasov Arthur
Published: October 2021

With the rapid economic development in China, substantial capital and resources are invested in urban logistics industry leading to quick expansion of the urban logistics. In this paper, the efficiency and energy efficiency of the urban logistics industry in China is measured through a stochastic frontier analysis based on a translog production function for a period of 2009–2017 using a sample of 216 prefecture-level cities. The results lead to several conclusions. (1) Average urban logistics efficiency and energy efficiency scores are at low levels and unbalanced between sample cities over the research period. Cities located in the eastern coastal region have the largest average efficiency scores, the central region has lower scores, and the western region has the lowest. (2) The difference in logistics efficiency between sample cities shows a downward trend for the entire country and eastern region. (3) Technical change plays an important role in promoting urban logistics efficiency. Technical inefficiency is the main cause of the nonefficient frontier of urban logistics. (4) Using the regression analysis, we found that digitalization and road density are positively correlated with the efficiency of urban logistics. Education has a long-term effect on the improvement of the urban logistics efficiency. In contrast, government intervention and environmental regulations are negatively correlated with the efficiency of urban logistics. (5) The effect of most factors on urban logistics efficiency across the sample stratified between eastern, central, and western regions is in line with the estimation results for the whole sample.
Application of Recombinant Human BMP-2 with Bone Marrow Aspirate Concentrate and Platelet-Rich Fibrin in Titanium Mesh for Vertical Maxillary Defect Reconstruction prior to Implant Placement
Authors: Alraei Kamel , Shrqawi Jameel , Alarusi Khawlah
Published: October 2021

Recombinant human bone morphogenetic protein 2 (rhBMP-2) is an alternative bone substitute for extensive maxillary bone defects which avoids the disadvantages associated with other grafting materials. This report details a case of a 32-year-old female with a severe vertical and horizontal maxillary bony defect that developed after tumor removal. She underwent two unsuccessful regenerative surgeries with an iliac bone graft. Reconstruction of the maxillary defect was planned by offlabel use of rhBMP-2/absorbable collagen sponge (ACS) combined with a bone marrow aspirate concentrate (BMAC) and allograft in a titanium mesh covered in platelet-rich fibrin (PRF). Clinical and radiographic evaluations showed good quality and quantity of bone formation, and she was rehabilitated with dental implants and prosthodontic treatment. Based on this case, the use of rhBMP-2 as a graft material appears encouraging with a satisfying outcome. The present case is aimed at reporting the clinical and radiographic effectiveness of rhBMP-2/ACS in combination with PRF and a titanium mesh for severe maxillary bone defects. Future investigations will be required to ascertain the long-term survival of implants in areas grafted with rhBMP-2.