bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Environmental Factors on Academic Performance of University Students Taking Online Classes during the COVID-19 Pandemic in Mexico
Authors: Realyvásquez-Vargas Arturo , Maldonado-Macías Aidé Aracely , Arredondo-Soto Karina Cecilia , Baez-Lopez Yolanda , Carrillo-Gutiérrez Teresa , Hernández-Escobedo Guadalupe
Published: November 2020

The COVID-19 pandemic and the quarantine period determined that university students (human resource) in Mexico had adopted the online class modality, which required them to adapt themselves to new technologies and environmental conditions that are different from classrooms at their university. Specifically, these new environmental conditions can be uncomfortable and have an impact on the students’ academic performance. Consequently, the present study aims to determine the impact that the lighting, noise, and temperature levels (independent variables) have on academic performance (dependent variable) in university students during the COVID-19 pandemic. To do this, a questionnaire was developed, which was applied to 206 university students online, and a structural equation model was built that integrates the four variables through three hypotheses, which were statistically validated through the partial least squares method. Results showed that temperature, lighting, and noise have significant direct effects on university students’ academic performance. As a conclusion, it was obtained that the three independent variables have an impact in the sustainability of university students (human resource).
A Smart Campus’ Digital Twin for Sustainable Comfort Monitoring
Authors: Zaballos Agustín , Briones Alan , Massa Alba , Centelles Pol , Caballero Víctor
Published: November 2020

Interdisciplinary cross-cultural and cross-organizational research offers great opportunities for innovative breakthroughs in the field of smart cities, yet it also presents organizational and knowledge development hurdles. Smart cities must be large towns able to sustain the needs of their citizens while promoting environmental sustainability. Smart cities foment the widespread use of novel information and communication technologies (ICTs); however, experimenting with these technologies in such a large geographical area is unfeasible. Consequently, smart campuses (SCs), which are universities where technological devices and applications create new experiences or services and facilitate operational efficiency, allow experimentation on a smaller scale, the concept of SCs as a testbed for a smart city is gaining momentum in the research community. Nevertheless, while universities acknowledge the academic role of a smart and sustainable approach to higher education, campus life and other student activities remain a mystery, which have never been universally solved. This paper proposes a SC concept to investigate the integration of building information modeling tools with Internet of Things- (IoT)-based wireless sensor networks in the fields of environmental monitoring and emotion detection to provide insights into the level of comfort. Additionally, it explores the ability of universities to contribute to local sustainability projects by sharing knowledge and experience across a multi-disciplinary team. Preliminary results highlight the significance of monitoring workspaces because productivity has been proven to be directly influenced by environment parameters. The comfort-monitoring infrastructure could also be reused to monitor physical parameters from educational premises to increase energy efficiency.
“Following the Science”: In Search of Evidence-Based Policy for Indoor Air Pollution from Radon in Ireland
Authors: Lacchia Anthea R. , Schuitema Geertje , Banerjee Aparajita
Published: November 2020

Radon, a naturally occurring radioactive gas that can accumulate inside dwellings, represents the second biggest cause of lung cancer globally. In Ireland, radon is linked to approximately 300 lung cancer cases every year, equating to 12% of all lung cancer deaths. Despite the health risks posed by radon air pollution, Ireland lacks well-defined and universally applicable air pollution-related public health policies. Through purposive literature sampling, we critically examine the case of indoor radon policy development in Ireland. Specifically, we analyse the evidence-based policymaking process relating to indoor radon pollution from three different knowledge dimensions, namely political, scientific, and practical knowledge. In doing so, we identify various challenges inherent to pollution-related public policymaking. We highlight the difficulties of balancing and integrating information from multiple disciplines and perspectives and argue that input from multiple scientific areas is crucial, but can only be achieved through continued, dialogic communication between stakeholders. On the basis of our analysis, we suggest that a transdisciplinary perspective, defined as a holistic approach which subordinates disciplines and looks at the dynamics of whole systems, will allow evidence-based policymaking to be effective. We end with recommendations for evidence-based policymaking when it comes to public health hazards such as radon, which are applicable to sustainable air pollution management beyond Ireland.
How to Shape an Organization’s Sustainable Green Management Performance: The Mediation Effect of Environmental Corporate Social Responsibility
Authors: Chang Tai-Wei , Yeh Yen-Li , Li Hung-Xin
Published: November 2020

Corporate social responsibility (CSR), a current mainstream issue in global corporate governance, is often used to verify a company’s financial performance and corporate image; however, few studies have focused on CSR for environmental issues. On the basis of the perspectives of the expectation value and signal theories, this study presents a new concept for determining the impact of green shared vision (GSV) on employee environmental performance (EEP) and green product development performance (GPDP), which could aid in exploring the GSV–environmental CSR (ECSR) relationship further. The current results demonstrated that ECSR contributes to enhancing EEP and GPDP. Therefore, enterprises must implement the promotion of ECSR to enhance their overall green management performance and achieve sustainable management.
Sustainability of Heritage Tourism: A Structural Perspective from Cultural Identity and Consumption Intention
Authors: Zhang Gege , Chen Xiaoyuan , Law Rob , Zhang Mu
Published: November 2020

Intangible cultural heritage can provide cultural value content for product development and marketing of tourism destinations, enabling these areas to obtain economic benefits. This study selects cultural identity as an antecedent variable, and applies the theory of planned behavior to construct the influence mechanism of cultural identity on tourists’ consumption intention in heritage tourism. In tourism development, visitors and local residents have reached a common cognitive basis for Kunqu Opera through cultural identity, thereby guiding consumer behavior and promoting the continuous development of Kunqu Opera tourism. This study takes Suzhou Kunqu Opera as a research object, designs a questionnaire for local residents and tourists, establishes a structural equation model, and explores the relationship between various impact factors. The results of the study show that cultural identity has a positive effect on consumption intentions in heritage tourism activities, confirming that cultural identity is an effective driving force to promote tourists’ consumption intention. Behavioral attitudes, subjective norms, and perceived behavioral control have a positive effect on consumption intentions. This study supplements the existing knowledge on tourists’ consumption intention in intangible cultural heritage destinations. The study also provides new insights to enhance the consumption intention and achieve long-term sustainable development of the destination.
Functional Autonomy Evaluation Levels in Middle-Aged and Older Spanish Women: On Behalf of the Healthy-Age Network
Authors: Marcos-Pardo Pablo Jorge , González-Gálvez Noelia , Vaquero-Cristóbal Raquel , Gea-García Gemma María , López-Vivancos Abraham , Espeso-García Alejandro , Velázquez-Díaz Daniel , Carbonell-Baeza Ana , Jiménez-Pavón David , Brandão Pinto de Castro Juliana , Vale Rodrigo Gomes de Souza
Published: November 2020

Aging is associated with a progressive loss of functional capacity that affects the health and quality of life of middle-aged and older people. The purpose of this study was to report functional autonomy evaluation levels in middle-aged and older women in the Spanish context. A total of 709 middle-aged and older women, between 50 and 90 years old, were selected to participate in the study. The sample was divided by age category every five years. The functional autonomy levels were determined by the Latin American Group for Maturity (GDLAM) protocol and we developed a classification pattern for middle-aged and older women living in Spain. The GDLAM Index (GI) was then calculated to assess functional autonomy. The classification of the tests and the GI followed the percentile rank (P) Very Good (p < 0.15), Good (p 0.16–p 0.50), Regular (p 0.51–p 0.85), and Poor (p > 0.85). It was considered that the lower the value found for the percentile, the better the result. The GDLAM protocol showed strong reliability with intraclass correlation coefficient (ICC) values greater than 0.92 in all tests. It is observed that all variables of the GDLAM protocol presented a positive and significant correlation with age (p < 0.001). The Roc Curve showed that GI values higher than 26 (CI95% = 0.97–1.00; p < 0.001) and 32 (CI95% = 0.98–1.00; p < 0.001) for middle-aged and elderly women, respectively, can predict and indicate low functional autonomy. The normative values hereby provided will enable evaluation and adequate interpretation of Spanish middle-aged and older women’s functional autonomy.
The Effect of Retail Electricity Price Levels on the FI Values of Smart-Grid Rooftop Solar Power Systems: A Case Study in the Central Highlands of Vietnam
Authors: Lan Tran Thi , Jirakiattikul Sopin , Chowdhury M. S. , Ali Dilawer , Niem Le Duc , Techato Kuaanan
Published: November 2020

Smart-grid rooftop solar electricity (SG rooftop PV) is an alternative sustainable energy resource. This research was conducted in the Central Highlands of Vietnam (CHV) in light of the different levels of retail electricity pricing, the sunshine duration, and the implementation of a feed-in-tariff system, in order to calculate the financial indicators (FIs) of SG rooftop PV, which would supply investors, companies supplying SG rooftop PV, and policymakers with useful information. The FI values were calculated based on the net present value, the payback period, and the internal return rate. The results show that the electricity retail price level affects the FI of SG rooftop PV. SG rooftop PV is installed to satisfy higher electricity consumption levels, which attracts a higher retail electricity price. As a result of the greater benefits, especially if SG rooftop PV is installed and the highest level of electricity (exceeds 400 kWh) is used to satisfy domestic consumption, users will recoup their investment in only four years and after that will enjoy free electricity. All the FI values derived from this research show that people in the CHV can derive benefits from installing SG rooftop PV.
An Integrated Approach to Optimal Charging Scheduling of Electric Vehicles Integrated with Improved Medium-Voltage Network Reconfiguration for Power Loss Minimization
Authors: Amin Adil , Tareen Wajahat Ullah Khan , Usman Muhammad , Memon Kamran Ali , Horan Ben , Mahmood Anzar , Mekhilef Saad
Published: November 2020

The uncoordinated integration of electric vehicles (EVs) severely deteriorates the operational performance of a distribution network. To optimize distribution network performance in an EV charging environment, this paper presents a two-stage optimization approach, which integrates coordinated EV charging with network reconfiguration. A formulation to minimize system power loss is presented, and an optimal solution is obtained using a binary particle swarm optimization algorithm. The proposed approach is tested on a modified IEEE 33-bus medium-voltage node test system, coupled with a low voltage distribution network. Results of the coordinated and uncoordinated EV charging are compared with those of the developed integrated approach, and the operational performance of the system is studied. The results show that the integration of network reconfiguration with coordinated EV charging significantly decreases network power losses and fairly improves voltage profile. Thus, the proposed strategy can lead to improved operational performance of the system while dealing with the growing penetration of EVs in the network.
Computing Nearest Correlation Matrix via Low-Rank ODE’s Based Technique
Authors: Rehman Mutti-Ur , Alzabut Jehad , Abodayeh Kamaleldin
Published: November 2020

For n-dimensional real-valued matrix A, the computation of nearest correlation matrix; that is, a symmetric, positive semi-definite, unit diagonal and off-diagonal entries between −1 and 1 is a problem that arises in the finance industry where the correlations exist between the stocks. The proposed methodology presented in this article computes the admissible perturbation matrix and a perturbation level to shift the negative spectrum of perturbed matrix to become non-negative or strictly positive. The solution to optimization problems constructs a gradient system of ordinary differential equations that turn over the desired perturbation matrix. Numerical testing provides enough evidence for the shifting of the negative spectrum and the computation of nearest correlation matrix.
Central Splitting of A2 Discrete Fourier–Weyl Transforms
Authors: Hrivnák Jiří , Myronova Mariia , Patera Jiří
Published: November 2020

Two types of bivariate discrete weight lattice Fourier–Weyl transforms are related by the central splitting decomposition. The two-variable symmetric and antisymmetric Weyl orbit functions of the crystallographic reflection group A2 constitute the kernels of the considered transforms. The central splitting of any function carrying the data into a sum of components governed by the number of elements of the center of A2 is employed to reduce the original weight lattice Fourier–Weyl transform into the corresponding weight lattice splitting transforms. The weight lattice elements intersecting with one-third of the fundamental region of the affine Weyl group determine the point set of the splitting transforms. The unitary matrix decompositions of the normalized weight lattice Fourier–Weyl transforms are presented. The interpolating behavior and the unitary transform matrices of the weight lattice splitting Fourier–Weyl transforms are exemplified.
Hmong Textiles, Symmetries, Perception and Culture
Authors: Magliveras Simeon S.
Published: November 2020

As part of this Special Issue, this paper attempts to add to a reflexive discussion and confront the simplistic understanding of why humans construct symmetries. This paper examines Hmong textiles called paj ntaub. The Hmong became a transnational people due to happenstance and the Vietnam War. Despite great trials and tribulations, the Hmong people and their art and culture survived. They express themselves and their identity through oral traditions and cultural practices, one of which is their textiles. The old textile styles, known as paj ntaub, are non-representational symmetric designs. The research for this paper was done in Laos. Grounded research, textual analysis and participant observation were the methods used. Though their textiles are a salient part of Hmong culture, little work has been done on the ontology of paj ntaub. This paper proposes a novel perspective to examining the paj ntaub by using anthropological symmetry, the gestalt theory on perception, and ethnographic analysis of the culture, meanings, and choices in design embedded in the textiles, as well as the process of making of the paj ntaub. This work proposes that the paj ntaub is not merely an expression of identity but a holistic expression in Hmong culture and reflects their relationship to their world.
Solar Irradiance Forecasting Based on Deep Learning Methodologies and Multi-Site Data
Authors: Brahma Banalaxmi , Wadhvani Rajesh
Published: November 2020

The ever-growing interest in and requirement for green energy have led to an increased focus on research related to forecasting solar irradiance recently. This study aims to develop forecast models based on deep learning (DL) methodologies and multiple-site data to predict the daily solar irradiance in two locations of India based on the daily solar radiation data obtained from NASA’s POWER project repository over 36 years (1983–2019). The forecast modeling of solar irradiance data is performed for extracting and learning the symmetry latent in data patterns and relationships by the machine learning models and utilizing it to predict future solar data. The goodness of fit and model performance are compared with rolling window evaluation using mean squared error, root-mean-square error and coefficient of determination (R2) for evaluation. The contributions of this study can be summarized as follows: (i) time series models based on deep learning methodologies were implemented to forecast the daily solar irradiance of two locations in India in consideration of the historical data collected by NASA; (ii) the models were developed on the basis of single-location univariate data as well as multiple-location data; (iii) the accuracy, performance and reliability of the model were investigated on the basis of standard performance evaluation metrics and rolling window evaluation; (iv) the feature importance of the nearby locations with respect to forecasting target location solar irradiance was analyzed and compared based on the solar irradiance data obtained from NASA over 36 years. The results indicate that the bidirectional long short-term memory (LSTM) and attention-based LSTM models can be used for forecasting daily solar irradiance data. According to the findings, the multiple-site data with solar irradiance historical data improve upon the forecast performance of single-location univariate solar data.
Modified Jacobi-Gradient Iterative Method for Generalized Sylvester Matrix Equation
Authors: Sasaki Nopparut , Chansangiam Pattrawut
Published: November 2020

We propose a new iterative method for solving a generalized Sylvester matrix equation A1XA2+A3XA4=E with given square matrices A1,A2,A3,A4 and an unknown rectangular matrix X. The method aims to construct a sequence of approximated solutions converging to the exact solution, no matter the initial value is. We decompose the coefficient matrices to be the sum of its diagonal part and others. The recursive formula for the iteration is derived from the gradients of quadratic norm-error functions, together with the hierarchical identification principle. We find equivalent conditions on a convergent factor, relied on eigenvalues of the associated iteration matrix, so that the method is applicable as desired. The convergence rate and error estimation of the method are governed by the spectral norm of the related iteration matrix. Furthermore, we illustrate numerical examples of the proposed method to show its capability and efficacy, compared to recent gradient-based iterative methods.
Comparative Analysis of Supervised and Unsupervised Approaches Applied to Large-Scale “In The Wild” Face Verification
Authors: Hachaj Tomasz , Mazurek Patryk
Published: November 2020

Deep learning-based feature extraction methods and transfer learning have become common approaches in the field of pattern recognition. Deep convolutional neural networks trained using tripled-based loss functions allow for the generation of face embeddings, which can be directly applied to face verification and clustering. Knowledge about the ground truth of face identities might improve the effectiveness of the final classification algorithm; however, it is also possible to use ground truth clusters previously discovered using an unsupervised approach. The aim of this paper is to evaluate the potential improvement of classification results of state-of-the-art supervised classification methods trained with and without ground truth knowledge. In this study, we use two sufficiently large data sets containing more than 200,000 “taken in the wild” images, each with various resolutions, visual quality, and face poses which, in our opinion, guarantee the statistical significance of the results. We examine several clustering and supervised pattern recognition algorithms and find that knowledge about the ground truth has a very small influence on the Fowlkes–Mallows score (FMS) of the classification algorithm. In the case of the classification algorithm that obtained the highest accuracy in our experiment, the FMS improved by only 5.3% (from 0.749 to 0.791) in the first data set and by 6.6% (from 0.652 to 0.718) in the second data set. Our results show that, beside highly secure systems in which face verification is a key component, face identities discovered by unsupervised approaches can be safely used for training supervised classifiers. We also found that the Silhouette Coefficient (SC) of unsupervised clustering is positively correlated with the Adjusted Rand Index, V-measure score, and Fowlkes–Mallows score and, so, we can use the SC as an indicator of clustering performance when the ground truth of face identities is not known. All of these conclusions are important findings for large-scale face verification problems. The reason for this is the fact that skipping the verification of people’s identities before supervised training saves a lot of time and resources.
Discrepancy between Power Radiated and the Power Loss Due to Radiation Reaction for an Accelerated Charge
Authors: Singal Ashok K.
Published: November 2020

We examine here the discrepancy between the radiated power, calculated from the Poynting flux at infinity, and the power loss due to radiation reaction for an accelerated charge. It is emphasized that one needs to maintain a clear distinction between the electromagnetic power received by distant observers and the mechanical power loss undergone by the charge. In the literature, both quantities are treated as almost synonymous; the two in general could, however, be quite different. It is shown that in the case of a periodic motion, the two formulations do yield the power loss in a time averaged sense to be the same, even though, the instantaneous rates are quite different. It is demonstrated that the discordance between the two power formulas merely reflects the difference in the power going in self-fields of the charge between the retarded and present times. In particular, in the case of a uniformly accelerated charge, power going into the self-fields at the present time is equal to the power that was going into the self-fields at the retarded time plus the power going in acceleration fields, usually called radiation. From a study of the fields in regions far off from the time retarded positions of the uniformly accelerated charge, it is shown that effectively the fields, including the acceleration fields, remain around the ‘present’ position of the charge which itself is moving toward infinity due to its continuous constant acceleration, with no other Poynting flow that could be termed as ‘radiation emitted’ by the charge.
Influence of the Replacement of the Actual Plastic Orthotropy with Various Approximations of Normal Anisotropy on Residual Stresses and Strains in a Thin Disk Subjected to External Pressure
Authors: Erisov Yaroslav , Surudin Sergei , Alexandrov Sergei , Lang Lihui
Published: November 2020

Plastic anisotropy is very common to metallic materials. This property may significantly affect the performance of structures. However, the actual orthotropic yield criterion is often replaced with a criterion based on the assumption of normal anisotropy. The present paper aims to reveal the influence of this replacement on the distribution of strains and residual strains in a thin hollow disk under plane stress conditions. The boundary-value problem is intentionally formulated such that it is possible to obtain an exact semi-analytical solution without relaxing the boundary conditions. It is assumed that the disk is loaded by external pressure, followed by elastic unloading. The comparative analysis of the distributions of residual strains shows a significant deviation of the distribution resulting from the solutions based on the assumption of normal anisotropy from the distribution found using the actual orthotropic yield criterion. This finding shows that replacing the actual orthotropic yield criterion with the assumption of normal anisotropy may result in very inaccurate predictions. The type of anisotropy accepted is of practical importance because it usually results from such processes as drawing end extrusion with an axis of symmetry.
ART-Treated Patients Exhibit an Adaptive Immune Response against the HFVAC Peptides, a Potential HIV-1 Therapeutic Vaccine (Provir/Latitude45 Study)
Authors: Fleury Hervé , Caldato Sabrina , Recordon-Pinson Patricia , Thebault Patricia , Guidicelli Gwenda-Line , Hessamfar Mojgan , Morlat Philippe , Bonnet Fabrice , Visentin Jonathan
Published: November 2020

We proposed a new HIV-1 therapeutic vaccine based on conserved cytotoxic T lymphocyte (CTL) epitopes of archived HIV-1 DNA according to their affinity to the dominant HLA-A and -B alleles of the population investigated. Our proposal (Hla Fitted VAC, HFVAC) was composed of 15 peptides originating from the RT, gag and nef parts of proviral DNA. Our aim was to investigate baseline immune reactivity to the vaccine in HIV-1 chronically infected patients at success of antiretroviral therapy (ART) who would be eligible for a therapeutic vaccine. Forty-one patients were tested. Most of them had been infected with HIV-1 subtype B and all had been receiving successful ART for 2 to 20 years. The predominant HLA-A and -B alleles were those of a Caucasian population. ELISPOT was carried out using the HFVAC peptides. In 22 patients, the PD-1 marker was investigated on CD4+ and CD8+ T cells by flow cytometry in order to evaluate global T cell exhaustion. ELISPOT positivity was 65% overall and 69% in patients exhibiting at least one HLA allele fitting with HFVAC. The percentages of CD4+ and CD8+ T cells expressing PD-1 were high (median values 23.70 and 32.60, respectively), but did not seem to be associated with an impairment of the immune response investigated in vitro. In conclusion, reactivity to HFVAC was high in this ART-treated population with dominant HLA alleles, despite potential cellular exhaustion associated with the PD-1 marker.
Monkeypox Virus in Nigeria: Infection Biology, Epidemiology, and Evolution
Authors: Alakunle Emmanuel , Moens Ugo , Nchinda Godwin , Okeke Malachy Ifeanyi
Published: November 2020

Monkeypox is a zoonotic disease caused by monkeypox virus (MPXV), which is a member of orthopoxvirus genus. The reemergence of MPXV in 2017 (at Bayelsa state) after 39 years of no reported case in Nigeria, and the export of travelers’ monkeypox (MPX) from Nigeria to other parts of the world, in 2018 and 2019, respectively, have raised concern that MPXV may have emerged to occupy the ecological and immunological niche vacated by smallpox virus. This review X-rays the current state of knowledge pertaining the infection biology, epidemiology, and evolution of MPXV in Nigeria and worldwide, especially with regard to the human, cellular, and viral factors that modulate the virus transmission dynamics, infection, and its maintenance in nature. This paper also elucidates the role of recombination, gene loss and gene gain in MPXV evolution, chronicles the role of signaling in MPXV infection, and reviews the current therapeutic options available for the treatment and prevention of MPX. Additionally, genome-wide phylogenetic analysis was undertaken, and we show that MPXV isolates from recent 2017 outbreak in Nigeria were monophyletic with the isolate exported to Israel from Nigeria but do not share the most recent common ancestor with isolates obtained from earlier outbreaks, in 1971 and 1978, respectively. Finally, the review highlighted gaps in knowledge particularly the non-identification of a definitive reservoir host animal for MPXV and proposed future research endeavors to address the unresolved questions.
Metagenomic Analysis of the Enteric RNA Virome of Infants from the Oukasie Clinic, North West Province, South Africa, Reveals Diverse Eukaryotic Viruses
Authors: Mogotsi Milton T. , Mwangi Peter N. , Bester Phillip A. , Mphahlele M. Jeffrey , Seheri Mapaseka L. , O’Neill Hester G. , Nyaga Martin M.
Published: November 2020

Establishing a diverse gut microbiota after birth is essential for preventing illnesses later in life. However, little knowledge exists about the total viral population (virome) present in the gut of infants during the early developmental stage, with RNA viruses being generally overlooked. Therefore, this small pilot longitudinal study investigated the diversity and changes in the enteric RNA virome in healthy infants from South Africa. Faecal samples (n = 12) were collected from four infants at three time points (on average at 8, 13, and 25 weeks), and then sequenced on an Illumina MiSeq platform. The genomic analysis revealed a diverse population of human enteric viruses from the infants’ stools, and changes in the enteric virome composition were observed over time. The Reoviridae family, more specifically the Rotavirus genus, was the most common and could be linked to viral shedding due to the administration of live-attenuated oral vaccines in South Africa, followed by the Picornaviridae family including parechoviruses, echoviruses, coxsackieviruses, enteroviruses, and polioviruses. Polioviruses were also linked to vaccine-related shedding. Astroviridae (astroviruses) and Caliciviridae (noroviruses) were present at low abundance. It is evident that an infant’s gut is colonized by distinct viral populations irrespective of their health state. Further characterization of the human virome (with a larger participant pool) is imperative to provide more conclusive insights into the viral community structure and diversity that has been shown in the current study, despite the smaller sample size.
Immune Checkpoint Blockade Enhances Immune Activity of Therapeutic Lung Cancer Vaccine
Authors: Kadam Pournima , Singh Ram P. , Davoodi Michael , Lee Jay M. , John Maie St. , Sharma Sherven
Published: November 2020

Background: Immune checkpoint blockade that downregulates T cell evasion for effective immunity has provided a renewed interest in therapeutic cancer vaccines. Methods: Utilizing murine lung cancer models, we determined: tumor burden, TIL cytolysis, immunohistochemistry, flow cytometry, RNA Sequencing, CD4 T cells, CD8 T cells, CXCL9 chemokine, and CXCL10 chemokine neutralization to evaluate the efficacy of Programmed cell death protein 1 (PD-1) blockade combined with chemokine (C-C motif) ligand 21-dendritic cell tumor antigen (CCL21-DC tumor Ag) vaccine. Results: Anti-PD1 combined with CCL21-DC tumor Ag vaccine eradicated 75% of 12-day established tumors (150 mm3) that was enhanced to 90% by administering CCL21-DC tumor Ag vaccine prior to combined therapy. The effect of combined therapy was blocked by CD4, CD8, CXCL9, and CXCL10 neutralizing antibodies. Conclusion: PD-1 blockade therapy plus CCL21-DC tumor Ag vaccine could be beneficial to lung cancer patients.
Artificial Floating Island with Vetiver for Treatment of Arsenic-Contaminated Water: A Real Scale Study in High-Andean Reservoir
Authors: Fonseca Largo Kalina Marcela , Ruiz Depablos Joseline Luisa , Espitia-Sarmiento Edgar Fabián , Llugsha Moreta Nataly Marisol
Published: November 2020

Arsenic found in agriculture water reservoirs represents a threat to water security and safe agricultural products in developing countries. Small farms do not implement traditional water treatments due to the high cost; hence, a nature-based solution is an alternative to tackling this challenge. This paper investigated the potential of artificial floating island with Vetiver (AFIV) for the geogenic arsenic removal present in the reservoir of the Ilinizas páramo in Ecuador. We constructed two AFIV systems using PVC pipes in a reservoir batch type with a 3.6 m3 treatment capacity. Arsenic and iron were analyzed in duplicated every 30 days at the affluent and effluent through 120 days. The average remediation of arsenic was recorded as 97% in water and 84% in sediment, while the average remediation of iron was 87% in sediment. The survival rate of macrophytes was 92%; they accumulated arsenic in its roots that acted as a barrier against the translocation. The research demonstrated that the use of AFIV has the potential to rehabilitate reservoirs contaminated with arsenic under adverse climatic conditions such as the páramo ecosystem.
Evaluation and Quantification of the Effects of Climate and Vegetation Cover Change on Karst Water Sources: Case Studies of Two Springs in South-Western Slovenia
Authors: Kovačič Gregor , Petrič Metka , Ravbar Nataša
Published: November 2020

Karst aquifers hold important water resources such as regional water budgets and freshwater supply. Due to highly dynamic hydrological processes in comparison to other less permeable systems, they are particularly susceptible to environmental changes. However, little research directly characterizes the impacts of climate and vegetation cover changes on karst water sources. In this study, we aimed to evaluate individual long-term impacts and impacts of sudden large-scale forest disturbances on changes in groundwater recharge and in spring discharge. The work is based on temporal analysis of forest cover and a comparison of trend analysis of hydro-meteorological parameters. To investigate and evaluate vegetation cover change impacts on groundwater recharge, we used a soil water balance model and compared estimated actual daily values of effective precipitation to its fictional estimation disregarding the vegetation cover change. The applied methodology enabled quantification of the impacts of climate and vegetation cover change on selected karst water sources. The study suggests that the vegetation cover can have a significant impact on the spring recharge. Large-scale disturbances that occurred in a short-term mitigated the effects expected from the trend analysis of hydro-meteorological parameters. In the long-term, in addition to climate changes, the multi-decadal natural vegetation overgrowth significantly contributed to the reduction in the spring’s discharge values, especially in the warm season when water demand is higher. Therefore, the results are of key importance for developing proper water management and environmental policies.
Use of Energy-Based Domain Knowledge as Feedback to Evolutionary Algorithms for the Optimization of Water Distribution Networks
Authors: Páez Diego , Salcedo Camilo , Garzón Alexander , González María Alejandra , Saldarriaga Juan
Published: November 2020

The optimization of water distribution networks (WDN) has evolved, requiring approaches that seek to reduce capital costs and maximize the reliability of the system simultaneously. Hence, several evolutionary algorithms, such as the non-dominated sorting-based multi-objective evolutionary algorithm (NSGA-II), have been widely used despite the high computational costs required to achieve an acceptable solution. Alternatively, energy-based methods have been used to reach near-optimal solutions with reduced computational requirements. This paper presents a method to combine the domain knowledge given by energy-based methods with an evolutionary algorithm, in a way that improves the convergence rate and reduces the overall computational requirements to find near-optimal Pareto fronts (PFs). This method is divided into three steps: parameters calibration, preprocessing of the optimal power use surface (OPUS) results, and periodic feedback using OPUS in NSGA II. The method was tested in four benchmark networks with different characteristics, seeking to minimize the costs of the WDN and maximizing its reliability. Then the results were compared with a generic implementation of NSGA-II, and the performance and quality of the solutions were evaluated using two metrics: hypervolume (HV) and modified inverted generational distance (IGD+). The results showed that the feedback procedure increases the efficiency of the algorithm, particularly the first time the algorithm is retrofitted.
Accuracy and Transferability of Artificial Neural Networks in Predicting in Situ Root-Zone Soil Moisture for Various Regions across the Globe
Authors: Souissi Roïya , Al Bitar Ahmad , Zribi Mehrez
Published: November 2020

This paper explores the accuracy in using an artificial neural network (ANN) to estimate root-zone soil moisture (RZSM) at multiple worldwide locations using only in situ surface soil moisture (SSM) as a training dataset. The paper also addresses the transferability of the trained ANN across climatic and soil texture conditions. Data from the International Soil Moisture Network (ISMN) were collected for several networks with variable soil texture and climate classes. Several scaling, feature extraction, and training approaches were tested. An artificial neural network employing rolling averages (ANNRAV) of SSM over 10, 30, and 90 days was developed. The results show that applying a standard scaling (SSCA) to the ANN input features improves the correlation, Nash–Sutcliffe efficiency (NSE), and root mean square error (RMSE) for 52%, 91%, and 87%, respectively, of the tested stations, compared to MinMax scaling (MMSCA). Different training sets are suggested, namely, training on data from all networks, data from one network, or data of all networks excluding one. Based on these trainings, new transferability (TranI) and contribution (ContI) indices are defined. The results show that one network cannot provide the best prediction accuracy if used alone to train the ANN. They also show that the removal of the less contributing networks enhances performance. For example, elimination of the densest network (SCAN) from the training enhances the mean correlation by 20.5% and the mean NSE by 42.5%. This motivates the implementation of a data filtering technique based on the ANN’s performance. A median, max, and min correlation of 0.77, 0.96, and 0.65, respectively, are obtained by the model after data filtering. The performances are also analyzed with respect to the covered climatic regions and soil texture, providing insights into the robustness and limitations of the approach, namely, the need for complementary information in highly evaporative regions. In fact, the ANN using only SSM to predict RZSM has low performance when decoupling between the surface and root zones is observed. The application of ANN to obtain spatialized RZSM will require integrating remote sensing-based surface soil moisture in the future.
TRANSFORMATION OF APPROACH TOWARDS PUBLIC SERVICE AND THE EMERGENCE OF HUMBOLDT UNIVERSITY MODEL IN PRUSSIA (1807–1810)
Authors: Ragozin German S. , Turygin Aleksandr A. , Boldyrev Roman Yu.
Published: November 2020

The paper deals with higher school transformation in Prussia between 1807 and 1810. Discussion on new university took place before 1806-1807, and had a purpose to design a new model connected with the practical application of the knowledge,
also in public administration. The reforms initiated by Baron vom Stein and Karl August Fürst von Hardenberg offered the national principles to basics of Prussian state. Traditional point of view is that Friedrich Wilhelm Christian Karl Ferdinand von Humboldt ideas prevailed in the reform, though Theodor Anton Heinrich Schmalz’s and Johann Gottfried Hoffmann’s offers tapped into Faculty of Law and Political economics programme concepts. As a result, new principles appeared, and the ideal statesman image. The reform had a deep impact on academic positions in Prussia, transfer of knowledge and ideas, and tapped into transformation of Prussia to national state. It is possible to state that new university and the new public servants training models made its commitment to the approach transformation towards the public service and political culture evolution. The new approach towards the Academy of Sciences, its relations with government and society became a catalyst towards political culture transfer to civil and national one. The new university tapped into continuity of social and political
reforms in the kingdom even within the Bourbon Restoration after 1815.
THE PORTRAIT OF SERGEI YESENIN IN ESSAYS-MEMOIRES OF YURY ANNENKOV AND MAXIM GORKY
Authors: Olyunina Margarita V.
Published: November 2020

The paper presents a comparative analysis of the methods of creating a verbal portrait in the essay by Maxim Gorky “Sergei Yesenin” and in the memoires of Yury Annenkov “Sergei Yesenin”. The possibility and necessity of comparing the two selected works is explained by both the factual material chosen by the authors (both writers devote their essays to Sergei Yesenin) and similar methods of creating a verbal portrait of the poet, and the context of the style of the era, which is reflected in the works and the individual style of each artist. The aim of this work is to substantiate the genre-style features
of the considered verbal image of Sergei Yesenin in the abovementioned works, which allows clarifying the created and already axiomatic image of the poet. The study is built using comparative historical and historical functional methods, the works of Alexander Veselovsky, Yuri Lotman, Yuriy Mineralov, as well as the experience of modern literary scholars involved in the theory and history of verbal painting. In the process of the comparative analysis of the works, it was revealed that Yury Annenkov and Maxim Gorky, recreating the verbal portrait of the poet Sergei Yesenin, was primarily seeking to portray him as an exponent of the tragic era. Capturing the image of the poet Sergei Yesenin, the painter creates his self-portrait, surrounded by his beloved, at the background of the era in which he lived, the writer tries to guide the reader inside the poetry laboratory of ‟nature”.
SURREALISATION OF SOUND: MUSICALITY, AUDIAL CULTURE AND SOUND IN THE MODERN RUSSIAN POETRY (VADIM BANNIKOV, VASILIY BORODIN, NIKITA SAFONOV)
Authors: Gorelov Oleg S.
Published: November 2020

The article discusses modern poetic practices that actualize the surrealistic code through a sound medium. Vadim Bannikov with the help of spontaneous sampling of material (figurative and verbal) brings sound and auditory constants to surrealistic
editing and metamorphosis. His “asemantic poetry” reveals the collaged polyphony of the Sprechgesang, forcing to reconsider the non-musicality of classical surrealism. Vasiliy Borodin’s auditory asemic letter becomes a solution to the poetry task of
“moving away from words” formulated by the poet himself, but in a surrealist context; this turns out to be a new stage in objectification of the code. If Vadim Bannikov’s automatism frees the subject, the surrealisation of Vasiliy Borodin frees the very musicality and audial culture (possibly “to the detriment” of poetry). The third alternative way to work with sound is offered by Nikita Safonov’s poetic practice. A general deterritorialisation of sound takes place in it, the sounding is freed through the objectification of sound, freed from the human as well. The sound landscape on equal terms includes silence (zero state of sound), the sounds themselves in their materiality and noise. The noise, understood as an empty sign, actualises the mathematical in sound. In the surrealist code, therefore, mathematics and abstraction become an important condition for further private implementations of surrealistic thought and aesthetics.
A NEW COMPLEX STUDY “RUSSIAN ESTATE AND EUROPE: DIACHRONY, NOSTALGIA, UNIVERSALISM”
Authors: Haltrin-Khalturina Elena V
Published: November 2020

This is a review of a scholarly edition focusing on the Russian manor-house topos and published by IMLI RAS as part of the book series «Russian estate in the world context». The review discusses the structure of the collective monograph, comments on the wide scope of the covered material, as well as on the cutting-edge research strategies employed here, which might command interest of the wide readership, since they are prompted by the Russian and comparative studies, literary and cultural studies, folklore studies and intellectual history. The reviewer highlights some uncommon and keen observations
made by the contributors to the monograph and offers a short list of country houses and stately homes worthy of further consideration in the same scholarly light.
Testing of the Wireless Sensor Network for the Express-Diagnostic of the State of Plant
Authors: Antonova H. , Kedych A.
Published: November 2020

The authors reviewed the types of network testing. The most common are simulation modeling, mock-up modeling, and full-scale experiments. It was examined existing software environments for simulation and debugging kits for mock testing. The main definitions and terms on the theory of experiment planning are given. According to the theory of experiment planning, the authors developed a plan for conducting a full-scale experiment and defined an algorithm for testing a wireless sensor network for express diagnostics of plants' state. Network testing parameters are the quality of network communication; network formation time; network communication distance; and battery life of sensors. The preparation and process of conducting a full-scale experiment for testing a WSN sample is described in detail. Wireless sensor network testing was carried out by different clusters, at different distances in five stages. During the experiment on testing the WSN, the operation of individual network nodes was checked, and the operation of the network as a whole. During the testing period, no abnormal operation of the sensors and the coordinator was revealed. 82 measurements were made in just five stages. The communication quality of the wireless sensor network has been checked. When testing the network, the transmission of data packets from the sensors to the coordinator was mostly successful. The integral estimate of unsuccessful data transmission sessions in the network was calculated. The communication range of the network at a distance of 20, 30, 40 and 60 m was checked. A graph of the dependence of the sensor signal power on the distance was built. Statistics were obtained on the decrease in the battery charge for each sensor. Based on the results of a full-scale experiment, the operation of a wireless sensor network for express diagnostics of the state of plants is considered successful.

Keywords: Zigbee, wireless sensor network, sensor, full-scale experiment.
Parque de España
Authors: MBM Estudio
Published: November 2020

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