bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of Highly Efficient Platinum Catalysts for Hydroalkoxylation and Hydroamination of Unactivated Alkene
Authors: Zhou Yali , Xu Xingjun , Sun Hongwei , Tao Guanyu , Chang Xiaoyong , Xing Xiangyou , Chen Bo , Xu Chen 
Published: October 2020

Abstract
Hydrofunctionalization, the direct additon of an X–H (e.g., X = O, N) bond across an alkene, is a desirable strategy to make heterocycles that are important structural components of naturally occurring molecules. Described here is the design and discovery of “donor–acceptor”-type platinum catalysts that are highly effective in both hydroalkoxylation and hydroamination of unactivated alkenes over a broad range of substrates under mild conditions. A number of alkene substitution patterns were accommodated, including tri-substituted, 1,1-disubstituted, (E)-disubstituted, (Z)-disubstituted and even mono-substituted double bonds. Detailed mechanistic investigations suggest a plausible pathway that includes an unexpected dissociation/re-association of the electron-deficient ligand to form an alkene-bound “donor–acceptor”-type intermediate. These mechanistic studies help understand the origins of the high reactivity exhibited by the catalytic system, and provide a foundation for the rational design of chiral catalysts towards asymmetric hydrofunctionalization reactions.
Incipient Gear Fault Detection Using Adaptive Impulsive Wavelet Filter Based on Spectral Negentropy
Authors: Gao Mang , Yu Gang , Li Ning Chang 
Published: October 2020

Abstract
Adaptive wavelet filtering is a very important fault feature extraction method in the domain of condition monitoring, however, due to the time-consuming computation and difficulty of choosing criteria used to represent incipient faults, the engineering applications are limited to some extent. In order to detect the incipient gear faults with a fast speed, a new criterion is proposed to optimize the parameters of modified impulsive wavelet for constructing an optimal wavelet filter to detect impulsive gear faults. Firstly, a new criterion based on the spectral negentropy is proposed. Then, a novel searching strategy is applied to optimize the parameters of the impulsive wavelet based on the new criterion. Finally, envelope spectral analysis is applied to find the incipient fault characteristic frequency. Both the simulation and experimental validation have shown the superiority of the proposed approach
Conflicting objectives of energy development and water security in Africa
Authors: Pappis Ioannis , Sridha Vignesh , Howells Mark , Medarac Hrvoje , Kougias Ioannis , Sánchez Rocío , Shivakumar Abhishek , Usher Will 
Published: October 2020

Abstract
Africa's economic and population growth prospects are likely to increase energy and water demands. This quantitative study shows that pathways towards decarbonization of the energy sector in Africa may lead to higher water withdrawals and consumption than expected. By 2065, investments in low-carbon energy infrastructure increase annual withdrawals from 1% (2.0oC) to 2% (1.5oC) of total renewable water resources compared to 3% in the baseline scenario, despite lower final energy demands in the mitigation scenarios. Water consumption, in comparison to the baseline, increases by 282% (2.0oC) and 300% (1.5oC) by 2065, due to the high water-intensity of the low-carbon energy system. To meet the 1.5oC pathway, the energy sector requires higher water consumption overall and per unit of energy than other scenarios. These findings demonstrate the crucial role of integrated energy planning and water resources management if Africa is to achieve climate-compatible growth.
The influence of peer support worker integration on co-production and co-creation in public mental health and addiction services: Protocol for a scoping review
Authors: Aakerblom Kristina Bakke , Ness Ottar 
Published: October 2020

Abstract
An increasing proportion of countries engage peer support workers (PSW) in their public mental health and addiction services. How PSW are integrated in the services and participate in co-production and co-creation processes will influence both the content and quality of services for service-users related to effectiveness, and the services ability to innovation and change. However, little is known about how PSW contribute in, and to, co-production and co-creation processes in the services, and the described outcomes of such processes. Knowledge from existing research literature about the types, objectives, conditions and outcomes of co-production and co-creation processes with PSW is key knowledge for understanding and developing these processes which in the next step will increase service user participation and ensure better adaptation of services to the target group.A scoping review are chosen to provide an overview of existing evidence base to address questions beyond those related to effectiveness and efficiency and can be useful for bringing together literature in disciplines with emerging evidence. This aim of this scoping review is to achieve an overview of the research status of co-production and co-creation related to or involving PSW in the public mental health and addiction field of studies. The search of the studies will be between August 31 to December 15, 2020. The studies reviewed will be the ones that provide a description of how PSW engage in or contribute in these public services, particularly in collaborative processes as co-production and co-creation in the services. All studies describing PSW roles and activities that PSW might have within the public mental health and addiction services and across organizational or institutional boundaries will be included. Intended database sources for the review are Medline, PsycINFO, Embase, Oria, WorldCat, Google Scholar, Scopus, Academic Search Elite, Cinahl. This scoping review explore how the integration of peer support in public mental health and addiction services influences forms of collaboration in these services, described in the literature both through the process of co-production and co-creation. Research question for this scoping review is: How do peer support workers integration influence co-production and co-creation in public mental health and addiction services and what are the described outcomes?
Electrolyte and renal disorders in patients with newly diagnosed glioblastoma
Authors: Pierscianek Daniela , Oppong Marvin Darkwah , Ahmadipour Yahya , Rauschenbach Laurèl , Michel Anna , Kebir Sied , Dammann Philipp , Wrede Karsten H. , Glas Martin , Hense Jörg , Pöttgen Christoph , Sure Ulrich , Jabbarli Ramazan 
Published: October 2020

Abstract
BackgroundElectrolyte disturbances and altered renal function have been linked to the prognosis of critically ill patients and recently also of cancer patients. Little is known about the prevalence and prognostic impact of electrolyte and renal disorders in patients with glioblastoma (GBM), the most frequent malignant primary brain tumor. This study aimed to assess electrolyte and renal disorders in GBM patients and evaluate their effect on patients’ outcome.MethodsPatients treated for newly diagnosed GBM between 2005 and 2018 were included. Electrolytes and renal function parameters were assessed preoperatively. Medical records of patients were retrospectively reviewed for demographic and clinical parameters, as well as patients’ survival.ResultsElectrolyte and renal disorders at admission were present in 275 (30.6%) and 544 (60.4%) of 900 GBM patients respectively and were more common in patients with higher age, previous comorbidities and poor initial clinical performance status. In univariate analysis and Kaplan-Meier survival plots, presence of hyponatremia, hypochloremia, hypocalcemia, hyperuricemia and low glomerular filtration rate were associated with poorer survival. Multivariate analysis revealed hypochloremia as an independent prognostic factor for overall (p=0.004) and 1-year (p=0.021) survival. ConclusionsPreoperative electrolyte and renal disorders are common in GBM patients. Of them, only hypochloremia showed a strong association with GBM prognosis, independently of age, sex, extent of resection, clinical performance status, postoperative therapy, and molecular status. Further studies are needed to evaluate the impact of hypochloremia on GBM survival.
The Association Between Frailty and All-Cause Mortality in Community-Dwelling Older Individuals: An Umbrella Review
Authors: Ekram A R M Saifuddin , Woods Robyn , Britt Carlene , Espinoza Sara E , Ernst Michael E , Ryan Joanne 
Published: October 2020

Abstract
Background Frailty is associated with multiple adverse health outcomes, including mortality. Several methods have been used to characterize frailty, each based on different frailty scales. These include scales based on a phenotype, multidomain, and deficit accumulations. Several systematic reviews have examined the association between frailty and mortality; however, it is unclear whether these different frailty scales similarly predict mortality. This umbrella review aims to examine the association between frailty assessed by different frailty scales and all-cause mortality among community-dwelling older adults. Methods The umbrella review protocol was registered at PROSPERO, and it was conducted following the PRISMA statement. MEDLINE, Embase, PubMed, Cochrane Database of Systematic Reviews, Joanna Briggs Institute (JBI) EBP database, and Web of Science database was searched to identify systematic reviews and meta-analyses examining the association between frailty and all-cause mortality. Methodological quality was assessed using the JBI. Critical Appraisal Checklist and online AMSTAR-2 critical appraisal checklist. For eligible studies, essential information was extracted and synthesized qualitatively. Results Five systematic reviews were included, with a total of 434,115 participants. Three systematic reviews focused on single frailty scales; one evaluated Fried physical frailty phenotype and its modifications; another focused on the deficit accumulation frailty index. The third evaluated the FRAIL (Fatigue, Resistance, Ambulation, Illness, and Loss of weight) scale. The two other systematic reviews determined the association between frailty and mortality using different frailty scales. All the systematic reviews performed meta-analyses and assessed between-study heterogeneity. All of the systematic reviews found that frailty was significantly associated with all-cause mortality.Conclusion This umbrella review demonstrates that frailty is a significant predictor of all-cause mortality, irrespective of the specific frailty scale.
Single channel approach for filtering EEG signals strongly contaminated with facial EMG
Authors: Silva Gustavo Moreira da , Queiroz Carlos Magno Medeiros , Walter Steffen , Peres Luciano Brink , Luiz Luiza Maire David , Costa Samila Carolina , Pereira Adriano Alves , Vieira Marcus Fraga , Andrade Adriano de Oliveira 
Published: October 2020

Abstract
Background Eliminating facial electromyography (EMG) from the electroencephalogram (EEG) is essential for the accuracy of applications such as brain computer interfaces (BCIs) and quantification of brain functionality. Although it is possible to find several studies that address EEG filtering, there is lack of researches that improve the filtering of EEG strongly corrupted by EMG signals with single-channel approaches, which are necessary in situations in which the number of available channels is reduced for the application of filtering methods based on multichannel techniques. In this context, this research proposes an EEG denoising method for filtering EMG from the masseter and frontal. This method, so-called EMDRLS, combines the use of Empirical Mode Decomposition (EMD) and a Recursive Least Square (RLS) filter to attenuate facial EMG noise from EEG. The results were compared with those obtained from Wavelet, EMD, Wiener and Wavelet-RLS (WRLS) filters. Besides the visual inspection of the resultant waveform of filtered signals, the following objective metrics were employed to contrast the performance of the filtering methods: (i) the signal-noise ratio (SNR) of the contaminated signal, (ii) the root mean square error (RMSE) between the power spectrum of artifact free and filtered EEG epochs, (iii) the spectral preservation of brain rhythms (i.e., delta, theta, alpha, beta, and gamma rhythms) of filtered signals.Results The EMDRLS method yielded filtered EEG signals with SNR varying from 0 to 10 dB for EEG signals with SNR below -10dB. The Spearman’s correlation coefficient estimated between the SNR of filtered and corrupted signals was below 0.04, suggesting, in the evaluated conditions, the independence of the EMDRLS filtering performance to the SNR of noisy signals. The technique also improved the RMSE between the power spectrum of artifact free and filtered EEG epochs by a factor of 27 (from 5.429 to 0.197) in the most corrupted EEG channels with the masseter muscle contraction. The Kruskal-Wallis test and the Tukey-Kramer post-hoc test (p < 0.05) confirmed the preservation of all brain rhythms given by EEG signals filtered with the EMDRLS method.Conclusions The results showed that the single-channel EMDRLS method can be applied to highly contaminated EEG signals by facial EMG signal with performance superior to that of the compared methods. The method can be applied for the offline filtering of EEG signals contaminated by facial EMG.
Chromatographic and Tandem mass spectroscopic characterization of Ayush Kwath Churnam-an Ayurvedic immunomodulatory drug during COVID-19
Authors: T Sulaiman C , M Deepak , S Madhavankutty T , M Anandan E , Balachandran Indira 
Published: October 2020

Abstract
Background: Severe acute respiratory syndrome coronavirus-2, the causative agent of coronavirus disease 2019 (COVID-19) is the global health crisis. There are no existing solutions to COVID 19 as yet. Ayush Kwath Churnam (AKC) is an Ayurvedic medicine promoted by Ministry of AYUSH, Government of India for the enhancement of body immunity in Covid-19 scenario and promoted many AYUSH clinics all over the country with an aim of enhancing immunity of the people to resist SARS Cov-2.Methods: In this study, chemical evaluation of AKC has been done by High Performance Thin Layer Chromatography (HPTLC) and Liquid Chromatography Mass Spectroscopic (LC-MS) analysis. Chemical characterization of AKC was carried out by Electro Spray chemical Ionization (ESI) in both positive and negative mode using Quadrupole Time-of-Flight (Q-TOF) mass spectroscopy. Results: Data processing of molecular ions obtained by mass fragmentation led to the identification of several phytoconstituents belonging to various classes of compounds such as alkaloids, phenolics, flavonoids and isoflavones. Conclusion: The study concluded that AKC contains variety of phytochemicals with numerous biological properties like immunomodulatory, anti-inflammatory and antioxidant activities.
Dynamics based on analysis of public data for spreading of disease
Authors: Lima Leonardo S. 
Published: October 2020

Abstract
The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supported by the public health agencies in countries as Brazil, EUA and India is investigated. We performed the numerical analysis using the stochastic differential equation for estimating of the novel cases diary as well as analytical calculations solving the correspondent partial equation for the distribution of novel cases P. Our results display that the model based in the Itô diffusion fits well to the results diary due to uncertain in the official data and to the number of tests realized in the populations of each country.
Don’t stop walking: an in-home rehabilitation program for peripheral artery disease patients during the COVID-19 pandemic.
Authors: Lamberti Nicola , Straudi Sofia , Manfredini Roberto , De Giorgi Alfredo , Gasbarro Vincenzo , Zamboni Paolo , Manfredini Fabio 
Published: October 2020

Abstract
Aims: We studied the outcomes of peripheral artery disease (PAD) patients enrolled in a structured in-home walking program before the lockdown due to the SARS-CoV-2 epidemic emergency, to determine whether this intervention ensured the maintenance of mobility in the case of strict movement restrictions.Methods: We considered 83 patients (age 72±11, males n=65) enrolled in a rehabilitation program based on two daily 8-minute sessions of slow intermittent in-home walking at a prescribed cadence with circa-monthly hospital visits. During the lockdown period, the program was updated by phone. The 6-minute (6MWD) and pain-free walking distance (PFWD) were measured pre- and postlockdown. Body weight (BW), blood pressure (BP), and the ankle-brachial index (ABI) were also determined.Results: Sixty-six patients were measured 117±23 days after their previous visit. A safe, pain-free execution the prescribed sessions, with a median distance covered of 74 km, was reported. Overall, the 6MWD was stable, while PFWD improved (p<0.001). Decreased BW with stable BP and ABI values were also recorded. When considering the outcome values according to the time of enrollment before the lockdown, new-entry subjects (≤3 months; n=35) obtained significant improvements, while those previously enrolled (>3 months; n= 31) were stable.Conclusion: In PAD patients, a structured exercise program easily performed in a home corridor and guided with phone assistance was adhered to by patients and showed effectiveness in maintaining mobility and risk factor control during the COVID-19 pandemic. Safe structured exercise may involve frail subjects regardless of walking ability, type of home and external conditions.
Prevalence of anxiety and depression among pregnant women during the COVID-19 pandemic: a systematic review and meta-analysis
Authors: Zhang Jiashuo , Yu Hongbiao , Gao Yijie , Xu Qin , Yin Yangxue , Zhou Rong 
Published: October 2020

Abstract
Background COVID-19 has become a global pandemic. Its occurrence has substantially affected the psychological condition of pregnant women. The purpose of this study is to learn about the incidence of anxiety and depression among pregnant women during the pandemic, and to conduct a meta-analysis of the existing research.Methods PubMed, Web of Science and EMBASE were searched without a lower time limit and up to August 13, 2020. The incidences of anxiety and depression among pregnant women were synthesized and discussed.Results The prevalence of anxiety in 8 studies with a total sample size of 7493 individuals was 43% (95% confidence interval: 0.28-0.58), and the prevalence of depression in 7 studies with a sample size of 6116 people was 32% (95% confidence interval: 0.26-0.37). Significant heterogeneity was detected across studies of these incidence estimates. Subgroup analysis included the economic status to explore the sources of heterogeneity, and Egger’s test was conducted to examine the publication bias.Conclusions Since significant heterogeneity has been detected in studies of anxiety and depression, we must interpret the results with caution. As the COVID-19 pandemic will not end in a short time, corresponding psychological interventions must be implemented to address the mental health of pregnant women.
Data suggest COVID-19 affected numbers greatly exceeded detected numbers, in four European countries, as per a delayed SEIQR model
Authors: Tiwari Sankalp , Vyasarayani C. P. , Chatterjee Anindya 
Published: October 2020

Abstract
People in many countries are now infected with COVID-19. By now, it is clear that the number of people infected is much more than the number of reported cases. To estimate the infected but undetected/unreported cases using a mathematical model, we can use a parameter called the probability of quarantining an infected individual. This parameter exists in the time-delayed SEIQR model (Scientific Reports, article number: 3505). Two limiting cases of a network of such models are used to estimate the undetected population. The first limit corresponds to the network collapsing onto a single node and is referred to as the mean-$\beta$ model. In the second case, the number of nodes in the network is infinite and results in a continuum model, treating the infectivity as statistically distributed. We use a shifted Pareto distribution to model the infectivity. This distribution has a long tail and incorporates the presence of super-spreaders that contribute to the disease progression. While both the models capture the {\em detected} numbers equally well, the predictions of {\em affected} numbers from the continuum model are more realistic. Results suggest that affected people outnumber detected people by one to two orders of magnitude in Spain, UK, Italy, and Germany.
Prediction of patients requiring intensive care for COVID-19: development and validation of an integer-based score using data from Centers for Disease Control and Prevention of South Korea.
Authors: Heo JoonNyung , Han Deokjae , Kim Hyung-Jun , Kim Daehyun , Lee Yeon-Kyeng , Lim Dosang , Hong Sung Ok , Park Mi-Jin , Ha Beomman , Seog Woong 
Published: October 2020

Abstract
Background Unavailability or saturation of the intensive care unit may be associated with the fatality of COVID-19. Prioritizing the patients for hospitalization and intensive care may be critical for reducing the fatality of COVID-19. This study aimed to develop and validate a new integer-based scoring system for predicting patients with COVID-19 requiring intensive care, using only the predictors available upon triage. Methods This is a retrospective study using cohort data from the Korean Centers for Disease Control and Prevention that included all admitted patients with COVID-19 between January 19 and June 3, 2020, in South Korea. The primary outcome was patients requiring intensive care defined as actual admission to the intensive care unit; at any time use of an extracorporeal life support device, mechanical ventilation, or vasopressors; death. Patients admitted until March 20 were included for the training dataset to develop the prediction models and externally validated for the patients admitted afterward. Two logistic regression models were developed with different predictors and the predictive performance was compared: one with patient-provided variables and the other with added radiologic and laboratory variables. An integer-based scoring system was developed based on the developed logistic regression model.Results A total of 5,193 patients were considered, with 4,663 patients included after excluding patients with age under 18 or insufficient data. For the training dataset, 3,238 patients were included. Of the included patients, 444 (9.5%) patients required intensive care. The model developed with only the clinical variables showed an area under the curve of 0.884 for the validation set. The performance did not differ when radiologic and laboratory variables were added. Seven variables were selected for developing an integer-based scoring system: age, sex, initial body temperature, dyspnea, hemoptysis, history of chronic kidney disease, and activities of daily living. The area under the curve of the scoring system was 0.880. Conclusions An integer-based scoring system was developed for predicting patients with COVID-19 requiring intensive care, with high performance. This system may aid decision support for prioritizing the patient for hospitalization and intensive care, particularly in a situation with limited medical resources.