bluuebunny/crossref_metadata_2025_split huggingface dataset:
Excess‐Heat Recovery and Promotion through Organic Chemical Heat Pumps
Authors: Pinela da Silva Luis António , João Isabel Maria , Silva João Miguel 
Published: September 2021

AbstractHeat recovery and promotion is essential to decarbonization, and chemical heat pumps based on reversible organic reactions can aid to fulfil this. This paper studied the isopropanol/acetone/hydrogen (IAH) and the tert‐butanol/isobutene/water (tB/iB) systems regarding their performance and economic competitiveness through simulation and found that the IAH presents satisfactory performance and has the potential to be a very promising solution in increasing the overall energy efficiency while also preventing the emission of massive amounts of CO2 and other greenhouse gases released during energy production and transformation. This system presents enough arguments to become a very successful solution if proper politico‐economic support and incentives are established and put into practice.
Separation of Indium from Acid Sulfate‐Containing Solutions by Ion Exchange with Impregnated Resins
Authors: Vostal Radek , Pavón Sandra , Kaiser Doreen , Bertau Martin 
Published: September 2021

AbstractIndium separation using ion exchange resins from acidic polymetallic and very diluted solutions are investigated. Since the selectivity of commercial ion exchange resins have proven to be too low for an effective separation from solutions with high content of other metals, Lewatit® TP 208 was impregnated with common extractants to enhance its properties. By resin impregnation with D2EHPA and Cyanex 272, not only the selective indium recovery was reached but also the resin capacity was increased approx. two times. The best loading and elution performance were shown by Cyanex 272‐impregnated Lewatit® TP 208, increasing the indium purity in the eluate from 0.75 % to 85 %.
Evacuation from various types of finite two‐dimensional square grid fields by a metamorphic robotic system
Authors: Nakamura Junya , Kamei Sayaka , Yamauchi Yukiko 
Published: September 2021

SummaryA metamorphic robotic system (MRS) is composed of anonymous, memoryless, and autonomous modules that execute an identical distributed algorithm to move while keeping the connectivity of the modules. For an MRS, the number of modules required to solve a given task is an important complexity measure. Here, we consider evacuation from a finite two‐dimensional square grid field by an MRS. This study aims to establish the minimum number of modules required to solve the evacuation problem under several conditions. We consider a rectangular field surrounded by walls with at least one exit. Our results show that two modules are necessary and sufficient for evacuation from any rectangular field if equipped with a global compass, which provides the modules with a common sense of direction. After that, we focus on the case of modules without a global compass and show that four (resp. seven) modules are necessary and sufficient for restricted (resp. any) initial shapes of an MRS. We also show that two modules are sufficient when an MRS is touching a wall in an initial configuration. Then, we clarify the condition to stop an MRS after evacuation of a rectangular field. Finally, we extend these results to mazes and convex fields.
Optimal resource allocation with deep reinforcement learning and greedy adaptive firefly algorithm in cloud computing
Authors: Karat Chitharanjan , Senthilkumar Radha 
Published: September 2021

AbstractThe allocation of resources is a foremost demanding task in cloud computing. Scholars are yet finding it difficult to allocate appropriate resources to the set of user tasks. Our objective is to provide a platform that optimizes a dynamic resource allocation scheme. Multi‐agent deep reinforcement learning‐based greedy adaptive firefly algorithm (MAD‐GAF) has been proposed herein includes both the resource management and allocation techniques. This chooses the best Quality of Service (QoS) measured host for a group of tasks efficiently and subsequently minimize the task execution time. The proposed cloud brokering architecture comprises a multi‐agent system, the cloud provider and the user. Initially, deep reinforcement learning has been built to recreate the request of cloud customers by forecasting the value of unused resources. Then the recreated customer request is forwarded to the global broker agent, which maps the virtual machine (VM) to the most appropriate cluster of physical machine (PM). The virtual machine monitor (VMM) selects VMs by managing and accessing the physical resources. The global utility agent allocates VMs using the GAF optimization algorithm, which specifies the best QoS measured host to decrease the whole tasks' average response time, thus optimizing resource allocation compared to the current approaches.
Stimuli‐Responsive Chiroptical Switching
Authors: Sahoo Diptiprava , Benny Renitta , KS Nithish Kumar , De Soumen 
Published: September 2021

Abstract“Chirality” governs many fundamental properties in chemistry and biochemistry. While early investigations on stereochemistry are primarily dedicated to static chirality, there is an increasing interest in the field of dynamic chirality (chiral switches). These chiral switches are essential in controlling the directionality in molecular motors. Dynamic chiralities are equally crucial in switchable stereoselectivity, switchable asymmetric catalysis and enantioselective separation. Herein, we limit our discussion to recent advances on stimuli‐induced chiroptical switching of axial, helical, and planar chirality in response to external stimuli. We also discuss a few examples of applications of the switchable chirality.
Transcutaneous electrical nerve stimulation in speech therapy rehabilitation of voice and swallowing function in adults—a systematic review
Authors: da Silva Milena Assis , Mangilli Laura Davison 
Published: September 2021

AbstractIntroductionIn recent years, a number of clinical trials have been published comparing transcutaneous electrical nerve stimulation (TENS) and traditional speech therapy treatment of voice and swallowing functions, but results have been conflicting.ObjectiveAssess the methodological quality of studies and determine whether TENS is an efficient therapeutic strategy for speech therapy treatment of healthy adults or those with dysphonia and/or dysphagia.MethodsThe databases used were Medical Literature Analysis and Retrieval System Online (MedLine), Biblioteca Virtual em Saúde (BVS), Cochrane Library and Web of Science (ISI Web of Knowledge). The study was conducted between May 2018 and January 2019, in line with Cochrane Handbook guidelines, and included studies on the use of TENS in healthy adults or those with compromised voice and/or swallowing function.ResultsAfter the search and extraction of studies, the following were identified: TENS + VOICE: 7 articles; TENS + SWALLOWING: 5 articles. The studies exhibited medium quality and are heterogeneous, making it difficult to determine their effectiveness and the parameters to be used in future research. There were no statistically significant differences between the use of TENS alone or associated with another therapeutic technique for voice. For swallowing function, one study proved better results in cases of associated techniques – TENS + traditional therapy.DiscussionSpeech therapy should increase the number of studies published and improve their methodological quality, reassessing methodological criteria. Current clinical practice is not grounded in evidence‐based science.Clinical Message
the studies analyzed exhibited medium methodological quality;
there are variations in the time, number and periodicity of the therapeutic sessions for TENS;
there were no statistically significant differences between the use of TENS alone or associated with another therapeutic technique in voice;
there were statistically significant differences between the use of TENS associated with traditional therapeutic in swallowing function.
Unsupervised mobile cognitive testing for use in preclinical Alzheimer's disease
Authors: Papp Kathryn V. , Samaroo Aubryn , Chou Hsiang‐Chin , Buckley Rachel , Schneider Olivia R. , Hsieh Stephanie , Soberanes Daniel , Quiroz Yakeel , Properzi Michael , Schultz Aaron , García‐Magariño Iván , Marshall Gad A. , Burke Jane G. , Kumar Raya , Snyder Noah , Johnson Keith , Rentz Dorene M. , Sperling Reisa A. , Amariglio Rebecca E. 
Published: September 2021

AbstractIntroductionUnsupervised digital cognitive testing is an appealing means to capture subtle cognitive decline in preclinical Alzheimer's disease (AD). Here, we describe development, feasibility, and validity of the Boston Remote Assessment for Neurocognitive Health (BRANCH) against in‐person cognitive testing and amyloid/tau burden.MethodsBRANCH is web‐based, self‐guided, and assesses memory processes vulnerable in AD. Clinically normal participants (n = 234; aged 50–89) completed BRANCH; a subset underwent in‐person cognitive testing and positron emission tomography imaging. Mean accuracy across BRANCH tests (Categories, Face‐Name‐Occupation, Groceries, Signs) was calculated.ResultsBRANCH was feasible to complete on participants’ own devices (primarily smartphones). Technical difficulties and invalid/unusable data were infrequent. BRANCH psychometric properties were sound, including good retest reliability. BRANCH was correlated with in‐person cognitive testing (r = 0.617, P < .001). Lower BRANCH score was associated with greater amyloid (r = –0.205, P = .007) and entorhinal tau (r = –0.178, P = .026).DiscussionBRANCH reliably captures meaningful cognitive information remotely, suggesting promise as a digital cognitive marker sensitive early in the AD trajectory.
Vitamin D deficiency associated with risk of prediabetes among older adults: Data from the National Health and Nutrition Examination Survey (NHANES), 2007–2012
Authors: Pojednic Rachele M. , Trussler Emily M. , Navon Julia D. , Lemire Sarah C. , Siu Elizabeth C. , Metallinos‐Katsaras Elizabeth S. 
Published: September 2021

AbstractAimTo examine the association between vitamin D (25(OH)D) deficiency and risk of prediabetes in Americans 50+ years of age.Materials and MethodsThis was a cross‐sectional analysis of NHANES (2007–2012) subjects aged 50+ years, free of kidney/liver diseases and diabetes. Prediabetes was defined as: HbA1c level 5.7%–6.4%, or fasting plasma glucose level 100–125 mg/dL, or Oral Glucose Tolerance Test result 140–199 mg/dL, with no laboratory value in the diabetic range. The comparison group had normal glucose tolerance (NGT) with no marker in the prediabetes/diabetes range. Total serum 25(OH)D levels were deficient at <50 nmol/L, insufficient 50–75 nmol/L, and sufficient >75 nmol/L. Logistic regression included strata, cluster and weight variables. Models were adjusted for body mass index (BMI), ethnicity, age and gender.ResultsThe final sample was 2286 adults, predominantly White (80.4%) and female (56.6%), with a mean age of 62.3 years. Within the sample, 1387 had prediabetes (59.1%) and 899 were NGT (40.9%). Individuals classified within a lower serum vitamin D category were more likely to have prediabetes (p = 0.03). Those with 25(OH)D deficiency were more likely to have prediabetes compared to 25(OH)D sufficient individuals (crude OR = 1.48, 95% CI 1.15–1.91), and this association remained significant after adjustment for ethnicity, BMI, age and gender (aOR = 1.39, 95% CI 1.02–1.89). There was no effect modification by BMI, gender or ethnicity.ConclusionsVitamin D status was associated with risk of prediabetes in this sample of Americans 50+ years of age. Future research should seek to understand the potential mechanistic relationship between vitamin D and prediabetes.
Cycloaddition Reactions of in situ Generated C2D2 in Dioxane: Efficient Synthetic Approach to D2‐Labeled Nitrogen Heterocycles
Authors: Voronin Vladimir V. , Ledovskaya Maria S. , Rodygin Konstantin S. , Ananikov Valentine P. 
Published: September 2021

AbstractIn this work, an universal synthetic approach for the synthesis of D2‐labeled nitrogen heterocycles based on cycloaddition reactions of in situ generated dideuteroacetylene is reported. A key feature of this method is the use of 1,4‐dioxane as a deuterium‐exchange‐proof solvent, which allowed the access to dideuterosubstituted heterocycles in up to 99 % deuteration degree. The method was demonstrated to be suitable for the synthesis of D2‐labeled triazoles, isoxazoles, pyrazoles and pyridazines.
To the brave scientists: Aren't we strong enough to stand (and profit from) uncertainty in Earth system measurement and modelling?
Authors: Paasche Hendrik , Gross Matthias , Lüttgau Jakob , Greenberg David S. , Weigel Tobias 
Published: September 2021

AbstractThe current handling of data in earth observation, modelling and prediction measures gives cause for critical consideration, since we all too often carelessly ignore data uncertainty. We think that Earth scientists are generally aware of the importance of linking data to quantitative uncertainty measures. But we also think that uncertainty quantification of Earth observation data too often fails at very early stages. We claim that data acquisition without uncertainty quantification is not sustainable and machine learning and computational modelling cannot unfold their potential when analysing complex natural systems like the Earth. Current approaches such as stochastic perturbation of parameters or initial conditions cannot quantify uncertainty or bias arising from the choice of model, limiting scientific progress. We need incentives stimulating the honest treatment of uncertainty starting during data acquisition, continuing through analysis methodology and prediction results. Computational modellers and machine learning experts have a critical role, since they enjoy high esteem from stakeholders and their methodologies and their results critically depend on data uncertainty. If both want to advance their uncertainty assessment of models and predictions of complex systems like the Earth, they have a common problem to solve. Together, computational modellers and machine learners could develop new strategies for bias identification and uncertainty quantification offering a more all‐embracing uncertainty quantification than any known methodology. But since it starts for computational modellers and machine learners with data and their uncertainty, the fundamental first step in such a development would be leveraging shareholder esteem to insistently advocate for reduction of ignorance when it comes to uncertainty quantification of data.
Characteristics of people with dementia lost to follow‐up from a dementia care center
Authors: Boyd Nicole D. , Naasan Georges , Harrison Krista L. , Garrett Sarah B. , D'Aguiar Rosa Talita , Pérez‐Cerpa Brenda , McFarlane Shamiel , Miller Bruce L. , Ritchie Christine S. 
Published: September 2021

AbstractObjectiveTo identify the prevalence and characteristics of people living with dementia (PLWD) lost to follow‐up (LTFU) from a specialized dementia care clinic and to understand factors influencing patient follow‐up status.MethodsWe conducted a retrospective chart review of PLWD seen at a dementia care clinic 2012–2017 who were deceased as of 2018 (n = 746). Participants were evaluated for follow‐up status at the time of death. Generalized linear regression was used to analyze demographic and diagnostic characteristics by follow‐up status. Text extracted from participant medical records was analyzed using qualitative content analysis to identify reasons patients became LTFU.ResultsAmong PLWD seen at a dementia care clinic, 42% became LTFU before death, 39% of whom had chart documentation describing reasons for loss to follow‐up. Increased rates of LTFU were associated with female sex (risk ratio 1.27, [95% confidence interval 1.09–1.49]; p = 0.003), educational attainment of high school or less (1.34, [1.13–1.61]; p = 0.001), and death in a long‐term care facility (1.46, [1.19–1.80]; p = 0.003). Commonly documented reasons for not returning for care at the clinic included switching care to another provider (42%), logistical difficulty accessing care (26%), patient‐family decision to discontinue care (24%), and functional challenges in accessing care (23%).ConclusionsPLWD are LTFU from specialized memory care at high rates. Attention to care coordination, patient–provider communication, and integrated use of alternative care models such as telehealth are potential strategies to improve care.
No increase in anti‐A isohemagglutinin titer after SARS‐CoV‐2 infection: A retrospective cohort analysis of group O apheresis platelet donors
Authors: Wasiluk Tomasz , Bujno Magdalena , Rybinska Kamila , Rogowska Anna , Zebrowska Agnieszka , Boczkowska‐Radziwon Barbara , Piszcz Jaroslaw , Bolkun Lukasz , Radziwon Piotr 
Published: September 2021

AbstractThe risk of a hemolytic reaction during the transfusion of ABO non‐identical PC is determined by the presence of natural anti‐A IgM antibodies, the titer of which may increase after infections. The aim of the study was to evaluate the titer of anti‐A isohemagglutinins in platelet concentrate (PC) obtained by apheresis from group O donors who experienced SARS‐CoV‐2 infection, and to compare the titer before and after infection. A retrospective single‐center analysis of 21 PC donors with a previous COVID‐19 history was performed. The results showed neither a statistically important increase in the anti‐A IgM antibody titers nor a significant correlation between the anti‐A IgM antibody level and anti‐SARS‐CoV‐2S1 antibody titer in the donors with an asymptomatic or mild COVID‐19. Further population‐based studies on anti‐A titers are necessary for a comprehensive assessment of this phenomenon.
Repurposing fusion inhibitor peptide against SARS‐CoV‐2
Authors: Efaz Faiyaz Md. , Islam Shafiqul , Talukder Shafi Ahmad , Akter Shaila , Tashrif Md. Zakaria , Ali Md. Ackas , Sufian Md. Abu , Parves Md. Rimon , Islam Md. Jahirul , Halim Mohammad A. 
Published: September 2021

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is continuously evolving. Although several vaccines were approved, this pandemic is still a major threat to public life. Till date, no established therapies are available against SARS‐CoV‐2. Peptide inhibitors hold great promise for this viral pathogen due to their efficacy, safety, and specificity. In this study, seventeen antiviral peptides which were known to inhibit SARS‐CoV‐1 are collected and computationally screened against heptad repeat 1 (HR1) of the SARS‐CoV‐2 spike protein (S2). Out of 17 peptides, Fp13 and Fp14 showed better binding affinity toward HR1 compared to a control peptide EK1 (a modified pan‐coronavirus fusion inhibitor) in molecular docking. To explore the time‐dependent interactions of the fusion peptide with HR1, molecular dynamics simulation was performed incorporating lipid membrane. During 100 ns MD simulation, structural and energy parameters of Fp13‐HR1 and Fp14‐HR1 complexes demonstrated lower fluctuations compared to the control EK1‐HR1 complex. Furthermore, principal component analysis and free energy landscape study revealed that these two peptides (Fp13 and Fp14) strongly bind to the HR1 with higher affinity than that of control EK1. Tyr917, Asn919, Gln926, lys933, and Gln949 residues in HR1 protein were found to be crucial residues for peptide interaction. Notably, Fp13, Fp14 showed reasonably better binding free energy and hydrogen bond contribution than that of EK1. Taken together, Fp13 and Fp14 peptides may be highly specific for HR1 which can potentially prevent the formation of the fusion core and could be further developed as therapeutics for treatment or prophylaxis of SARS‐CoV‐2 infection.
The expression profile and clinical application value of hsa_circ_0016148 in head and neck squamous cell carcinoma
Authors: Shen Zhisen , Wang Liuqian , Ye Dong 
Published: September 2021

AbstractBackgroundDysregulated circular RNAs (circRNAs) are involved in human cancers and may be used as biomarkers with the potential of clinical application. However, little is known regarding the mechanism of circRNAs and their clinical application value in head and neck squamous cell carcinoma (HNSCC).MethodsIn the current study, we established the profile of circRNAs in HNSCC using microarray and then measured the expression of hsa_circ_0016148 in 137 paired HNSCC tissues by qRT‐PCR technique, analyzed the relationship between hsa_circ_0016148 and clinicopathological data, and investigated its diagnostic and prognostic value. The hsa_circ_0016148‐miRNA‐mRNA interaction network was predicted and constructed by Cytoscape.ResultsOur study showed a circRNA expression profile and confirmed downregulated hsa_circ_0016148 in HNSCC tissues (p = 2.64E‐35). The hsa_circ_0016148 expression is remarkably correlated with lymph node metastasis (p = 0.001) and clinical stage (p = 0.029). Then, the area under the receiver characteristic curve (AUC) was 0.912 with 92% of sensitivity and 86.9% specificity, respectively. Besides, our study demonstrated that lower‐expressed hsa_circ_0016148 could independently predict poorer overall survival of HNSCC patients (hazard ratio [HR] = 0.456; 95% confidence interval [CI] = 0.265–0.784; p = 0.005). The hsa_circ_0016148‐miRNA‐mRNA interaction network was constructed, which included a total of nine targeted miRNAs.ConclusionTaken together, our results revealed that hsa_circ_0016148 might play a critical role in HNSCC tumorigenesis and may serve as an indicator with the potential of diagnosis and prognosis for HNSCC.
Impact of COVID‐19 on psychological distress among SME owners in Ghana: Partial least square–structural equation modeling (PLS‐SEM) approach
Authors: Uzir Md U. H. , Bukari Zakari , Jerin Ishraq , Hasan Najmul , Abdul Hamid Abu B. , Thurasamy Ramayah  
Published: September 2021

AbstractA critical part of the national economy is small and medium enterprises (SMEs). SME owners are vital contributors to the overall economy. Due to their limited capital and assets, they are more vulnerable. In comparison to their contribution, the value of assessing SME owner's depression, anxiety, and mental stress has been very minimal during the COVID‐19 outbreak. Firms were forced to close due to lockdown, and they faced substantial business losses. Thus, this study aims to investigate SME owners' psychological distress due to business losses during this pandemic. The study used psychological parameters: Depression, Anxiety, Stress Scale‐21 (DASS‐21) to examine SME owners' psychological distress. A total number of 217 owners were surveyed through a judgmental sampling technique using a structured questionnaire. Data were analyzed employing partial least square‐based structural equation modeling (PLS‐SEM). The findings showed that DASS‐21 parameters and fear of business loss affected psychological distress. Besides, fear of business loss increases psychological distress, whereas government support lessens the distress. Theoretically, this study extended the scope of DASS‐21 scale and contributed to the literature of psychology. In terms of policy implications, this study provides useful information for government, policymakers, and SME owners about the effects mentioned above.