bluuebunny/crossref_metadata_2025_split huggingface dataset:
Steady air flow model for large sewer networks: a theoretical framework
Authors: Zhang Qi , Shao Weiyun , Zhu David Z. , Xu Weilin 
Published: July 2020

Abstract
Modelling air movement in sewer networks is needed in order to address the issues related to sewer odour complaints and sewer corrosions due to hydrogen sulphide in sewers. Most of the existing air flow models can only be applied in small sewer networks or the trunk lines of sewer systems. The purpose of this paper is therefore to propose a theoretical approach to formulate a general governing equation set for modelling steady air movement in large sewer systems. This approach decomposes the sewer system of interest into its basic physical components as pipes and nodes, and builds local topology of each pipe and each node based on geographic information system data as the fundamentals of model formulation. It avoids manually identifying each branch of the sewer system, eliminates the effect of physically closed networks in sewer systems on the governing equations, and considers key sewer components and all known driving forces. The proposed approach was applied to a real sewer system with over 500 pipes. The results show that the proposed model is applicable in modelling air movement in a large sewer system and provides a general idea of sewer gases moving through the system and their emission.
Multi-year diagnosis of unpredictable fouling occurrences in a full-scale membrane bioreactor
Authors: Carlson A. L. , Daigger G. T. , Love N. G. , Hart E. 
Published: July 2020

AbstractThe membrane bioreactor (MBR) at the Traverse City Regional Wastewater Treatment Plant has experienced sudden and unpredictable periods of substantial permeability decline since 2011. Early observations detected irregularly-shaped gram-positive bacteria that correlated with plant upsets. Use of biomolecular techniques, such as DNA sequencing of laboratory isolates and the mixed liquor microbial community, and fluorescent in situ hybridization, identified the dispersed organisms as members of the genus Staphylococcus. However, Staphylococcus species were consistently present during normal operation and therefore were more likely to be an indicator of the upset, not the cause. The results suggest that these microorganisms are responding to specific influent wastewater constituents. We chemically analysed seven mixed liquor samples from periods of permeability decline in 2017 and 2018, and four samples from a period of normal operation. During upset conditions, the total carbohydrate content exceeded that of normal operation by 40%. Additionally, mixed liquor calcium concentrations were 65% above normal during the upset in 2017. It is hypothesized and supported through multivariate statistical analysis and estimation of specific resistance to filtration values that a calcium-intermediated polymer bridging mechanism with extracellular polymeric substance constituents is a major contributor to fouling and permeability disruptions in the Traverse City MBR.
Release Characteristics of an Essential Oil Component Encapsulated with Cyclodextrin Shell Matrices
Authors: Li Zhe , Wen Wangwen , Chen Xulong , Zhu Lin , Cheng Genjinsheng , Liao Zhenggen , Huang Hao , Ming Liangshan 
Published: July 2020

Background:
Essential oils are poor aqueous solubility and high volatility compounds. The
encapsulation of essential oils with Cyclodextrins (CDs) can protect them from adverse environmental
conditions and improve their stability. Therefore, increasing the functional capabilities of essential oils
when they were used as additives in pharmaceutical and food systems. Additionally, the release of active
compounds is an important issue. However, there were few studies about the effect of different
CDs on the release of drugs after encapsulation. Therefore, the information on the study of release
models is considerably limited.

Objective:
This study aimed to (i) characterize the physico-chemical properties and release behavior of
myrcene encapsulated in the four different shell matrices of α-CD, β-CD, γ-CD and 2-hydroxypropyl-β-
cyclodextrin (HP-β-CD), which were selected from the perspective of stability, and (ii) determine the
release mechanism of myrcene in Inclusion Complexes (ICs).

Methods:
ICs of myrcene and four CDs were prepared by freeze-drying. The physico-chemical properties
of ICs were fully characterized by laser diffraction particle size analyzer, Scanning Electron Microscope
(SEM), Fourier-Transform Infrared spectroscopy (FT-IR) and Differential Scanning Calorimeter
(DSC). The release behaviors of ICs at 50, 60, 70 and 80 °C were determined and described by zeroorder
or first-order kinetics with the Henderson-Pabis, Peppas, Avrami and Page mathematical models.
Moreover, the possible binding modes of ICs were identified with molecular modelling technique.

Results:
Firstly, the structure of Particle Size Distribution (PSD), FT-IR, DSC and SEM showed that (i)
CDs could effectively encapsulate the myrcene molecules, and (ii) the release kinetics were well simulated
by Avrami and Page models. Secondly, the release rates of the ICs experienced an unsteady state
in the early stage, and gradually became almost constants period after 20 hours. Except that the release
of myrcene in γ-CD/myrcene belonged to the first-order kinetic, the release models of the remaining
three ICs belonged to diffusion mode. Thirdly, the calculated binding energies of the optimized structures
for α-CD/myrcene, β-CD/myrcene, γ-CD/myrcene, and HP-β-CD/myrcene ICs were −4.28, −3.82,
−4.04, and −3.72 kcal/mol, respectively. Finally, the encapsulation of myrcene with α-CD and β-CD
was preferable according to the stability and release characteristics.

Conclusion:
The encapsulation of myrcene was profoundly affected by the type of CDs, and the stability
could be improved by complexation with suitable CDs. The binding behavior between guest and CD
molecules, and the release profile of the guest molecules could be effectively explained by the kinetics
parameters and molecular modelling. This study can provide an effective basis and guide for screening
suitable shell matrices.
Conventional and Microwave Pyrolysis for Preparation of Sewage Sludge- Activated Carbons for Pharmaceuticals Removal: A Mini-Review
Authors: dos Reis Glaydson Simoes , Lima Eder Claudio , Thue Pascal Silas 
Published: July 2020

Abstract:
Sewage sludge shows excellent potential as pyrolysis feedstock in generating valuable
products such as Activated Carbons (ACs). In this mini-review the preparation of sewage sludge-
ACs by two kinds of pyrolysis conventional and microwave heating is presented and discussed. The
main difference between conventional pyrolysis and the microwave-assisted method is the way the
heat is generated, and both can provide ACs with different textural and chemical properties. Based on
what was demonstrated in this work, it is possible to say that both kinds of pyrolysis (microwave and
conventional methods) can produce high specific surface area and efficiently activated carbons from
sewage sludge. It was also demonstrated that sludge-ACs produced by both pyrolysis methods could
reach very high uptakes of pharmaceuticals from aqueous solutions. The van der Waals interactions,
hydrogen bonding and π-π interactions of the aromatic ring of the adsorbent with the aromatic rings
of the pharmaceuticals have been mentioned to be some of the main mechanisms governing the
pharmaceuticals adsorption by ACs.
Extraction of Bioactive Proteins from Seeds (Corn, Sorghum, and Sunflower) and Sunflower Byproduct: Enzymatic Hydrolysis and Antioxidant Properties
Authors: do Prado Danielle M.F. , de Almeida Adrielle B. , de Oliveira Filho Josemar G. , Alves Cassia C. F. , Egea Mariana B. , Lemes Ailton C. 
Published: July 2020

Background:
Food proteins have benefits for human health, which justifies their production
and use. In this context, the use of seeds and byproducts that would be otherwise discarded is
highlighted in the present work, to produce protein extracts and hydrolyzed proteins, generating opportunities
to reduce environmental impacts.

Objective:
This work aimed to use different extraction methods to obtain protein extracts from
seeds (corn, sorghum, and sunflower) and sunflower byproduct to determine their antioxidant activity,
and apply different proteolytic enzymes in the hydrolysis of sunflower byproduct.

Methods:
The seeds of corn, sorghum, and sunflower, and sunflower byproduct were ground to produce
flour and the protein extracts were prepared using five different methods. The bioactivity of
fractions was analyzed by different methods (ABTS, DPPH, and FRAP) to evaluate the antioxidant
activity.

Results:
The most effective methods, which resulted in higher protein extraction and antioxidant activity,
were those in which NH4HCO3 (5 mM, pH 8.0) and H2O/C2H6O (2:3) were used. The highest
protein contents were 797.9, 303.8, and 11296.5 μg/g, and the highest antioxidant activity was
34417.5, 9732.6, and 47473.1 μg TE/g from Soxhlet and Bligh and Dyer defatted extractions for
sunflower seed, and sunflower byproduct, respectively. Regarding enzymatic hydrolysis, sunflower
byproduct was the substrate that presented the highest degree of hydrolysis (11.06%) when Neutrase
® enzyme was used. Enzymatic hydrolysis increased antioxidant activity in the hydrolyzed proteins,
approximately by 20.0%, using Neutrase® and 22.3% using Flavourzyme® treatments.

Conclusion:
The protein extracts and the hydrolyzed proteins exhibited high antioxidant activity,
demonstrating great potential for use as natural antioxidants in food systems.
Diabetic Peripheral Neuropathy: Diagnosis and Treatment
Authors: Røikjer Johan , Mørch Carsten Dahl , Ejskjaer Niels 
Published: July 2020

Background:
Diabetic peripheral neuropathy (DPN) is traditionally divided into large
and small fibre neuropathy (SFN). Damage to the large fibres can be detected using nerve conduction
studies (NCS) and often results in a significant reduction in sensitivity and loss of protective
sensation, while damage to the small fibres is hard to reliably detect and can be either asymptomatic,
associated with insensitivity to noxious stimuli, or often manifests itself as intractable neuropathic
pain.

Objective:
To describe the recent advances in both detection, grading, and treatment of DPN as well
as the accompanying neuropathic pain.

Methods:
A review of relevant, peer-reviewed, English literature from MEDLINE, EMBASE and
Cochrane Library between January 1st 1967 and January 1st 2020 was used.

Results:
We identified more than three hundred studies on methods for detecting and grading DPN,
and more than eighty randomised-controlled trials for treating painful diabetic neuropathy.

Conclusion:
NCS remains the method of choice for detecting LFN in people with diabetes, while a
gold standard for the detection of SFN is yet to be internationally accepted. In the recent years, several
methods with huge potential for detecting and grading this condition have become available including
skin biopsies and corneal confocal microscopy, which in the future could represent reliable
endpoints for clinical studies. While several newer methods for detecting SFN have been developed,
no new drugs have been accepted for treating neuropathic pain in people with diabetes. Tricyclic
antidepressants, serotonin-norepinephrine reuptake inhibitors and anticonvulsants remain first line
treatment, while newer agents targeting the proposed pathophysiology of DPN are being developed.
Iron (III) Chloride Hexahydrate as a Highly Efficient Catalyst for Acetylation of Protic Nucleophiles with Acetic Anhydride under Solvent-free Conditions
Authors: Eddine Naoures J. , Jennen Fayçal , Kacem Yakdhane , Kraiem Jamil 
Published: July 2020

Background:
Acetylation of protic nucleophiles is used to protect these functional groups.
Most of the methods described in the literature use solvents, one or more equivalent of toxic bases or
expensive and toxic catalysts. Therefore, new methodologies, above all, greener and more economical
procedures, are still in demand.

Objective:
An eco-efficient method was developed for the acetylation of alcohols, phenols, thiols,
amines, and carbohydrates, using acetic anhydride and a catalytic amount of the environmentally benign
and inexpensive FeCl3.6H2O, under solvent-free conditions.

Methods:
Acetylation of a variety of protic nucleophiles was performed using 0.2 mol % of
FeCl3.6H2O as the catalyst, and 1.2 equivalent of Ac2O as the acetylating agent at room temperature
and under solvent-free conditions.

Results:
This procedure appears to be highly efficient and promoted rapid and quantitative acetylation
under simple and minimum manipulation. Chromatography or recrystallization was generally not necessary
for the purification of products.

Conclusion:
This eco-friendly protocol appears to be potentially universally applicable in organic design
to protect protic nucleophiles and isscalable for industrial fields.
Perceived Need and Acceptability of an App to Support Activities of Daily Living in People With Cognitive Impairment and Their Carers: Pilot Survey Study
Authors: Lai Rhoda , Tensil Maria , Kurz Alexander , Lautenschlager Nicola T , Diehl-Schmid Janine 
Published: July 2020

Background
Modern technologies, including smartphone apps, have the potential to assist people with cognitive impairment with activities of daily living, allowing them to maintain their independence and reduce carer burden. However, such tools have seen a slow rate of uptake in this population, and data on the acceptability of assistive technologies in this population are limited.

Objective
This pilot study included older adults with cognitive impairment and their carers, and explored the perceived needs for and acceptability of an app that was designed to be a simple assistive tool for activities of daily living. In particular, this study aimed to assess the acceptability of common app functions such as communication, reminder, navigation, and emergency tools in this population, and to compare patients’ and carers’ responses to them.

Methods
A total of 24 German participants with mild cognitive impairment or dementia and their family carers separately completed two short questionnaires. The first questionnaire asked the participants with cognitive impairment and their carers to self-rate the patients’ cognitive impairment levels and affinity to technology. Following a demonstration of the app, participants rated the usability and acceptability of the app and its functions in a second questionnaire.

Results
Participants rated themselves as much less cognitively impaired than their carers did (P=.01), and insight into the level of support they received was low. The majority of the participants (19/24, 79%) and their carers (20/24, 83%) had low affinity to technology, and even after the demonstration, 63% (15/24) of the participants had low interest in using the app. A breakdown of acceptability responses by app function revealed that participants were more amenable to the reminder function, the emergency feature, and a wearable form of the app. Features that centered around carers monitoring participants’ movements were reported to be less acceptable to participants.

Conclusions
This study highlights the importance of focusing on acceptability and the consumer’s perceptions in the development of assistive technology for older adults with cognitive impairment. Participants showed an aversion to functions they perceived as eroding their independence, while functions that more closely aligned with independence and autonomy were perceived as more acceptable.
Asthma Exacerbation Prediction and Risk Factor Analysis Based on a Time-Sensitive, Attentive Neural Network: Retrospective Cohort Study
Authors: Xiang Yang , Ji Hangyu , Zhou Yujia , Li Fang , Du Jingcheng , Rasmy Laila , Wu Stephen , Zheng W Jim , Xu Hua , Zhi Degui , Zhang Yaoyun , Tao Cui 
Published: July 2020

Background
Asthma exacerbation is an acute or subacute episode of progressive worsening of asthma symptoms and can have a significant impact on patients’ quality of life. However, efficient methods that can help identify personalized risk factors and make early predictions are lacking.

Objective
This study aims to use advanced deep learning models to better predict the risk of asthma exacerbations and to explore potential risk factors involved in progressive asthma.

Methods
We proposed a novel time-sensitive, attentive neural network to predict asthma exacerbation using clinical variables from large electronic health records. The clinical variables were collected from the Cerner Health Facts database between 1992 and 2015, including 31,433 adult patients with asthma. Interpretations on both patient and cohort levels were investigated based on the model parameters.

Results
The proposed model obtained an area under the curve value of 0.7003 through a five-fold cross-validation, which outperformed the baseline methods. The results also demonstrated that the addition of elapsed time embeddings considerably improved the prediction performance. Further analysis observed diverse distributions of contributing factors across patients as well as some possible cohort-level risk factors, which could be found supporting evidence from peer-reviewed literature such as respiratory diseases and esophageal reflux.

Conclusions
The proposed neural network model performed better than previous methods for the prediction of asthma exacerbation. We believe that personalized risk scores and analyses of contributing factors can help clinicians better assess the individual’s level of disease progression and afford the opportunity to adjust treatment, prevent exacerbation, and improve outcomes.
Números naturales: distintas metodologías que convergen en el análisis de su naturaleza y de cómo los entendemos
Authors: Vivanco Melisa 
Published: July 2020

José Ferreirós y Abel Lasalle Casanave (coordinadores), El árbol de los números: cognición, lógica y práctica matemática, Editorial Universidad de Sevilla, Sevilla, 2015, 256 pp.
In Amateur Athletes With Type 1 Diabetes, a 9-Day Period of Cycling at Moderate-to-Vigorous Intensity Unexpectedly Increased the Time Spent in Hyperglycemia, Which Was Associated With Impairment in Heart Rate Variability
Authors: Lespagnol Elodie , Bocock Olivia , Heyman Joris , Gamelin François-Xavier , Berthoin Serge , Pereira Bruno , Boissière Julien , Duclos Martine , Heyman Elsa 
Published: July 2020

OBJECTIVE
In type 1 diabetes, autonomic dysfunction may occur early as a decrease in heart rate variability (HRV). In populations without diabetes, the positive effects of exercise training on HRV are well-documented. However, exercise in individuals with type 1 diabetes, particularly if strenuous and prolonged, can lead to sharp glycemic variations, which can negatively impact HRV. This study explores the impact of a 9-day cycling tour on HRV in this population, with a focus on exercise-induced glycemic excursions.

RESEARCH DESIGN AND METHODS
Twenty amateur athletes with uncomplicated type 1 diabetes cycled 1,500 km. HRV and glycemic variability were measured by heart rate and continuous glucose monitoring. Linear mixed models were used to test the effects of exercise on HRV, with concomitant glycemic excursions and subject characteristics considered as covariates.

RESULTS
Nighttime HRV tended to decrease with the daily distance traveled. The more time the subjects spent in hyperglycemia, the lower the parasympathetic tone was. This result is striking given that hyperglycemic excursions progressively increased throughout the 9 days of the tour, and to a greater degree on the days a longer distance was traveled, while time spent in hypoglycemia surprisingly decreased. This phenomenon occurred despite no changes in insulin administration and a decrease in carbohydrate intake from snacks.

CONCLUSIONS
In sports enthusiasts with type 1 diabetes, multiday prolonged exercise at moderate-to-vigorous intensity worsened hyperglycemia, with hyperglycemia negatively associated with parasympathetic cardiac tone. Considering the putative deleterious consequences on cardiac risks, future work should focus on understanding and managing exercise-induced hyperglycemia.
Factors Contributing to the Rising National Cost of Glucose-Lowering Medicines for Diabetes During 2005–2007 and 2015–2017
Authors: Zhou Xilin , Shrestha Sundar S. , Shao Hui , Zhang Ping 
Published: July 2020

OBJECTIVEWe examined changes in glucose-lowering medication spending and quantified the magnitude of factors that are contributing to these changes.RESEARCH DESIGN AND METHODSUsing the Medical Expenditure Panel Survey, we estimated the change in spending on glucose-lowering medications during 2005–2007 and 2015–2017 among adults aged ≥18 years with diabetes. We decomposed the increase in total spending by medication groups: for insulin, by human and analog; and for noninsulin, by metformin, older, newer, and combination medications. For each group, we quantified the contributions by the number of users and cost-per-user. Costs were in 2017 U.S. dollars.RESULTSNational spending on glucose-lowering medications increased by $40.6 billion (240%), of which insulin and noninsulin medications contributed $28.6 billion (169%) and $12.0 billion (71%), respectively. For insulin, the increase was mainly associated with higher expenditures from analogs (156%). For noninsulin, the increase was a net effect of higher cost for newer medications (+88%) and decreased cost for older medications (−34%). Most of the increase in insulin spending came from the increase in cost-per-user. However, the increase in the number of users contributed more than cost-per-user in the rise of most noninsulin groups.CONCLUSIONSThe increase in national spending on glucose-lowering medications during the past decade was mostly associated with the increased costs for insulin, analogs in particular, and newer noninsulin medicines, and cost-per-user had a larger effect than the number of users. Understanding the factors contributing to the increase helps identify ways to curb the growth in costs.
The Effect of a Novel Low-Volume Aerobic Exercise Intervention on Liver Fat in Type 2 Diabetes: A Randomized Controlled Trial
Authors: Sabag Angelo , Way Kimberley L. , Sultana Rachelle N. , Keating Shelley E. , Gerofi James A. , Chuter Vivienne H. , Byrne Nuala M. , Baker Michael K. , George Jacob , Caterson Ian D. , Twigg Stephen M. , Johnson Nathan A. 
Published: July 2020

OBJECTIVE
The aim of this study was to examine the effect of a novel low-volume high-intensity interval training (HIIT), moderate-intensity continuous training (MICT), or placebo (PLA) intervention on liver fat, glycemia, and cardiorespiratory fitness using a randomized placebo-controlled design.

RESEARCH DESIGN AND METHODS
Thirty-five inactive adults (age 54.6 ± 1.4 years, 54% male; BMI 35.9 ± 0.9 kg/m2) with obesity and type 2 diabetes were randomized to 12 weeks of supervised MICT (n = 12) at 60% VO2peak for 45 min, 3 days/week; HIIT (n = 12) at 90% VO2peak for 4 min, 3 days/week; or PLA (n = 11). Liver fat percentage was quantified through proton MRS.

RESULTS
Liver fat reduced in MICT (−0.9 ± 0.7%) and HIIT (−1.7 ± 1.1%) but increased in PLA (1.2 ± 0.5%) (P = 0.046). HbA1c improved in MICT (−0.3 ± 0.3%) and HIIT (−0.3 ± 0.3%) but not in PLA (0.5 ± 0.2%) (P = 0.014). Cardiorespiratory fitness improved in MICT (2.3 ± 1.2 mL/kg/min) and HIIT (1.1 ± 0.5 mL/kg/min) but not in PLA (−1.5 ± 0.9 mL/kg/min) (P = 0.006).

CONCLUSIONS
MICT or a low-volume HIIT approach involving 12 min of weekly high-intensity aerobic exercise may improve liver fat, glycemia, and cardiorespiratory fitness in people with type 2 diabetes in the absence of weight loss. Further studies are required to elucidate the relationship between exercise-induced reductions in liver fat and improvements in glycemia.