bluuebunny/crossref_metadata_2025 huggingface dataset:
Malignant insulinoma hypoglycaemia: complex palliative management
Authors: Simkiss Lauri , Hakkak Frances , Raghavan Rajeev
Published: June 2021

This case presentation describes a 65-year-old woman with metastatic malignant insulinoma who experienced frequent episodes of hypoglycaemia causing significant distress and burden to her quality of life. The report describes how medical management was altered and how the patient was supported in order to alleviate these burdens. In particular, the report highlights the first documented use of flash glucose monitoring in insulinoma, which was beneficial in reducing the discomfort of lancet use and anxiety associated with hypoglycaemic episodes. This case demonstrates the benefits of an individualised approach, collaboration with other specialisms and recommends further evaluation of the use of flash glucose monitoring in palliative care.
Location of out-of-hospital cardiac arrest and the awareness time interval: a nationwide observational study
Authors: Kim Seo Young , Lee Sun Young , Kim Tae Han , Shin Sang Do , Song Kyoung Jun , Park Jeong Ho
Published: June 2021

Aims

A short awareness time interval (ATI, time from witnessing the arrest to calling for help) and bystander cardiopulmonary resuscitation (CPR) are important factors affecting neurological recovery after out-of-hospital cardiac arrest (OHCA). This study investigated the association of the location of OHCA with the length of ATI and bystander CPR.

Methods

This population-based observational study used the nationwide Korea OHCA database and included all adults with layperson-witnessed OHCA with presumed cardiac aetiology between 2013 and 2017. The exposure was the location of OHCA (public places, private housing and nursing facilities). The primary outcome was short ATI, defined as <4 min from witnessing to calling for emergency medical service (EMS). The secondary outcome was the frequency of provision of bystander CPR. Multivariable logistic regression analysis was performed to evaluate the association of location of OHCA with study outcomes.

Results

Of 30 373 eligible OHCAs, 66.6% occurred in private housing, 24.0% occurred in public places and 9.4% occurred in nursing facilities. In 67.3% of the cases, EMS was activated within 4 min of collapse, most frequently in public places (public places 77.0%, private housing 64.2% and nursing facilities 64.8%; p<0.01). The overall rate of bystander CPR was 65.5% with highest in nursing facilities (77.0%), followed by public places (70.1%) and private housing 62.3%; p<0.01). Compared with public places, the adjusted ORs (AORs) (95% CIs) for a short ATI were 0.58 (0.54 to 0.62) in private housing and 0.62 (0.56 to 0.69) in nursing facilities. The AORs (95% CIs) for bystander CPR were 0.75 (0.71 to 0.80) in private housing and 1.57 (1.41 to 1.75) in nursing facilities.

Conclusion

OHCAs in private housing and nursing facilities were less likely to have immediate EMS activation after collapse than in public places. A public education is needed to increase the awareness of necessity of prompt EMS activation.
Biologics recommendations in the ECCO guidelines on therapeutics in Crohn's disease: medical treatment
Authors: Sriranganathan Danujan , Segal Jonathan P , Garg Mayur
Published: June 2021

In 2019, the European Crohn’s and Colitis Organisation released guidelines for the medical management of Crohn’s disease, concerning the induction of remission, the maintenance of remission and the treatment of fistulising perianal disease. This review summarises the key recommendations regarding the use of biologics in these settings.
Prenatal exercise and cardiovascular health (PEACH) study: the remote effect of aerobic exercise training on conduit artery and resistance vessel function
Authors: Boparai Rakhbeer , Skow Rachel J. , Farooq Sauleha , Steinback Craig D. , Davenport Margie H.
Published: June 2021

We assessed the impact of a structured lower-limb aerobic exercise training intervention during pregnancy on brachial artery endothelial function, shear rate and patterns, and forearm blood flow and reactive hyperemia. Twenty-seven pregnant women were recruited and randomized into either a control group (n = 11; 31.0 ± 0.7 years), or an exercise intervention group (n = 16; 32.6 ± 0.9 years). The exercise group completed 40 minutes of aerobic exercise (50–70% heart rate reserve) 3–4 times per week, between the second and third trimester of pregnancy. Endothelial function was assessed using flow-mediated dilation (FMD, normalized for shear stress) at pre- (16–20 weeks) and post-intervention (34–36 weeks). The exercise training group experienced an attenuated increase in mean arterial pressure (MAP) relative to the control group (ΔMAP exercise: +2 ± 2 mm Hg vs. control: +7 ± 3 mm Hg; p = 0.044) from pre- to post-intervention. % FMD change corrected for shear stress was not different between groups (p = 0.460); however, the post-occlusion mean flow rate (exercise: 437 ± 32 mL/min vs. control: 364 ± 35 mL/min; p = 0.001) and post-occlusion anterograde flow rate (exercise: 438 ± 32 mL/min vs. control: 364 ± 46 mL/min; p = 0.001) were larger for the exercise training group compared with controls, post-intervention. Although endothelial function was not different between groups, we observed an increase in microcirculatory dilatory capacity, as suggested by the augmented reactive hyperemia in the exercise training group. Registered at ClinicalTrials.gov: NCT02948439.

Novelty: Endothelial function was not altered with exercise training during pregnancy. Exercise training did contribute to improved cardiovascular outcomes, which may have been associated with augmented reactive hyperemia, indicative of increased microcirculatory dilatory capacity.
Mild hyperhomocysteinemia induces blood–brain barrier dysfunction but not neuroinflammation in the cerebral cortex and hippocampus of wild-type mice
Authors: Chu Min , Teng Jijun , Guo Lei , Wang Yuyang , Zhang Liang , Gao Jing , Liu Lijun
Published: June 2021

This study explored the potential effects of mild hyperhomocysteinemia (HHcy) on the blood–brain barrier (BBB) and neuroinflammation. Seven-week-old male wild-type C57BL/6 mice were fed normal mouse chow (the control group) or a methionine-enriched diet (the HHcy group) for 14 weeks. Mice in the HHcy group exhibited a slight increase in serum Hcy levels (13.56 ± 0.61 μmol/L). Activation of the ERK signaling pathway, up-regulation of matrix metalloproteinase-9 (MMP-9), and degradation of tight junction proteins (occludin and claudin-5) were observed in both the cerebral cortex and hippocampus of mice with mild HHcy. However, microglia were not activated and the levels of tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) were not changed in either the cerebral cortex or hippocampus of mice with mild HHcy. Moreover, the signaling activity of STAT3 also did not differ significantly between the two groups. These findings demonstrate that the BBB is highly vulnerable to homocysteine insult. Even a slight increase in serum homocysteine levels up-regulates MMP-9 expression and disrupts the BBB integrity. Meanwhile, microglia activation or the STAT3 pathway might not contribute to the effects of mild HHcy on the brain.
Secondary vertex finding in jets with neural networks
Authors: Shlomi Jonathan , Ganguly Sanmay , Gross Eilam , Cranmer Kyle , Lipman Yaron , Serviansky Hadar , Maron Haggai , Segol Nimrod
Published: June 2021

Jet classification is an important ingredient in measurements and searches for new physics at particle colliders, and secondary vertex reconstruction is a key intermediate step in building powerful jet classifiers. We use a neural network to perform vertex finding inside jets in order to improve the classification performance, with a focus on separation of bottom vs. charm flavor tagging. We implement a novel, universal set-to-graph model, which takes into account information from all tracks in a jet to determine if pairs of tracks originated from a common vertex. We explore different performance metrics and find our method to outperform traditional approaches in accurate secondary vertex reconstruction. We also find that improved vertex finding leads to a significant improvement in jet classification performance.
An Inequality for the Number of Periods in a Word
Authors: Gabric Daniel , Rampersad Narad , Shallit Jeffrey
Published: June 2021

We prove an inequality for the number of periods in a word [Formula: see text] in terms of the length of [Formula: see text] and its initial critical exponent. Next, we characterize all periods of the length-[Formula: see text] prefix of a characteristic Sturmian word in terms of the lazy Ostrowski representation of [Formula: see text], and use this result to show that our inequality is tight for infinitely many words [Formula: see text]. We propose two related measures of periodicity for infinite words. Finally, we also consider special cases where [Formula: see text] is overlap-free or squarefree.
On NH-embedded subgroups of finite groups
Authors: Gao Yaxin , Li Xianhua
Published: June 2021

Let [Formula: see text] be a finite group and [Formula: see text] a subgroup of [Formula: see text]. [Formula: see text] is said to be [Formula: see text]-embedded in [Formula: see text] if there exists a normal subgroup [Formula: see text] of [Formula: see text] such that [Formula: see text] is a Hall subgroup of [Formula: see text] and [Formula: see text], where [Formula: see text] is the largest [Formula: see text]-semipermutable subgroup of [Formula: see text] contained in [Formula: see text]. In this paper, we give some new characterizations of [Formula: see text]-nilpotent and supersolvable groups by using [Formula: see text]-embedded subgroups. Some known results are generalized.
Self-evaluation Interventions: Impact on Self-efficacy and Performance in Introductory Programming
Authors: Lishinski Alex , Yadav Aman
Published: June 2021

Research has repeatedly shown self-efficacy to be associated with course outcomes in CS and across other fields. CS education research has documented this and has developed CS-specific self-efficacy measurement instruments, but to date there have been only a few studies examining interventions intended to improve students’ self-efficacy in CS, and several types of self-efficacy interventions suggested by previous research remain to be tested in CS. This study attempts to address this lack of research by reporting on the results of a trial intervention intended to improve students’ self-efficacy in an introductory programming course. Students were recruited to complete a self-evaluation task, which previous research has suggested could have a beneficial impact on self-efficacy, which should in turn have a beneficial impact on course performance. Participating students’ course outcomes and self-efficacy were compared with those of the students who did not complete the self-evaluation task, using propensity score weighting adjustments to control for differences between the groups on entering characteristics and prior values of self-efficacy and course outcomes. We found that, whereas there was only marginal evidence for the self-evaluation intervention having a direct effect on self-efficacy, students who completed the self-evaluation task had significantly higher project scores during the weeks they were asked to complete it, compared to the students who did not participate. These findings suggest that there are potential benefits to incorporating self-evaluation tasks into introductory CS courses, although perhaps not by virtue of directly influencing self-efficacy.
Brefeldin A and kifunensine modulate LPS-induced lung endothelial hyperpermeability in human and bovine cells
Authors: Kubra Khadeja-Tul , Barabutis Nektarios
Published: June 2021

Endothelial hyperpermeability is the hallmark of acute respiratory distress syndrome (ARDS). Laborious efforts in the investigation of the molecular pathways involved in the regulation of the vascular barrier shall reveal novel therapeutic targets toward that respiratory disorder. Herein, we investigate in vitro the effects of the α-1,2-mannosidase 1 inhibitor kifunensine (KIF) and brefeldin A (BFA) in the lipopolysaccharides (LPS)-induced endothelial breakdown. Our results suggest that BFA opposes the deteriorating effects of KIF [unfolded protein response (UPR) suppressor] toward the lung microvasculature. Since KIF is a UPR suppressor, and brefeldin A is a UPR inducer, we suggest that a carefully devised UPR manipulation may deliver novel therapeutic avenues in diseases related to endothelial barrier dysfunction (e.g., ARDS and sepsis).
Caloric Restriction and Cardiovascular Health: the Good, the Bad, and the Renin-Angiotensin System
Authors: de Souza Aline M. A. , Ecelbarger Carolyn M. , Sandberg Kathryn
Published: June 2021

Much excitement exists over the cardioprotective and life-extending effects of caloric restriction (CR). This review integrates population studies with experimental animal research to address the positive and negative impact of mild and severe CR on cardiovascular physiology and pathophysiology, with a particular focus on the renin-angiotensin system (RAS). We also highlight the gaps in knowledge and areas ripe for future physiological research.
Fetal Growth Restriction and Asthma: Is the Damage Done?
Authors: Wang Kimberley C. W. , James Alan L. , Noble Peter B.
Published: June 2021

Trajectories of airway remodeling and functional impairment in asthma are consistent with the notion that airway pathology precedes or coincides with the onset of asthma symptoms and may be present at birth. An association between intrauterine growth restriction (IUGR) and asthma development has also been established, and there is value in understanding the underlying mechanism. This review considers airway pathophysiology as a consequence of IUGR that increases susceptibility to asthma.
[Retracted] Dance Motion Capture Based on Data Fusion Algorithm and Wearable Sensor Network
Authors: Li Yueru
Published: June 2021

In this paper, through an in‐depth study and analysis of dance motion capture algorithms in wearable sensor networks, the extended Kalman filter algorithm and the quaternion method are selected after analysing a variety of commonly used data fusion algorithms and pose solving algorithms. In this paper, a sensor‐body coordinate system calibration algorithm based on hand‐eye calibration is proposed, which only requires three calibration poses to complete the calibration of the whole‐body sensor‐body coordinate system. In this paper, joint parameter estimation algorithm based on human joint constraints and limb length estimation algorithm based on closed joint chains are proposed, respectively. The algorithm is an iterative optimization algorithm that divides each iteration into an expectation step and a great likelihood step, and the best convergence value can be found efficiently according to each iteration step. The feature values of each pose action are fed into the algorithm for model learning, which enables the training of the model. The trained model is then tested by combining the collected gesture data with the algorithmic model to recognize and classify the gesture data, observe its recognition accuracy, and continuously optimize the model to achieve accurate recognition of human gesture actions.
Comprehensive Analysis of Competing Endogenous RNA Network Focusing on Long Noncoding RNA Involved in Cirrhotic Hepatocellular Carcinoma
Authors: Zhang Yuli , Chen Dinggui , Yang Miaomiao , Qian Xianfeng , Long Chunmei , Zheng Zhongwei
Published: June 2021

The role of long noncoding RNAs- (lncRNAs-) associated competing endogenous RNA (ceRNA) in the field of hepatocellular carcinoma (HCC) biology is well established, but the involvement of lncRNAs competing interactions in the progression of liver cirrhosis to HCC is still unclear. We aimed to explore the differential expression profiles of lncRNAs, microRNAs (miRNA), and messenger RNAs (mRNAs) to construct a functional ceRNA network in cirrhotic HCC. The lncRNA, miRNA, and mRNA expression datasets were obtained from Gene Expression Omnibus and The Cancer Genome Atlas. Based on miRanda and TargetScan, the HCC-specific ceRNA network was constructed to illustrate the coexpression regulatory relationship of lncRNAs, miRNAs, and mRNAs. The potential prognostic indicators in the network were confirmed by survival analysis and validated by qRT-PCR. A total of 74 lncRNAs, 36 intersection miRNAs, and 949 mRNAs were differentially expressed in cirrhotic HCC samples compared with cirrhosis samples. We constructed a ceRNA network, including 47 lncRNAs, 35 miRNAs, and 168 mRNAs. Survival analysis demonstrated that 2 lncRNAs (EGOT and SERHL), 4 miRNAs, and 40 mRNAs were significantly associated with the overall survival of HCC patients. Two novel regulatory pathways, EGOT-miR-32-5p-XYLT2 axis and SERHL-miR-1269a/miR-193b-3p-BCL2L1/SYK/ARNT/CHST3/LPCAT1 axis, were built up and contribute to the underlying mechanism of HCC pathogenesis. The higher-expressed SERHL was associated with a higher risk of all-cause death. The expressions of SERHL-miR-1269a-BCL2L1 were significantly different using qRT-PCR in vitro studies. lncRNAs EGOT and SERHL might serve as effective prognostic biomarkers and potential therapeutic targets in cirrhotic HCC treatment.
Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss
Authors: Huang Chengjun , Chen Maoqi , Zhang Yingchun , Li Sheng , Zhou Ping
Published: June 2021

This study presents a model-based sensitivity analysis of the strength of voluntary muscle contraction with respect to different patterns of motor unit loss. A motor unit pool model was implemented including simulation of a motor neuron pool, muscle force, and surface electromyogram (EMG) signals. Three different patterns of motor unit loss were simulated, including (1) motor unit loss restricted to the largest ones, (2) motor unit loss restricted to the smallest ones, and (3) motor unit loss without size restriction. The model outputs including muscle force amplitude, variability, and the resultant EMG-force relation were quantified under two different motor neuron firing strategies. It was found that motor unit loss restricted to the largest ones had the most dominant impact on muscle strength and significantly changed the EMG-force relation, while loss restricted to the smallest motor units had a pronounced effect on force variability. These findings provide valuable insight toward our understanding of the neurophysiological mechanisms underlying experimental observations of muscle strength, force control, and EMG-force relation in both normal and pathological conditions.
Cytoreductive Surgery plus Hyperthermic Intraperitoneal Chemotherapy Improves Survival with Acceptable Safety for Advanced Ovarian Cancer: A Clinical Study of 100 Patients
Authors: Zhang Jue , Li Xin-bao , Ji Zhong-he , Ma Ru , Bai Wen-pei , Li Yan
Published: June 2021

Background. The mainstay of treatment for advanced ovarian cancer is debulking surgery followed by chemotherapy that includes carboplatin and paclitaxel, but the prognosis is poor. This study is aimed at evaluating the efficacy and safety of cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy (CRS+HIPEC) as first‐line surgical treatment in patients with advanced ovarian cancer (AOC). Methods. FIGO stage III/IV AOC patients underwent CRS+HIPEC as first‐line surgical treatment at our center from December 2007 to January 2020. The primary endpoint was survival, and the secondary endpoint was safety. Results. Among 100 patients, the median Karnofsky performance status (KPS) score was 80 (50‐100), median peritoneal cancer index (PCI) was 19 (1‐39), median completeness of cytoreduction (CC) score was 1 (0‐3), number of organ regions removed was 4 (3‐9), number of peritoneal regions removed was 4 (1‐9), and number of anastomoses was 1 (0‐4). The median follow‐up was 36.8 months; 75 (75.0%) patients were still alive, and 25 (25.0%) had died. The median overall survival (mOS) was 87.6 (95% CI: 72.1‐103.0) months, and the 1‐, 2‐, 3‐, 4‐, and 5‐year survival rates were 94.1%, 77.2%, 68.2%, 64.2%, and 64.2%, respectively. Univariate analysis showed that better mOS correlated with an age ≤, KPS ≥ 80, ascites ≤ 1000 ml, PCI < 19, and CC score 0‐1. Multivariate Cox analysis showed that CC was an independent factor for OS; patients who underwent CRS with a CC score 0‐1 had a mPFS of 67.8 (95% CI: 48.3‐87.4) months. The perioperative serious adverse event and morbidity rates were 4.0% and 2.0%, respectively. Conclusions. CRS+HIPEC improves survival for AOC patients with acceptable safety at experienced high‐volume centers. Stringent patient selection and complete CRS are key factors for better survival.
Formation Mechanism and Prediction Method for the Permian Fused Breccia Tuff Reservoir, Wuxia Region, Junggar Basin
Authors: Xu Duonian , Pan Jianguo , Pan Shuxin , Gao Bin , Yin Lu , Qu Yongqiang , Zhang Lei
Published: June 2021

Fused breccia tuff occurs globally, but its formation mechanism is very controversial. Volcanic reservoirs have developed at the bottom of the Permian Fengcheng Formation in the Wuxia region of the Junggar Basin, and here, the lithology is fused breccia tuff. The reservoir porosity is mainly vesicles, but the development and relative filling of the vesicles vary spatially, resulting in strong reservoir heterogeneity. Through core and thin section observations and structural analysis, and combined with reconstructions of the paleosedimentary environment, we discussed in detail the formation mechanism of the fused breccia tuff reservoir. Our conclusions are as follows. In the high-temperature and high-pressure environment of the deep crust, intermediate acidic lava containing volatile components rapidly rose to the earth’s surface along a fault. The volatile components in the lava foamed strongly and then exploded due to the sharp decline of pressure and temperature. A small part of the volcanic dust and pyroclastic material was erupted into the upper atmosphere. Most of the magma became magmatic pyroclast, vitric pyroclast, rock debris, dust, and other matter. This material was in a semimolten state and overflowed into a nearby low-lying lake. The extremely high-temperature pyroclastic flow quickly vaporized the water into high-pressure water vapor, which was squeezed into the pyroclastic flow and became mixed with other volatiles in the foam. On cooling, the pyroclastic material solidified into rock, and the vesicles were preserved. In a later period, due to strong tectonic movement, faults and fractures developed, surface water penetrated into the vesicles along the faults and fractures, and silica and other substances were deposited, filling the primary vesicles. To quantify the development and relative filling of vesicles, drilling parameters were used to establish different geologic models, and wave equation forward modeling was used to obtain a relationship between the development and filling of vesicles, and the seismic amplitude. The 3D seismic amplitude attributes were then extracted to predict the extent of the reservoir, yielding prediction results consistent with the drilling observations.
Sharing Economy for Cost Reduction and Efficiency Increase: The Case of Sharing E‐Commerce Logistics
Authors: Wei Qiang , Sun Daguang , Gou Xinyu , Bai Chunguang
Published: June 2021

In the real business environment, due to unpredictable market demand or high prediction difficulty and low prediction accuracy, there will be inevitably operational loss in the field of e‐commerce logistics caused by undersupply or oversupply of express service capabilities. At present, China is deepening the supply‐side structural reforms. Confronted with the growing demand for e‐commerce logistics express delivery, especially the urgent demand for tackling orders piling up to 1 billion pieces during the recent “Double 11” shopping carnival, it is very important and practical for us to study how to make scientific decisions on the supply side in the field of e‐commerce express delivery. Therefore, in this paper, we design a sharing logistics cooperation mechanism considering both the undersupply and oversupply of express delivery service capabilities under stochastic demand. By comparing the earnings data of several listed express companies, we analyze four types of optimization strategies: the order flow proportion revenue sharing strategy (RE‐OFP), the combined factors revenue sharing strategy (RE‐RSF), the order flow proportion risk sharing strategy (RS‐OFP), and the combined factors risk sharing strategy (RS‐RSF). The research results demonstrate that the four optimization strategies of RE‐OFP, RE‐RSF, RS‐OFP, and RS‐RSF could achieve Pareto improvements in the operational performance of e‐commerce express service. The performance of four revenue sharing and risk sharing strategies varies with different revenue sharing or risk sharing factors. Under some certain combined factors, the revenue sharing contract could help realize the supply chain coordination of the sharing logistics service. The sharing logistics cooperation mechanism based on equity investment proposed hereafter provides a feasible solution to solve the problems of high empty driving rate and operational cost of e‐commerce express delivery service in urban areas.
Algebraic Parameter Identification of Nonlinear Vibrating Systems and Non Linearity Quantification Using the Hilbert Transformation
Authors: Trujillo-Franco Luis Gerardo , Silva-Navarro Gerardo , Beltran-Carbajal Francisco
Published: June 2021

A novel algebraic scheme for parameters’ identification of a class of nonlinear vibrating mechanical systems is introduced. A nonlinearity index based on the Hilbert transformation is applied as an effective criterion to determine whether the system is dominantly linear or nonlinear for a specific operating condition. The online algebraic identification is then performed to compute parameters of mass and damping, as well as linear and nonlinear stiffness. The proposed algebraic parametric identification techniques are based on operational calculus of Mikusiński and differential algebra. In addition, we propose the combination of the introduced algebraic approach with signals approximation via orthogonal functions to get a suitable technique to be applied in embedded systems, as a digital signals’ processing routine based on matrix operations. A satisfactory dynamic performance of the proposed approach is proved and validated by experimental case studies to estimate significant parameters on the mechanical systems. The presented online identification approach can be extended to estimate parameters for a wide class of nonlinear oscillating electric systems that can be mathematically modelled by the Duffing equation.
An Empirical Assessment of Factors Influencing Injury Severities of Motor Vehicle Crashes on National Highways of Pakistan
Authors: Ullah Hanif , Farooq Asim , Shah Akhtar Ali
Published: June 2021

Road transport is the dominant mode of transport in Pakistan carrying 91% of the country’s passenger traffic and 96% of freight traffic. National highways, being 3.7% of the entire road network, carry 80% of commercial traffic. Due to the high number of road traffic crashes and resulting fatalities, a random parameters logit model was estimated to determine the risk factors that influence the severity of injuries caused by motor vehicle crashes on national highways. The effects of driver characteristics, crash characteristics, highway characteristics, temporal characteristics, and environmental characteristics were considered for the analysis. From the results, it was revealed that many factors such as overspeeding, driver dozing, driver carelessness, driver age <25 years, truck, rickshaw, single vehicle, horizontal curve, potholes, night without road lights, AM peak, Tuesday, weekdays, May, July, November, cloudy weather, clear weather, normal visibility, and wet road surface affect injury severity of the crash victims. The results are expected to be useful for transport planners, traffic managers, road engineers, and other stakeholders both from public and private sectors in prioritizing road sections for improvements and implementing suitable road safety interventions. This will ultimately result in the decreased social and economic burden of road traffic injuries (RTIs).
Geographical Origin Identification of Tequila Based on Multielement and Stable Isotopes
Authors: Zhang Jian , Ma Yiqian , Shao Feilong , Lu Yuanyu , Zhu Libo , Xu Xiansong
Published: June 2021

To explore the regional characteristics of multielement and stable isotopes in tequila and the viability of tracing the geographical origin, both inductively coupled plasma mass spectrometry (ICP-MS) and stable isotope ratio mass spectrometry (IRMS) were applied in this study to determine the multielement content and stable isotope ratios of tequila. Then, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) as chemometrics were conducted in combination to establish a model for determining the geographical origin of Mexican tequila. According to the analytical results, the content of 22 elements varied, as did the ranges of stable isotope δ13C and δ18O values for the tequila obtained from the 4 producing areas. Besides, there were regional characteristics shown to some extent. PCA and PLS-DA methods can be adopted to identify the geographical origin of tequila in Mexico. According to the discriminant verification of 16 samples, the accuracy of prediction reached 93.75%. It has been demonstrated that it is possible to distinguish tequila of different geographical origins in Mexico by combining the determination of the multielement content and stable isotope ratios with chemometric analysis, which lays a foundation for tracing the geographical origin of tequila.
Data‐Driven Robust Optimization for Solving the Heterogeneous Vehicle Routing Problem with Customer Demand Uncertainty
Authors: Zhang Jingling , Yu Mengfan , Feng Qinbing , Leng Longlong , Zhao Yanwei
Published: June 2021

In practice, the parameters of the vehicle routing problem are uncertain, which is called the uncertain vehicle routing problem (UVRP). Therefore, a data‐driven robust optimization approach to solve the heterogeneous UVRP is studied. The uncertain parameters of customer demand are introduced, and the uncertain model is established. The uncertain model is transformed into a robust model with adjustable parameters. At the same time, we use a least‐squares data‐driven method combined with historical data samples to design a function of robust adjustable parameters related to the maximum demand, demand range, and given vehicle capacity to optimize the robust model. We improve the deep Q‐learning‐based reinforcement learning algorithm for the fleet size and mix vehicle routing problem to solve the robust model. Through test experiments, it is proved that the robust optimization model can effectively reduce the number of customers affected by the uncertainty, greatly improve customer satisfaction, and effectively reduce total cost and demonstrate that the improved algorithm also exhibits good performance.
Methodological Considerations in N-of-1 Trials of Traditional Chinese Medicine
Authors: Huang Haiyin , An Jiaqi , Lu Lizhi , Wang Mingli , Chen Huijia , Chen Xinlin , Shen Lihua
Published: June 2021

More and more scholars choose N-of-1 trials for TCM clinical research. However, the quality of the experimental designs was uneven. Accumulating more than eight years of experience in exploring the N-of-1 trials of TCM, the authors and their team searched the related literature in main Chinese and English databases, referenced to relevant Chinese and international guidelines. The design, implementation, and data analysis of N-of-1 trials of TCM are still in in-depth exploration and practice. “Carryover effect” may affect the design and quality of the trials. Individualized treatment should be guided by the classic theories of TCM. It is expected to formulate reasonable observation periods and pairs and closely integrate individual and group statistical analysis.
Circular RNAs: Novel Players in the Oxidative Stress‐Mediated Pathologies, Biomarkers, and Therapeutic Targets
Authors: Wang Yunguang , He Wenfang , Ibrahim Sherif A. , He Qiang , Jin Juan
Published: June 2021

Oxidative stress (OxS) is a wildly described cause of damage to macromolecules, resulting in abnormal physiological conditions. In recent years, a few studies have shown that oxidation/antioxidation imbalance plays a significant role in developing diseases involving different systems and organs. However, the research on the circular RNA (circRNA) roles in OxS is still in its very infancy. Therefore, we hope to provide a comprehensive overview of the recent research that explored the function of circRNAs associated with OxS and its role in the pathogenesis of different diseases that affect different body systems like the nervous system, cardiovascular system, kidneys, and lungs. It provides the possibilities of using these circRNAs as superior diagnostic and therapeutic options for OxS associated with these disease conditions.
Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios in Nondialysis Chronic Kidney Patients
Authors: Brito Gysllene M. C. , Fontenele Andrea M. M. , Carneiro Erika Cristina R. L. , Nogueira Iara Antonia L. , Cavalcante Tamires B. , Vale André A. M. , Monteiro Sally Cristina M. , Salgado Filho Natalino
Published: June 2021

Background. The Neutrophil-to-Lymphocyte Ratio (NLR) and the Platelet-to-Lymphocyte Ratio (PLR) are inflammatory biomarkers for several diseases, such as cancer and cardiovascular morbidities; however, there are currently few studies on kidney diseases. We aimed to evaluate nondialysis patients and determine the association of NLR and PLR with inflammation in these patients. Methods. A prospective cross-sectional study was conducted with 85 patients at different stages of chronic kidney disease (CKD), treated at the Kidney Disease Prevention Center of the University Hospital of the Federal University of Maranhão. This study included adult nondialysis patients diagnosed with CKD. The participants’ blood samples were collected for a high-sensitivity C-reactive protein (hs-CRP) test and blood count. They were divided into two groups according to the presence or absence of inflammation based on the hs-CRP value (<0.5 mg/dL). NLR and PLR were calculated based on the absolute number of neutrophils, lymphocytes, and platelets and were compared between them and with hs-CRP. Statistical analysis was performed using the Stata software, with the Shapiro–Wilk, Mann–Whitney, Spearman’s Correlation, and receiver operating characteristic curve tests. This study was approved by the local ethics committee. Results. The participants were categorized into two groups: with inflammation (n = 64) and without inflammation (n = 21). The mean age was 61.43 ± 14.63 y. The NLR and PLR values were significantly different between the groups with and without inflammation (

p
=
0.045

and

p
=
0.004

, respectively). However, only PLR showed a significant positive correlation with hs-CRP (

p
=
0.015

). The best cutoff point for NLR to detect inflammation was 1.98, with 76.19% sensitivity and 48.44% specificity. For PLR, it was 116.07, with 85.71% sensitivity and 51.56% specificity. There was no significant difference between the area under the NLR and PLR curve (0.71 vs. 0.64;

p
=
0.186

) for this population. Conclusions. This study showed that PLR was positively correlated with hs-CRP in nondialysis CKD patients and can be used to identify inflammation in this population.
Brooke–Spiegler Syndrome: Familial Cylindromatosis, a Rare Variant of a Rare Familial Syndrome
Authors: Patel Harsh , Naber William , Cusick Austin , Oser Craig
Published: June 2021

Brooke–Spiegler Syndrome (BSS) is a rare autosomal dominant familial disorder resulting in dermatologic neoplasms of copious nodular appendages. Here, we report a case of Familial Cylindromatosis (FC), a subtype of BSS, in a patient with the largest cylindroma of 7.4 × 5.6 × 3.8 cm on the scalp. The patient had undiagnosed cylindromas growing for 36 years at presentation; however, he did not seek out healthcare evaluation. Excision and pathologic investigation of three large masses from different body sites determined a shared phenotype of cylindromas. Subsequent evaluation of the patient's son separately, after primary patient excision, confirmed cylindroma development as well. The pathologic evidence of cylindromas in the patient with a new history of family incidence confirmed the diagnosis of the FC variant of BSS.
Investigation on the Influence of Temperature and Confining Pressure on the Hydraulic Conductivity of the Integrated and Fractured Jurassic Conglomerates
Authors: Zhang Dingyang , Sui Wanghua , Liu Jiawei
Published: June 2021

This paper presents an experimental investigation on the properties of hydraulic conductivity and permeability of conglomerates under different temperatures and confining pressures with integrated samples and samples with shear failure. Constant head tests were carried out in a temperature-controlled triaxial cell with samples obtained from the Zhuxianzhuang Coal Mine. Five levels of temperatures (10°C, 20°C, 28°C, 35°C, and 50°C) and three levels of confining pressures (3 MPa, 5 MPa, and 7 MPa) were chosen for the tests. The results show that there is a negative relationship between hydraulic conductivity and confining pressure with both original and shear failure samples. An inflection point of 35°C is found in the relationship between the flow rate and temperature. However, with increasing temperature conditions, hydraulic conductivity first increases and then decreases at 50°C with the intact sample, while hydraulic conductivity first decreases from 20°C and then increases with the shear failure sample. Finally, nonlinear regression equations of hydraulic conductivity and temperature were obtained under different confining pressures.
Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review
Authors: Ahmed Naseer , Abbasi Maria Shakoor , Zuberi Filza , Qamar Warisha , Halim Mohamad Syahrizal Bin , Maqsood Afsheen , Alam Mohammad Khursheed
Published: June 2021

Objective. The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry. Materials and Methods. Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty‐two full‐text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted. Results. The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty‐two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics. Conclusion. The included studies describe that AI is a reliable tool to make dental care smooth, better, time‐saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state‐of‐the‐art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.
Open Data Release and Privacy Concerns: Complexity in Mitigating Vulnerability with Controlled Perturbation
Authors: Alam Shah Imran , Khan Ihtiram Raza , Hassan Syed Imtiyaz , Siddiqui Farheen , Alam M. Afshar , Mahto Anil Kumar
Published: June 2021

The benefits of open data were realised worldwide since the past decades, and the efforts to move more data under the license of open data intensified. There was a steep rise of open data in government repositories. In our study, we point out that privacy is one of the consistent and leading barriers among others. Strong privacy laws restrict data owners from opening the data freely. In this paper, we attempted to study the applied solutions and to the best of our knowledge, we found that anonymity-preserving algorithms did a substantial job to protect privacy in the release of the structured microdata. Such anonymity-preserving algorithms argue and compete in objectivethat not only could the released anonymized data preserve privacy but also the anonymized data preserve the required level of quality. K-anonymity algorithm was the foundation of many of its successor algorithms of all privacy-preserving algorithms. l-diversity claims to add another dimension of privacy protection. Both these algorithms used together are known to provide a good balance between privacy and quality control of the dataset as a whole entity. In this research, we have used the K-anonymity algorithm and compared the results with the addon of l-diversity. We discussed the gap and reported the benefits and loss with various combinations of K and l values, taken in combination with released data quality from an analyst’s perspective. We first used dummy fictitious data to explain the general expectations and then concluded the contrast in the findings with the real data from the food technology domain. The work contradicts the general assumptions with a specific set of evaluation parameters for data quality assessment. Additionally, it is intended to argue in favour of pushing for research contributions in the field of anonymity preservation and intensify the effort for major trends of research, considering its importance and potential to benefit people.
[Retracted] Nomogram for Predicting Deep Venous Thrombosis in Lower Extremity Fractures
Authors: Lin Ze , Mi Bobin , Liu Xuehan , Panayi Adriana C. , Xiong Yuan , Xue Hang , Zhou Wu , Cao Faqi , Liu Jing , Hu Liangcong , Hu Yiqiang , Chen Lang , Yan Chenchen , Xie Xudong , Guo Junfei , Hou Zhiyong , Sun Yun , Zhang Yingze , Hu Yu , Liu Guohui
Published: June 2021

Deep venous thrombosis (DVT) is a common complication in patients with lower extremity fractures, causing delays in recovery short‐term and possible impacts on quality of life long‐term. Early prediction and prevention of thrombosis can effectively reduce patient pain while improving outcomes. Although research on the risk factors for thrombosis is prevalent, there is a stark lack of clinical predictive models for DVT occurrence specifically in patients with lower limb fractures. In this study, we aim to propose a new thrombus prediction model for lower extremity fracture patients. Data from 3300 patients with lower limb fractures were collected from Wuhan Union Hospital and Hebei Third Hospital, China. Patients who met our inclusion criteria were divided into a thrombosis and a nonthrombosis group. A multivariate logistic regression analysis was carried out to identify predictors with obvious effects, and the corresponding formulas were used to establish the model. Model performance was evaluated using a discrimination and correction curve. 2662 patients were included in the regression analysis, with 1666 in the thrombosis group and 996 in the nonthrombosis group. Predictive factors included age, Body Mass Index (BMI), fracture‐fixation types, energy of impact at the time of injury, blood transfusion during hospitalization, and use of anticoagulant drugs. The discriminative ability of the model was verified using the C‐statistic (0.676). For the convenience of clinical use, a score table and nomogram were compiled. Data from two centers were used to establish a novel thrombus prediction model specific for patients with lower limb fractures, with verified predictive ability.
A Sparse Deep Transfer Learning Model and Its Application for Smart Agriculture
Authors: Chen Zhikui , Zhang Xu , Chen Shi , Zhong Fangming
Published: June 2021

The introduction of deep transfer learning (DTL) further reduces the requirement of data and expert knowledge in various uses of applications, helping DNN‐based models effectively reuse information. However, it often transfers all parameters from the source network that might be useful to the task. The redundant trainable parameters restrict DTL in low‐computing‐power devices and edge computing, while small effective networks with fewer parameters have difficulty transferring knowledge due to structural differences in design. For the challenge of how to transfer a simplified model from a complex network, in this paper, an algorithm is proposed to realize a sparse DTL, which only transfers and retains the most necessary structure to reduce the parameters of the final model. Sparse transfer hypothesis is introduced, in which a compressing strategy is designed to construct deep sparse networks that distill useful information in the auxiliary domain, improving the transfer efficiency. The proposed method is evaluated on representative datasets and applied for smart agriculture to train deep identification models that can effectively detect new pests using few data samples.
[Retracted] Oral English Development of EFL Learners from the Perspective of Complexity Dynamic Theory
Authors: Dou Qiang , Li Guohua , Tang Yuan
Published: June 2021

With the development of economic globalization and cultural integration, the learning of a second language has become increasingly important for economic, political, and cultural exchanges in the world today. Complex dynamic system theory is an important research theory of foreign language learning methods for nonnative speakers. However, the research and application of the complex dynamic system theory in oral foreign language learning of English as a Foreign Language (EFL) learners are not prominent. The purpose of this paper is to explore the learning situation of oral English of EFL learners from the perspective of the complex dynamic system theory and provide some new learning methods and suggestions for EFL learners’ oral English learning based on the research of complex dynamic system theory. First, this article discusses and analyzes the current situation of oral English learning of EFL learners through literature research and a questionnaire survey. Then, based on the related research on the theory of complex dynamic systems, this article proposes countermeasures and learning method recommendations for the problems existing in the current oral English learning of EFL learners. After that, this paper sets up a controlled test of oral English learning through the learning method formulated by the complex dynamic system theory and verifies the learning effect of the oral English learning method proposed in this paper according to the mathematical theory research method of the complex dynamic system. Finally, this article discusses the reliability of the experimental research conclusions based on the error analysis and confidence level estimation of the experimental results. The research results show shows that there is 95% confidence that the second language learning method proposed in this paper under the perspective of the complex dynamic system theory has a positive effect on the oral English learning of EFL learners.