bluuebunny/crossref_metadata_2025 huggingface dataset:
Case–control study to estimate odds of death within 28 days of positive test for SARS-CoV-2 prior to vaccination for residents of long-term care facilities in England, 2020–2021
Authors: Paranthaman Karthik , Allen Hester , Chudasama Dimple , Verlander Neville Q , Sedgwick James
Published: November 2021

Background

Persons living in long-term care facilities (LTCFs) are presumed to be at higher risk of adverse outcomes from SARS-CoV-2 infection due to increasing age and frailty, but the magnitude of increased risk is not well quantified.

Methods

After linking demographic and mortality data for cases with confirmed SARS-CoV-2 infection between March 2020 and January 2021 in England, a random sample of 6000 persons who died and 36 000 who did not die within 28 days of a positive test was obtained from the dataset of 3 020 800 patients. Based on an address-matching process, the residence type of each case was categorised into one of private home and residential or nursing LTCF. Univariable and multivariable logistic regression analysis was conducted.

Results

Multivariable analysis showed that an interaction effect between age and residence type determined the outcome. Compared with a 60-year-old person not living in LTCF, the adjusted OR (aOR) for same-aged persons living in residential and nursing LTCFs was 1.77 (95% CI 1.21 to 2.6, p=0.0017) and 3.95 (95% CI 2.77 to 5.64, p<0.0001), respectively. At 90 years of age, aORs were 0.87 (95% CI 0.72 to 1.06, p=0.21) and 0.74 (95% CI 0.61 to 0.9, p=0.001), respectively. The model had an overall accuracy of 94.2% (94.2%) when applied to the full dataset of 2 978 800 patients.

Conclusion

This study found that residents of LTCFs in England had higher odds of death up to 80 years of age. Beyond 80 years, there was no difference in the odds of death for LTCF residents compared with those in the wider community.
Prevalence and correlates of REM sleep behaviour disorder in patients with major depressive disorder: a two-phase study
Authors: Wang Jing , Chau Steven W H , Lam Siu Ping , Liu Yaping , Zhang Jihui , Chan Ngan Yin , Cheung Maxine M S , Yu Mandy Wai Man , Tsang Jessie C T , Chan Joey W Y , Huang Bei , Li Shirley X , Mok Vincent , Wing Yun Kwok
Published: November 2021

Objective

To investigate the prevalence and clinical correlates of video polysomnography (vPSG)-confirmed rapid eye movement sleep behaviour disorder (RBD) in patients with major depressive disorder (MDD).

Methods

This is a clinic-based two-phase epidemiological study. In phase 1, patients with MDD were screened by a validated questionnaire, RBD Questionnaire-Hong Kong (RBDQ-HK). In phase 2, a subsample of both the screen-positive (RBDQ-HK >20) and screen–negative patients with MDD underwent further clinical and sleep assessment (vPSG) to confirm the diagnosis of RBD (MDD+RBD). Poststratification weighting method was used to estimate the prevalence of MDD+RBD. The total likelihood ratio and the probability of prodromal Parkinson’s disease (PD) were calculated from prodromal markers and risk factors, as per the Movement Disorder Society research criteria.

Results

A total of 455 patients with MDD were screened (median age (IQR)=52.66 (15.35) years, 77.58% woman, 43.74% positive). Eighty-one patients underwent vPSG and 12 of them were confirmed MDD+RBD. The prevalence of MDD+RBD was estimated to be 8.77% (95% CI: 4.33% to 16.93%), with possibly male predominance. MDD+RBD were associated with colour vision and olfaction deficit and a higher probability for prodromal PD.

Conclusions

Almost 9% of patients with MDD in the psychiatric outpatient clinic has vPSG-confirmed RBD. Comorbid MDD+RBD may represent a subtype of MDD with underlying α-synucleinopathy neurodegeneration. Systematic screening of RBD symptoms and necessity of vPSG confirmation should be highlighted for capturing this MDD subtype with a view to enhance personalised treatment and future neuroprotection to prevent neurodegeneration.
Retinal inter-eye difference and atrophy progression in multiple sclerosis diagnostics
Authors: Nij Bijvank Jenny , Uitdehaag B M J , Petzold Axel
Published: November 2021

Background

The visual system could be included in the diagnostic criteria for multiple sclerosis (MS) to demonstrate dissemination in space (DIS) and dissemination in time (DIT).

Objective

To investigate the diagnostic value of retinal asymmetry in MS.

Methods

A prospective, longitudinal study in individuals with MS (n=151) and healthy controls (n=27). Optical coherence tomography (OCT) was performed at 0, 2 and 4 years. Macular ganglion cell and inner plexiform layer (mGCIPL) thickness was determined as well as measures for retinal asymmetry: the inter-eye percentage difference (IEPD) and inter-eye absolute difference (IEAD). Receiver operator characteristics curves were plotted and the area under the curve (AUC) was calculated for group comparisons of the mGCIPL, IEPD, IEAD and atrophy rates.

Results

The diagnostic accuracy of both the IEPD and IEAD for differentiating bilateral and unilateral MS optic neuritis was high and stable over time (AUCs 0.88–0.93). The IEPD slightly outperformed the IEAD. Atrophy rates showed low discriminatory abilities for differentiating MS from controls (AUC 0.49–0.58).

Conclusion

The inter-eye differences of the mGCIPL have value for demonstration of DIS but in individuals with longstanding MS not for DIT. This may be considered as a test to detect DIS in future diagnostic criteria. Validation in a large prospective study in people presenting with symptoms suggestive of MS is required.
A novel fluorometric chemosensor based on imidazo[4,5-b]phenazine-2-thione for ultrasensitive detection and separation of Hg2+ in aqueous solution
Authors: Huang Qing , Li Qiao , Zhang Hai-Li , Zhu Wei , Qu Wen-Juan , Lin Qi , Yao Hong , Zhang You-Ming , Wei Tai-Bao
Published: November 2021

We synthesized and developed 1,3-dihydro-2H-imidazo[4,5-b]phenazine-2-thione as a ratiometric chemosensor for Hg2+ recognition in a DMSO/H2O (v/v = 9:1) binary solution. We rationally introduced the phenazine imidazole group as the fluorophore and the thione moiety as the recognition site to bind Hg2+. Interestingly, the chemosensor showed an ultrasensitive response to Hg2+, and the lowest limit of detection was 0.167 nM. In addition, it can also separate Hg2+ from aqueous solutions with excellent ingestion capacity, with an adsorption ratio of up to 96%. Furthermore, ion test strips based on chemosensors were fabricated for convenient and efficient detection of Hg2+.
Seasonal changes in the abundance and activity of bacterial and fungal denitrifying communities associated with different compost amendments
Authors: Novinscak Amy , Goyer Claudia , Wilson Carolyn , Zebarth Bernie J. , Burton David L. , Chantigny Martin H. , Filion Martin
Published: November 2021

Composts can be efficient organic amendments in potato culture as they can supply carbon and nutrients to the soil. However, more information is required on the effects of composts on denitrification and nitrous oxide emissions (N2O) and emission-producing denitrifying communities. The effects of three compost amendments (municipal source separated organic waste compost (SSOC), forestry waste mixed with poultry manure compost (FPMC), and forestry residues compost (FRC)) on fungal and bacterial denitrifying communities and activity was examined in an agricultural field cropped to potatoes during the fall, spring, and summer seasons. The denitrification enzyme activity (DEA), N2O emissions, and respiration were measured in parallel. N2O emission rates were greater in FRC-amended soils in the fall and summer, whereas soil respiration was highest in the SSOC-amended soil in the fall. A large number of nirK denitrifying fungal transcripts were detected in the fall, coinciding with compost application, while the greatest nirK bacterial transcripts were measured in the summer when plants were actively growing. Denitrifying community and transcript levels were poor predictors of DEA, N2O emissions, or respiration rates in compost-amended soil. Overall, the sampling date was driving the population and activity levels of the three denitrifying communities under study.
On the Gaussian traveling wave solution to a special kind of Schrödinger equation with logarithmic nonlinearity
Authors: Kai Yue , Yin Zhixiang
Published: November 2021

We present the complete analysis of traveling wave solutions to a special kind of nonlinear Schrödinger equation with logarithmic nonlinearity, and obtain all traveling wave solutions. As a result, we prove this equation does not have any Gaussian traveling wave solution. However, by modifying this equation into another form, we can actually obtain a Gaussian traveling wave solution, which verifies the conclusion that existing Gaussian traveling solution requires two restrictions: (1) balance between the dispersion terms and logarithmic nonlinearity; and (2) balance of the parameters.
FRACTAL SURFACE RECOVERY AND SELF-HEALING CONTRIBUTED TO SUSTAINABLE SUPERHYDROPHOBICITY: A REVIEW
Authors: PENG YUNFEI , MA ZHIHANG , WANG XIAO , LI JUNRU , LI XINLIN , ZHANG CHUANWEI , HE TIAN , LI GUOQIANG , ZHANG PENGFEI
Published: November 2021

The concept of superhydrophobicity has been widely used after years of theoretical and experimental exploration. Researchers have obtained materials with excellent surface superhydrophobicity for numerous areas (e.g. textiles, paints, and coatings industries), through different design and synthesis methods using low surface energy components (LSECs) and micro/nanohierarchy composite structures. However, the durability of superhydrophobic material surfaces has gradually become a prominent obstacle to restricting applications. In this paper, advances in improving the durability of superhydrophobic surfaces in the past decade are reviewed, covering different schemes for recovering fractal surfaces based on the LSECs and micro/nanocomposite structures. It also presents a balanced review on wet chemical methods, chemical vapor deposition (CVD), layer-by-layer (LbL), microarc oxidation (MAO), and self-healing of the fractal surfaces, with the aim at developing sustainable superhydrophobicity. In addition, it innovatively summarized the research on the synthesis of self-healing superhydrophobic materials by machine learning methods. By the end it discusses perspectives on future development in this emerging research area.
Irreversibility and Biased Ensembles in Active Matter: Insights from Stochastic Thermodynamics
Authors: Fodor Étienne , Jack Robert L. , Cates Michael E.
Published: November 2021

Active systems evade the rules of equilibrium thermodynamics by constantly dissipating energy at the level of their microscopic components. This energy flux stems from the conversion of a fuel, present in the environment, into sustained individual motion. It can lead to collective effects without any equilibrium equivalent, some of which can be rationalized by using equilibrium tools to recapitulate nonequilibrium transitions. An important challenge is then to delineate systematically to what extent the character of these active transitions is genuinely distinct from equilibrium analogs. We review recent works that use stochastic thermodynamics tools to identify, for active systems, a measure of irreversibility comprising a coarse-grained or informatic entropy production. We describe how this relates to the underlying energy dissipation or thermodynamic entropy production, and how it is influenced by collective behavior. Then, we review the possibility of constructing thermodynamic ensembles out of equilibrium, where trajectories are biased toward atypical values of nonequilibrium observables. We show that this is a generic route to discovering unexpected phase transitions in active matter systems, which can also inform their design.
Multirobot Control Strategies for Collective Transport
Authors: Farivarnejad Hamed , Berman Spring
Published: November 2021

One potential application of multirobot systems is collective transport, a task in which multiple robots collaboratively move a payload that is too large or heavy for a single robot. In this review, we highlight a variety of control strategies for collective transport that have been developed over the past three decades. We characterize the problem scenarios that have been addressed in terms of the control objective, the robot platform and its interaction with the payload, and the robots’ capabilities and information about the payload and environment. We categorize the control strategies according to whether their sensing, computation, and communication functions are performed by a centralized supervisor or specialized robot or autonomously by the robots. We provide an overview of progress toward control strategies that can be implemented on robots with expanded autonomous functionality in uncertain environments using limited information, and we suggest directions for future work on developing such controllers.
Secure Networked Control Systems
Authors: Sandberg Henrik , Gupta Vijay , Johansson Karl H.
Published: November 2021

Cyber-vulnerabilities are being exploited in a growing number of control systems. As many of these systems form the backbone of critical infrastructure and are becoming more automated and interconnected, it is of the utmost importance to develop methods that allow system designers and operators to do risk analysis and develop mitigation strategies. Over the last decade, great advances have been made in the control systems community to better understand cyber-threats and their potential impact. This article provides an overview of recent literature on secure networked control systems. Motivated by recent cyberattacks on the power grid, connected road vehicles, and process industries, a system model is introduced that covers many of the existing research studies on control system vulnerabilities. An attack space is introduced that illustrates how adversarial resources are allocated in some common attacks. The main part of the article describes three types of attacks: false data injection, replay, and denial-of-service attacks. Representative models and mathematical formulations of these attacks are given along with some proposed mitigation strategies. The focus is on linear discrete-time plant models, but various extensions are presented in the final section, which also mentions some interesting research problems for future work.
The Science of Leadership: A Theoretical Model and Research Agenda
Authors: Carton Andrew M.
Published: November 2021

I review the empirical literature on leadership, focusing on papers published since 2010. To do so, I introduce a framework composed of two features: whether theories ( a) involve the study of leaders or leading (i.e., the person versus the process) and ( b) conceptualize leadership as a cause or a consequence (i.e., an independent versus dependent variable). This framework can enable future research to accumulate in a more programmatic fashion and help scholars determine where their own studies are located within the landscape of leadership research. I end the review by critically evaluating existing work, arguing that the most popular subcategory of leadership research—lumped conceptualizations of leading, in which scholars examine multiple leader behaviors within a single construct—has significant limitations and may need to be replaced by a greater focus on split conceptualizations of leading, wherein scholars isolate single leader behaviors.
Mitochondrial H+ Leak and Thermogenesis
Authors: Bertholet Ambre M. , Kirichok Yuriy
Published: November 2021

Mitochondria of all tissues convert various metabolic substrates into two forms of energy: ATP and heat. Historically, the primary focus of research in mitochondrial bioenergetics was on the mechanisms of ATP production, while mitochondrial thermogenesis received significantly less attention. Nevertheless, mitochondrial heat production is crucial for the maintenance of body temperature, regulation of the pace of metabolism, and prevention of oxidative damage to mitochondria and the cell. In addition, mitochondrial thermogenesis has gained significance as a pharmacological target for treating metabolic disorders. Mitochondria produce heat as the result of H+ leak across their inner membrane. This review provides a critical assessment of the current field of mitochondrial H+ leak and thermogenesis, with a focus on the molecular mechanisms involved in the function and regulation of uncoupling protein 1 and the ADP/ATP carrier, the two proteins that mediate mitochondrial H+ leak.
A Practical Guide to Family Studies with Lifetime Data
Authors: Scheike Thomas H. , Holst Klaus Kähler
Published: November 2021

Familial aggregation refers to the fact that a particular disease may be overrepresented in some families due to genetic or environmental factors. When studying such phenomena, it is clear that one important aspect is the age of onset of the disease in question, and in addition, the data will typically be right-censored. Therefore, one must apply lifetime data methods to quantify such dependence and to separate it into different sources using polygenic modeling. Another important point is that the occurrence of a particular disease can be prevented by death—that is, competing risks—and therefore, the familial aggregation should be studied in a model that allows for both death and the occurrence of the disease. We here demonstrate how polygenic modeling can be done for both survival data and competing risks data dealing with right-censoring. The competing risks modeling that we focus on is closely related to the liability threshold model.
Is There a Cap on Longevity? A Statistical Review
Authors: Belzile Léo R. , Davison Anthony C. , Gampe Jutta , Rootzén Holger , Zholud Dmitrii
Published: November 2021

There is sustained and widespread interest in understanding the limit, if there is any, to the human life span. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security systems. A central question is whether the endpoint of the underlying lifetime distribution is finite. Recent analyses of data on the oldest human lifetimes have led to competing claims about survival and to some controversy, due in part to incorrect statistical analysis. This article discusses the particularities of such data, outlines correct ways of handling them, and presents suitable models and methods for their analysis. We provide a critical assessment of some earlier work and illustrate the ideas through reanalysis of semisupercentenarian lifetime data. Our analysis suggests that remaining life length after age 109 is exponentially distributed and that any upper limit lies well beyond the highest lifetime yet reliably recorded. Lower limits to 95% confidence intervals for the human life span are about 130 years, and point estimates typically indicate no upper limit at all.
Endothelin receptor blockade blunts the pressor response to acute stress in men and women with obesity
Authors: Derella Cassandra C. , Blanks Anson M. , Wang Xiaoling , Tucker Matthew A. , Horsager Chase , Jeong Jin Hee , Rodriguez-Miguelez Paula , Looney Jacob , Thomas Jeffrey , Pollock David M. , Harris Ryan A.
Published: November 2021

Findings from our current translational investigation demonstrate that dual endothelin A/B receptor antagonism blunts the pressor response to acute stress in overweight/obese individuals. These results suggest that modulation of the endothelin system may represent a novel therapeutic target to reduce cardiovascular disease (CVD) risk by blunting the stress response in overweight/obese individuals.
Estimating exercise PaCO2 in patients with heart failure with preserved ejection fraction
Authors: Balmain Bryce N. , Tomlinson Andrew R. , MacNamara James P. , Sarma Satyam , Levine Benjamin D. , Hynan Linda S. , Babb Tony G.
Published: November 2021

[Formula: see text] provides a better estimate of [Formula: see text] than PJCO2 at peak exercise, and VD/VT[ET] provides a better estimate of VD/VT[art] than VD/VT[J] at peak exercise. Although we reported significant correlations, we did not find an identity between [Formula: see text] and estimates of [Formula: see text], nor did we find an identity between VD/VT[art] and estimates of VD/VT[art]. Thus, caution should be taken and estimates of [Formula: see text] and VD/VT should only be used if sampling arterial blood during CPET is not feasible.
Boundedness of Fractional Integral Operators on Hardy-Amalgam Spaces
Authors: Cheung Ka Luen , Ho Kwok-Pun , Yee Tat-Leung
Published: November 2021

We establish the boundedness of the fractional integral operators on the Hardy-amalgam spaces.
Computer-Aided Diagnosis of Children with Cerebral Palsy under Deep Learning Convolutional Neural Network Image Segmentation Model Combined with Three-Dimensional Cranial Magnetic Resonance Imaging
Authors: Yang Rui , Zuo Haoran , Han Shusheng , Zhang Xiaoping , Zhang Qian
Published: November 2021

In this paper, we analyzed the application value and effect of deep learn-based image segmentation model of convolutional neural network (CNN) algorithm combined with 3D brain magnetic resonance imaging (MRI) in diagnosis of cerebral palsy in children. 3D brain model was segmented based on CNN algorithm to obtain the segmented MRI images of brain tissue, and the validity was verified. Then, 70 children with cerebral palsy were rolled into the observation group (n = 35), which received MRI for diagnosis after segmentation of brain tissue, and control group (n = 35), which were diagnosed by computed tomography (CT). The diagnosis results of the two groups were compared. The validity experiment verified that the image segmentation method based on CNN algorithm can obtain effective style graphics. In clinical trials, the diagnostic accuracy of 88.6% in the observation group was evidently superior to that of 80% in the control group (

P
<
0.05

). In the observation group, one patient was diagnosed as normal, four patients had white matter lesions, 17 patients had corpus callosum lesions, and five patients had basal ganglia softening foci. In the control group, two patients were diagnosed as normal, two patients had white matter lesions, 19 patients had corpus callosum lesions, and four patients had basal ganglia softening foci. No notable difference was found between the two groups (

P
>
0.05

). According to the research results, in the diagnosis of cerebral palsy in children, the image segmentation of brain 3D model based on CNN to obtain the MRI image of segmented brain tissue can effectively improve the detection accuracy. Moreover, the specific symptoms can be diagnosed clearly. It can provide the corresponding diagnostic basis for clinical diagnosis and treatment and was worthy of clinical promotion.
An Adaptive Variational Mode Decomposition Technique with Differential Evolution Algorithm and Its Application Analysis
Authors: Wang Yuanxin
Published: November 2021

Variational mode decomposition is an adaptive nonrecursive signal decomposition and time‐frequency distribution estimation method. The improper selection of the decomposition number will cause under decomposition or over decomposition, and the improper selection of the penalty factor will affect the bandwidth of modal components, so it is very necessary to look for the optimal parameter combination of the decomposition number and the penalty factor of variational mode decomposition. Hence, differential evolution algorithm is used to look for the optimization combination of the decomposition number and the penalty factor of variational mode decomposition because differential evolution algorithm has a good ability at global searching. The method is called adaptive variational mode decomposition technique with differential evolution algorithm. Application analysis and discussion of the adaptive variational mode decomposition technique with differential evolution algorithm are employed by combining with the experiment. The conclusions of the experiment are that the decomposition performance of the adaptive variational mode decomposition technique with differential evolution algorithm is better than that of variational mode decomposition.
Research on the Training Model of E‐Commerce Professionals Based on Big Data Analysis
Authors: Lin Chun-Yi , Xi Zhao , Gao Chaomin , Tsai Sang-Bing
Published: November 2021

In a new era of booming information technology, E‐commerce has become an important developing country in China, and parents and students have gradually welcomed this profession. In the information age, how to improve the quality of training in professional higher education and then meet the employment needs of industries and enterprises has become a key issue for higher vocational education in China. This article mainly studies the E‐commerce professional talent training model based on identity inheritance. This article analyzes the current situation of E‐commerce talent training, combines pragmatism, and proposes strategies for training talented E‐commerce experts in underdeveloped western regions. The theory of business talent development has certain theoretical significance for guiding and promoting electronic trade and socioeconomic development. The research in this article shows that despite a large number of international trade graduates every year, the electronic trading group (70.1%) is still international trade, and 85.9% of companies still believe that there is a gap between transnational E‐commerce traders. In order to “effectively connect” the training of E‐commerce talents in higher vocational education and social needs, it is necessary to take the needs of industrial development as the driving force and market demand as the guidance and take practical measures to improve the school‐enterprise matching. The distance between talents ultimately promotes professional construction and talent training and achieves a win‐win situation for both schools and enterprises.
Asymptomatic COVID-19 as a Risk Factor of Diabetic Ketoacidosis and Mucormycosis: A Case Report and Review of the Literature
Authors: Torabiyan Soheila , Dalfardi Behnam , Sanjari Mojgan
Published: November 2021

Mucormycosis is a lethal and life-threatening fungal infection. Several cases describing the association of COVID-19 and mucormycosis have been reported. In this article, we report a 58-year-old female with a history of diabetes mellitus type 2 who presented by diabetic ketoacidosis, rhino-orbital mucormycosis, and COVID-19. The patient was treated with liposomal amphotericin B and debridement of necrotic tissue of the rhino-orbital area and paranasal sinuses. Unfortunately, she passed away a few days after orbital surgery. We also conducted a review of the literature and reported 3 other similar cases that suffered from mucormycosis in association with COVID-19 and diabetic ketoacidosis and discussed the importance of this association.
A Novel Vision‐Based PRPL Multistage Image Processing Algorithm for Autonomous Aerial Refueling
Authors: Wu Ling , Sun Yongrong , Zhao Kedong , Fu Xiyu
Published: November 2021

Autonomous aerial refueling (AAR) technology can increase the flight endurance of unmanned air vehicles (UAVs) effectively. Drogue detection and target tracking method are significant for probe‐drogue refueling system in the docking stage. This paper proposes a novel vision‐based multistage image processing algorithm of drogue detection and target tracking for AAR. This algorithm divides the whole task into four stages: preprocessor, recognizer, predictor, and locker (PRPL). The adaptive threshold segmentation (ATS) algorithm and support vector machine (SVM) classifier are utilized in preprocessor and recognizer for drogue detection. An improved kernelized correlation filter (IKCF) tracking algorithm and scale adaptive method by window position as well as image resolution adjusted are adopted in predictor and locker for target tracking in complex dynamic environments. Finally, the proposed PRPL multistage image processing strategy is tested using an autonomous aerial refueling testbed. The results indicate that the proposed algorithm achieves high precision, good reliability, and real‐time capability compared with conventional algorithms. The average processing time is within 11 ms in various environments, which can meet the requirement for drogue detection and tracking in AAR.
Upper and Lower Limb Motor Function Correlates with Ipsilesional Corticospinal Tract and Red Nucleus Structural Integrity in Chronic Stroke: A Cross-Sectional, ROI-Based MRI Study
Authors: Peters Denise M. , Fridriksson Julius , Richardson Jessica D. , Stewart Jill C. , Rorden Chris , Bonilha Leonardo , Middleton Addie , Fritz Stacy L.
Published: November 2021

Background. Structural integrity of the ipsilesional corticospinal tract (CST) is important for upper limb motor recovery after stroke. However, additional neuromechanisms associated with motor function poststroke are less well understood, especially regarding the lower limb. Objective. To investigate the neural basis of upper/lower limb motor deficits poststroke by correlating measures of motor function with diffusion tensor imaging-derived indices of white matter integrity (fractional anisotropy (FA), mean diffusivity (MD)) in primary and secondary motor tracts/structures. Methods. Forty-three individuals with chronic stroke (time poststroke,

64.4
±
58.8

months) underwent a comprehensive motor assessment and MRI scanning. Correlation and multiple regression analyses were performed to examine relationships between FA/MD in a priori motor tracts/structures and motor function. Results. FA in the ipsilesional CST and red nucleus (RN) was positively correlated with motor function of both the affected upper and lower limb (

r
=
0.36
‐
0.55

,

p
≤
0.01

), while only ipsilesional RN FA was associated with gait speed (

r
=
0.50

). Ipsilesional CST FA explained 37.3% of the variance in grip strength (

p
<
0.001

) and 31.5% of the variance in Arm Motricity Index (

p
=
0.004

). Measures of MD were not predictors of motor performance. Conclusions. Microstructural integrity of the ipsilesional CST is associated with both upper and lower limb motor function poststroke, but appears less important for gait speed. Integrity of the ipsilesional RN was also associated with motor performance, suggesting increased contributions from secondary motor areas may play a role in supporting chronic motor function and could become a target for interventions.
Comparison of Foamy Oil Behaviour between Shallow and Middepth Heavy Oil Reservoirs in the Orinoco Belt
Authors: Li Xingmin , Chen Changchun , Liu Zhangcong , Wu Yongbin , Shi Xiaoxing
Published: November 2021

Nowadays, extra heavy oil reservoirs in the Orinoco Heavy-Oil-Belt in Venezuela are exploited via cold production process, which present different production performance in well productivity and primary recovery factor. The purpose of this study is to investigate the causes for such differences with the aspect of foamy oil mechanism. Two typical oil samples were adopted from a shallow reservoir in western Junìn region and a middepth reservoir in eastern Carabobo region in the Belt, respectively. A depletion test was conducted using 1D sand-pack with a visualized microscopic flow observation installation for each of the oil samples under simulated reservoir conditions. The production performance, the foamy oil behaviour, and the oil and gas morphology were recorded in real time during the tests. The results indicated that the shallow heavy oil reservoir in the Belt presents a weaker foamy oil phenomenon when compared with the middepth one; its foamy oil behaviour lasts a shorter duration with a smaller scope, with bigger bubble size and less bubble density. The difference in foamy oil behaviour for those two types of heavy oil reservoir is caused by the difference in reservoir pressure, solution GOR, asphaltene content, etc. Cold production presents obvious features of three stages under the action of strong foamy oil displacement mechanism for the middepth heavy oil reservoir, which could achieve a more favourable production performance. In the contrary, no such obvious production characteristics for the shallow heavy oil reservoir are observed due to weaker foamy oil behaviour, and its primary recovery factor is 9.38 percent point lower than which of the middle heavy oil reservoirs.
Effects of Buzhong Yiqi Decoction Combined with THP Bladder Perfusion on Postoperative Efficacy in Patients with Bladder Cancer
Authors: Wang Yunfeng , Zhang Yan , Liu Zhongguo , Li Qiuying , Jin Huijing
Published: November 2021

Background. As a traditional Chinese medicine tonic, Buzhong Yiqi decoction has the effects of invigorating Qi and lifting Yang. In this study, the effects of Buzhong Yiqi Shenge decoction combined with THP bladder perfusion on postoperative efficacy in bladder cancer were investigated. Methods. A total of 70 cases of bladder cancer patients were divided into the experimental group and control group according to the random number table method, with 35 cases in each group. The control group was treated with THP bladder perfusion. The experimental group was treated with Buzhong Yiqi Shenge decoction on the basis of the control group. The number of urine white blood cells, VEGF level, the incidence of adverse reactions, and KPS score were compared between the two groups before and after treatment. Results. After 3 and 6 months of therapy, the KPS score of the experimental group increased significantly compared with the control group. However, after 12 months of treatment, there was no difference in KPS scores between the two groups. Moreover, there was no significant variation in serum VEGF between two groups after 3 months of treatment. However, Buzhong Yiqi decoction notably reduced the level of VEGF after 6 months and 12 months. After 3 months, the urine white blood cell count was lower in the experimental group than in the control group. After 6 and 12 months, there was no difference in urine white blood cell count between the two groups. Furthermore, a total of 14 patients in two groups had reoccurrence after one year. Our results showed that there was no significant difference in postoperative recurrence rate between the experimental group and the control group. The occurrence rates of frequent and urgent urination, nausea/loss, and abnormal urine routine of appetite in the experimental group were significantly lower than those in the control group. But there was no difference in the occurrence rate of low heat, hematuria between the experimental group and the control group. Conclusion. Buzhong Yiqi decoction combined with THP bladder perfusion has no advantage in the short-term recurrence rate of bladder cancer patients. However, Buzhong Yiqi decoction can alleviate the symptoms of adverse reactions and improve the quality of life of patients.
RF‐GANs: A Method to Synthesize Retinal Fundus Images Based on Generative Adversarial Network
Authors: Chen Yu , Long Jun , Guo Jifeng
Published: November 2021

Diabetic retinopathy (DR) is a diabetic complication affecting the eyes, which is the main cause of blindness in young and middle‐aged people. In order to speed up the diagnosis of DR, a mass of deep learning methods have been used for the detection of this disease, but they failed to attain excellent results due to unbalanced training data, i.e., the lack of DR fundus images. To address the problem of data imbalance, this paper proposes a method dubbed retinal fundus images generative adversarial networks (RF‐GANs), which is based on generative adversarial network, to synthesize retinal fundus images. RF‐GANs is composed of two generation models, RF‐GAN1 and RF‐GAN2. Firstly, RF‐GAN1 is employed to translate retinal fundus images from source domain (the domain of semantic segmentation datasets) to target domain (the domain of EyePACS dataset connected to Kaggle (EyePACS)). Then, we train the semantic segmentation models with the translated images, and employ the trained models to extract the structural and lesion masks (hereafter, we refer to it as Masks) of EyePACS. Finally, we employ RF‐GAN2 to synthesize retinal fundus images using the Masks and DR grading labels. This paper verifies the effectiveness of the method: RF‐GAN1 can narrow down the domain gap between different datasets to improve the performance of the segmentation models. RF‐GAN2 can synthesize realistic retinal fundus images. Adopting the synthesized images for data augmentation, the accuracy and quadratic weighted kappa of the state‐of‐the‐art DR grading model on the testing set of EyePACS increase by 1.53% and 1.70%, respectively.
Duck Interleukin-22: Identification and Expression Analysis in Riemerella anatipestifer Infection
Authors: Flores Rochelle A. , Cammayo Paula Leona T. , Nguyen Binh T. , Fernandez-Colorado Cherry P. , Kim Suk , Kim Woo H. , Min Wongi
Published: November 2021

Riemerella anatipestifer is one of the most devastating pathogens affecting the global duck farms. Infection is involved in secretion of proinflammatory cytokines, including interleukin- (IL-) 17A. During the immune response to infection, IL-22 and IL-17A are often produced concurrently and at high levels in inflamed tissues. Little is known about duck IL-22 (duIL-22) during R. anatipestifer infection. We describe the characterization of duIL-22 and its mRNA expression analysis in splenic lymphocytes and macrophages treated with heat-killed R. anatipestifer and in the spleens and livers of R. anatipestifer-infected ducks. Full-length cDNA of duIL-22 encoded 197 amino acids. The deduced amino acid sequence of duIL-22 shared a 30.4–40.5% similarity with piscine counterparts, 57.4–60.1% with mammalian homologs, and 93.4% similarity to the chicken. Duck IL-22 mRNA expression level was relatively high in the skin of normal ducks. It was increased in mitogen-stimulated splenic lymphocytes and in killed R. anatipestifer-activated splenic lymphocytes and macrophages. Compared with healthy ducks, IL-22 transcript expression was significantly upregulated in the livers and spleens on days 1 and 4 postinfection, but not on day 7. IL-17A was significantly increased in the spleens only on day 4 postinfection and in the livers at all time points. When splenic lymphocytes were stimulated with heat-killed R. anatipestifer, CD4+ cells predominantly produced IL-22 while IL-17A was expressed both by CD4+ and CD4- cells. These results suggested that IL-22 and IL-17A are likely expressed in different cell types during R. anatipestifer infection.
Economic Growth Prediction Algorithm of Coastal Area Based on Impulse Response Function
Authors: Rong-Shan Qiu , Ding Ding , Li-Min Han
Published: November 2021

In order to solve the problems of low accuracy and long prediction time of traditional economic growth prediction algorithms in coastal areas, an algorithm based on impulse response function was designed to analyze economic growth prediction in coastal areas. Crawler technology is used to capture the economic data of coastal areas and normalize the captured data. Based on the processed data, the impulse response function is used to analyze the relationship between different economic variables, so as to build the PSO-LSTM model, which is used to predict the economic growth trend of coastal areas. The experimental results show that, compared with the experimental comparison algorithm, the prediction accuracy of the algorithm designed in this paper is always above 97%, and the prediction time is always below 1 s, which has certain practical significance.
The Effect of Using Peer on Self-Care, Quality of Life, and Adherence in Elderly People with Coronary Artery Disease
Authors: Roshandel Mojtaba , Rakhshan Mahnaz , Najafi Kalyani Majid
Published: November 2021

Introduction. Coronary artery disease is one of the most common diseases and the cause of death among elderly people. Due to the chronic nature of this disease, regular follow-up, lifestyle changes, and adherence to recommendations can reduce the complications and improve the quality of life among elderly individuals. Given the importance of using educational methods that are based on the patient’s age and disease stage, the present study aimed to investigate the effect of using a peer group on self-care, adherence, and quality of life in elderly people. Method. This single-blind clinical trial was conducted on 30 old patients with coronary artery disease aged 60 years in Shiraz from March to June 2021. The patients were selected using simple random sampling and were then randomly assigned to the peer education and control groups (15 participants in each group) via permuted block randomization. The patients in the peer education group received the necessary education about medications, lifestyle, daily activities, self-care, and adherence through three educational clips by educated peer. The patients in the control group received routine education using two clips by the ward nurses. The levels of self-care, adherence, and quality of life were assessed in the intervention and control groups before and one month after the intervention. Data analysis was performed by SPSS 20 software using an independent t-test, paired sample t-test, and chi-square test.

P
<
0.05

was considered statistically significant. Findings. The results showed no statistically significant difference between the two groups with respect to the mean scores of self-care and quality of life before the intervention (

P
>
0.05

). Following the educational intervention, however, a statistically significant difference was found between the two groups concerning the mean scores of self-care and adherence (

P
<
0.05

). Moreover, the mean differences between the two groups regarding the three variables were statistically significant before and after the intervention (

P
<
0.05

). Conclusion. Education based on multimedia clips by peer was effective in increasing the mean scores of self-care, adherence, and quality of life among the elderly people with coronary artery disease. Given the low cost, high effectiveness, and decrease in the nurses’ workload, this method is recommended to be used alongside other methods in order to educate elderly individuals suffering from coronary artery disease.
Classification of Date Fruits into Genetic Varieties Using Image Analysis
Authors: Koklu Murat , Kursun Ramazan , Taspinar Yavuz Selim , Cinar Ilkay
Published: November 2021

A great number of fruits are grown around the world, each of which has various types. The factors that determine the type of fruit are the external appearance features such as color, length, diameter, and shape. The external appearance of the fruits is a major determinant of the fruit type. Determining the variety of fruits by looking at their external appearance may necessitate expertise, which is time-consuming and requires great effort. The aim of this study is to classify the types of date fruit, that are, Barhee, Deglet Nour, Sukkary, Rotab Mozafati, Ruthana, Safawi, and Sagai by using three different machine learning methods. In accordance with this purpose, 898 images of seven different date fruit types were obtained via the computer vision system (CVS). Through image processing techniques, a total of 34 features, including morphological features, shape, and color, were extracted from these images. First, models were developed by using the logistic regression (LR) and artificial neural network (ANN) methods, which are among the machine learning methods. Performance results achieved with these methods are 91.0% and 92.2%, respectively. Then, with the stacking model created by combining these models, the performance result was increased to 92.8%. It has been concluded that machine learning methods can be applied successfully for the classification of date fruit types.
Antispasmodic Potential of Medicinal Plants: A Comprehensive Review
Authors: Rauf Abdur , Akram Muhammad , Semwal Prabhakar , Mujawah Adil A. H. , Muhammad Naveed , Riaz Zerfishan , Munir Naveed , Piotrovsky Dmitry , Vdovina Irina , Bouyahya Abdelhakim , Adetunji Charles Oluwaseun , Shariati Mohammad Ali , Almarhoon Zainab M. , Mabkhot Yahia N. , Khan Haroon
Published: November 2021

Numerous medicinal plants have been utilized for the treatment of different types of diseases and disorders including gastrointestinal (GI) diseases. GI diseases are the most common complaints that normally affects the largest proportion of children and adolescents with overlapping clinical manifestation in diagnosis and medical needs. Drugs with antispasmodic effects are normally applied for the symptomatic treatment of contraction and cramping of smooth muscles in gastrointestinal diseases as well as in other critical clinical situations. In alternative system of medicines, the antispasmodic herbs played a significant role in the cure of GI diseases. These medicinal plants and their herbal products are used from generation to generation because of multiple nutritional and therapeutic benefits. The multiple uses might be attributed to the presence on biologically active chemical constitutes. The main aim of this review is to focus on the medicinal potential of plants possessing antispasmodic activities with their proposed mechanism of action. Several databases such as Google Scholar, Cochrane database, Scopus, and PubMed were used to search the relevant literature regarding “plants with antispasmodic activities.” This present study highlights the updated and quantified information on several medicinal plants with antispasmodic activity like Zanthoxylum armatum, Matricaria chamomilla, Foeniculum vulgare, Pycnocycla spinosa, Atropa belladonna, Lavandula angustifolia, Mentha pulegium, Glycyrrhiza ularensis, Anethum graveolens, and Origanum majorana. Moreover, recent studies on other medicinal plant species also have been included in this review article. Additionally, the study also revealed that the active compounds of all these plants possess significant spasmolytic effect which is safest, efficacious, and cost effective as compared to the available synthetic drugs.
Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model
Authors: Cai Yubin , Ma Xin , Wu Wenqing , Deng Yanqiao
Published: November 2021

Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonhomogeneous grey model with fractional-order accumulation is introduced along with discussions between other existing grey models. A random search optimization scheme is then introduced to optimize the nonlinear parameter of the grey model. And the complete forecasting scheme is built based on the rolling mechanism. The case study is executed based on the updated data set of natural gas consumption of the power sector in the United States. The comparison of results is analyzed from different step sizes, different grey system models, and benchmark models. They all show that the proposed method has significant advantages over the other existing methods, which indicates the proposed method has high potential in short-term forecasting for natural gas consumption of the power sector in United States.