bluuebunny/crossref_metadata_2025 huggingface dataset:
Context-Aware Semantic Annotation of Mobility Records
Authors: Wang Huandong , Li Yong , Lin Junjie , Cao Hancheng , Jin Depeng
Published: October 2021

The wide adoption of mobile devices has provided us with a massive volume of human mobility records. However, a large portion of these records is unlabeled, i.e., only have GPS coordinates without semantic information (e.g., Point of Interest (POI)). To make those unlabeled records associate with more information for further applications, it is of great importance to annotate the original data with POIs information based on the external context. Nevertheless, semantic annotation of mobility records is challenging due to three aspects: the complex relationship among multiple domains of context, the sparsity of mobility records, and difficulties in balancing personal preference and crowd preference. To address these challenges, we propose CAP, a context-aware personalized semantic annotation model, where we use a Bayesian mixture model to model the complex relationship among five domains of context—location, time, POI category, personal preference, and crowd preference. We evaluate our model on two real-world datasets, and demonstrate that our proposed method significantly outperforms the state-of-the-art algorithms by over 11.8%.
Unsupervised Adversarial Network Alignment with Reinforcement Learning
Authors: Zhou Yang , Ren Jiaxiang , Jin Ruoming , Zhang Zijie , Zheng Jingyi , Jiang Zhe , Yan Da , Dou Dejing
Published: October 2021

Network alignment, which aims at learning a matching between the same entities across multiple information networks, often suffers challenges from feature inconsistency, high-dimensional features, to unstable alignment results. This article presents a novel network alignment framework, Unsupervised Adversarial learning based Network Alignment(UANA), that combines generative adversarial network (GAN) and reinforcement learning (RL) techniques to tackle the above critical challenges. First, we propose a bidirectional adversarial network distribution matching model to perform the bidirectional cross-network alignment translations between two networks, such that the distributions of real and translated networks completely overlap together. In addition, two cross-network alignment translation cycles are constructed for training the unsupervised alignment without the need of prior alignment knowledge. Second, in order to address the feature inconsistency issue, we integrate a dual adversarial autoencoder module with an adversarial binary classification model together to project two copies of the same vertices with high-dimensional inconsistent features into the same low-dimensional embedding space. This facilitates the translations of the distributions of two networks in the adversarial network distribution matching model. Finally, we develop an RL based optimization approach to solve the vertex matching problem in the discrete space of the GAN model, i.e., directly select the vertices in target networks most relevant to the vertices in source networks, without unstable similarity computation that is sensitive to discriminative features and similarity metrics. Extensive evaluation on real-world graph datasets demonstrates the outstanding capability of UANA to address the unsupervised network alignment problem, in terms of both effectiveness and scalability.
Test Points for Online Monitoring of Quantum Circuits
Authors: Acharya Nikita , Urbanek Miroslav , De Jong Wibe A. , Saeed Samah Mohamed
Published: October 2021

Noisy Intermediate-Scale Quantum (NISQ) computers consisting of tens of inherently noisy quantum bits (qubits) suffer from reliability problems. Qubits and their gates are susceptible to various types of errors. Due to limited numbers of qubits and high error rates, quantum error correction cannot be applied. Physical constraints of quantum hardware including the error rates are used to guide the design and the layout of quantum circuits. The error rates determine the selection of qubits and their operations. The resulting circuit is executed on the quantum computer.

This study explores the risk of unexpected changes in the error rates of NISQ computers post-calibration. We show that unexpected changes in error rates can alter the output state of a quantum circuit. To detect these changes, we propose the insertion of test points into the quantum circuit to enable online monitoring of the physical qubit behavior. We utilize classical, superposition, and uncompute test points. Furthermore, we use a gate error coverage metric to assess the quality of the tests. We verify the effectiveness of the proposed scheme on different IBM quantum computers (IBM Q), in addition to a noisy simulation that shows the scalability of the proposed approach.
Time-Aware Graph Embedding: A Temporal Smoothness and Task-Oriented Approach
Authors: Xu Yonghui , Sun Shengjie , Zhang Huiguo , Yi Chang’an , Miao Yuan , Yang Dong , Meng Xiaonan , Hu Yi , Wang Ke , Min Huaqing , Song Hengjie , Miao Chuanyan
Published: October 2021

Knowledge graph embedding, which aims at learning the low-dimensional representations of entities and relationships, has attracted considerable research efforts recently. However, most knowledge graph embedding methods focus on the structural relationships in fixed triples while ignoring the temporal information. Currently, existing time-aware graph embedding methods only focus on the factual plausibility, while ignoring the temporal smoothness, which models the interactions between a fact and its contexts, and thus can capture fine-granularity temporal relationships. This leads to the limited performance of embedding related applications. To solve this problem, this article presents a Robustly Time-aware Graph Embedding (RTGE) method by incorporating temporal smoothness. Two major innovations of our article are presented here. At first, RTGE integrates a measure of temporal smoothness in the learning process of the time-aware graph embedding. Via the proposed additional smoothing factor, RTGE can preserve both structural information and evolutionary patterns of a given graph. Secondly, RTGE provides a general task-oriented negative sampling strategy associated with temporally aware information, which further improves the adaptive ability of the proposed algorithm and plays an essential role in obtaining superior performance in various tasks. Extensive experiments conducted on multiple benchmark tasks show that RTGE can increase performance in entity/relationship/temporal scoping prediction tasks.
Social Group Query Based on Multi-Fuzzy-Constrained Strong Simulation
Authors: Liu Guliu , Li Lei , Liu Guanfeng , Wu Xindong
Published: October 2021

Traditional social group analysis mostly uses interaction models, event models, or other social network analysis methods to identify and distinguish groups. This type of method can divide social participants into different groups based on their geographic location, social relationships, and/or related events. However, in some applications, it is necessary to make more specific restrictions on the members and the interactions between members of the group. Generally, Graph Pattern Matching (GPM) technique is used to solve this problem. However, the existing GPM methods rarely consider the rich contextual information of nodes and edges to measure the credibility between members. In this article, first, a social group query problem that needs to consider the trust between members of the group is proposed. Then, to solve this problem, a multi-fuzzy-constrained strong simulation matching model is proposed based on multi-constrained simulation, and a
Strong Simulation
GPM algorithm (NTSS) based on the exploration of pattern
Node Topological
ordered sequence is proposed. Aiming at the inefficiency of the NTSS algorithm when pattern graph with multiple nodes with zero in-degree and the problem of repeated calculation of matching edges shared by multiple matching subgraphs, two optimization strategies are proposed. Finally, we conduct verification experiments on the effectiveness and efficiency of the NTSS algorithm and the algorithms with the optimization strategies on four social network datasets in real applications. Experimental results show that the NTSS algorithm is significantly better than the existing multi-constrained GPM algorithm, and the NTSS_Inv_EdgC algorithm, which combines two optimization strategies, greatly improves the efficiency of the NTSS algorithm.
Towards All-optical Stochastic Computing Using Photonic Crystal Nanocavities
Authors: El-Derhalli Hassnaa , Constans Léa , Le Beux Sébastien , De Rossi Alfredo , Raineri Fabrice , Tahar Sofiène
Published: October 2021

Stochastic computing allows a drastic reduction in hardware complexity using serial processing of bit streams. While the induced high computing latency can be overcome using integrated optics technology, the design of realistic optical stochastic computing architectures calls for energy efficient switching devices.
Photonics Crystal (PhC)
nanocavities are μm
2
 scale devices offering 100fJ switching operation under picoseconds-scale switching speed. Fabrication process allows controlling the Quality factor of each nanocavity resonance, leading to opportunities to implement architectures involving cascaded gates and multi-wavelength signaling. In this paper, we investigate the design of cascaded gates architecture using nanocavities in the context of stochastic computing. We propose a transmission model considering key nanocavity device parameters, such as Quality factors, resonance wavelength, and switching efficiency. The model is calibrated with experimental measurements. We propose the design of XOR gate and multiplexer. We illustrate the use of the gates to design an edge detection filter. System-level exploration of laser power, bit-stream length and bit-error rate is carried out for the processing of gray-scale images. The results show that the proposed architecture leads to 8.5nJ/pixel energy consumption and 512ns/pixel processing time.
Retreatment of Experimental Carrier-Based Obturators with the Remover NiTi Instrument: Evaluation of Apical Extrusion and Effects of New Kinematics
Authors: Pirani Chiara , Iacono Francesco , Zamparini Fausto , Generali Luigi , Prati Carlo
Published: October 2021

The objective of this study is to evaluate the retreatment time and weight of apically extruded debris yielded by two different kinematics during the removal of different root canal filling materials. Forty straight single-rooted extracted teeth were instrumented with HyFlex CM files and obturated with two different techniques: 25.04 HyFlex experimental carrier-based obturators (Coltène/Whaledent, Altstätten, Switzerland) (group 1) or 25.04 single gutta-percha cones (Roeko Coltène/Whaledent, Altstätten, Switzerland) (group 2) and Guttaflow Bioseal as the sealer. Samples were divided into four subgroups (n = 10) according to the used kinematics for the removal of root canal filling materials: continuous rotation (A) or retreatment motion (B) with a Remover and HyFlex EDM Nickel-Titanium instruments activated with a CanalPro Jeni micromotor (Coltène/Whaledent, Altstätten, Switzerland). Time for retreatment was digitally recorded, and debris extruded from the apex was collected in Eppendorf tubes and weighted with an analytical balance. Data on retreatment time and apical extrusion were statistically analyzed with the Kruskal–Wallis test (

p
<
0.05

). Working length was achieved in all the retreated samples. The removal of root filling material resulted significantly faster with the Jeni mode (

p
<
0.001

), and the difference was significant for the removal of both filling materials (

p
<
0.05

). No significant differences on debris extrusion between single cone and experimental obturators groups were noted (

p
>
0.05

), and no significant differences between kinematics (continuous rotation vs. Jeni motion) were observed (

p
>
0.05

). All the tested retreatment strategies lead to an extrusion of material from the apex, and the weight of apically extruded debris was similar. The use of the innovative CanalPro Jeni kinematics accelerates the time for the removal of root filling materials.
Genotypic and Phenotypic Characterizations of Methicillin-Resistant Staphylococcus aureus (MRSA) on Frequently Touched Sites from Public Hospitals in South Africa
Authors: Mkhize Siyethaba , Amoako Daniel G. , Shobo Christiana O. , Zishiri Oliver T. , Bester Linda A.
Published: October 2021

The hospital environment acts as a reservoir in the transmission of pathogens, such as MRSA, which may cause hospital-acquired infections. This study aimed to ascertain the prevalence, genetic relatedness, antibiotic resistance, and virulence profile of MRSA on some frequently touched hospital sites in South Africa. A total of 777 swabs were randomly collected from 11 frequently touched sites in the hospital environment of three wards of four public hospitals in the KwaZulu-Natal province of South Africa. Isolation of S. aureus and confirmation were done using genotypic and phenotypic methods. Antibiotic susceptibility testing was performed using the Kirby–Bauer disk-diffusion method. MRSA isolates were determined by the presence of the mecA gene. Virulence and resistance genes were detected using a standard monoplex PCR assay. ERIC-PCR was conducted to evaluate the genetic relatedness. An overall prevalence of 12.7% for S. aureus isolates was obtained. Out of these, 89.9% (89/99) were confirmed to be MRSA. The sites with the highest prevalence were the occupied beds (16.2% (16/99)), unoccupied beds (16.2% (16/99)), patient files (14.1% (14/99)), ward phones (13.1% (13/99)), and nurses’ tables (14.1% (14/99)). The virulence genes with the highest observed frequency were hld (87 (87.9%)) and LukS/F-PV (53 (53.5%)). The resistance genes with the highest frequency were the tetM and tetK genes detected in 60 (60.6%) and 57 (57.6%) isolates, respectively. The ERIC-PCR results obtained indicated a high level of genetic diversity; however, intraclonal (within a hospital) and interclonal (between hospitals) clusters of MRSA were observed. The study showed that MRSA can contaminate various surfaces, and this persistence allows for the dissemination of bacteria within the hospital environment. This highlights the need for improved infection prevention and control (IPC) strategies in public hospitals in the country to curb their potential transmission risks.
Optimization Design of Wind Turbine Blade Based on an Improved Particle Swarm Optimization Algorithm Combined with Non‐Gaussian Distribution
Authors: Sun Fangjin , Xu Zhonghao , Zhang Daming
Published: October 2021

To overcome the problem of particle swarm optimization (PSO) being trapped in local minima, a particle swarm optimization algorithm combined with non‐Gaussian stochastic distribution is presented for optimization design of wind turbine blade. Before updating the particle velocity, a limited test was performed for every particle to search for the global best solution. Taking the maximum wind turbine annual power generation as the final objective, a 1.3 MW wind turbine blade was optimized. The results were compared with those of the original wind turbine blades and traditional particle swarm optimization. Compared with the original output power, the year output power increased by 5.3% with non‐Gaussian stochastic distribution combined with PSO, whereas the computation time was 65% of the traditional PSO. As time step increased, residuals of non‐Gaussian stochastic distribution combined with PSO greatly diminished, with improved computation efficiency. It is shown that the non‐Gaussian distribution combined with PSO ensures the global best solution. The non‐Gaussian distribution combined with PSO provides a more reliable theoretical basis for the design of wind turbine blades.
Natural Compounds from Hatikana Extract Potentiate Antidiabetic Actions as Displayed by In Vivo Assays and Verified by Network Pharmacological Tools
Authors: Rahman Md. Atiar , Uddin Md. Nazim , Babteen Nouf Abubakr , Alnajeebi Afnan M. , Zakaria Zainul Amiruddin , Aboelenin Salama Mostafa
Published: October 2021

Background. Hatikana is a traditional medicinal plant used to treat inflammation, urolithiasis, goiter, cancer, wounds and sores, gastrointestinal, tumor, tetanus, arthritis, hepatic damage, neurodegeneration, and other ailments. The goal of this study is to investigate the antidiabetic properties of Hatikana extract (HKEx) and to construct the effects of its natural constituents on the genes and biochemical indices that are connected with them. Methods. HKEx was evaluated using GC‐MS and undertaken for a three‐week intervention in fructose‐fed STZ‐induced Wistar albino rats at the doses of HKEx50, HKEx100, and HKEx200 mg/kg bw. Following intervention, blood serum was examined for biochemical markers, and liver tissue was investigated for the mRNA expression of catalase (CAT), glutathione peroxidase (GPx), and superoxide dismutase (SOD1) by RTPCR analysis. Most abundant compounds (oleanolic acid, 7α, 28‐olean diol, and stigmasterol) from GC‐MS were chosen for the network pharmacological assay to verify function‐specific gene‐compound interactions using STITCH, STRING, GSEA, and Cytoscape plugin cytoHubba. Results. In vivo results showed a significant (P < 0.05) decrease of blood sugar, aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine kinase (CK‐MB), and lactate dehydrogenase (LDH) and increase of liver glycogen, glucose load, and serum insulin. Out of three antioxidative genes, catalase (CAT) and superoxide dismutase (SOD1) were found to be few fold increased. Oleanolic acid and stigmasterol were noticed to strongly interact with 27 target proteins. Oleanolic acid interacted with the proteins AKR1B10, CASP3, CASP8, CYP1A2, CYP1A2, HMGB1, NAMPT, NFE2L2, NQO1, PPARA, PTGIR, TOP1, TOP2A, UGT2B10, and UGT2B11 and stigmasterol with ABCA1, ABCG5, ABCG8, CTSE, HMGCR, IL10, CXCL8, NR1H2, NR1H3, SLCO1B1, SREBF2, and TNF. Protein‐protein interaction (PPI) analysis revealed the involvement of 25 target proteins out of twenty seven. Cytoscape plugin cytoHubba identified TNF, CXCL8, CASP3, PPARA, SREBF2, and IL10 as top hub genes. Pathway analysis identified 31 KEGG metabolic, signaling, and immunogenic pathways associated with diabetes. Notable degree of PPI enrichment showed that SOD1 and CAT are responsible for controlling signaling networks and enriched pathways. Conclusion. The findings show that antioxidative genes have regulatory potential, allowing the HKEx to be employed as a possible antidiabetic source pending further validation.
Based on Temporal and Spatial Traffic Characteristics for Energy-Efficient Wi-Fi Network
Authors: Li Zhigang , Wang Xin , Yue Xinan , Zou Dongyao , Li Jun , Si Lina
Published: October 2021

With the rapid development of information and communication technology (ICT) industry, the energy consumption caused by the development of mobile communications is increasing exponentially. Huge energy consumption and increasing environmental awareness prompt people to study the dynamic distribution of users and traffic in Wi-Fi networks in order to design an energy-efficient mechanism for Wi-Fi networks. Based on real data, this paper explores the spatial and temporal characteristics of human mobility and data traffic distribution. The results of access point (AP) traffic analysis show a tidal effect and obvious periodicity in time and space dimension, which can be used for the dynamic design of AP sleep or shutdown strategy. At the same time, we design a new service area (SA) zooming and AP cooperation mode. Through the simulation experiment, we find that the energy consumption can be reduced by about 35% and the communication service quality can be guaranteed.
Low‐Energy Secure Routing Protocol for WSNs Based on Multiobjective Ant Colony Optimization Algorithm
Authors: Wang Xueli
Published: October 2021

As one of the three pillars of information technology, wireless sensor networks (WSNs) have been widely used in environmental detection, healthcare, military surveillance, industrial data sampling, and many other fields due to their unparalleled advantages in deployment cost, network power consumption, and versatility. The advent of the 5G standard and the era of Industry 4.0 have brought new opportunities for the development of wireless sensor networks. However, due to the limited power capacity of the sensor nodes themselves, the harsh deployment environment will bring a great difficulty to the energy replenishment of the sensor nodes, so the energy limitation problem has become a major factor limiting its further development; how to improve the energy utilization efficiency of WSNs has become an urgent problem in the scientific and industrial communities. Based on this, this paper researches the routing technology of wireless sensor networks, from the perspective of improving network security, and reducing network energy consumption, based on the study of ant colony optimization algorithm, further studies the node trust evaluation mechanism, and carries out the following research work: (1) study the energy consumption model of wireless sensor networks; (2) basic ant colony algorithm improvement; (3) multiobjective ant colony algorithm based on wireless sensor routing algorithm optimization. In this study, the NS2 network simulator is used as a simulation tool to verify the performance of the research algorithm. Compared with existing routing algorithms, the simulation results show that the multiobjective ant colony optimization algorithm has better performance in evaluation indexes such as life cycle, node energy consumption, node survival time, and stability compared with the traditional algorithm and the dual cluster head ant colony optimization algorithm.
Investigation on Microstructure and Tensile Properties of High‐Strength AA2014 Aluminium Alloy Welds Joined by Pulsed CMT Welding Process
Authors: Chinnasamy Rajendran , Chelladurai Samson Jerold Samuel , Sonar Tushar
Published: October 2021

High‐strength AA 2014 aluminium alloys are broadly employed for many applications because of their good mechanical properties, high strength‐to‐weight ratio, and better resistance to corrosion and are recyclable. The major problems in welding of AA 2014 aluminum alloy using a traditional joining process are partially melted zone, hot cracking, and alloy segregation. Cold metal transfer‐welding (CMT) process is an advanced variant of gas metal arc welding process characterized by reduced heat input in which the welding wire is retracted during the short circuit which allows sufficient time for the weld to cool before placing each drop. In this investigation, the pulsed CMT welding process was chosen to weld high‐strength AA2014 aluminium alloy under T6 condition. The joint tensile properties were compared with the parent material and correlated to the microstructural features. The defect‐free weld was achieved at constant welding speed of 450 mm/min, welding current of 110 A, and electrode feed rate of 5550 mm/min. The joint weld using pulsed CMT yields a maximum strength of 303 MPa, extending joint efficiency up to 67%. It mainly refers to the beneficial effects of welding wire pulsing and dip and retreat motion which causes refining of dendritic grains in weld metal and enhances the strength of joints.
Regional Bank Consolidation and SMEs’ Credit Availability: Evidence from China
Authors: Hou Xiaohui , He Wei , Ke Kong-Lin
Published: October 2021

We conjecture that locally government‐led bank consolidation may negatively affect the SMEs’ credit availability in China because the breakdown of privately benefit‐based relationships among small business borrowers, loan officers, and senior managers could reduce loan officers’ incentives to use their soft information. Empirical results show that this is indeed the case.
Mining Sufficient Knowledge via Progressive Feature Fusion for Efficient Material Recognition
Authors: Zhang Hongbin , Xiong Qipeng , Shi Haowei , Liang Weinan , Zhong Xiang , Zhu Zhiliang , Li Xiong , Ji Donghong
Published: October 2021

Material images are susceptible to changes, depending on the light intensity, visual angle, shooting distance, and other conditions. Feature learning has shown great potential for addressing this issue. However, the knowledge achieved using a simple feature fusion method is insufficient to fully represent the material images. In this study, we aimed to exploit the diverse knowledge learned by a novel progressive feature fusion method to improve the recognition performance. To obtain implicit cross-modal knowledge, we perform early feature fusion and capture the cluster canonical correlations among the state-of-the-art (SOTA) heterogeneous squeeze-and-excitation network (SENet) features. A set of more discriminative deep-level visual semantics (DVSs) is obtained. We then perform gene selection-based middle feature fusion to thoroughly exploit the feature-shared knowledge among the generated DVSs. Finally, any type of general classifier can use the feature-shared knowledge to perform the final material recognition. Experimental results on two public datasets (Fabric and MattrSet) showed that our method outperformed other SOTA baseline methods in terms of accuracy and real-time efficiency. Even most traditional classifiers were able to obtain a satisfactory performance using our method, thus demonstrating its high practicality.
Detection of Herbal Combinations and Pharmacological Mechanisms of Clinical Prescriptions for Coronary Heart Disease Using Data Mining and Network Pharmacology
Authors: Bi Siling , Xu Liang , Chen Shouqiang , Bu Shuai , Xu Yunsheng
Published: October 2021

Though widely used in the treatment of coronary heart disease (CHD), the mechanism of traditional Chinese medicine (TCM) is still unclear because of its complex prescription rules. This study prospectively collected 715 prescriptions of TCM for the treatment of CHD. The characteristics of TCM in prescriptions were described and analyzed, and the rules of prescriptions were analyzed by using association rules. Frequency statistics showed that the high-frequency herbs with a frequency of more than 60% were Gan-cao, Huang-qi, Dang-gui, Chuan-xiong, Yan-hu-suo, and San-qi. The high-frequency herb combinations were summarized by using association rules. By using the method of the “Top N groups” to excavate the empirical prescriptions, the basic prescriptions for treating CHD were summarized. We named the intersection herbs of the basic prescriptions and the high frequency herbs as the core herbal prescription. To explore the possible mechanisms underlying the anti-CHD effect of the core herbal prescription, the bioactive components of core herbal prescription and their targets were screened out by using network pharmacology. Molecular docking was performed between the bioactive components and core targets. A total of 28 potential active ingredients and 5 core targets were identified for the treatment of CHD with core herbal prescription. The enrichment analysis results indicated that the mechanism of action mainly involved neuroactive ligand-receptor interaction and calcium signaling pathway. The commonly used herbal pairs for CHD with qi deficiency and blood stasis syndrome were Huang-qi and Dang-gui. The mechanism of action of common herbal pairs was also studied by network pharmacology. This study summarized the prescription rule of TCM in the treatment of CHD and may provide a new idea for the treatment of CHD.
Center Variability in Medicare Claims–Based Publicly Reported Transcatheter Aortic Valve Replacement Outcome Measures
Authors: Thompson Michael P. , Hou Hechuan , Brescia Alexander A. , Pagani Francis D. , Sukul Devraj , McCullough Jeffrey S. , Likosky Donald S.
Published: October 2021

Background

Public reporting of transcatheter aortic valve replacement (TAVR) claims–based outcome measures is used to identify high‐ and low‐performing centers. Whether claims‐based TAVR outcomes can reliably be used for center‐level comparisons is unknown. In this study, we sought to evaluate center variability in claims‐based TAVR outcomes used in public reporting.

Methods and Results

The study sample included 119 554 Medicare beneficiaries undergoing TAVR between January 2014 and October 2018 based on procedure codes in 100% Medicare inpatient claims. Multivariable hierarchical logistic regression was used to estimate center‐specific adjusted rates and reliability (R) of 30‐day mortality, discharge not to home/self‐care, 30‐day stroke, and 30‐day readmission. Reliability was defined as the ratio of between‐hospital variation to the sum of the between‐ and within‐hospital variation. The median (interquartile range [IQR]) center‐level adjusted outcome rates were 3.1% (2.9%–3.4%) for 30‐day mortality, 41.4% (31.3%–53.4%) for discharge not to home, 2.5% (2.3%–2.7%) for 30‐day stroke, and 14.9% (14.4%–15.5%) for 30‐day readmission. Median reliability was highest for the discharge not to home measure (R=0.95; IQR, 0.94–0.97), followed by the 30‐day stroke (R=0.92; IQR, 0.87–0.94), 30‐day mortality (R=0.86; IQR, 0.81–0.91), and 30‐day readmission measures (R=0.42; IQR, 0.35–0.51). Across outcomes, there was an inverse relationship between center volume and measure reliability.

Conclusions

Claims‐based TAVR outcome measures for mortality, discharge not to home, and stroke were reliable measures for center‐level comparisons, but readmission measures were unreliable. Stakeholders should consider these findings when evaluating claims‐based measures to compare center‐level TAVR performance.
Temporal Trends and Factors Associated With the Inclusion of Patient‐Reported Outcomes in Heart Failure Randomized Controlled Trials: A Systematic Review
Authors: Eliya Yousif , Averbuch Tauben , Le NhatChinh , Xie Feng , Thabane Lehana , Mamas Mamas A. , Van Spall Harriette G. C.
Published: October 2021

Background

Patient‐reported outcomes (PROs) are important measures of treatment response in heart failure. We assessed temporal trends in and factors associated with inclusion of PROs in heart failure randomized controlled trials (RCTs).

Methods and Results

We searched MEDLINE, Embase, and CINAHL for studies published between January 2000 and July 2020 in journals with an impact factor ≥10. We assessed temporal trends using the Jonckheere‐Terpstra test and conducted multivariable logistic regression to explore trial characteristics associated with PRO inclusion. We assessed the quality of PRO reporting using the Consolidated Standards of Reporting Trials (CONSORT) PRO extension. Of 417 RCTs included, PROs were reported in 226 (54.2%; 95% CI, 49.3%–59.1%), with increased reporting between 2000 and 2020 (
P
<0.001). The odds of PRO inclusion were greater in RCTs that were published in recent years (adjusted odds ratio [aOR] per year, 1.08; 95% CI, 1.04–1.12;
P
<0.001), multicenter (aOR, 1.89; 95% CI, 1.03–3.46;
P
=0.040), medium‐sized (aOR, 2.35; 95% CI, 1.26–4.40;
P
=0.008), coordinated in Central and South America (aOR, 5.93; 95% CI, 1.14–30.97;
P
=0.035), and tested health service (aOR, 3.12; 95% CI, 1.49–6.55;
P
=0.003), device/surgical (aOR, 6.66; 95% CI, 3.15–14.05;
P
<0.001), or exercise (aOR, 4.66; 95% CI, 1.81–12.00;
P
=0.001) interventions. RCTs reported a median of 4 (interquartile interval , 3–6) of a possible of 11 CONSORT PRO items.

Conclusions

Just over half of all heart failure RCTs published in high impact factor journals between 2000 and 2020 included PROs, with increased inclusion of PROs over time. Trials that were large, tested pharmaceutical interventions, and coordinated in North America / Europe had lower adjusted odds of reporting PROs relative to other trials. The quality of PRO reporting was modest.
Redistribution of Outpatient Oncologic Surgical Specialty Referrals During COVID-19
Authors: Sutjiadi Brian , McRae Joyce , Silva Trevor , Selleck Matthew , Reeves Mark , Garberoglio Carlos , Lum Sharon
Published: October 2021

Background

Initial reports of significantly worse outcomes for cancer patients with COVID-19 led to guidelines for triaging surgical cancer treatment. We sought to evaluate the effects of the COVID-19 pandemic on oncologic surgical specialty referrals.

Methods

We compared referrals to oncologic surgical specialty clinics at an academic tertiary care institution following implementation of stay-at-home orders in California (3/19/20–7/31/20, “COVID”) to the same time period the year prior (3/19/19–7/31/19, “Pre-COVID”). The number of appointments, consulted surgical services, insurance types, acuity of diagnoses, and times from referral to first appointment (TRFA) were assessed.

Results

The overall number of patients seen in matched time periods decreased by 21.6% from 900 (pre-COVID) to 705 (COVID). Proportions of patients with malignant and suspicious diagnoses, surgical and thoracic oncology visits, and Medicaid insurance differed from comparison groups during the COVID period ( P < .05). Overall median (interquartile range) TRFA decreased from 14 (20) to 12 (19) days ( P = .001) during COVID.

Conclusion

After implementation of stay-at-home orders, higher acuity and vulnerable patients were appropriately seen in oncologic surgical specialty clinics. While the long-term effects of decreased clinic visits during COVID remain uncertain, further examination of scheduling practices that led to shorter referral times may identify methods to improve timeliness of care and surgical oncologic outcomes in non-pandemic settings.
The academic effects of chronic exposure to neighbourhood violence
Authors: Schwartz Amy Ellen , Laurito Agustina , Lacoe Johanna , Sharkey Patrick , Ellen Ingrid Gould
Published: October 2021

This paper estimates the causal effect of repeated exposure to violent crime on test scores in New York City. We use two empirical strategies; value-added models linking student performance on standardised exams to violent crimes on students’ residential block, and a regression discontinuity approach that identifies the acute effect of additional crime exposure within a one-week window. Exposure to violent crime reduces academic performance. Value-added models suggest the average effect is very small (approximately −0.01 standard deviations) but grows with repeated exposure. Regression discontinuity (RD) models also find a larger effect among children previously exposed. The marginal acute effect is as large as −0.04 standard deviations for students with two or more prior exposures. Among these, it is almost one tenth of a standard deviation for Black students. We provide credible causal evidence that repeated exposure to neighbourhood violence harms test scores, and this negative effect increases with exposure.
Pervasive Uncertainty under Threat: Mental Health Disorders and Experiences of Uncertainty for Correctional Workers
Authors: Ricciardelli Rosemary , Mitchell Meghan , Taillieu Tamara , Angehrn Andreanne , Afifi Tracie , Carleton R. Nicholas
Published: October 2021

Exposure to potentially psychologically traumatic events for correctional workers is high. However, the mechanisms driving the high prevalence are relatively unexplained. Using data from a cross-sectional, online survey of correctional service workers ( n = 845) in Ontario, Canada, collected in 2017–2018, we assess the prevalence of mental disorders with a specific focus on uncertainty in the workplace and between correctional roles. We find that correctional officers, institutional governance, and probation/parole officers appear most at risk of mental disorders (prevalence of any mental disorder was 56.9%, 60.3%, and 59.2%, respectively). We argue slightly lower prevalence among institutional wellness, training, and administrative staff may result in part from their more predictable work environment, where they have more control. The results reaffirm a need for evidence-based proactive mental health activities, knowledge translation, and treatment and a need to explore how authority without control (i.e., unpredictability at work) can inform employee mental health.
Democratising media policymaking: a stakeholder-centric, systemic approach to copyright consultation
Authors: Edwards Lee , Moss Giles
Published: October 2021

Media policymaking is often regarded with suspicion by stakeholders, with the result that policy can lack legitimacy and be difficult to implement effectively. This paper reports on a UK-based, collaborative and impact-oriented project where we engage stakeholders in a process of meta-deliberation, aimed at producing a stakeholder-centric, systemic understanding of copyright consultations and a strategy for change. Based on the findings, we propose a framework of purposes and principles that provides both a means of critical evaluation of copyright consultations and a guide for their reform. We conclude that shifting focus from policy outcomes to policy process is a constructive way to move debate forward in intractable policy areas like copyright, characterised by polarised and seemingly intransigent stakeholder positions. While changing the policymaking process would face significant institutional barriers, the framework we present here supports those who are concerned with taking the policymaking process in more democratic directions, whether they are officials within public authorities or activists outside them.
Monitoring excimer laser-guided cardiac lead extractions by uniportal video-assisted thoracoscopy: A single center experience
Authors: Wacker Max , Thewes Lena , Lux Anke , Busk Henning , Zardo Patrick , Scherner Maximilian , Awad George , Varghese Sam , Veluswamy Priya , Wippermann Jens , Slottosch Ingo
Published: October 2021

Background

Though laser guided extractions of cardiac implantable electronic devices leads have become a routine procedure, the severe complications are associated with a high mortality. Here, we report our single center experience using uniportal video-assisted thoracoscopy for laser lead extraction and compare it to stand-alone laser lead extraction.

Methods

The intraoperative data and postoperative clinical outcomes of patients undergoing laser lead extraction with concomitant thoracoscopy ( N = 28) or without ( N = 43) in our institution were analyzed retrospectively.

Results

Neither the median x-ray time (612.0 s for the thoracoscopy group vs. 495.5 s for the non-thoracoscopy group, p = 0.962), length of the operation (112.5 vs. 100.0 min, p = 0.676) or the median length of hospital stay (9.0 vs. 10.0 days, p = 0.990) differed significantly. The mean intensive care unit stay was longer for patients in the non-thoracoscopy group (0.8 vs. 2.5 days, p = 0.005). The 30-day-mortality in the thoracoscopy group was zero, whereas five patients died in the non-thoracoscopy group. Furthermore, four patients in the non-thoracoscopy group had encountered haemothorax, while none were observed in the thoracoscopy group ( p = 0.148).

Conclusions

The adoption of uniportal video-assisted thoracoscopy during laser-guided lead extraction of cardiac implantable electronic devices can be considered safe and does not lengthen the operating time or hospital stay. It might be useful in the detection of severe complications and, in experienced hands, possibly allow direct bleeding control.
Information anxiety in the workplace: Scale development and validation
Authors: Naveed Muhammad Asif , Anwar Mumtaz Ali
Published: October 2021

This research intends to develop and validate an Information Anxiety Scale for individuals in the context of the workplace. This study was completed in two phases. In the first phase, the statements related to information anxiety were generated based on an extensive review of the literature on information-related anxieties, library and information avoidance, and information literacy along with two focus group interviews. Afterward, these statements were submitted to a panel of experts for content and face validity. Lastly, the data were collected for pilot testing of the instrument. Whereas in the second phase, the construct validity and reliability of the scale were established using a variety of statistical procedures such as exploratory factor analysis, Cronbach alpha coefficient, test-retest The results indicated a 33-items instrument structured into six dimensions, namely, ‘Task Anxiety’ (5 items), ‘Need Recognition Anxiety’ (5 items), ‘Finding Anxiety’ (6 items), ‘Evaluation Anxiety’ (5 items), ‘Access Anxiety’ (5 items) and ‘Usage Anxiety’ (7 items). Each item had loading strengths greater than .572 and the model explained about 52% of the total variance. There were high values of reliability coefficient for overall scale (CA  =  .901) and correlation coefficients of test-retest ranging from 0.70 to .83. Thus, the newly developed scale was a valid and reliable measure assessing information anxiety in the workplace. It is hoped that this study would be a worthy contribution to the existing research on workplace information anxiety as no such scale has appeared in the existing literature.
Lane Lines Detection under Complex Environment by Fusion of Detection and Prediction Models
Authors: Haris Malik , Hou Jin , Wang Xiaomin
Published: October 2021

The lane lines’ length, width, and direction are very regular, serialized, and structurally associated, which are not easily affected by the environment. To enhance lane detection in a complicated environment, an approach combines visual information with the spatial distribution. Firstly, the grid density of the target detection algorithm YOLOv3 (you only look once V3) is improved from S×S to S×2S, aiming at the particular points in the bird’s-eye view where the lane lines had different densities in the horizontal and vertical directions. The obtained YOLOv3 (S×2S) is more suitable for detecting objects with small and large aspect ratios. It also identifies image features along with balances the detection speed and accuracy. Secondly, based on a bi-directional gated recurrent unit (BGRU), a new lane line prediction model BGRU-Lane (BGRU-L) based on the distribution of lane lines is proposed using the characteristic of lane line serialization and structural correlation. Finally, Dempster-Shafer (D-S) algorithm based on confidence was used to integrate the results of YOLOv3 (S×2S) and BGRU-L to improve the lane line detection ability under complex environments. The experiment was carried out on the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) dataset, while Euro Truck Simulator 2 (ETS2) is used as a supplement dataset. After fusing YOLOv3 (S×2S) and BGRU-L models in the D-S model, the detection results have high accuracy in a complex environment by 90.28 mAP. The detection speed is 40.20fps, which enables real-time detection.
Planned Special Event Network Optimization Model Considering Parking and Ridesharing Drop-Off
Authors: Xiao Jun , Lou Yingyan
Published: October 2021

A planned special event (PSE), such as a sports game or a concert, can greatly affect the normal operations of a transportation system. To facilitate traffic, the road network is usually reconfigured, which could include road closures, reversed lanes, and limited access to parking facilities. For recurring PSEs, event-goers are often provided with recommended routes to designated parking areas in advance. Such network reconfiguration and route and parking recommendations are, however, often ad hoc in practice. This paper focuses on the PSE traffic planning problem. We propose to simultaneously consider parking, ridesharing, and network configuration. The problem is formulated as an optimization problem with integer decision variables. We developed a flow-based traffic simulation tool that is able to incorporate parking and lane changing (which cannot be ignored around ridesharing drop-off locations) to evaluate the objective function. We also developed effective and efficient heuristic solution algorithms. The models and algorithms are tested using the real network and traffic data from Super Bowl XLIX in 2015. The results show that our methods and approaches are able to produce an effective comprehensive traffic plan with reasonable computation time. For the Super Bowl XLIX case study, the resulting optimal plan is able to save 39.6% of the total vehicle-hours associated with default network configurations. Sensitivity analysis has also been conducted with respect to the compliance rate of travelers following recommended routes. It is found that the resulting near-optimal PSE traffic plans are able to tolerate some uncertainty in the compliance rate.
Optimization and Estimation Algorithm of Vehicle Spatial Form Based on Monocular Traffic Camera
Authors: Wang Wei , Tang Xinyao , Li Ying
Published: October 2021

Accurate and rapid acquisition of vehicle spatial form is of great importance in the fields of intelligent transportation and autonomous driving. However, given the limitations of projective geometry, it is difficult to obtain the 3-D structure of vehicles using monocular cameras. The purpose of this paper is, therefore, to estimate the vehicle spatial form using monocular traffic cameras. Firstly, we establish the camera calibration model of the road scene, and jointly construct the geometric constraint model of the vehicle spatial form by vanishing points. Secondly, the contour and edge constraints of the vehicle are obtained based on Mask R-CNN. Then, based on these constraints, the error constraint function is constructed to calculate the projection error of the vehicle spatial form. Finally, a particle swarm optimization algorithm is used to iteratively optimize the parameters in the constraint space to obtain accurate vehicle spatial form information. Experiments are carried on the BrnoCompSpeed data set and the home-made data set. The experimental results show that the processing time of a single frame is less than 0.5 s and the average accuracy is higher than 94%. Moreover, the proposed algorithm has good robustness to the issue of vehicle occlusion and queuing in the scene, which outperforms existing methods.
Preparation and characterization of soluble heat-resistant polyimide films containing bis-N-phenyl-benzimidazole
Authors: Li Dandan , Wang Chengyang , Ma Shengqi , Zhou Hongwei , Lu Ran
Published: October 2021

To prepare soluble polyimides with high temperature resistance, two new diamine monomers, namely, 2,2′-(4,4′-oxybisphenylene)-bis(1-phenyl-5-aminobenzimidazole) (5a), and 2,2′-(4,4′-hexafluoroisopropylidene)-bis(1-phenyl-5- aminobenzimidazole) (5b), were synthesized and exploited to prepare three series of poly(benzimidazole imides)s (PBIIs) by a conventional two-stage synthesis. The resulting PI films were flexible and tough, possessing high glass-transition temperatures (Tgs = 311°C–390°C), improved optical transparency, and excellent solubility. Moreover, the effect of different configuration on performance was revealed, and these data provided a feasible method to enhance both Tg and solubility of PIs by incorporating N-phenyl benzimidazole and corresponding functional moieties.
Public support for government use of network surveillance: An empirical assessment of public understanding of ethics in science administration
Authors: Sapp Stephen G. , Dorius Shawn F. , Bertelson Katharine A. , Harper Shannon B.
Published: October 2021

This article relies upon the recreancy theorem to empirically assess the extent to which people’s desires for technology efficacy, personal security, and social justice affect their trust in and support for government use of network surveillance as it is applied to local law enforcement and homeland security. The recreancy theorem complements technology adoption models in that it focuses upon public assessments of innovations as they are managed by societal institutions, thereby providing conceptual congruity between technology adoption and public assessments of institutional competency and integrity. Based upon the results of a social survey of 1488 adults living in the contiguous United States, the article expands our conceptual understanding of public opinions of network surveillance and empirically documents public demand for network surveillance that fosters goals of social justice more so than goals of self-interest.