bluuebunny/crossref_metadata_2025 huggingface dataset:
Monochromic Radiations Provided by Light Emitted Diode (LED) Modulate Infection and Defense Response to Fire Blight in Pear Trees
Authors: Sgamma Tiziana , Forgione Ivano , Luziatelli Francesca , Iacona Calogero , Mancinelli Roberto , Thomas Brian , Ruzzi Maurizio , Muleo Rosario
Published: September 2021

Pathogenesis-related (PR) proteins are part of the systemic signaling network that perceives pathogens and activates defenses in the plant. Eukaryotic and bacterial species have a 24-h ‘body clock’ known as the circadian rhythm. This rhythm regulates an organism’s life, modulating the activity of the phytochromes (phys) and cryptochromes (crys) and the accumulation of the corresponding mRNAs, which results in the synchronization of the internal clock and works as zeitgeber molecules. Salicylic acid accumulation is also under light control and upregulates the PR genes expression, increasing plants’ resistance to pathogens. Erwinia amylovora causes fire blight disease in pear trees. In this work, four bacterial transcripts (erw1-4), expressed in asymptomatic E. amylovora-infected pear plantlets, were isolated. The research aimed to understand how the circadian clock, light quality, and related photoreceptors regulate PR and erw genes expression using transgenic pear lines overexpressing PHYB and CRY1 as a model system. Plantlets were exposed to different circadian conditions, and continuous monochromic radiations (Blue, Red, and Far-Red) were provided by light-emitting diodes (LED). Results showed a circadian oscillation of PR10 gene expression, while PR1 was expressed without clear evidence of circadian regulation. Bacterial growth was regulated by monochromatic light: the growth of bacteria exposed to Far-Red did not differ from that detected in darkness; instead, it was mildly stimulated under Red, while it was significantly inhibited under Blue. In this regulatory framework, the active form of phytochrome enhances the expression of PR1 five to 15 fold. An ultradian rhythm was observed fitting the zeitgeber role played by CRY1. These results also highlight a regulating role of photoreceptors on the expression of PRs genes in non-infected and infected plantlets, which influenced the expression of erw genes. Data are discussed concerning the regulatory role of photoreceptors during photoperiod and pathogen attacks.
Scaled Synthesis of Polyamine-Modified Cellulose Nanocrystals from Bulk Cotton and Their Use for Capturing Volatile Organic Compounds
Authors: Brummel Beau R. , Narangoda Chandima J. , Attia Mohamed F. , Swasy Maria I. , Smith, Jr. Gary D. , Alexis Frank , Whitehead Daniel C.
Published: September 2021

We have previously demonstrated that cellulose nanocrystals modified with poly(ethylenimine) (PEI-f-CNC) are capable of capturing volatile organic compounds (VOCs) associated with malodors. In this manuscript, we describe our efforts to develop a scalable synthesis of these materials from bulk cotton. This work culminated in a reliable protocol for the synthesis of unmodified cellulose nanocrystals (CNCs) from bulk cotton on a 0.5 kg scale. Additionally, we developed a protocol for the modification of the CNCs by means of sequential 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO) oxidation and 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) coupling to modify their surface with poly(ethylenimine) on a 100 g scale. Subsequently, we evaluated the performance of the PEI-f-CNC materials that were prepared in a series of VOC capture experiments. First, we demonstrated their efficacy in capturing volatile fatty acids emitted at a rendering plant when formulated as packed-bed filter cartridges. Secondly, we evaluated the potential to use aqueous PEI-f-CNC suspensions as a spray-based delivery method for VOC remediation. In both cases, the PEI-f-CNC formulations reduced detectable malodor VOCs by greater than 90%. The facile scaled synthesis of these materials and their excellent performance at VOC remediation suggest that they may emerge as a useful strategy for the remediation of VOCs associated with odor.
Mechanical Properties of Sugar Palm (Arenga pinnata Wurmb. Merr)/Glass Fiber-Reinforced Poly(lactic acid) Hybrid Composites for Potential Use in Motorcycle Components
Authors: Sherwani S. F. K. , Zainudin E. S. , Sapuan S. M. , Leman Z. , Abdan K.
Published: September 2021

This research aims to determine the mechanical properties of sugar palm fiber (Arenga pinnata Wurmb. Merr) (SPF)/glass fiber (GF)-reinforced poly(lactic acid) (PLA) hybrid composites for potential use in motorcycle components. The mechanical (hardness, compressive, impact, and creep) and flammability properties of SPF/GF/PLA hybrid composites were investigated and compared to commercially available motorcycle Acrylonitrile Butadiene Styrene (ABS) plastic components. The composites were initially prepared using a Brabender Plastograph, followed by a compression molding method. This study also illustrated the tensile and flexural stress–strain curves. The results revealed that alkaline-treated SPF/GF/PLA had the highest hardness and impact strength values of 88.6 HRS and 3.10 kJ/m2, respectively. According to the results, both alkaline and benzoyl chloride treatments may improve the mechanical properties of SPF/GF/PLA hybrid composites, and a short-term creep test revealed that the alkaline treated SPF/GF/PLA composite displayed the least creep deformation. The findings of the horizontal UL 94 testing indicated that the alkaline-treated SPF/GF/PLA hybrid composites had good flame resistance. However, alkaline-treated SPF/GF/PLA composites are more suitable materials for motorcycle components.
High-Performance Hydrogel Adsorbent Based on Cellulose, Hemicellulose, and Lignin for Copper(II) Ion Removal
Authors: Shan Shuang , Sun Xiao-Feng , Xie Yangyang , Li Wenbo , Ji Tiezheng
Published: September 2021

Cellulose, hemicellulose, and lignin are three kinds of biopolymer in lignocellulosic biomass, and the utilization of the three biopolymers to synthesize hydrogel adsorbent could protect the environment and enhance the economic value of the biomass. A novel hydrogel adsorbent was prepared using cellulose, lignin, and hemicellulose of wheat straw by a one-pot method, and the adsorbent showed excellent adsorption performance for copper(II) ions. Scanning electron microscopy and Fourier transform infrared spectroscopy analysis showed that the prepared straw-biopolymer-based hydrogel had porous structure, and cellulose fibrils had crosslinked with lignin and hemicellulose by poly(acrylic acid) chains. The effects of contact time, initial concentration, and temperature on the copper(II) ion removal using the prepared hydrogels were investigated, and the obtained results indicated that the adsorption kinetics conformed to the pseudo-second-order and Elovich equation models and the adsorption isotherm was in accord with the Freundlich model. The adsorption thermodynamics study indicated that the adsorption process was spontaneous and accompanied by heat. X-ray photoelectron spectroscopy analysis revealed that the adsorption behavior resulted from ion exchange. The prepared hydrogel based on cellulose, hemicellulose, and lignin could be used for water treatment and soil remediation because of its high performances of excellent heavy metal ion removal and water retention.
Potency of Urea-Treated Halloysite Nanotubes for the Simultaneous Boosting of Mechanical Properties and Crystallization of Epoxidized Natural Rubber Composites
Authors: Surya Indra , Waesateh Kamaruddin , Saiwari Sitisaiyidah , Ismail Hanafi , Othman Nadras , Hayeemasae Nabil
Published: September 2021

Halloysite nanotubes (HNTs) are naturally occurring tubular clay made of aluminosilicate sheets rolled several times. HNT has been used to reinforce many rubbers. However, the narrow diameter of this configuration causes HNT to have poor interfacial contact with the rubber matrix. Therefore, increasing the distance between layers could improve interfacial contact with the matrix. In this work, Epoxidized Natural Rubber (ENR)/HNT was the focus. The HNT layer distance was successfully increased by a urea-mechanochemical process. Attachment of urea onto HNT was verified by FTIR, where new peaks appeared around 3505 cm−1 and 3396 cm−1, corresponding to urea’s functionalities. The intercalation of urea to the distance gallery of HNT was revealed by XRD. It was also found that the use of urea-treated HNT improved the modulus, tensile strength, and tear strength of the composites. This was clearly responsible for interactions between ENR and urea-treated HNT. It was further verified by observing the Payne effect. The value of the Payne effect was found to be reduced at 62.38% after using urea for treatment. As for the strain-induced crystallization (SIC) of the composites, the stress–strain curves correlated well with the results from synchrotron wide-angle X-ray scattering.
Polysaccharide Vaccines: A Perspective on Non-Typhoidal Salmonella
Authors: Perera Sumudu R. , Sokaribo Akosiererem S. , White Aaron P.
Published: September 2021

Polysaccharides are often the most abundant antigens found on the extracellular surfaces of bacterial cells. These polysaccharides play key roles in interactions with the outside world, and for many bacterial pathogens, they represent what is presented to the human immune system. As a result, many vaccines have been or currently are being developed against carbohydrate antigens. In this review, we explore the diversity of capsular polysaccharides (CPS) in Salmonella and other selected bacterial species and explain the classification and function of CPS as vaccine antigens. Despite many vaccines being developed using carbohydrate antigens, the low immunogenicity and the diversity of infecting strains and serovars present an antigen formulation challenge to manufacturers. Vaccines tend to focus on common serovars or have changing formulations over time, reflecting the trends in human infection, which can be costly and time-consuming. We summarize the approaches to generate carbohydrate-based vaccines for Salmonella, describe vaccines that are in development and emphasize the need for an effective vaccine against non-typhoidal Salmonella strains.
Photovoltaic Module Fault Detection Based on a Convolutional Neural Network
Authors: Lu Shiue-Der , Wang Meng-Hui , Wei Shao-En , Liu Hwa-Dong , Wu Chia-Chun
Published: September 2021

With the rapid development of solar energy, the photovoltaic (PV) module fault detection plays an important role in knowing how to enhance the reliability of the solar photovoltaic system and knowing the fault type when a system problem occurs. Therefore, this paper proposed the hybrid algorithm of chaos synchronization detection method (CSDM) with convolutional neural network (CNN) for studying PV module fault detection. Four common PV module states were discussed, including the normal PV module, module breakage, module contact defectiveness and module bypass diode failure. First of all, the defects in 16 pieces of 20W monocrystalline silicon PV modules were preprocessed, and there were four pieces of each fault state. When the signal generator delivered high frequency voltage to the PV module, the original signal was measured and captured by the NI PXI-5105 high-speed data acquisition system (DAS) and was calculated by CSDM, to establish the chaos dynamic error map as the image feature of fault diagnosis. Finally, the CNN was employed for diagnosing the fault state of the PV module. The findings show that after entering 400 random fault data (100 data for each fault) into the proposed method for recognition, the recognition accuracy rate of the proposed method was as high as 99.5%, which is better than the traditional ENN algorithm that had a recognition rate of 86.75%. In addition, the advantage of the proposed algorithm is that the mass original measured data can be reduced by CSDM, the subtle changes in the output signals are captured effectively and displayed in images, and the PV module fault state is accurately recognized by CNN.
Humanist Chaplains Entering Traditionally Faith-Based NHS Chaplaincy Teams
Authors: van Dijk Lindsay Jane
Published: September 2021

Healthcare chaplaincy in the National Health Service (NHS) has rapidly changed in the last few years. Research shows a decline of people belonging to traditional faith frameworks, and the non-religious patient demographic in the NHS has increased swiftly. This requires a different approach to healthcare chaplaincy. Where chaplaincy has originally been a Christian profession, this has expanded to a multi-faith context. Over the last five years, humanists with non-religious beliefs have entered the profession for the first time, creating multi-faith and belief teams. As this is a very new development, this article will focus on literature about humanists entering traditionally faith-based NHS chaplaincy teams within the last five years in England. This article addresses the question “what are the developments resulting from the inclusion of humanist chaplains in healthcare chaplaincy?” Topics arising from the literature are an acknowledgement of a changing healthcare chaplaincy field, worries about changing current practices and chaplaincy funding, the use of (Christian) language excluding non-religious people and challenging assumptions about those who identify as non-religious.
“It’s Not Doctrine, This Is Just How It Is Happening!”: Religious Creativity in the Time of COVID-19
Authors: Taragin-Zeller Lea , Kessler Edward
Published: September 2021

Drawing on thirty in-depth interviews with faith leaders in the UK (including Islam, Christianity, Judaism, Hinduism, and Sikhism), we examine the diverse ways religious groups reorient religious life during COVID-19. Analysing the shift to virtual and home-based worship, we show the creative ways religious communities altered their customs, rituals, and practices to fit a new virtual reality amidst rigid social distancing guidelines. This study offers a distinctive comparative perspective into religious creativity amidst acute social change, allowing us to showcase notable differences, especially in terms of the possibility to fully perform worship online. We found that whilst all faith communities faced the same challenge of ministering and supporting their communities online, some were able to deliver services and perform worship online but others, for theological reasons, could not offer communal prayer. These differences existed within each religion rather than across religious boundaries, representing intra-faith divergence at the same time as cross-faith convergence. This analysis allows us to go beyond common socio-religious categories of religion, while showcasing the diverse forms of religious life amidst COVID-19. This study also offers a diverse case study of the relationship between religions as well as between religion, state, and society amidst COVID-19.
Household Financial Situation during the COVID-19 Pandemic with Particular Emphasis on Savings—An Evidence from Poland Compared to Other CEE States
Authors: Szustak Grażyna , Gradoń Witold , Szewczyk Łukasz
Published: September 2021

The aim of this article is to analyze and assess the impact of the pandemic on the finances of households in Poland, compared to other CEE countries (including Czech Republic, Slovakia and Hungary), with particular emphasis on changes in the level of their savings, which are considered to be the foundation for the development of the indicated research group. There is no doubt that the pandemic had an impact on the situation of households, which is mainly visible in the labor market (rising unemployment), and thus the question arises to what extent have the households’ approaches to financial decisions changed because of this situation? The propensity to save was taken into account as a main aspect of this problem, because it has, among others, a big impact on the financial well-being (in a broader sense). Using the multiple linear regression method, the factors that influence the level of household savings were determined. The results of the research show that these factors are different in the analyzed countries and have a different impact on the level of the explained variable, which is the gross saving rate. The research should also be treated as a preliminary one. It constitutes a contribution to in-depth research with the use of more sophisticated statistical and econometric methods, which will allow for the better assessment of the examined issue.
Fine-Grained Large-Scale Vulnerable Communities Mapping via Satellite Imagery and Population Census Using Deep Learning
Authors: Salas Joaquín , Vera Pablo , Zea-Ortiz Marivel , Villaseñor Elio-Atenogenes , Pulido Dagoberto , Figueroa Alejandra
Published: September 2021

One of the challenges in the fight against poverty is the precise localization and assessment of vulnerable communities’ sprawl. The characterization of vulnerability is traditionally accomplished using nationwide census exercises, a burdensome process that requires field visits by trained personnel. Unfortunately, most countrywide censuses exercises are conducted only sporadically, making it difficult to track the short-term effect of policies to reduce poverty. This paper introduces a definition of vulnerability following UN-Habitat criteria, assesses different CNN machine learning architectures, and establishes a mapping between satellite images and survey data. Starting with the information corresponding to the 2,178,508 residential blocks recorded in the 2010 Mexican census and multispectral Landsat-7 images, multiple CNN architectures are explored. The best performance is obtained with EfficientNet-B3 achieving an area under the ROC and Precision-Recall curves of 0.9421 and 0.9457, respectively. This article shows that publicly available information, in the form of census data and satellite images, along with standard CNN architectures, may be employed as a stepping stone for the countrywide characterization of vulnerability at the residential block level.
Black Carbon over Wuhan, China: Seasonal Variations in Its Optical Properties, Radiative Forcing and Contribution to Atmospheric Aerosols
Authors: Ma Yingying , Fan Ruonan , Jin Shikuan , Ma Xin , Zhang Ming , Gong Wei , Liu Boming , Shi Yifan , Zhang Yiqun , Li Hui
Published: September 2021

As an important fraction of light-absorbing particles, black carbon (BC) has a significant warming effect, despite accounting for a small proportion of total aerosols. A comprehensive investigation was conducted on the characteristics of atmospheric aerosols and BC particles over Wuhan, China. Mass concentration, optical properties, and radiative forcing of total aerosols and BC were estimated using multi-source observation data. Results showed that the BC concentration monthly mean varied from 2.19 to 5.33 μg m−3. The BC aerosol optical depth (AOD) maximum monthly mean (0.026) occurred in winter, whereas the maximum total AOD (1.75) occurred in summer. Under polluted-air conditions, both aerosol radiative forcing (ARF) and BC radiative forcing (BCRF) at the bottom of the atmosphere (BOA) were strongest in summer, with values of −83.01 and −11.22 W m−2, respectively. In summer, ARF at BOA on polluted-air days was more than two-fold that on clean-air days. In addition, compared with clean-air days, BCRF at BOA on polluted-air days was increased by 76% and 73% in summer and winter, respectively. The results indicate an important influence of particulate air pollution on ARF and BCRF. Furthermore, the average contribution of BCRF to ARF was 13.8%, even though the proportion of BC in PM2.5 was only 5.1%.
An Advanced SAR Image Despeckling Method by Bernoulli-Sampling-Based Self-Supervised Deep Learning
Authors: Yuan Ye , Wu Yanxia , Fu Yan , Wu Yulei , Zhang Lidan , Jiang Yan
Published: September 2021

As one of the main sources of remote sensing big data, synthetic aperture radar (SAR) can provide all-day and all-weather Earth image acquisition. However, speckle noise in SAR images brings a notable limitation for its big data applications, including image analysis and interpretation. Deep learning has been demonstrated as an advanced method and technology for SAR image despeckling. Most existing deep-learning-based methods adopt supervised learning and use synthetic speckled images to train the despeckling networks. This is because they need clean images as the references, and it is hard to obtain purely clean SAR images in real-world conditions. However, significant differences between synthetic speckled and real SAR images cause the domain gap problem. In other words, they cannot show superior performance for despeckling real SAR images as they do for synthetic speckled images. Inspired by recent studies on self-supervised denoising, we propose an advanced SAR image despeckling method by virtue of Bernoulli-sampling-based self-supervised deep learning, called SSD-SAR-BS. By only using real speckled SAR images, Bernoulli-sampled speckled image pairs (input–target) were obtained as the training data. Then, a multiscale despeckling network was trained on these image pairs. In addition, a dropout-based ensemble was introduced to boost the network performance. Extensive experimental results demonstrated that our proposed method outperforms the state-of-the-art for speckle noise suppression on both synthetic speckled and real SAR datasets (i.e., Sentinel-1 and TerraSAR-X).
The Sample Size Matters: To What Extent the Participant Reduction Affects the Outcomes of a Neuroscientific Research. A Case-Study in Neuromarketing Field
Authors: Vozzi Alessia , Ronca Vincenzo , Aricò Pietro , Borghini Gianluca , Sciaraffa Nicolina , Cherubino Patrizia , Trettel Arianna , Babiloni Fabio , Di Flumeri Gianluca
Published: September 2021

The sample size is a crucial concern in scientific research and even more in behavioural neurosciences, where besides the best practice it is not always possible to reach large experimental samples. In this study we investigated how the outcomes of research change in response to sample size reduction. Three indices computed during a task involving the observations of four videos were considered in the analysis, two related to the brain electroencephalographic (EEG) activity and one to autonomic physiological measures, i.e., heart rate and skin conductance. The modifications of these indices were investigated considering five subgroups of sample size (32, 28, 24, 20, 16), each subgroup consisting of 630 different combinations made by bootstrapping n (n = sample size) out of 36 subjects, with respect to the total population (i.e., 36 subjects). The correlation analysis, the mean squared error (MSE), and the standard deviation (STD) of the indexes were studied at the participant reduction and three factors of influence were considered in the analysis: the type of index, the task, and its duration (time length). The findings showed a significant decrease of the correlation associated to the participant reduction as well as a significant increase of MSE and STD (p < 0.05). A threshold of subjects for which the outcomes remained significant and comparable was pointed out. The effects were to some extents sensitive to all the investigated variables, but the main effect was due to the task length. Therefore, the minimum threshold of subjects for which the outcomes were comparable increased at the reduction of the spot duration.
Enjoyment of Physical Activity—Not MVPA during Physical Education—Predicts Future MVPA Participation and Sport Self-Concept
Authors: Ramer Jared D. , Houser Natalie E. , Duncan Robert J. , Bustamante Eduardo E.
Published: September 2021

There exists a general understanding that physical education (PE) is a means to create a physically healthy population. However, disagreements arise over primary practices within PE to achieve this end. The primary divergence is whether PE facilitators should primarily ensure participants exert a specific level of energy during class or develop their confidence, competence, knowledge, and motivation for meaningful physical activity (PA) participation outside of the PE classroom (referred to as physical literacy (PL)). This study uses structural equation modeling to examine associations between enjoyment of PA and minutes of moderate to vigorous physical activity (MVPA) in PE class in grade 5 (mean age = 10) and participation in PA and feelings about PA 1 year later, in grade 6 (mean age = 11), in the NICHD Study of Early Child Care and Youth Development (SECCYD, N = 1364). Enjoyment of PA in grade 5 predicted sport self-concept (β = 0.347, p ≤ 0.001), MVPA (β = 0.12, p ≤ 0.001), and enjoyment of PA (β = 0.538, p ≤ 0.001) in grade 6. These associations remained when including weekday MVPA performed in grade 5 as an indirect effect (β = 0.058, p ≤ 0.001). MVPA performed during PE in grade 5 was not associated with any PA outcomes in grade 6. Findings suggest PE instructors should prioritize PL development over maintenance of high energy expenditure during PE class for long-term MVPA.
Mobility and Urban Centralities: An Analysis Based on the Motorized Flows Attraction in Belo Horizonte/State of Minas Gerais/Brazil
Authors: Lessa Daniela A. , Lobo Carlos
Published: September 2021

The issues encompassing planning and management of the urban space are directly related to the transport system, of which the flow plays a central role. Therefore, an interdependence among urban tissue, space structuring, and demand for mobility are taken into account. The objective of this work, using the data taken from the last two Origin and Destination surveys (2002 and 2012), is to assess the possible reduced power of attraction of the Central Area of Belo Horizonte by means of the motorized flows as a result of the process of induction of power of attraction of new urban centralities through planning and management policies. The results presented in this work generally indicate that the spatial structure of Belo Horizonte has remained concentrated in the Central Area, though new flows seem to converge to the consolidation of new municipal centralities. Even if additional care in the interpretation of results is necessary due to the limited time cuts and the database used, besides the specific features of Belo Horizonte, the empirical evidence translated in the proposed indicators allow a more accurate reflection on the recent urban space configuration, with the connections established through the space mobility of the population.
Social Learning in Empowering Leadership: A Moderated Mediation Analysis
Authors: Byun Gukdo , Lee Soojin
Published: September 2021

This study suggests a comprehensive social learning model of empowering leadership by focusing on the antecedents and processes of empowering leadership. Data were obtained from subordinate–supervisor dyads from the South Korean Army. The results support the social learning of empowering leadership. Specifically, the empowering leadership of high-level leaders facilitates that of low-level leaders, and this relationship is mediated by leader-leader exchange (LLX). Additionally, the results confirm the existence of a moderated mediation relationship among the constructs of interest; that is, the exchange ideology of low-level leaders moderates the relationship between LLX and their empowering leadership, such that the relationship is stronger when the exchange ideology is weak rather than strong. Thus, a weak exchange ideology strengthens the indirect effects of the empowering leadership of high-level leaders on that of low-level leaders through LLX. Theoretical and practical implications are also discussed.
The Contribution of Natural Resource Producing Sectors to the Economic Development of the Sakha Republic
Authors: Tabata Shinichiro
Published: September 2021

This paper provides basic materials for considering the sustainability of natural resource development in the Arctic, taking the Sakha Republic as a case study of the Russian Arctic regions. The author clarifies the contribution of the mining industry to the economic development of Sakha with special attention paid to the contribution to government budgets by numerical and statistical analysis of regional and municipal data. The paper demonstrates that the mining industry has been a driving force of the economic growth of Sakha and that the oil sector has sharply increased its presence while the diamond sector has decreased its presence. Simultaneously, it reveals that the mining industry is unevenly developed in Sakha, which has caused significant inequality in per capita Gross Municipal Product (GMP). Then, the analysis of the paper shows that Sakha’s contribution to the federal budget has increased significantly in recent years due to growing oil production and that the diamond sector is still more influential than the oil sector in the contribution to the republican and local budgets.
Using Multivariate Regression and ANN Models to Predict Properties of Concrete Cured under Hot Weather
Authors: Maqsoom Ahsen , Aslam Bilal , Gul Muhammad Ehtisham , Ullah Fahim , Kouzani Abbas Z. , Mahmud M. A. Parvez , Nawaz Adnan
Published: September 2021

Concrete is an important construction material. Its characteristics depend on the environmental conditions, construction methods, and mix factors. Working with concrete is particularly tricky in a hot climate. This study predicts the properties of concrete in hot conditions using the case study of Rawalpindi, Pakistan. In this research, variable casting temperatures, design factors, and curing conditions are investigated for their effects on concrete characteristics. For this purpose, water–cement ratio (w/c), in-situ concrete temperature (T), and curing methods of the concrete are varied, and their effects on pulse velocity (PV), compressive strength (fc), depth of water penetration (WP), and split tensile strength (ft) were studied for up to 180 days. Quadratic regression and artificial neural network (ANN) models have been formulated to forecast the properties of concrete in the current study. The results show that T, curing period, and moist curing strongly influence fc, ft, and PV, while WP is adversely affected by T and moist curing. The ANN model shows better results compared to the quadratic regression model. Furthermore, a combined ANN model of fc, ft, and PV was also developed that displayed higher accuracy than the individual ANN models. These models can help construction site engineers select the appropriate concrete parameters when concreting under hot climates to produce durable and long-lasting concrete.
Factors Affecting the Sustainability Performance of Financial Institutions in Bangladesh: The Role of Green Finance
Authors: Zheng Guang-Wen , Siddik Abu Bakkar , Masukujjaman Mohammad , Fatema Nazneen
Published: September 2021

Despite the increasing popularity of green finance and sustainable investment in the field of Sustainable Development Goals (SDGs), very few studies have investigated the effect of green finance dimensions on the sustainable performance of banks. Therefore, this study attempts to examine the dimensions of green finance and their effects on the sustainability performance of financial institutions in developing economies such as Bangladesh. The study also depicts the level of green financing adoption among the banks and non-bank financial institutions in the country between 2015 and 2020. Considering the nature of the dataset, the structural equation modeling technique was employed in this study to fulfil the research objectives. Amongst banks and non-bank financial institutions, the study highlighted private commercial banks as being the highest contributor to green financing, accounting for 78.12% of the total green financing in Bangladesh. In addition, the empirical findings revealed that the dimensions of green finance are related to the economic, social, and environmental aspects of the SDGs. Furthermore, empirical findings indicated that the dimensions of green finance—social, economic, and environmental—have a strong positive effect on the sustainability performance of banks. The study also discovered that approximately 95% of bankers identify green financing as an essential element in the short- and long-term development of banking strategies in Bangladesh. Consequently, this study adds to the body of knowledge on green finance development and the sustainability performance of banks and financial institutions in emerging economies such as Bangladesh. Therefore, major managerial policy implications are discussed.
Leveraging a Community of Practice to Build Faculty Resilience and Support Innovations in Teaching during a Time of Crisis
Authors: Mead Taryn , Pietsch Carlie , Matthew Victoria , Lipkin-Moore Surbhi , Metzger Ellen , Avdeev Ilya V. , Ruzycki Nancy J.
Published: September 2021

Amidst the COVID-19 upheaval to higher education, a grantor-led community of practice (CoP) supported faculty members to deliver an innovative, sustainability-oriented entrepreneurship curriculum and maintain resiliency as teaching professionals. This paper discusses how through engagement in the CoP, this group of faculty from across engineering, material science, business, and geosciences demonstrated resilience, adaptability, and pivoted to create curriculum for students in real time, as the events of the COVID-19 pandemic unfolded throughout 2020 and impacted face-to-face learning. The role the community of practice played in sustaining and supporting the faculty will be discussed. Case studies from faculty members will demonstrate how sustainable design and social responsibility can be integrated into entrepreneurially focused classes and student experiences across disciplines. The primary contribution of this research is the important role that an emergent learning framework can play in informing how best to optimize the CoP format and approach in a way that leverages and addresses individual member strengths, challenges, and experiences, and supports the needs of CoP members during a time of significant change and crisis.
Land Use Sustainability Monitoring: “Trees Outside Forests” in Temperate FAO-Ecozones (Oceanic, Continental, and Mediterranean) in Europe (2000–2015)
Authors: García-Montero Luis G. , Pascual Cristina , Sanchez-Paus Díaz Alfonso , Martín-Fernández Susana , Martín-Ortega Pablo , García-Robredo Fernando , Calderón-Guerrero Carlos , Patriarca Chiara , Mollicone Danilo
Published: September 2021

The global distribution of forest trees is essential for monitoring land-use sustainability. For this reason, FAO developed the Global Forest Survey (GFS), a systematic regional level survey with a homogeneous sampling design. Preliminary results revealed an interest in analyzing “Trees Outside Forests” (TOFs). We analyzed more than 11,150 sample GFS plots in temperate FAO-ecozones in Europe through a photo-interpretation approach using FAO’s Collect Earth platform. Our results showed that forest land was the most predominant use of land (41%) in temperate FAO-ecozones in Europe in 2015. Forest IPCC land use followed a moderate upward trend from 2000 to 2015 (0.2%). Trees Outside Forests in temperate FAO-ecozones in Europe accounted for 22% of the inventoried area. Trees Outside Forests represent 30% and 48% of cropland and grassland IPCC land uses, respectively, as well as 75% in settlement uses. Comparing our results with previous studies on the Mediterranean, temperate FAO-ecozone TOFs showed a downward trend in Europe and an upward trend in the Mediterranean area, despite its smaller surface area. The greening of the Common Agricultural Policy may increase the extension of TOFs, although our results may indicate that this effect is not yet evident in the field.
Evaluating the Impact of Environmental Education on Ecologically Friendly Behavior of University Students in Pakistan: The Roles of Environmental Responsibility and Islamic Values
Authors: Begum Abida , Jingwei Liu , Marwat Imran Ullah Khan , Khan Salim , Han Heesup , Ariza-Montes Antonio
Published: September 2021

With increasing global environmental problems, considerable evidence now suggests that environmental education can influence students’ ecologically friendly behavior significantly. Addressing increased environmental problems requires better understanding of the relations between focused and explicit environmental education, environmental responsibility, and religious values. The current study examined the relationship between environmental education and ecologically friendly behavior, utilizing insights from resource conservation theory. The relationship between the variables mentioned above was examined to determine the mediating effect of environmental responsibility and the moderating effect of Islamic values. Through a cross-sectional approach, data were gathered from 413 university students. The data were analyzed using analytical techniques such as “structural equation modeling” and “PROCESS.” The study’s findings support the predicted conceptual model, indicating that environmental education was positively related to environmentally friendly behavior. Furthermore, environmental responsibility partially mediated the relationship above, whereas Islamic values positively moderated the relationships between environmental education and ecologically friendly behavior as well as between environmental education and environmental responsibility. These findings emphasize the critical role of environmental education and Islamic values in comprehending the ecological behaviors of Muslim students.
Majority Decision Aggregation with Binarized Data in Wireless Sensor Networks
Authors: Liu Fanpyn
Published: September 2021

Wireless sensor networks (WSNs) are the cornerstone of the current Internet of Things era. They have limited resources and features, a smaller packet size than other types of networks, and dynamic multi-hop transmission. WSNs can monitor a particular area of interest and are used in many different applications. For example, during the COVID-19 pandemic, WSNs have been used to measure social distancing/contact tracing among people. However, the major challenge faced by WSN protocols is limited battery energy. Therefore, the whole WSN area is divided into odd clusters using k-means++ clustering to make a majority rule decision to reduce the amount of additional data sent to the base station (or sink) and achieve node energy-saving efficiency. This study proposes an energy-efficient binarized data aggregation (EEBDA) scheme, by which, through a threshold value, the collected sensing data are asserted with binary values. Subsequently, the corresponding cluster head (CH), according to the Hamming weight and the final majority decision, is calculated and sent to the base station (BS). The EEBDA is based on each cluster and divides the entire WSN area into four quadrants. All CHs construct a data-relay transmission link in the same quadrant; the binary value is transferred from the CHs to the sink. The EEBDA adopts a CH rotation scheme to aggregate the data based on the majority results in the cluster. The simulation results demonstrate that the EEBDA can reduce redundant data transmissions, average the energy consumption of nodes in the cluster, and obtain a better network lifetime when compared to the LEACH, LEACH-C, and DEEC algorithms.
Perfect Reconciliation in Quantum Key Distribution with Order-Two Frames
Authors: Lizama-Pérez Luis Adrián , López-Romero José Mauricio
Published: September 2021

We present an error reconciliation method for Quantum Key Distribution (QKD) that corrects 100% of errors generated in regular binary frames transmitted over a noisy quantum channel regardless of the quantum channel error rate. In a previous investigation, we introduced a novel distillation QKD algorithm whose secret key rate descends linearly with respect to the channel error rate. Now, as the main achievement of this work, we demonstrate an improved algorithm capable of retaining almost all the secret information enclosed in the regular binary frames. Remarkably, this technique increases quadratically the secret key rate as a function of the double matching detection events and doubly quadratically in the number of the quantum pulses. Furthermore, this reconciliation method opens up the opportunity to use less attenuated quantum pulses, would allow greater QKD distances at drastically increased secret key rate. Since our method can be implemented as a software update, we hope that quantum key distribution technology would be fast deployed over global data networks in the quantum era.
A Novel Underdetermined Blind Source Separation Method Based on OPTICS and Subspace Projection
Authors: Wang Qingyi , Zhang Yiqiong , Yin Shuai , Wang Yuduo , Wu Genping
Published: September 2021

In recent years, the problem of underdetermined blind source separation (UBSS) has become a research hotspot due to its practical potential. This paper presents a novel method to solve the problem of UBSS, which mainly includes the following three steps: Single source points (SSPs) are first screened out using the principal component analysis (PCA) approach, which is based on the statistical features of signal time-frequency (TF) points. Second, a mixing matrix estimation method is proposed that combines Ordering Points To Identify the Clustering Structure (OPTICS) with an improved potential function to directly detect the number of source signals, remove noise points, and accurately calculate the mixing matrix vector; it is independent of the input parameters and offers great accuracy and robustness. Finally, an improved subspace projection method is used for source signal recovery, and the upper limit for the number of active sources at each mixed signal is increased from m−1 to m. The unmixing process of the proposed algorithm is symmetrical to the actual signal mixing process, allowing it to accurately estimate the mixing matrix and perform well in noisy environments. When compared to previous methods, the source signal recovery accuracy is improved. The method’s effectiveness is demonstrated by both theoretical and experimental results.
Developing Complexity-Informed COVID-19 Responses to Optimize Community Well-Being: A Systems Thinking Approach
Authors: Bogdewic Stephanie , Ramaswamy Rohit
Published: September 2021

Despite a range of federal and state interventions to slow the spread of COVID-19, the US has seen millions of infections and hundreds of thousands of deaths. Top-down mandates have been ineffective because the community spread of the pandemic has been influenced by complex local dynamics that have evolved over time. Systems thinking approaches, specifically causal loop diagrams, and leverage points, are important techniques for representing complexity at the local level and identifying responsive systems change opportunities. This commentary presents a causal loop diagram highlighting the progressive effects of prolonged state-level COVID-19 mandates at the community level. We also identify potential system leverage points that address these effects and present an imagined future state causal loop diagram in which these solutions are implemented. Our future system demonstrates the importance of collaborations to enable community-driven, bottom-up approaches to public health crises, such as the COVID-19 pandemic, that are adaptive and responsive to local needs.
Molecular Characterization and Cross-Reactivity of Feline Calicivirus Circulating in Southwestern China
Authors: Zhou Long , Fu Nengsheng , Ding Lu , Li Yan , Huang Jian , Sha Xue , Zhou Qun , Song Xin , Zhang Bin
Published: September 2021

Feline calicivirus (FCV) is an important pathogen of cats that has two genogroups (GI and GII). To investigate the prevalence and molecular characteristics of FCVs in southwestern China, 162 nasal swab samples were collected from cats in animal shelters and pet hospitals. In total, 38 of the clinical samples (23.46%) were identified as FCV positive using nested RT-PCR. Phylogenetic analyses using 10 capsid protein VP1 sequences revealed that 8 GI and 2 GII strains formed two independent clusters. Additionally, three separated FCVs that were not clustered phylogenetically (two GI and one GII strains) were successfully isolated from clinical samples and their full-length genomes were obtained. Phylogenetic and recombinant analyses of a GI FCV revealed genomic breakpoints in ORF1 and ORF2 regions with evidence for recombinant events between GI sub-genogroups, which is reported in China for the first time. Furthermore, sera obtained from mice immunized independently with the three FCV isolates and a commercial vaccine were used to evaluate the cross-reactivity of neutralizing antibodies. The three separate FCVs were neutralized by each other at a 1:19 to 1:775 titer range, whereas the triple-inactivated vaccine was at a titer of 1:16, which suggested that different genogroup/sub-genogroup FCV strains exhibit significantly different titers of neutralizing antibodies, including the commercial FCV vaccine. Thus, our study revealed the genetic diversity and complex cross-reactivity levels of FCVs in southwestern China, which provides new insights for application in vaccination strategies.
Acute Transverse Myelitis Following COVID-19 Vaccination
Authors: Gao Jhih-Jian , Tseng Hung-Pin , Lin Chun-Liang , Shiu Jr-Shiang , Lee Ming-Hsun , Liu Ching-Hsiung
Published: September 2021

An increasing number of people are undergoing vaccination for COVID-19 because of the ongoing pandemic. The newly developed, genetically engineered mRNA vaccines are critical for controlling the epidemic disease. However, major adverse effects, including neuroimmunological disorders, are being attributed to this vaccine. For instance, several cases of acute transverse myelitis (ATM) after COVID-19 vaccination have been reported in clinical trials. Here, we report an exceedingly rare case of longitudinally extensive transverse myelitis (LETM), a rare subtype of ATM involving three or more vertebral segments, that occurred shortly after vaccination with the Moderna COVID-19 (mRNA-1273) vaccine, with a comorbidity of vitamin B12 deficiency. The findings of subsequent investigations suggest the possibility that autoimmune responses are triggered by the reactions between anti-SARS-CoV-2 spike protein antibodies and tissue proteins, as well as the interaction between spike proteins and angiotensin-converting enzyme 2 receptors.
Recombinant Antigen of Type 2 Porcine Reproductive and Respiratory Syndrome Virus (PRRSV-2) Promotes M1 Repolarization of Porcine Alveolar Macrophages and Th1 Type Response
Authors: Wahyuningtyas Rika , Lai Yin-Siew , Wu Mei-Li , Chen Hsin-Wei , Chung Wen-Bin , Chaung Hso-Chi , Chang Ko-Tung
Published: September 2021

The polarization status of porcine alveolar macrophages (PAMs) determines the infectivity of porcine reproductive and respiratory syndrome virus (PRRSV). PRRSV infection skews macrophage polarization toward an M2 phenotype, followed by T-cells inactivation. CD163, one of the scavenger receptors of M2 macrophages, has been described as a putative receptor for PRRSV. In this study, we examined two types of PRRSV-2-derived recombinant antigens, A1 (g6Ld10T) and A2 (lipo-M5Nt), for their ability to mediate PAM polarization and T helper (Th1) response. A1 and A2 were composed of different combination of ORF5, ORF6, and ORF7 in full or partial length. To enhance the adaptive immunity, they were conjugated with T cells epitopes or lipidated elements, respectively. Our results showed that CD163+ expression on PAMs significantly decreased after being challenged with A1 but not A2, followed by a significant increase in pro-inflammatory genes (TNF-α, IL-6, and IL-12). In addition, next generation sequencing (NGS) data show an increase in T-cell receptor signaling in PAMs challenged with A1. Using a co-culture system, PAMs challenged with A1 can induce Th1 activation by boosting IFN-γ and IL-12 secretion and TNF-α expression. In terms of innate and T-cell-mediated immunity, we conclude that A1 is regarded as a potential vaccine for immunization against PRRSV infection due to its ability to reverse the polarization status of PAMs toward pro-inflammatory phenotypes, which in turn reduces CD163 expression for viral entry and increases immunomodulation for Th1-type response.