bluuebunny/crossref_metadata_2025 huggingface dataset:
Constraining visible neutrino decay at KamLAND and JUNO
Authors: Porto-Silva Yago P. , Prakash Suprabh , Peres O. L. G. , Nunokawa Hiroshi , Minakata Hisakazu
Published: October 2020

We study visible neutrino decay at the reactor neutrino experiments KamLAND and, JUNO. Assuming the Majoron model of neutrino decay, we obtain constraints on the couplings between Majoron and neutrino as well as on the lifetime/mass of the most massive neutrino state i.e., $$\tau _{3} / m_{3}$$

τ
3

/

m
3

or $$\tau _{2} / m_{2}$$

τ
2

/

m
2

, respectively, for the normal or the inverted mass orderings. We obtain the constraints on the lifetime $$\tau _{2} / m_{2} \ge 1.4 \times 10^{-9}~{\mathrm{s/eV}}$$

τ
2

/

m
2

≥
1.4
×

10

-
9

s
/
eV

in the inverted mass ordering for both KamLAND and JUNO at 90% CL. In the normal ordering in which the bound can be obtained for JUNO only, the constraint is milder than the inverted ordering case, $$\tau _{3} / m_{3} \ge 1.0 \times 10^{-10}$$

τ
3

/

m
3

≥
1.0
×

10

-
10

 s/eV at 90% CL. We find that the dependence of lightest neutrino mass ($$=m_{{{\mathrm{lightest}}}}$$

=

m
lightest

), $$m_1 (m_3)$$

m
1

(

m
3

)

for the normal (inverted) mass ordering, on the constraints for the different types of couplings (scalar or pseudo-scalar) is rather strong, but the $$m_{{{\mathrm{lightest}}}}$$

m
lightest

dependence on the lifetime/mass bound is only modest.
Earth tomography with atmospheric neutrino oscillations
Authors: D’Olivo Juan Carlos , Herrera Lara José Arnulfo , Romero Ismael , Sampayo Oscar A. , Zapata Gabriel
Published: October 2020

The study of the flux of atmospheric neutrino crossing the Earth can provide useful information not only on the matter density of the different layers that make up the planet but also on their chemical composition. The key phenomenon that makes this possible is flavor oscillations and their dependence on the electron density along the neutrino baseline. To extract the relevant information, we simulate the energy and azimuth angle distribution of events produced in a generic neutrino telescope by atmospheric neutrinos passing through the deepest parts of the Earth. Changes in the densities of the outer core and the mantle are implemented by varying the location of the boundary between these layers so that the restrictions on the mass of and the moment of inertia of the Earth are both satisfied. This allows us to examine the effect of simultaneous changes in composition and density of the outer core, unlikely other works on the subject, where only one of these quantities was varied.
Functional Outcome of Early, Selective Surgical Nerve Decompression in Leprous Neuropathy
Authors: Khan Yasim , Prakash Saket , Kalra Pulkit , Arora Sumit , Dhal Anil
Published: October 2020

Background: Leprous neuropathy is a significant, yet preventable, cause of disability worldwide. Decompressive surgery and oral steroids have been used along with Multi Drug Therapy (MDT) for treating leprous neuropathy with varied success as reported in literature.

Methods: We prospectively studied 16 peripheral nerves in 10 patients with leprous neuropathy of less than a year duration and not responding to steroid therapy in 3 weeks. The patients were divided into 2 groups: Group-A (decompressive nerve surgery was done within 12 weeks of onset of neurological deficit), and Group-B (nerve decompression was performed after 12 weeks from onset of neurological deficit). Post-operatively patients were assessed for regression of deformity, sensory, motor, vasomotor recovery and neuropathic pain.

Results: Median age of patients was 32 years (range; 18 years to 46 years). Mean motor score and mean grip strength was significantly better for group A patients at 2 years follow-up (p < 0.05). Mean sensory score improved significantly in both the groups (p < 0.05). Similarly, mean VAS score for neuropathic pain improved significantly in both the groups (p < 0.05). Recovery of autonomic function was observed in 3 nerves in group A and 1 in group B.

Conclusions: The cases who underwent nerve decompression surgery within 12 weeks had better functional outcomes, especially in terms of motor recovery, than those who were operated after that. Studies involving larger number of patients are required to draw firm conclusions.
Subungual Schwannoma, a Rare Entity: A Case Report and Literature Review
Authors: Wink Jason D. , Familusi Olatomide , Lin Ines C.
Published: October 2020

We present a case of a 26-year-old right hand dominant male landscaper with a slow growing right ring finger subungual mass. MRI confirmed a 0.9 × 1.5 × 0.9 cm well circumscribed subungual mass believed to be consistent with a glomus tumor, although size and symptoms were not consistent with that diagnosis. The mass was completely excised and diagnosis of schwannoma was confirmed by H&E histology. A literature search was performed utilizing the term “subungual schwannoma.” Four case reports were found describing this diagnosis in the hand as well as a single case report describing it in the foot. In summary, this is a 26-year-old male who presents with a schwannoma in the unusual subungual location. Although rare, based on our case and the existing literature, subungual schwannomas should be included in the differential diagnosis of a slow growing subungual mass, particularly if symptoms and exam are inconsistent with more common etiologies.
Approximating Edit Distance Within Constant Factor in Truly Sub-quadratic Time
Authors: Chakraborty Diptarka , Das Debarati , Goldenberg Elazar , Koucký Michal , Saks Michael
Published: October 2020

Edit distance is a measure of similarity of two strings based on the minimum number of character insertions, deletions, and substitutions required to transform one string into the other. The edit distance can be computed exactly using a dynamic programming algorithm that runs in quadratic time. Andoni, Krauthgamer, and Onak (2010) gave a nearly linear time algorithm that approximates edit distance within approximation factor poly(log
n
).

In this article, we provide an algorithm with running time Õ(
n
2−2/7
) that approximates the edit distance within a constant factor.
COVID-19 and computation for policy
Authors: Johnson Jeffrey , Denning Peter , Delic Kemal , Bromley Jane
Published: October 2020

Governments across the world are formulating and implementing medical, social, economic and other policies to manage the COVID-19 pandemic and protect their citizens. Many governments claim that their policies follow the best available scientific advice. Much of that advice comes from computational modeling. Two of the main types of model are presented: the SIR (Susceptible, Infected, Recovered) model developed by Kermack and McKendrick in the 1920s and the more recent Agent Based Models. The SIR model gives a good intuition of how epidemics spread; including how mass vaccination can contain them. It is less useful than Agent Based Modeling for investigating the effects of policies such as social distancing, self-isolation, wearing facemasks, and test-trace-isolate.

Politicians and the public have been perplexed to observe the lack of consensus in the scientific community and there being no single 'best science' to follow. The outcome of computational models depends on the assumptions made and the data used. Different assumptions will lead to different computational outcomes, especially when the available data are so poor. This leads some commentators to argue that the models are wrong and dangerous. Some may be, but computational modeling is one of the few ways available to explore and try to understand the space of possible futures. This lack of certainty means that computational modeling must be seen as just one of many inputs into the political decision making process. Politicians must balance all the competing inputs and make timely decisions based on their conclusions---be they right or wrong. In the same way that democracy is the least worst form of government, computational modeling may be the least worst way of trying to understand the future for policy making.
High-intensity exercise impairs extradiaphragmatic respiratory muscle perfusion in patients with COPD
Authors: Louvaris Zafeiris , Rodrigues Antenor , Dacha Sauwaluk , Gojevic Tin , Janssens Wim , Vogiatzis Ioannis , Gosselink Rik , Langer Daniel
Published: October 2020

We simultaneously assessed the blood flow index (BFI) in three respiratory muscles during hyperpnea and high-intensity constant-load cycling sustained at comparable levels of work of breathing and respiratory neural drive in patients with COPD. We demonstrated that high-intensity exercise impairs respiratory muscle perfusion, as intercostal, scalene, and abdominal BFI increased during hyperpnea but not during cycling. Insufficient adjustment in respiratory muscle perfusion during exercise was associated with greater dyspnea sensations in patients with COPD.
Acupoint Injection for Nonspecific Chronic Low Back Pain: A Systematic Review and Meta‐Analysis of Randomized Controlled Studies
Authors: Xie Guanli , Wang Tao , Tang Xiaoxia , Guo Xiaobo , Xu Yanfei , Deng Li , Sun Haomin , Ma Zhenxian , Ai Yuanliang , Jiang Bo , Li Lvyu , Luo Wen , Huang Wenze , Xia Yubo , Zhao Heng , Wang Xin , Guo Ying , Liao Jianglong
Published: October 2020

Introduction. Nonspecific chronic low back pain (NCLBP) became a public health and economic problem. Acupoint injection was used widely for patients with NCLBP. However, there were inconsistent results on the efficacy for these people. Therefore, this review was performed to systematically assess the efficacy and safety of acupoint injection. Materials and Methods. The literature sources were collected via EMBASE, Medline, CENTRAL, CINAHL, CNKI, VIP, Wanfang, and Sino‐Med Database from their inception to October 13, 2019. Endnote X7, widely used document management software, was used to manage and screen the literature sources. Each record was screened according to the predetermined inclusion criteria by two review authors independently. Quality assessment tool, “Risk of table,” was used to assess the quality of the included studies according to the recommendation of the Cochrane Handbook for Systematic Reviews of Interventions. Data extraction was performed by one reviewer and verified by another reviewer. Any disagreement was addressed via consulting with a third reviewer in the abovementioned processes. All procedures were performed according to the Cochrane Handbook for Systematic Reviews of Interventions. Results. This review included 13 studies involving 1381 patients with NCLBP. Quantitative analysis results indicated that there is no sufficient evidence that acupoint injection can improve the pain of patients with low back pain based on two trails: Visual Analogue Scale (VAS: MD = −1.33, 95% confidence interval (95% CI) −3.30 to 0.64, P = 0.18, random‐effect model). When assessing the effectiveness of acupoint injection therapy, the results indicated that acupoint injection can improve the effective rate for nonspecific chronic low back pain (OR = 3.64, 95% CI 2.4 to 5.21, P < 0.0001, fixed‐effect model). Conclusion. There is insufficient evidence to indicate that acupoint injection therapy could improve the pain for patients with NCLBP. However, the level of evidence was downgraded to “very low quality” because of the poor methodological quality and clinical heterogeneity. The results should be interpreted with caution. Higher quality RCTs with more appropriate comparison, more objective outcome instruments, and adequate follow‐up periods are necessary to assess the efficacy of acupoint injection for NCLBP. The PROSPERO Research registration identifying number is CRD42019119158.
Modeling and Control of the Public Opinion: An Agree-Disagree Opinion Model
Authors: Bidah Sara , Zakary Omar , Rachik Mostafa
Published: October 2020

In this paper, we aim to investigate optimal control to a new mathematical model that describes agree-disagree opinions during polls, which we presented and analyzed in Bidah et al., 2020. We first present the model and recall its different compartments. We formulate the optimal control problem by supplementing our model with a objective functional. Optimal control strategies are proposed to reduce the number of disagreeing people and the cost of interventions. We prove the existence of solutions to the control problem, we employ Pontryagin’s maximum principle to find the necessary conditions for the existence of the optimal controls, and Runge–Kutta forward-backward sweep numerical approximation method is used to solve the optimal control system, and we perform numerical simulations using various initial conditions and parameters to investigate several scenarios. Finally, a global sensitivity analysis is carried out based on the partial rank correlation coefficient method and the Latin hypercube sampling to study the influence of various parameters on the objective functional and to identify the most influential parameters.
Modelling and Prediction of Random Delays in NCSs Using Double-Chain HMMs
Authors: Ge Yuan , Zhang Yan , Gao Wengen , Cheng Fanyong , Yu Nuo , Wu Jincenzi
Published: October 2020

This paper is concerned with the modelling and prediction of random delays in networked control systems. The stochastic distribution of the random delay in the current sampling period is assumed to be affected by the network state in the current sampling period as well as the random delay in the previous sampling period. Based on this assumption, the double-chain hidden Markov model (DCHMM) is proposed in this paper to model the delays. There are two Markov chains in this model. One is the hidden Markov chain which consists of the network states and the other is the observable Markov chain which consists of the delays. Moreover, the delays are also affected by the hidden network states, which constructs the DCHMM-based delay model. The initialization and optimization problems of the model parameters are solved by using the segmental K-mean clustering algorithm and the expectation maximization algorithm, respectively. Based on the model, the prediction of the controller-to-actuator (CA) delay in the current sampling period is obtained. The prediction can be used to design a controller to compensate the CA delay in the future research. Some comparative experiments are carried out to demonstrate the effectiveness and superiority of the proposed method.
Sarcopenia in Type 2 Diabetes Mellitus: A Cross-Sectional Observational Study
Authors: Pechmann L. M. , Jonasson T. H. , Canossa V. S. , Trierweiler H. , Kisielewicz G. , Petterle R. R. , Moreira C. A. , Borba V. Z. C.
Published: October 2020

Background. The aim of this study was to compare the prevalence of low muscle mass and sarcopenia in patients with type 2 diabetes mellitus (T2DM) versus paired controls (control group, CG) and the association between sarcopenia and chronic diabetes complications. Methods. Men and women ≥50 years with T2DM (T2DM group, T2DMG) were recruited during routine outpatient visits. Total body densitometry and handgrip strength (HGS) were evaluated in the T2DMG and CG, while the T2DMG was also evaluated for the physical performance using the gait speed (GS) test. Sarcopenia was diagnosed according to the criteria of the Foundation for the National Institutes of Health Sarcopenia Project (FNIH). Results. The study included 177 individuals in the T2DMG and 146 in the CG. The mean HGS value was lower in the T2DMG (24.4 ± 10.3 kg) compared with the CG (30.9 ± 9.15 kg),

p
<
0.001

, with low HGS in 46 (25.9%) and 10 (9%) in the T2DMG and CG, respectively (

p
<
0.001

). The prevalence of sarcopenia defined according to the FNIH criteria was higher in the T2DMG 23 (12.9%) compared with the CG 8 (5.4%),

p
<
0.03

. The presence of albuminuria increased the odds of sarcopenia (odds ratio (OR) 2.84, 95% confidence interval (CI) 1.07–7.68,

p
=
0.04

) and osteoporosis (OR 3.38, 95% CI 1.12–9.89,

p
=
0.03

), even in patients with mild to moderate nephropathy. The body composition analysis showed increased odds of sarcopenia with increased percentage of total fat (%TF) in women (OR 1.18, 95% CI, 1.03–1.43,

p
=
0.03

) and men (OR 1.31, 95% CI, 1.10–1.75,

p
=
0.01

). Conclusion. Patients with T2DM presenting with albuminuria, osteoporosis, and increased %TF were more likely to have sarcopenia. This finding emphasizes the need for patients with T2DM to be evaluated for sarcopenia to allow for early implementation of measures to prevent or treat this disorder.
Mechanisms of Acupuncture in the Regulation of Oxidative Stress in Treating Ischemic Stroke
Authors: Su Xin-Tong , Wang Lu , Ma Si-Ming , Cao Yan , Yang Na-Na , Lin Lu-Lu , Fisher Marc , Yang Jing-Wen , Liu Cun-Zhi
Published: October 2020

Ischemic stroke is the major type of cerebrovascular disease usually resulting in death or disability among the aging population globally. Oxidative stress has been closely linked with ischemic stroke. Disequilibrium between excessive production of reactive oxygen species (ROS) and inherent antioxidant capacity leads to subsequent oxidative damage in the pathological progression of ischemic brain injury. Acupuncture has been applied widely in treating cerebrovascular diseases from time immemorial in China. This review mainly lays stress on the evidence to illuminate the possible mechanisms of acupuncture therapy in treating ischemic stroke through regulating oxidative stress. We found that by regulating a battery of molecular signaling pathways involved in redox modulation, acupuncture not only activates the inherent antioxidant enzyme system but also inhibits the excessive generation of ROS. Acupuncture therapy possesses the potential in alleviating oxidative stress caused by cerebral ischemia, which may be linked with the neuroprotective effect of acupuncture.
Impact of Awareness to Control Malaria Disease: A Mathematical Modeling Approach
Authors: Ibrahim Malik Muhammad , Kamran Muhammad Ahmad , Naeem Mannan Malik Muhammad , Kim Sangil , Jung Il Hyo
Published: October 2020

The mathematical modeling of malaria disease has a crucial role in understanding the insights of the transmission dynamics and corresponding appropriate prevention strategies. In this study, a novel nonlinear mathematical model for malaria disease has been proposed. To prevent the disease, we divided the infected population into two groups, unaware and aware infected individuals. The growth rate of awareness programs impacting the population is assumed to be proportional to the unaware infected individuals. It is further assumed that, due to the effect of awareness campaign, the aware infected individuals avoid contact with mosquitoes. The positivity and the boundedness of solutions have been derived through the completing differential process. Local and global stability analysis of disease-free equilibrium has been investigated via basic reproductive number R0, if R0 < 1, the system is stable otherwise unstable. The existence of the unique endemic equilibrium has been also determined under certain conditions. The solution to the proposed model is derived through an iterative numerical technique, the Runge–Kutta method. The proposed model is simulated for different numeric values of the population of humans and anopheles in each class. The results show that a significant increase in the population of susceptible humans is achieved in addition to the decrease in the population of the infected mosquitoes.
GNEA: A Graph Neural Network with ELM Aggregator for Brain Network Classification
Authors: Bi Xin , Liu Zhixun , He Yao , Zhao Xiangguo , Sun Yongjiao , Liu Hao
Published: October 2020

Brain networks provide essential insights into the diagnosis of functional brain disorders, such as Alzheimer’s disease (AD). Many machine learning methods have been applied to learn from brain images or networks in Euclidean space. However, it is still challenging to learn complex network structures and the connectivity of brain regions in non-Euclidean space. To address this problem, in this paper, we exploit the study of brain network classification from the perspective of graph learning. We propose an aggregator based on extreme learning machine (ELM) that boosts the aggregation ability and efficiency of graph convolution without iterative tuning. Then, we design a graph neural network named GNEA (Graph Neural Network with ELM Aggregator) for the graph classification task. Extensive experiments are conducted using a real-world AD detection dataset to evaluate and compare the graph learning performances of GNEA and state-of-the-art graph learning methods. The results indicate that GNEA achieves excellent learning performance with the best graph representation ability in brain network classification applications.
Approximate Lie Symmetry Conditions of Autoparallels and Geodesics
Authors: Jamal Sameerah
Published: October 2020

This paper is devoted to the study of approximate Lie point symmetries of general autoparallel systems. The significance of such systems is that they characterize the equations of motion of a Riemannian space under an affine parametrization. In particular, we formulate the first-order symmetry determining equations based on geometric requirements and stipulate that the underlying Riemannian space be approximate in nature. Lastly, we exemplify the results by application to some approximate wave-like manifolds.
Practical Hybrid Machine Learning Approach for Estimation of Ultimate Load of Elliptical Concrete‐Filled Steel Tubular Columns under Axial Loading
Authors: Le Tien-Thinh
Published: October 2020

In this study, a hybrid machine learning (ML) technique was proposed to predict the bearing capacity of elliptical CFST columns under axial load. The proposed model was Adaptive Neurofuzzy Inference System (ANFIS) combined with Real Coded Genetic Algorithm (RCGA), denoted as RCGA‐ANFIS. The evaluation of the model was performed using the coefficient of determination (R2) and root mean square error (RMSE). The results showed that the RCGA‐ANFIS (R2 = 0.974) was more reliable and effective than conventional gradient descent (GD) technique (R2 = 0.952). The accuracy of the present work was found superior to the results published in the literature (R2 = 0.776 or 0.768) when predicting the load capacity of elliptical CFST columns. Finally, sensitivity analysis showed that the thickness of the steel tube and the minor axis length of the elliptical cross section were the most influential parameters. For practical application, a Graphical User Interface (GUI) was developed in MATLAB for researchers and engineers and to support the teaching and interpretation of the axial behavior of CFST columns.
Prescribed Performance Neural Control of Strict-Feedback Systems via Disturbance Observers
Authors: Xiang Wei , Xu Guangkui , Zhu Fang , Yang Chunzhi
Published: October 2020

This paper provides a disturbance observer-based prescribed performance control method for uncertain strict-feedback systems. To guarantee that the tracking error meets a design prescribed performance boundary (PPB) condition, an improved prescribed performance function is introduced. And radial basis function neural networks (RBFNNs) are used to approximate nonlinear functions, while second-order filters are employed to eliminate the “explosion-complexity” problem inherent in the existing method. Meanwhile, disturbance observers are constructed to estimate the compounded disturbance which includes time-varying disturbances and network construction errors. The stability of the whole closed-loop system is guaranteed via Lyapunov theory. Finally, comparative simulation results confirm that the proposed control method can achieve better tracking performance.
MTAD-TF: Multivariate Time Series Anomaly Detection Using the Combination of Temporal Pattern and Feature Pattern
Authors: He Q. , Zheng Y. J. , Zhang C.L. , Wang H. Y.
Published: October 2020

Currently, multivariate time series anomaly detection has made great progress in many fields and occupied an important position. The common limitation of many related studies is that there is only temporal pattern without capturing the relationship between variables and the loss of information leads to false warnings. Our article proposes an unsupervised multivariate time series anomaly detection. In the prediction part, multiscale convolution and graph attention network are mainly used to capture information in temporal pattern with feature pattern. The threshold selection part uses the root mean square error between the predicted value and the actual value to perform extreme value analysis to obtain the threshold. Finally, the model in this paper outperforms other latest models on actual datasets.
Thermoformed Retainer: An Effective Option for Long-Term Stability
Authors: Giancotti A. , Mozzicato P. , Mampieri G.
Published: October 2020

Introduction. The concept of orthodontic retention is moving toward the idea that teeth will move unless retained indefinitely. However, permanent retention implies permanent supervision, and that is where reality clashes with stability. The cornerstone of Essix permanent retention is the complete delegation of responsibility to the patient. Essix retainers have nothing to adjust, but maximum collaboration of the patient is essential to achieve long-term stability. The purpose of this paper is to show the effectiveness of the thermoplastic appliance as a retainer, using a clinical case with a 10-year follow-up. Case Report. A 33-year-old male patient presented with a class II malocclusion division 2 and normal skeletal pattern. According to the patient’s desire, a treatment plan was proposed to obtain the aesthetic result of the smile, maintaining the molar and canine class II relationship. The orthodontic therapy was performed by using the Invisalign System. In this case, it was possible to appreciate a posterior occlusal stability after 10 years. Conclusion. Currently, among orthodontists, the use of removable plastic devices is gaining popularity thanks to their capability to encapsulate and retain both posterior and anterior teeth. In this article, the technical features of thermoformed retainers will be described and one clinical case with a 10-year follow-up will be presented to emphasize the effectiveness of these retainers.
Decision Tree Algorithm-Based Model and Computer Simulation for Evaluating the Effectiveness of Physical Education in Universities
Authors: Zhang Zhifei , Zhao Zijian , Yeom Doo-Seoung
Published: October 2020

In this paper, the forest algorithm and the decision tree algorithm are mainly used to analyze students’ physical education information, course exam results, and student learning data and relevant feature attributes from the online teaching platform. We aim to generate decision trees using the decision tree algorithm for the purpose of generating classification rules, based on which we can find factors that are important to students’ physical education performance and form data basis for improving teaching quality to help teaching management and teachers improve teaching methods and adjust teaching strategies. We specifically achieved this objective by constructing a model for assessing the effectiveness of student teaching, the steps of which include data collection and preparation, data preprocessing (data cleaning, conversion, integration), model construction (algorithm training), and algorithm optimization, as well as realizing the simulation results of the model. At the same time, the importance of the relevant attributes of the model is analyzed, and some measures are proposed to improve the universities: the standard of physical education teaching and the corresponding strategies for improving teaching methods. The mainstream development environment is chosen to ensure the complete operation of the project system that integrates learning, operation, and evaluation. The sports virtual simulation experimental teaching system realized in this paper has good functionality, stability, and application benefits in operation and use.
Massive Pulmonary Embolism Complicating Coronavirus Disease 2019 (COVID-19) Pneumonia: A Case Report
Authors: Hegde Shruti , Yesodharan Gemini , Tedrow John , Goldman Alena
Published: October 2020

Background. Patients with severe COVID-19 pneumonia are hypercoagulable and are at risk for acute pulmonary embolism. Timely diagnosis is imperative for their prognosis and recovery. This case describes an otherwise healthy 55-year-old man with respiratory failure requiring mechanical ventilatory support secondary to COVID-19 pneumonia. Massive acute pulmonary embolism with right heart failure complicated his course. Case. A healthy 55-year-old man presented to our emergency department (ED) with a sore throat, cough, and myalgia. A nasopharyngeal swab was obtained, and he was discharged for home quarantine. His swab turned positive for SARS-CoV-2 infection on real-time reverse transcriptase-polymerase chain reaction assay (RT-PCR) on day 2 of his ED visit. A week later, he represented with worsening shortness of breath, requiring intubation for hypoxic respiratory failure due to COVID-19 pneumonia. Initially, he was easy to oxygenate, had no hemodynamic compromise, and was afebrile. On day 3, he became febrile and developed significant hemodynamic instability requiring maximum vasopressor support and oxygenation difficulty. His ECG revealed sinus tachycardia with S1Q3T3 pattern. On bedside TTE, there was evidence of right heart strain and elevated pulmonary artery systolic pressure of 45 mmHg. All data was indicative of a massive APE as the etiology for his hemodynamic collapse. A decision was made to forgo computed tomography pulmonary angiography (CTPA), given his clinical instability, and systemic thrombolytic therapy was administered. Within the next 12-24 hours, his hemodynamic status significantly improved. Conclusions. This case highlights the importance of considering massive APE in COVID-19 patients as a cause of the sudden and rapid hemodynamic decline. Furthermore, timely diagnosis can be made to aid in appropriate management with the help of bedside TTE and ECG in cases where CTPA is not feasible secondary to the patient’s hemodynamic instability.
High-Dimensional Text Clustering by Dimensionality Reduction and Improved Density Peak
Authors: Sun Yujia , Platoš Jan
Published: October 2020

This study focuses on high-dimensional text data clustering, given the inability of K-means to process high-dimensional data and the need to specify the number of clusters and randomly select the initial centers. We propose a Stacked-Random Projection dimensionality reduction framework and an enhanced K-means algorithm DPC-K-means based on the improved density peaks algorithm. The improved density peaks algorithm determines the number of clusters and the initial clustering centers of K-means. Our proposed algorithm is validated using seven text datasets. Experimental results show that this algorithm is suitable for clustering of text data by correcting the defects of K-means.
A Model for Shear Strength of FRP Bar Reinforced Concrete Beams without Stirrups
Authors: Gao Danying , Zhang Changhui
Published: October 2020

The shear failure of a reinforced concrete beam generally occurs when the principal tensile stress near the neutral axis is equal to or greater than the tension strength of concrete. In order to set up a model for shear strength for FRP bar reinforced concrete beams without stirrups by the mechanical method, this paper equivalently transformed the FRP bar reinforced concrete rectangular beam with cracks as one composed of ideal elastic material to facilitate the analysis and proposed a new and more reasonable model of shear strength for FRP bar reinforced concrete beams without stirrups. Then, an experimental database including 235 FRP bar reinforced beams without stirrups was compiled to verify the validity of the proposed model. It was found that the values from the proposed model are in better agreement with the experimental results of shear strength of FRP bar reinforced concrete beams without stirrups in comparison with the models in codes.
The Bearing and Breakage Characteristics of Crushed Stone Aggregates in the Bedding Course of Permeable Roads
Authors: Cai Zhongbing , Qiu Chengchun
Published: October 2020

The current study of permeable roads helps address urban flooding in Chinese cities caused by frequent heavy rainfall and build smart cities with sponge‐like functionality. Crushed stone is widely used in constructing the bedding course of permeable roads because it has good water permeability. Experiments on the compaction of crushed stone were carried out by considering the impact of particle size and gradation to examine the strength and particle breakage characteristics of crushed stone and evaluate its use as the aggregate in the bedding course of permeable roads. The compaction process can be divided into two stages, i.e., the preliminary compaction stage and the particle crushing and intensive compaction stage. The latter consists of an alternating cycle of compacting and crushing. The particle size distribution after crushing can be described analogously to the Talbot continuous gradation equation. Single particle size samples are subject to earlier and stronger particle breakage than the mixed particle size sample, which are affected by both compaction level and loading speed. This study has important application value, and it provides experimental support for the study of materials for urban permeable roads.
Vibration Measurement and Prediction for Foundation Slab Design of a High-Tech Lab Based on In Situ Testing
Authors: Xu Zhaogang , Lou Yu , Chen Liu
Published: October 2020

Reduction of road traffic-induced vibrations has gained importance with rapid development of high-tech industry and nanotechnology. This study focuses on the in situ vibration measurement and transmissibility-based vibration prediction for the foundation slab design of a high-tech lab subjected to truck-induced vibrations. The truck-induced vibrations come from a proposed road 30 m away from the high-tech lab. The allowable vertical vibration velocity for the foundation slab of the high-tech lab was 60 μm/s in the frequency range of 5–50 Hz. The truck-induced ground vibrations in the proximity of an existing road with the same design as the proposed road were taken as the vibration source response used in the foundation design. The ground vibration transmissibility from the proposed road area to the high-tech lab area was determined by conducting frequency sweep tests in the free field. Based on the vibration source response and the ground vibration transmissibility, two antivibration foundation prototypes with different thicknesses were constructed at the site. The vibration transmissibility from the subgrade soil to the surfaces of the two foundation prototypes was obtained by measuring the ground vibrations at the high-tech lab area and the surface vibrations of the two foundation prototypes. The vertical vibration velocities of the two foundation prototypes were predicted based on the measured transmissibility and the vibration source response. The final thickness of the antivibration foundation was determined by comparing the predicted vibration velocities with the allowable vibration velocity. After construction of the high-tech lab and the road, vibration tests were conducted to assess the performance of the actual antivibration foundation. The results showed that the actual antivibration foundation was able to reduce the vibration levels at the high-tech lab to acceptable levels.
Forest Loss and Susceptible Area Prediction at Sefwi Wiawso District (SWD), Ghana
Authors: Osei-Wusu William , Quaye-Ballard Jonathan , Antwi Terah , Quaye-Ballard Naa Lamkai , Awotwi Alfred
Published: October 2020

Forests provide immeasurable merits for the economies of most developing countries. Forests in developing countries experience harmful human-induced impacts such as unregulated removal of biodiversity and unsustainable land conversion. The Sefwi Wiawso District (SWD) located in Ghana, which includes portions of six protected forest reserves (FRs) such as Muro, Tano Suhien, Tano Suraw, Suhuma, Sui River, and Krokosua, is the subject of this study. The impacts of selected spatial variables on forest losses were examined using retrospective and predictive approaches. Past deforestation patterns were analyzed using classified Landsat 5 and 7 imagery from 1984 to 2017. Pixel areas in hectares (ha) from land use land cover (LULC) classifications were used to detect land cover classes that were vulnerable to potential loss. The study also carried out a simple forest prediction using the simple moving averages (SMA) forecasting model based on the past and present deforestation patterns from LULC classification. The results showed that 3587.49 hectares (ha) of protected forest cover was converted into agricultural lands and barelands. In addition, 2532.96 hectares (ha) was converted from close forest to nonforest land cover from 2000 to 2017, which is equivalent to a 16% reduction in close forest cover within the FRs in the SWD. This loss was also 11% higher than close forest areas between 2000 and 2010. SMA forecasting showed that from 2017 to 2024, 877.38 hectares (ha) of close forest resources will convert to open forest resources and other nonforest land cover. Subtle accessibility routes such as navigable rivers and unofficial roads are the key instigators of protected forest clearance in the Sefwi Wiawso Forest District (SWFD). The SWFD is surrounded by many communities and is susceptible to uncontrollable biodiversity removal due to lack of proper monitoring of agricultural practices, mining operations, fuelwood collection, and illegal hunting, which represents a means of livelihood for the forest fringe community dwellers. The research serves as a benchmark for similar studies in efforts to investigate, measure, and project land cover change in protected forest areas.
Research on Carbonation Characteristics and Frost Resistance of Iron Tailings Powder Concrete under Low‐Cement Clinker System
Authors: Wu Ruidong , Liu Juanhong , Zhang Guangtian , Zhang Yueyue , An Shuhao
Published: October 2020

The accelerated carbonation, natural carbonation, fast freeze‐thaw test, and pore structure analysis of C30 and C50 concrete with different proportions of iron tailings powder and slag powder were tested, respectively. The results show that the accelerated carbonation depth and natural carbonation depth of concrete increase with the increase of iron tailings powder content. The prediction model of carbonation depth of iron tailings powder concrete is established by introducing the iron tailings content coefficient and strength influence coefficient. The error between the calculated value of the model and the test value of 28 d curing concrete natural carbonation depth is small, which proves that the model is completely feasible. When iron tailings powder accounts for 50% of mineral admixture, it is helpful to improve the frost resistance of concrete. According to the pore structure analysis, the introduction of iron tailings powder can optimize the pore structure, improve the porosity of harmless and less harmful pores, and thus improve the frost resistance.
Prognostic Value of the Residual SYNTAX Score on In-Hospital and Follow-Up Clinical Outcomes in ST Elevation Myocardial Infarction Patients Undergoing Percutaneous Coronary Interventions
Authors: Altekin Refik Emre , Kilinc Ali Yasar , Onac Mehdi , Cicekcibasi Orhan
Published: October 2020

Aims. We investigated the prognostic significance of residual SYNTAX score (RSS) in patients undergoing PCI due to STEMI and relationship between RSS and in-hospital and long-term ischemic cardiac events. Methods. Between June 2015 and December 2018, 538 patients who underwent primary PCI were evaluated for in-hospital events and 478 patients were evaluated for clinical events during follow-up. Primary and secondary endpoints for both in-hospital and follow-up periods were cardiac death and major adverse cardiac events (MACE). Results. 538 patients were included the study. RSS values of 131 patients were 0, and RSS values of 407 patients were >0. The median value of the RSS > 0 group was 7. According to this value, the RSS > 0 group was divided into 2 groups as R-ICR (RSS < 7, N = 188) and ICR (RSS ≥ 7, n = 219). In the RSS ≥ 7 group, during in-hospital and follow-up period, both mortality and MACE rates were higher than the other two groups. Area under the curve (AUC) for RSS for in-hospital death was found to be higher than SS (

p
=
0.035

) but similar to Grace Score (GS) (

p
=
0.651

). For MACE, RSS was higher than SS (

p
=
0.025

) and higher than the GS (

p
=
0.041

). For follow-up cardiac mortality, the AUC of the RSS was found to be higher than SS (0.870/0.763,

p
=
0.02

) and GS (0.870/0.733,

p
=
0.001

). For MACE, the AUC of RSS was higher than SS (

p
=
0.03

) and GS (

p
=
0.004

). Conclusions. High RSS values in STEMI patients are associated with increased risk of ischemic cardiac events. RSS may help determine revascularization and level of additional PCI to improve prognosis by reducing the risk of ischemic cardiac events after P-PCI.
Outcome and Safety of Unplanned-Start Peritoneal Dialysis according to Break-In Periods: A Systematic Review and Meta-Analysis
Authors: Yin Yiyu , Cao Yanpei , Yuan Li
Published: October 2020

Introduction: The best timing of peritoneal dialysis (PD) initiation after catheter implantation is still controversial. It is necessary to explore whether there exists a waiting period to minimize the risk of complications. Methods: A systematic review and meta-analysis were searched in multiple electronic databases published from inception to February 29, 2020, to identify cohort studies for evaluating the outcome and safety of unplanned-start PD (<14 days after catheter insertion). Risks of bias across studies were evaluated using Newcastle-Ottawa Quality Assessment Scale. Results: Fourteen cohort studies with a total of 2,401 patients were enrolled. We found that early-start PD was associated with higher prevalence of leaks (RR: 2.67, 95% CI, 1.55–4.61) and omental wrap (RR: 3.28, 95% CI, 1.14–9.39). Furthermore, patients of unplanned-start PD in APD group have higher risk of leaks, while those in CAPD group have a higher risk of leaks, omental wrap, and catheter malposition. In shorter break-in period (BI) group, the risk of suffering from catheter obstruction and malposition was higher for patients who started dialysis within 7 days after the surgery than for patients within 7–14 days. No significant differences were found in peritonitis (RR: 1.00; 95% CI, 0.78–1.27) and exit-site infections (RR: 1.12; 95% CI, 0.72–1.75). However, shorter BI was associated with higher risk of mortality and transition to hemodialysis (HD) while worsen early technical survival, with pooled RR of 2.14 (95% CI, 1.52–3.02), 1.42 (95% CI, 1.09–1.85) and 0.95 (95% CI, 0.92–0.99), respectively. Conclusions: Evidence suggests that patients receiving unplanned-start PD may have higher risks of mechanical complications, transition to HD, and even mortality rate while worsening early technical survival, which may not be associated with infectious complications. Rigorous studies are required to be performed.
Infectious Proctitis in Ulcerative Colitis: The Importance of an Accurate Differential Diagnosis
Authors: Mascarenhas Saraiva Miguel , Ribeiro Tiago Filipe , Macedo Guilherme
Published: October 2020

The authors present the case of a 62-year-old male presenting with a relapse of ulcerative colitis. He had unprotected anal intercourse with other men and his medical record was remarkable for HIV infection. He was admitted to the emergency department with bloody diarrhea, tenesmus, urgency, and recent weight loss. Laboratory workup revealed de novo mild anemia and mild elevation of inflammation parameters. Endoscopic evaluation displayed loss of normal vascular pattern, edema, erythema, exudation, and superficial ulceration in the distal rectum. Biopsies showed chronic proctitis with mild to moderate activity. The patient was treated with intravenous glucocorticoids, but symptoms persisted. Extensive microbial study allowed the identification of multiple infectious agents with potential for infectious proctitis: cytomegalovirus, Chlamydia trachomatis, and Blastocystis hominis. This case highlights the importance of careful microbial investigation, supporting a detailed clinical history, in patients presenting with symptoms of inflammatory bowel disease flare, particularly in risk groups such as that with sexual risk.
The Lived Experience of First-Episode Psychosis: A Systematic Review and Metasynthesis of Qualitative Studies
Authors: Noiriel Amelie , Verneuil Laurence , Osmond Ingrid , Manolios Emilie , Revah-Levy Anne , Sibeoni Jordan
Published: October 2020

Both research and care have focused on first episodes of psychosis (FEPs) as a way to address the issue of early stages of schizophrenia and to reduce the duration of untreated psychosis. The objective of this study was to explore specifically the lived experience of FEP from the point of view of patients and their families by applying a metasynthetic approach, including a systematic review of the literature and analyses of qualitative studies on the subject. This metasynthesis follows thematic synthesis procedures. Four databases were systematically searched for qualitative studies reporting FEP from the patient or family’s perspective. Article quality was assessed with the Critical Appraisal Skills Program. Thematic analysis was used to identify key themes and synthesize them. Thirty-eight articles were included, covering data from 554 participants (378 patients and 176 relatives). Three themes emerged from the analyses: (1) When and how does a FEP start? (2) What are its negative and positive aspects? (3) How do patients and families recount FEPs? Our results found important discrepancies between the experiences of patients and those of their families, especially regarding positive aspects. In light of the confusion reported by patients and notable in our results, we also discuss the gap between the name, FEP, and the lived experience of patients and family members in order to explore its practical implications.
Associations of Buying-Shopping Disorder Symptoms with Identity Confusion, Materialism, and Socially Undesirable Personality Features in a Community Sample
Authors: Müller Astrid , Claes Laurence , Birlin Annika , Georgiadou Ekaterini , Laskowski Nora M. , Steins-Loeber Sabine , Brand Matthias , de Zwaan Martina
Published: October 2020

Introduction: While identity problems and materialistic value endorsement have been described as predisposing factors for buying-shopping disorder (BSD) in the literature, little empirical data are available on the role of socially undesirable personality features that may contribute to financial misconduct and manipulative interpersonal behaviors in BSD. The dark triad of personality refers to such offensive yet non-pathological personality traits and has been applied to addictive behaviors in the past. The aim of the present study was to investigate whether the “dark triad” dimensions Machiavellianism, subclinical narcissism, and subclinical psychopathy predict symptoms of BSD above and beyond identity confusion and materialism, or moderate the relationship between materialism and symptoms of BSD. Method: The participants comprised a convenience sample (N = 272, 72.4% women) aged between 18 and 67 years. Assessment included standard questionnaires for BSD, identity problems, materialism, and the dark triad of personality. Results: Zero-order correlations indicate a weak association between BSD and the dark triad dimensions Machiavellianism and narcissism, but not psychopathy. Results of a moderated regression analysis with BSD symptoms as a dependent variable revealed significant main effects for materialism, female gender, and a significant “narcissism by materialism” effect, after accounting for identity confusion/synthesis and the single dark triad traits. Conclusion: The findings suggest that individuals with BSD attempt to address their narcissistic deficits via materialistic possessions. This assumption warrants further investigation in a clinical sample.