bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparison of Artificial Neural Network and Decision Trees with Logistic Regression as Classification Models for Breast Cancer Survival
Authors: Mudunuru Venkateswara Rao , Skrzypek Leslaw A.
Published: August 2020

In the field of medicine, several recent studies have shown the value of Artificial Neural Networks, decision trees, logistic regression are playing a major role as the predictor, and classification methods. The research has been expanded to estimate the incidence of breast, lung, liver, ovarian, cervical, bladder and skin cancer. The main aim of this paper is to develop models of logistic regression, Artificial Neural Networks, and Decision trees using the same input and output variables and to compare their success in predicting breast cancer survival in woman. To find the best model for breast cancer survival, the sensitivity and specificity of all these models are measured and evaluated with their respective confidence intervals and the ROC values.
Chaotic Behaviour in Two-parameter Family of Transcendental Functions Associated with Exponential Map
Authors: Sajid Mohammad , Alsuwaiyan Abdullah S.
Published: August 2020

This article is devoted to the study of chaos and bifurcation in the real dynamics of a newly proposed two-parameter family of transcendental functions. We assume that one parameter is continuous and other parameter is discrete. For certain parameters, the theoretical computations of the real fixed points of a family of functions are given. The numerical simulations of the real periodic points of functions are described. The bifurcation diagrams of the real dynamics of these functions for some selected parameter values are provided. In these bifurcation diagrams, the period-doubling occurs which proceeds to a pathway toward chaos in the dynamics of functions. Further, the periodic-three window is visible in the bifurcation diagrams which implies chaos. Lastly, chaos is quantified in the dynamics of functions by calculating Lyapunov exponents.
Rank-Based Solution Methods and their Applications in Determination of Non-Dominated Points Set For A Multi-Objective Integer Programming Model
Authors: Al-Hasani Ali , Al-Rabeeah Masar , Kumar Santosh , Eberhard Andrew
Published: August 2020

For any single-objective mathematical programming model, rank-based optimal solutions are computationally difficult to find compared to an optimal solution to the same single-objective mathematical programming model. In this paper, several methods have been presented to find these rank-based optimal solutions and based on them a new rank-based solution method (RBSM) is outlined to identify non-dominated points set of a multi-objective integer programming model. Each method is illustrated by a numerical example, and for each approach, we have discussed its limitations, advantages and computational complexity.
A Mathematical Model to Assess the Material Removal Rate during Gas-Assisted Electrical Discharge Drilling Process
Authors: Singh Nishant Kumar , Singh Yashvir , Sharma Abhishek
Published: August 2020

This research work investigates the use of Gas-Assisted Electrical Discharge Drilling (GAEDD) of high carbon-chromium die steel. The poor material removal rate (MRR) is one of the profound drawbacks of the traditional Electrical Discharge Drilling (EDD) process. Hence, over the years researchers have been feeling the requisite to develop an advanced strategy that can enhance the MRR. This study has examined the utilization of compressed gas in conventional EDM under the constraint state to assess MRR. The impact of procedure parameters likedischarge current, pulse on time, duty cycle, electrode speed, and discharge gas pressure, on MRR, has been explored too. In addition, Variance Analysis (ANOVA) was performed to determine the significant parameters affecting the MRR. During the examination, a mathematical model was established MRR employing Buckingham π-theorem while the GAEDD was being applied. The experiment and anticipated values of the model show a noteworthy impact of the coefficient of thermal expansion in GAEDD of high carbon-chromium steel. In addition, the Response Surface Method (RSM) model has also been evolved. The comparative analysis of the models developed shows considerable agreement in anticipation. Moreover, the semi-empirical model appears to be even more adaptable especially in comparison to the RSM-based model. In fact, the conclusion of this work is that the dimensional analysis model is an effective and reliable strategy to precise EDD response prediction.
A Two-Stage Mutation Stochastic Model of Carcinogenesis Driven by a Two Level Random Environment
Authors: Yadavalli V. S. S. , Udayabaskaran S. , Pravina C. T. Dora , Sreelakshmi S.
Published: August 2020

In this paper, we present a two-stage stochastic model of carcinogenesis in a two level random environment. The random environment switches between two levels, say, 1 and 2 alternately. When the environment is in level 1, a normal cell either divides into two normal cells or dies; and an intermediate cell divides into two intermediate cells or dies. When the environment is in level 2, a normal cell either divides into two intermediate cells or divides into one normal cell and one intermediate cell or divides into two normal cells or dies; and an intermediate cell either divides into two malignant cells or divides into one intermediate cell and one malignant cell or divides into two intermediate cells or dies. It is assumed that, once a malignant cell is produced, it generates a malignant tumor with probability 1. We obtain the mean numbers of normal, intermediate and malignant cells.
Hybrid Binary Dragonfly Optimization Algorithm with Statistical Dependence for Feature Selection
Authors: Qasim Omar S. , Mahmoud Mohammed Sabah , Hasan Fatima Mahmood
Published: August 2020

The aim of the feature selection technique is to obtain the most important information from a specific set of datasets. Further elaborations in the feature selection technique will positively affect the classification process, which can be applied in various areas such as machine learning, pattern recognition, and signal processing. In this study, a hybrid algorithm between the binary dragonfly algorithm (BDA) and the statistical dependence (SD) is presented, whereby the feature selection method in discrete space is modeled as a binary-based optimization algorithm, guiding BDA and using the accuracy of the k-nearest neighbors classifier on the dataset to verify it in the chosen fitness function. The experimental results demonstrated that the proposed algorithm, which we refer to as SD-BDA, outperforms other algorithms in terms of the accuracy of the results represented by the cost of the calculations and the accuracy of the classification.
Genetic Algorithm Based Solution of Fuzzy Multi-Objective Transportation Problem
Authors: Sosa Jaydeepkumar M. , Dhodiya Jayesh M.
Published: August 2020

Optimizing problems in the modern era, the single objective optimization problems are insufficient to hold the full data of the problem. Therefore, multi-objective optimization problems come to the rescue. Similarly, in daily life problems, the parameters used in the optimization problem are not always fixed but there may be some uncertainty and it can characterize by fuzzy number. This work underlines the genetic algorithm (GA) based solution of fuzzy transportation problem with more than one objective. With a view to providing the multifaceted choices to decision-maker (DM), the exponential membership function is used with the decision-makers desired number of cases which consisted of shape parameter and aspiration level. Here, we consider the objective functions which are non-commensurable and conflict with each other. To interpret, evaluate and exhibit the usefulness of the proposed method, a numerical example is given.
An Optimal Approach of Adaptive Neuro -Fuzzy Inference System to Predict the Roof Ductility Demand of EBFs Subjected to Near-Fault Pulse-Like Ground Motions
Authors: Razavi Seyed Abdonnabi , Siahpolo Navid , Adeli Mehdi Mahdavi
Published: August 2020

Careful estimation of global ductility will certainly lead to greater accuracy in the design of structural members. In this paper, a new and optimal intelligent model is proposed to predict the roof ductility (μR) of EBF steel frames exposed to the near-fault pulse-like earthquakes, using the Adaptive Neuro-Fuzzy Inference System (ANFIS). To achieve this goal, a databank consisting of 12960 data is created. To establish different geometrical properties of models, 3-,6-, 9-, 12-, 15, 20-stories, steel EBF frames are considered with 3 different types of link beam, column stiffness, and brace slenderness. All models are analysed to reach 4 different performance levels using nonlinear time history under 20 near-fault earthquakes. About 6769 data are applied as ANFIS training data. Subtractive clustering and Fuzzy C-Mean clustering (FCM) methods are applied to generate the purposed model. The results show that FCM provides more accurate outcomes. Moreover, to validate the model, 2257 data are applied (as test data) in order to calculate the correlation coefficient (R) and mean squared error (MSE) between the predicted values of (μR) and the real values. The results of correlation analysis show the high accuracy of the proposed intelligent model.
Procedures for the Integration of Drones into the Airspace Based on U-Space Services
Authors: Alarcón Víctor , García Manuel , Alarcón Francisco , Viguria Antidio , Martínez Ángel , Janisch Dominik , Acevedo José Joaquín , Maza Ivan , Ollero Aníbal
Published: September 2020

A safe integration of drones into the airspace is fundamental to unblock the potential of drone applications. U-space is the drone traffic management solution for Europe, intended to handle a large number of drones in the airspace, especially at very low level (VLL). This paper presents the procedures we have designed and tested in real flights in the SAFEDRONE European project to pave the way for a safe integration of drones into the airspace using U-space services. We include three important aspects: Design of procedures related to no-fly zones, ensure separation with manned aircraft, and autonomous non-cooperative detect-and-avoid (DAA) technologies. A specific U-space architecture has been designed and implemented for flight campaigns with up to eight drones with different configurations and a manned aircraft. From this experience, specific recommendations about procedures to exit and avoiding no-fly zones are presented. Additionally, it has been concluded that the use of surveillance information of manned aircraft will allow a more efficient use of the airspace while maintaining a proper safety level, avoiding the creation of large geofence areas.
Evaluation of Changes in Glomalin-Related Soil Proteins (GRSP) Content, Microbial Diversity and Physical Properties Depending on the Type of Soil as the Important Biotic Determinants of Soil Quality
Authors: Gałązka Anna , Niedźwiecki Jacek , Grządziel Jarosław , Gawryjołek Karolina
Published: August 2020

The aim of the study was to evaluate the changes in glomalin-related soil proteins (GRSP) content, microbial diversity and soil physical quality depending on the type of soil measures of soil improvement and changes in soil health. The study was based on a 100-year stationary field microplot experiment where the soil profiles were collected with preserving the natural soil horizons. The microplot experiment was carried out on eight different soil types: Brunic Arenosol (Dystric I), Rendzic Leptosol, Fluvic Cambisol, Haplic Cambisol (Eutric), Gleyic Phaeozem, Brunic Arenosol (Dystric II), Haplic Cambisol (Eutric II) and Haplic Cambisol (Dystric). These soils are the most common types of agricultural soils in Poland. Relatively significant correlations with the soil quality, physical parameters and the glomalin-related soil proteins have been found. The study determined the total GRSP (T-GRSP) and easily extractable GRSP (EE-GRSP) levels in soils as well as the soil physical quality index and soil’s microbial biodiversity. The GRSP depended on the type of soil and correlated with S-Index and also was responsible for the unique chemical and physical properties of soils. Soils characterized by the highest T-GRSP content belonged to the group of very good and good soil physical quality characterized also by high biological activity, for which there were strong correlations with such parameters as dehydrogenase activity (DHA), microbial biomass content (MBC), microbial nitrogen content (MBN) and total bacteria number (B). The highest T-GRSP content and higher microbial diversity were found in Gleyic Phaeozem, Rendzic Leptosol and Fluvic Cambisol. The T-GRSP and EE-GRSP content were additionally correlated with the number of AMF spores. Very poor and poor soil physical quality according to S-Index characterized Brunic Arenosol (Dystric I) and Haplic Cambisol (Dystric). This research indicates that a specific edaphone of soil microorganisms and GRSP content may be of great importance when assessing a soil’s quality and improvements in soil health. The abundance of glomalin-producing fungi significantly affects the quality of the soil. This effect is particularly important for agricultural soils are threatened by ongoing land degradation.
Improving of Cherry Fruit Quality and Bearing Regularity by Chemical Thinning with Fertilizer
Authors: Kurlus Robert , Rutkowski Krzysztof , Łysiak Grzegorz P.
Published: August 2020

The study’s objective was to evaluate the influence of thinning on the quality and regularity of yield of ‘Regina’ cherries grown on a dwarf Gisela 5 rootstock. The experiments were conducted in the years 2009–2012 in Western Poland. Trees were thinned using a chemical agent, ammonium thiosulphate (ATS), at doses of 20 g ATS L−1, 30 g ATS L−1 and 40 g ATS L−1, and by hand, and the results of chemical and hand thinning were compared with those obtained for unthinned trees. The course of weather conditions in winter and during flowering had a significant impact on yield. Chemical thinning is known to be an effective method to regulate fruiting of pome trees, but it can also be successful if applied to cherry trees, as reflected by the alternate bearing index, which was the lowest after applying ATS at a dose of 40 g. ATS treatment improved fruit quality in full crop years. Thinning resulted in, among other things, larger and darker fruit and higher content of total soluble solids and titratable acidity. Treatment with 40 g ATS L−1 significantly stimulated the vegetative growth of trees.
Management of Risk Factors Associated with Chronic Oral Lesions in Sheep
Authors: Ruiz de Arcaute Marta , Lacasta Delia , González José María , Ferrer Luis Miguel , Ortega Miren , Ruiz Héctor , Ventura José Antonio , Ramos Juan José
Published: August 2020

Oral disorders constitute a significant cause of weight loss in sheep. In a study of disorders of the oral cavity of 36,033 sheep from 60 meat sheep flocks in Spain, we looked for management risk factors associated with chronic oral lesions. Mandibular and maxillary disorders were assessed as an external manifestation of oral lesions by palpation, searching for tissue swellings, fistulae, or open wounds. The prevalence of flocks containing sheep with jaw disorders was 98.3%, with an average individual prevalence of 5.5%. The majority of lesions were located in in the mid-region of the mandible, and the most relevant risk factor was increasing age. Use of acidic diets based on silage and inclusion of hard foods, such as maize straw or hay, was associated with the occurrence of jaw inflammation. It was concluded that hard diets containing plant material with edges and sharp areas, plus acidic foods including silage, are more likely to cause lesions of the gingiva, enabling entry of pathogens to the oral mucosa that eventually establish locally in bony tissues, usually as mandibular osteomyelitis. It was also observed that mineral supplementation appears to prevent the occurrence of these lesions.
A Review of Legal Regulation of Religious Slaughter in Australia: Failure to Regulate or a Regulatory Fail?
Authors: Loyer Jessica , Whittaker Alexandra L. , Buddle Emily A. , Ankeny Rachel A.
Published: August 2020

While religious slaughter is not a new practice in Australia, it has recently attracted public concern regarding questions of animal welfare following unfavourable media coverage. However, the details of religious slaughter practices, including related animal welfare provisions, appear to be poorly understood by the Australian public, and no existing literature concisely synthesises current regulations, practices, and issues. This paper addresses this gap by examining the processes associated with various types of religious slaughter and associated animal welfare issues, by reviewing the relevant legislation and examining public views, while highlighting areas for further research, particularly in Australia. The paper finds shortcomings in relation to transparency and understanding of current practices and regulation and suggests a need for more clear and consistent legislative provisions, as well as increased independence from industry in the setting of the standards, enforcement and administration of religious slaughter. A starting point for legal reform would be the relocation of important provisions pertaining to religious slaughter from delegated codes to the responsible act or regulation, ensuring proper parliamentary oversight. In addition, more active public engagement must occur, particularly with regard to what constitutes legal practices and animal welfare standards in the Australian context to overcome ongoing conflict between those who oppose religious slaughter and the Muslim and Jewish communities.
The Impacts of Animal Health Service Providers on Antimicrobial Use Attitudes and Practices: An Examination of Poultry Layer Farmers in Ghana and Kenya
Authors: Afakye Kofi , Kiambi Stella , Koka Eric , Kabali Emmanuel , Dorado-Garcia Alejandro , Amoah Ann , Kimani Tabitha , Adjei Benjamin , Caudell Mark A
Published: August 2020

International organizations and governments have argued that animal health service providers can play a vital role in limiting antimicrobial resistance by promoting the prudent use of antimicrobials. However, there is little research on the impact of these service providers on prudent use at the farm level, especially in low- and middle-income countries where enforcement of prudent-use regulations is limited. Here, we use a mixed-methods approach to assess how animal health-seeking practices on layer farms in Ghana (n = 110) and Kenya (n = 76) impact self-reported antimicrobial usage, engagement in prudent administration and withdrawal practices and perceptions of antimicrobial resistance. In general, our results show that the frequency of health-seeking across a range of service providers (veterinarians, agrovets, and feed distributors) does not significantly correlate with prudent or non-prudent use practices or the levels of antimicrobials used. Instead, we find that patterns of antimicrobial use are linked to how much farmers invest in biosecurity (e.g., footbaths) and the following vaccination protocols. Our results emphasize that more research is required to understand the interactions between animal health service providers and farmers regarding antimicrobial use and antimicrobial resistance. Addressing these gaps will be crucial to inform antimicrobial stewardship training, curriculums and, guidelines whose ultimate purpose is to limit the selection and transmission of antimicrobial resistance.
Feasibility Study of the World Health Organization Health Care Facility-Based Antimicrobial Stewardship Toolkit for Low- and Middle-Income Countries
Authors: Maki Gina , Smith Ingrid , Paulin Sarah , Kaljee Linda , Kasambara Watipaso , Mlotha Jessie , Chuki Pem , Rupali Priscilla , Singh Dipendra R. , Bajracharya Deepak C. , Barrow Lisa , Johnson Eliaser , Prentiss Tyler , Zervos Marcus
Published: August 2020

Antimicrobial stewardship (AMS) has emerged as a systematic approach to optimize antimicrobial use and reduce antimicrobial resistance. To support the implementation of AMS programs, the World Health Organization developed a draft toolkit for health care facility AMS programs in low- and middle-income countries. A feasibility study was conducted in Bhutan, the Federated States of Micronesia, Malawi, and Nepal to obtain local input on toolkit content and implementation of AMS programs. This descriptive qualitative study included semi-structured interviews with national- and facility-level stakeholders. Respondents identified AMS as a priority and perceived the draft toolkit as a much-needed document to further AMS program implementation. Facilitators for implementing AMS included strong national and facility leadership and clinical staff engagement. Barriers included lack of human and financial resources, inadequate regulations for prescription antibiotic sales, and insufficient AMS training. Action items for AMS implementation included improved laboratory surveillance, establishment of a stepwise approach for implementation, and mechanisms for reporting and feedback. Recommendations to improve the AMS toolkit’s content included additional guidance on defining the responsibilities of the committees and how to prioritize AMS programming based on local context. The AMS toolkit was perceived to be an important asset as countries and health care facilities move forward to implement AMS programs.
Characteristics and Management of Candidaemia Episodes in an Established Candida auris Outbreak
Authors: Mulet Bayona Juan V. , Tormo Palop Nuria , Salvador García Carme , Herrero Rodríguez Paz , Abril López de Medrano Vicente , Ferrer Gómez Carolina , Gimeno Cardona Concepción
Published: August 2020

The multi-resistant yeast Candida auris has become a global public health threat because of its ease to persist and spread in clinical environments, especially in intensive care units. One of the most severe manifestations of invasive candidiasis is candidaemia, whose epidemiology has evolved to more resistant non-albicansCandida species, such as C. auris. It is crucial to establish infection control policies in order to control an outbreak due to nosocomial pathogens, including the implementation of screening colonisation studies. We describe here our experience in managing a C. auris outbreak lasting more than two and a half years which, despite our efforts in establishing control measures and surveillance, is still ongoing. A total of 287 colonised patients and 47 blood stream infections (candidaemia) have been detected to date. The epidemiology of those patients with candidaemia and the susceptibility of C. auris isolates are also reported. Thirty-five patients with candidaemia (74.5%) were also previously colonised. Forty-three patients (91.5%) were hospitalised (61.7%) or had been hospitalised (29.8%) in the ICU before developing candidaemia. Antifungal therapy for candidaemia consisted of echinocandins in monotherapy or in combination with amphotericin B or isavuconazole. The most common underlying disease was abdominal surgery (29.8%). The thirty-day mortality rate was 23.4% and two cases of endophtalmitis due to C. auris were found. All isolates were resistant to fluconazole and susceptible to echinocandins and amphotericin B. One isolate became resistant to echinocandins two months after the first isolate. Although there are no established clinical breakpoints, minimum inhibitory concentrations for isavuconazole were low (≤ 1 μg/mL).
Deep Instance Segmentation of Laboratory Animals in Thermal Images
Authors: Mazur-Milecka Magdalena , Kocejko Tomasz , Ruminski Jacek
Published: August 2020

In this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal images requires smart algorithms for automatic processing of millions of thermal frames. Instance image segmentation allows to extract each animal from a frame and track its activity and thermal patterns. In this work, we adopted two instance segmentation algorithms, i.e., Mask R-CNN and TensorMask. Both methods in different configurations were applied to a set of thermal sequences, and both achieved high results. The best results were obtained for the TensorMask model, initially pre-trained on visible light images and finally trained on thermal images of rodents. The achieved mean average precision was above 90 percent, which proves that model pre-training on visible images can improve results of thermal image segmentation.
Dispersion Analysis of Periodically Loaded Transmission Lines with Twist Symmetry Using the Mode-Matching Technique
Authors: Zetterstrom Oskar , Valerio Guido , Mesa Francisco , Ghasemifard Fatemeh , Norgren Martin , Quevedo-Teruel Oscar
Published: August 2020

A mode-matching formulation is presented and used to analyze the dispersion properties of twist-symmetric transmission lines. The structures are coaxial lines periodically loaded with infinitely thin screens, which are rotated with respect to each other to possess twist symmetry. The results obtained using the proposed formulation are in good agreement with those of commercial simulators. Furthermore, using the presented mode-matching formulation, it is demonstrated that the propagation characteristics in the twist-symmetric structures are linked to the scattering and coupling of the higher order modes. The physical insight offered by this analysis is valuable for the design of various electromagnetic devices, such as filters, antennas, and phase-shifters.
Large Deformation Modeling of Wing-Like Structures Based on Support Vector Regression
Authors: An Chao , Xie Changchuan , Meng Yang , Shi Xiaofei , Yang Chao
Published: August 2020

Large flexible aircrafts produce large deformation during flight, leading to obvious geometric nonlinearities. Large deformation modeling is essential for modern aircraft design. Calculation of large deformation based on a full-order model often carries an unbearable computing burden. The reduced-order model (ROM) can be efficient in calculation but requires lots of test datasets. This study investigates support vector regression (SVR) to build a regression model to calculate the static large deformation of wing-like structures. The correlation coefficient (R) and root mean square error (RMSE) are used to evaluate the performance of the regression models. In contrast to the ROM that has been proposed, the regression model based on SVR requires far fewer training cases, with almost the same accuracy in this research. Meanwhile, comparison with another prediction model built based on random forest regression (RFR) has also been reported. The results reveal that the SVR algorithm has better accuracy on this issue. Finally, ground test results of a real large flexible wing model show that the regression model proposed here reaches a good agreement with measurement data under applied load. This work illustrates that the machine learning algorithm is an efficient and accurate way to predict large deformation of aircrafts.
CPW-Fed Transparent Antenna for Vehicle Communications
Authors: Trujillo-Flores Jorge Iván , Torrealba-Meléndez Richard , Muñoz-Pacheco Jesús Manuel , Vásquez-Agustín Marco Antonio , Tamariz-Flores Edna Iliana , Colín-Beltrán Edgar , López-López Mario
Published: August 2020

In this paper, a fully transparent multiband antenna for vehicle communications is designed, fabricated, and analyzed. The antenna is coplanar waveguide-fed to facilitate its manufacture and increase its transmittance. An indium-tin-oxide film, a type of transparent conducting oxide, is selected as the conductive material for the radiation path and ground plane, with 8 ohms/square sheet resistance. The substrate is glass with a relative permittivity of 5.5, and the overall dimensions of the optimized design are 50 mm × 17 mm × 1.1 mm. The main antenna parameters, namely, sheet resistance, reflection coefficient, and radiation diagram, were measured and compared with simulations. The proposed antenna fulfills the frequency requirements for vehicular communications according to the IEEE 802.11p standard. Additionally, it covers the frequency bands from 1.82 to 2.5 GHz for possible LTE communications applied to vehicular networks.
Harmful Effects of Ambient Nitrogen Dioxide on Atopic Dermatitis: Comparison of Exposure Assessment Based on Monitored Concentrations and Modeled Estimates
Authors: Kim Young-Min , Oh Inbo , Kim Jihyun , Kang Yoon-Hee , Ahn Kangmo
Published: August 2020

Precise exposure assessment of air pollutants is crucial in epidemiologic studies to ensure valid estimates of health effects. We conducted a longitudinal study to evaluate the role of air quality monitoring (AQM) measurements and high-resolution modeling outcomes focusing on nitrogen dioxide (NO2) exposure and atopic dermatitis (AD). A total of 128 young children with AD in Seoul Metropolitan Area, Korea, were recruited as a panel. We estimated the participants’ exposure to NO2 for four months, from 1 April through 31 July 2014 based on (1) monitored levels from 60 AQM stations located at varying distances from residential areas (AQM station-based NO2, AQM-NO2) and (2) estimates from a community multi-scale air quality (CMAQ) modeling system with a high-resolution (1 × 1 km) (CMAQ-NO2). We then compared the effect of AQM-NO2 on AD symptoms with that of CMAQ-NO2. The average distance between the participants’ residences and the nearest AQM station was 2.03 ± 1.06 km, ranging from 0.28 km to 5.73 km. Based on AQM-NO2, the AD symptoms increased by 10.28% (95% confidence interval (CI): 3.24, 17.79) with an increase of 10 ppb of NO2. The effect estimates of CMAQ-NO2 were similar to those of AQM-NO2 when assessed in patients living within 3 km from the nearest AQM station. Even within 1 km, the CI estimate obtained from the CMAQ was much narrower than from AQM (44.18–49.54 vs. 7.02–64.75). However, the association of AQM-NO2 with AD symptoms of patients living beyond 3 km was not positive, whereas that of CMAQ-NO2 maintained positive. In conclusion, exposure to ambient NO2 is significantly associated with aggravation of AD symptoms in young children. In addition, our study suggests that exposure assessment of NO2 using measurement data obtained from monitoring stations far from residential locations can lead to misclassification bias.
Can We Vacuum Our Air Pollution Problem Using Smog Towers?
Authors: Guttikunda Sarath , Jawahar Puja
Published: August 2020

In November 2019, the Supreme Court of India issued a notification to all the states in the National Capital Region of Delhi to install smog towers for clean air and allocated INR 36 crores (~USD 5.2 million) for a pilot. Can we vacuum our air pollution problem using smog towers? The short answer is “no”. Atmospheric science defines the air pollution problem as (a) a dynamic situation where the air is moving at various speeds with no boundaries and (b) a complex mixture of chemical compounds constantly forming and transforming into other compounds. With no boundaries, it is unscientific to assume that one can trap air, clean it, and release into the same atmosphere simultaneously. In this paper, we outline the basics of atmospheric science to describe why the idea of vacuuming outdoor air pollution is unrealistic, and the long view on air quality management in Indian cities.
Up- or Downregulation of Melanin Synthesis Using Amino Acids, Peptides, and Their Analogs
Authors: Boo Yong Chool
Published: September 2020

Harmonious synthesis and distribution of melanin in the skin contribute to the expression of beauty and the maintenance of health. When skin pigmentary disorders occur because of internal or external factors or, when there is a need to artificially increase or reduce the pigmentation level of the skin for aesthetic or therapeutic purposes, various pharmacological therapies are applied but the results are not always satisfactory. Studies have been conducted to improve the efficacy and safety of these treatment strategies. In this review, we present the latest studies regarding peptides and related compounds that may be useful in artificially increasing or reducing skin melanin levels. Certain analogs of α-melanocyte stimulating hormone (MSH) and oligopeptides with the sequences derived from the hormone were shown to promote melanin synthesis in cells and in vivo models. Various amino acids, peptides, their analogs, and their hybrid compounds with other chemical moieties were shown to inhibit tyrosinase (TYR) catalytic activity or downregulate TYR gene expression. Certain peptides were shown to inhibit melanosome biogenesis or induce autophagy, leading to decreased pigmentation. In vivo and clinical evidence are available for some compounds, including [Nle4-D-Phe7]-α-MSH, glutathione disulfide, and glycinamide hydrochloride. For many other compounds, additional studies are required to verify their efficacy and safety in vivo and in clinical trials. The accumulating information regarding pro- and antimelanogenic activity of peptides and related compounds will lead to the development of novel drugs for the treatment of skin pigmentary disorders.
Emotional Education in Early Onset Schizophrenia and Asperger’s Syndrome
Authors: Frolli Alessandro , Ricci Maria Carla , Tortorelli Francesco Alberto , Cavallaro Antonella , Valenzano Luana , Rega Angelo , Operto Francesca Felicia , Corrivetti Giulio
Published: August 2020

In this study, we aim to verify how emotional training can improve empathy and theory of mind (ToM) in patients diagnosed with early onset schizophrenia and Asperger’s syndrome. The study design includes 100 subjects divided into two experimental groups and two control groups. The two experimental groups followed a rational emotive behavior therapy (REBT) protocol. The two control groups instead underwent cognitive behavioral psychotherapy training. Analysis of Variance (ANOVA) was applied to analyze the difference between the Asperger’s syndrome (AS) and early onset schizophrenia (EOS) groups, pre and post training. Our analysis shows that the AS group improved post emotional training but only when emotions were internalized, as demonstrated by the improvement of the scores in the post-treatment eye test (ET) but not in the emotional quotient (EQ) test. The EOS group instead showed post-training improvement, not only concerning skills leading to internalizing emotions but also in empathy, as demonstrated by the improvement of EQ and Reflective Functioning Questionnaire (RFQ) test scores. These scores remained lower than in the control group. Finally, our findings reveal that the value of the treatment was more considerable for the EOS group than for the AS group due to the improvement in first- and second-order ToM skills and an improvement of empathic skills in the first group, followed by the group comprising AS subjects. In the AS group, the treatment only favored the enhancement of first-order ToM skills; however, this improved quality of life and social adaptation.
Radiomics at a Glance: A Few Lessons Learned from Learning Approaches
Authors: Capobianco Enrico , Deng Jun
Published: August 2020

Processing and modeling medical images have traditionally represented complex tasks requiring multidisciplinary collaboration. The advent of radiomics has assigned a central role to quantitative data analytics targeting medical image features algorithmically extracted from large volumes of images. Apart from the ultimate goal of supporting diagnostic, prognostic, and therapeutic decisions, radiomics is computationally attractive due to specific strengths: scalability, efficiency, and precision. Optimization is achieved by highly sophisticated statistical and machine learning algorithms, but it is especially deep learning that stands out as the leading inference approach. Various types of hybrid learning can be considered when building complex integrative approaches aimed to deliver gains in accuracy for both classification and prediction tasks. This perspective reviews some selected learning methods by focusing on both their significance for radiomics and their unveiled potential.
Investigating the Role of Methylation in Silencing of VDR Gene Expression in Normal Cells during Hematopoiesis and in Their Leukemic Counterparts
Authors: Nowak Urszula , Janik Sylwia , Marchwicka Aleksandra , Łaszkiewicz Agnieszka , Jakuszak Agnieszka , Cebrat Małgorzata , Marcinkowska Ewa
Published: August 2020

(1) Background: Vitamin D receptor (VDR) is present in multiple types of blood cells, and its ligand, 1,25-dihydroxyvitamin D (1,25D), is important for the proper functioning of the immune system. Activity of VDR is higher in hematopoietic stem and progenitor cells than in fully differentiated blood cells of mice and humans. In some human acute myeloid leukemia (AML) blasts, the expression of the VDR gene is also high. The mechanism of silencing the VDR gene expression during differentiation of blood cells has been addressed in this work. (2) Methods: The cells have been obtained using fluorescence activated sorting from murine tissues and from human umbilical cord blood (UCB). Then, the expression of the VDR gene and transcriptional activity of the VDR protein has been tested in real-time polymerase chain reaction (PCR). Eventually, the methylation of VDR promoter regions was tested using bisulfite sequencing. (3) Results: The CpG islands in VDR promoters were not methylated in the cells studied both in mice and in humans. The use of hypomethylating agents had no effect toward expression of human VDR transcripts, but it increased expression of the VDR-target gene, CYP24A1. (4) Conclusions: The expression of the VDR gene and transcriptional activity of the VDR protein varies at successive stages of hematopoietic differentiation in humans and mice, and in blasts from AML patients. The experiments presented in this case indicate that methylation of the promoter region of the VDR gene is not the major mechanism responsible for these differences.
Adipose-Derived Stromal/Stem Cells
Authors: Baer Patrick C.
Published: August 2020

Adipose tissue is a rich, ubiquitous, and easily accessible source for multipotent mesenchymal stromal/stem cells (MSCs), so-called adipose-derived stromal/stem cells (ASCs) [...]
Quantifying the Language Barrier—A Total Survey of Parents’ Spoken Languages and Local Language Skills as Perceived by Different Professions in Pediatric Palliative Care
Authors: Dreier Larissa Alice , Zernikow Boris , Wager Julia
Published: September 2020

To date, there are no specific figures on the language-related characteristics of families receiving pediatric palliative care. This study aims to gain insights into the languages spoken by parents, their local language skills and the consistency of professional assessments on these aspects. Using an adapted version of the “Common European Framework of Reference for Languages”, the languages and local language skills of parents whose children were admitted to an inpatient pediatric palliative care facility (N = 114) were assessed by (a) medical staff and (b) psychosocial staff. Nearly half of the families did not speak the local language as their mother tongue. The most frequently spoken language was Turkish. Overall, the medical staff attributed better language skills to parents than the psychosocial staff did. According to them, only 27.0% of mothers and 38.5% of fathers spoke the local language at a high level while 37.8% of mothers and 34.6% of fathers had no or rudimentary language skills. The results provide important information on which languages pediatric palliative care practitioners must be prepared for. They sensitize to the fact that even within an institution there can be discrepancies between the language assessments of different professions.
Mindfulness and Smartphone Addiction before Going to Sleep among College Students: The Mediating Roles of Self-Control and Rumination
Authors: Cheng Shi-Shi , Zhang Chun-Qing , Wu Jiang-Qiu
Published: August 2020

This study aims to examine the effects among college students of mindfulness on smartphone addiction before going to bed at night. We examined the mediating roles of self-control and rumination on the mindfulness–smartphone addiction path. Participants (n = 270, 59.3% females, 18–24 years old) completed self-reporting questionnaires measuring mindfulness, self-control, smartphone addiction, and rumination. In addition to the correlation analysis, we adopted a stepwise regression analysis with bootstrapping to test the mediating effects. It was found that mindfulness was inversely related to smartphone addiction before going to sleep. Most importantly, self-control and rumination significantly mediated the effects of mindfulness on smartphone addiction among college students. The findings of this study indicated that mindfulness training is beneficial to improve the ability of self-control and reduce rumination levels, thereby inhibiting the negative impact of smartphone addiction on college students before they go to sleep, and further promoting their sleep health and mental health.
Dataset of Nile Red Fluorescence Readings with Different Yeast Strains, Solvents, and Incubation Times
Authors: Ramirez-Castrillon Mauricio , Jaramillo-Garcia Victoria , Barros Helio , Henriques João , Stefani Valter , Valente Patricia
Published: September 2020

We used Nile red to estimate lipid content in oleaginous yeasts using a high-throughput approach. We measured the fluorescence intensity of Nile red using different solvents, yeast strains, and incubation times in optimized excitation/emission wavelengths. The data show the relative fluorescence units (RFU) for Nile red excitation, using 1× PBS, 1× PBS and 5% v/v isopropyl alcohol, 50% v/v glycerol, culture medium A-gly broth, and A-gly broth supplemented with 5% v/v DMSO. In addition, we showed the RFU for the Nile red dye for different oleaginous and non-oleaginous yeast strains, such as Meyerozyma guilliermondii BI281A, Yarrowia lipolytica QU21 and Saccharomyces cerevisiae MRC164. Other measurements of lipid accumulation kinetics were shown for the above and additional yeast strains. These datasets provide the guidelines to obtain the optimal solvent system and the minimal interaction time for the Nile red dye to enter in the cells and obtain a stable readout.
The Microbiome as a Therapeutic Target for Multiple Sclerosis: Can Genetically Engineered Probiotics Treat the Disease?
Authors: Kohl Hannah M. , Castillo Andrea R. , Ochoa-Repáraz Javier
Published: August 2020

There is an increasing interest in the intestinal microbiota as a critical regulator of the development and function of the immune, nervous, and endocrine systems. Experimental work in animal models has provided the foundation for clinical studies to investigate associations between microbiota composition and function and human disease, including multiple sclerosis (MS). Initial work done using an animal model of brain inflammation, experimental autoimmune encephalomyelitis (EAE), suggests the existence of a microbiota–gut–brain axis connection in the context of MS, and microbiome sequence analyses reveal increases and decreases of microbial taxa in MS intestines. In this review, we discuss the impact of the intestinal microbiota on the immune system and the role of the microbiome–gut–brain axis in the neuroinflammatory disease MS. We also discuss experimental evidence supporting the hypothesis that modulating the intestinal microbiota through genetically modified probiotics may provide immunomodulatory and protective effects as a novel therapeutic approach to treat this devastating disease.
Insights Before Flights: How Community Perceptions Can Make or Break Medical Drone Deliveries
Authors: Truog Susan , Maxim Luciana , Matemba Charles , Blauvelt Carla , Ngwira Hope , Makaya Archimede , Moreira Susana , Lawrence Emily , Ailstock Gabriella , Weitz Andrea , West Melissa , Defawe Olivier
Published: August 2020

Drones are increasingly used to transport health products, but life-saving interventions can be stalled if local community concerns and preferences are not assessed and addressed. In order to inform the introduction of drones in new contexts, this paper analyzed similarities and differences in community perceptions of medical delivery drones in Malawi, Mozambique, the Democratic Republic of the Congo (DRC) and the Dominican Republic (DR). Community perceptions were assessed using focus group discussions (FGDs) and key informant interviews (KIIs) conducted with stakeholders at the national level, at health facilities and in communities. Data were collected on respondents’ familiarity with drones, perceptions of benefits and risks of drones, advice on drone operations and recommendations on sharing information with the community. The comparative analysis found similar perceptions around the potential benefits of using drones, as well as important differences in the perceived risks of flying drones and culturally appropriate communication mechanisms based on the local context. Because community perceptions are heavily influenced by culture and local experiences, a similar assessment should be conducted before introducing drone activities in new areas and two-way feedback channels should be established once drone operations are established in an area. The extent to which a community understands and supports the use of drones to transport health products will ultimately play a critical role in the success or failure of the drone’s ability to bring life-saving products to those who need them.
Thermophoretic Micron-Scale Devices: Practical Approach and Review
Authors: Lee Namkyu , Wiegand Simone
Published: August 2020

In recent years, there has been increasing interest in the development of micron-scale devices utilizing thermal gradients to manipulate molecules and colloids, and to measure their thermophoretic properties quantitatively. Various devices have been realized, such as on-chip implements, micro-thermogravitational columns and other micron-scale thermophoretic cells. The advantage of the miniaturized devices lies in the reduced sample volume. Often, a direct observation of particles using various microscopic techniques is possible. On the other hand, the small dimensions lead to some technical problems, such as a precise temperature measurement on small length scale with high spatial resolution. In this review, we will focus on the “state of the art” thermophoretic micron-scale devices, covering various aspects such as generating temperature gradients, temperature measurement, and the analysis of the current micron-scale devices. We want to give researchers an orientation for their development of thermophoretic micron-scale devices for biological, chemical, analytical, and medical applications.