bluuebunny/crossref_metadata_2025 huggingface dataset:
Seasonal Variation in Visitor Satisfaction and Its Management Implications in Banff National Park
Authors: Geng Dehui Christina , Innes John L. , Wu Wanli , Wang Weiwei , Wang Guangyu
Published: February 2021

Seasonal variations in tourist satisfaction is an important issue for the sustainable management of national parks worldwide. Visitors should have high-quality experiences in both the high season and the off-season. This research investigated visitor satisfaction patterns and determinants in Banff National Park in different seasons. The study was conducted through a face-to-face questionnaire survey that collected visitor demographic, expectation and satisfaction data in July 2019 (high season) and December 2019 (off-season) in Banff National Park. The data analyses were based on a sample of 741 respondents and were processed using principal component analysis, correlation analysis and logistic regression models for different seasons. There were significant differences in visitor satisfaction levels and their determinants in different seasons. The quality of the park’s natural characteristics and the park’s activities were the most important determinant of visitor satisfaction in the high season and off-season, respectively. The correlation between visitor satisfaction and expectations in the high season was generally negative, whereas all correlations in the off-season were positive. The results fill a knowledge gap by examining the seasonal differences in visitor experience and their determinants in the national park, and by building a bridge between visitor experience and tourism seasonality. The findings may assist both practitioners and scholars in understanding visitor expectations and satisfaction in different seasons. They may assist in the prioritization and effective management of the park to optimize the visitor experience in both seasons and achieve tourism sustainability.
Crop Wild Relatives (CWR) Priority in Italy: Distribution, Ecology, In Situ and Ex Situ Conservation and Expected Actions
Authors: Perrino Enrico Vito , Wagensommer Robert Philipp
Published: February 2021

The study presents an updated overview of the 14 non-endemic threatened crop wild relatives (CWR) in Italy: Aegilops biuncialis, Ae. uniaristata, Ae. ventricosa, Asparagus pastorianus, Beta macrocarpa, Brassica insularis, B. montana, Crambe hispanica subsp. hispanica, C. tataria subsp. tataria, Ipomoea sagittata, Lathyrus amphicarpos, L. palustris, Vicia cusnae and V. serinica. Geographical distribution, ecology (with plant communities and habitat 92/43/EEC aspects), genetics (focused on gene pools), property, and in situ and ex situ conservation were analyzed. In addition, with the aim of their protection and valorization, specific actions are recommended.
Characteristics and Specificities of Local Innovation Accelerators: A Case of Poland
Authors: Szczukiewicz Konrad , Makowiec Marek
Published: February 2021

Accelerators are one of the most recent and prominent institutions that support start-up development. The phenomenon of accelerators impacts academia as well as policy makers and practitioners. However, the research on accelerators is still very scant and the majority of research concerns the most prestigious and successful American accelerators. The purpose of this paper is to outline the characteristics of Polish accelerators and their specificities, with the focus on the differences between public and private accelerators. The collateral aim of the authors was to describe characteristics and components of an innovation accelerator and its placement in the ecosystem of institutional support for start-ups. The first part of the study focuses on the definition of an accelerator, the review of relevant literature and the differences between other well established institutions such as incubators and business angels. The second part of the study presents the current state of accelerators in Poland. It is observed that the majority of the accelerators in Poland are publicly funded and accelerators avoid taking equity in accelerated start-ups. This is an effect of the competition from public accelerators, which offer a sizable equity-free grant of 200,000 PLN. This study enriches the research on different models of local accelerators and their acceleration programs.
Machine Learning Aided Design and Prediction of Environmentally Friendly Rubberised Concrete
Authors: Huang Xu , Zhang Jiaqi , Sresakoolchai Jessada , Kaewunruen Sakdirat
Published: February 2021

Not only can waste rubber enhance the properties of concrete (e.g., its dynamic damping and abrasion resistance capacity), its rational utilisation can also dramatically reduce environmental pollution and carbon footprint globally. This study is the world’s first to develop a novel machine learning-aided design and prediction of environmentally friendly concrete using waste rubber, which can drive sustainable development of infrastructure systems towards net-zero emission, which saves time and cost. In this study, artificial neuron networks (ANN) have been established to determine the design relationship between various concrete mix composites and their multiple mechanical properties simultaneously. Interestingly, it is found that almost all previous studies on the ANNs could only predict one kind of mechanical property. To enable multiple mechanical property predictions, ANN models with various architectural algorithms, hidden neurons and layers are built and tailored for benchmarking in this study. Comprehensively, all three hundred and fifty-three experimental data sets of rubberised concrete available in the open literature have been collected. In this study, the mechanical properties in focus consist of the compressive strength at day 7 (CS7), the compressive strength at day 28 (CS28), the flexural strength (FS), the tensile strength (TS) and the elastic modulus (EM). The optimal ANN architecture has been identified by customising and benchmarking the algorithms (Levenberg–Marquardt (LM), Bayesian Regularisation (BR) and Scaled Conjugate Gradient (SCG)), hidden layers (1–2) and hidden neurons (1–30). The performance of the optimal ANN architecture has been assessed by employing the mean squared error (MSE) and the coefficient of determination (R2). In addition, the prediction accuracy of the optimal ANN model has ben compared with that of the multiple linear regression (MLR).
An Ensemble Model based on Deep Learning and Data Preprocessing for Short-Term Electrical Load Forecasting
Authors: Shen Yamin , Ma Yuxuan , Deng Simin , Huang Chiou-Jye , Kuo Ping-Huan
Published: February 2021

Electricity load forecasting is one of the hot concerns of the current electricity market, and many forecasting models are proposed to satisfy the market participants’ needs. Most of the models have the shortcomings of large computation or low precision. To address this problem, a novel deep learning and data processing ensemble model called SELNet is proposed. We performed an experiment with this model; the experiment consisted of two parts: data processing and load forecasting. In the data processing part, the autocorrelation function (ACF) was used to analyze the raw data on the electricity load and determine the data to be input into the model. The variational mode decomposition (VMD) algorithm was used to decompose the electricity load raw-data into a set of relatively stable modes named intrinsic mode functions (IMFs). According to the time distribution and time lag determined using the ACF, the input of the model was reshaped into a 24 × 7 × 8 matrix M, where 24, 7, and 8 represent 24 h, 7 days, and 8 IMFs, respectively. In the load forecasting part, a two-dimensional convolutional neural network (2D-CNN) was used to extract features from the matrix M. The improved reshaped layer was used to reshape the extracted features according to the time order. A temporal convolutional network was then employed to learn the reshaped time-series features and combined with the fully connected layer to complete the prediction. Finally, the performance of the model was verified in the Eastern Electricity Market of Texas. To demonstrate the effectiveness of the proposed model data processing and load forecasting, we compared it with the gated recurrent unit (GRU), TCN, VMD-TCN, and VMD-CNN models. The TCN exhibited better performance than the GRU in load forecasting. The mean absolute percentage error (MAPE) of the TCN, which was over 5%, was less than that of the GRU. Following the addition of VMD to the TCN, the basic performance of the model was 2–3%. A comparison between the SELNet model and the VMD-TCN model indicated that the application of a 2D-CNN improves the forecast performance, with only a few samples having an MAPE of over 4%. The model’s prediction effect in each season is discussed, and it was found that the proposed model can achieve high-precision prediction in each season.
Real Time Safety Model for Pedestrian Red-Light Running at Signalized Intersections in China
Authors: Wu Yao , Guo Yanyong , Yin Wei
Published: February 2021

The traditional way to evaluate pedestrian safety is a reactive approach using the data at an aggregate level. The objective of this study is to develop real-time safety models for pedestrian red-light running using the signal cycle level traffic data. Traffic data for 464 signal cycles during 16 h were collected at eight crosswalks on two intersections in the city of Nanjing, China. Various real-time safety models of pedestrian red-light running were developed based on the different combination of explanatory variables using the Bayesian Poisson-lognormal (PLN) model. The Bayesian estimation approach based on Markov chain Monte Carlo simulation is utilized for the real-time safety models estimates. The models’ comparison results show that the model incorporated exposure, pedestrians’ characteristics and crossing maneuver, and traffic control and crosswalk design outperforms the model incorporated exposure and the model incorporated exposure, pedestrians’ characteristics, and crossing maneuver. The result indicates that including more variables in the real-time safety model could improve the model fit. The model estimation results show that pedestrian volume, ratio of males, ratio of pedestrians on phone talking, pedestrian waiting time, green ratio, signal type, and length of crosswalk are statistically significantly associated with the pedestrians’ red-light running. The findings from this study could be useful in real-time pedestrian safety evaluation as well as in crosswalk design and pedestrian signal optimization.
The Environmental Impact of Ecological Intensification in Soybean Cropping Systems in the U.S. Upper Midwest
Authors: Cecchin Andrea , Pourhashem Ghasideh , Gesch Russ W. , Mohammed Yesuf A. , Patel Swetabh , Lenssen Andrew W. , Berti Marisol T.
Published: February 2021

Introducing cover crops is a form of ecological intensification that can potentially reduce local, regional and global environmental impacts of soybean cropping systems. An assessment of multiple environmental impacts (global warming potential, eutrophication, soil erosion and soil organic carbon variation) was performed on a continuous soybean system in the U.S. upper Midwest. Four sequences were assessed and compared: a soybean cropping system with winter camelina, field pennycress, or winter rye as cover crop, plus a control (sole soybean). Cover crops were interseeded into standing soybean in Year 1, while in Year 2 soybean was relay-cropped into standing camelina or pennycress. Rye was terminated before sowing soybean. When compared with the control, sequences with cover crops showed lower eutrophication potential (4–9% reduction) and soil erosion (5–32% reduction) per ha year−1, in addition to a lower global warming potential (3–8% reduction) when the cover crop was not fertilized. However, when the economic component was included in the assessment, and the results expressed per USD net margin, the sequences with cover crops significantly reduced their performance in all categories of impact considered. A further optimization of field management for camelina and pennycress is recommended to make the cropping system more sustainable.
Youth Agricultural Entrepreneurship: Assessing the Impact of Agricultural Training Programmes on Performance
Authors: Adeyanju Dolapo , Mburu John , Mignouna Djana
Published: February 2021

Using the case of the Fadama Graduate Unemployed Youth and Women Support (GUYS) programme, this study investigated the impact of agricultural training programmes on youth agripreneurship performance in Nigeria. A total of 977 respondents comprising of 455 participants of the programme and 522 non-participants were sampled across three states in Nigeria. Data were collected using a well-structured questionnaire programmed on Open Data Kit (ODK). Data were analysed using the Endogenous Treatment Effect Regression (ETER) model. The probit model results revealed that participation in the programme was significantly influenced by age, years of formal education, marital status, current residence, employment type, and perception of training. The empirical analysis showed that after controlling for endogeneity, participation in the programme led to better performance which was measure in terms of average income from agripreneurship activities. These findings highlight the significance of training in improving the performance of young agripreneurs and suggest the need to encourage and out-scale programmes such as the Fadama GUYS, both in Nigeria and elsewhere in Africa as they can contribute to better performance of youth-owned agribusiness firms.
Evaluation of Environmental and Economic Sustainability for the Building Envelope of Low-Carbon Schools
Authors: Bazzocchi Frida , Ciacci Cecilia , Di Naso Vincenzo
Published: February 2021

To achieve a carbon-free economy by 2050, the construction of low-carbon schools in Italy must select the proper structural and technological solutions for the building envelope while ensuring a low economic cost. The aim of this study was to analyze and compare several technological solutions for the building envelope and the related structural solutions in terms of thermo-dynamic properties, energy performance, environmental sustainability parameters, and economic evaluations, to obtain one or more alternatives. After a general study, the binomial load-bearing structure–external wall was investigated given its strong influence on both the environment and the total cost. The solutions were used in a new typological model for the kindergarten. All the solutions are comparable from an energy and environmental point of view, obtaining a primary energy demand of <25 kWh/(m2year) and an environmental impact of <20 kWh/(m2year). However, considering the economic factor and analyzing the binomial load-bearing structure–external wall, the advisable solutions are those that use wooden structures with insulation layer in wood fiber as they have a significantly lower environmental impact, along with the same good energy performance and have an acceptable cost compared to other analyzed solutions.
Investigation of Lithium Application and Effect of Organic Matter on Soil Health
Authors: Hayyat Muhammad Umar , Nawaz Rab , Siddiq Zafar , Shakoor Muhammad Bilal , Mushtaq Maira , Ahmad Sajid Rashid , Ali Shafaqat , Hussain Afzal , Irshad Muhammad Atif , Alsahli Abdulaziz Abdullah , Alyemeni Mohammed Nasser
Published: February 2021

The extensive use of lithium (Li) ion-based batteries has increased the contamination of soil and water systems due to widespread dispersal of Li products in the environment. In the current study, the influence of Li application on soil fertility and leachate was observed. Three soil samples were collected and five treatments of Li (0, 50, 100, 150 and 200 mg/L) were applied. After three months of Li treatment, leachate was collected and soil samples were subjected to physical and chemical analyses. The results showed that the mean values of soil pH were increased slightly after Li application while electrical conductivity (EC) ranged from 1.2 to 5.1 µS/cm, indicating that soil was slightly saline in nature. The sodium was observed to be greater than the recommended values (0.3–0.7 mg/kg) in Li-amended soil while calcium and magnesium values decreased in soils compared to untreated soil. Mean values of phosphorus and potassium were greater before Li application and reduced considerably after Li application. Leachate analysis showed that all the parameters differed significantly except those of zinc and iron. The EC of leachate samples ranged from 2286–7188 µS/cm, which shows strong salinity. The sodium adsorption ratio (SAR) ranged from 1–11, which indicates that it falls into the marginal soil category. Lithium concentration in leachate samples ranged from 0–95 mg/L, which was significantly higher than the acceptable value for lithium (2.5 mg/L) in leachate. A soil sample (3) with an additional 10% organic matter showed that after Li application, the loss of nutrients in leachate was less as compared to the other two samples, demonstrating that organic matter improved soil conditions and suppressed the negative effects of Li on soil. Our results could raise concerns about risks in situations where food and fodder crops are associated with Li-contaminated waste disposal.
Adventure Tourism in the Spanish Population: Sociodemographic Analysis to Improve Sustainability
Authors: Rojo-Ramos Jorge , Vidal-Espinoza Rubén , Palacios-Cartagena Roxana Paola , Galán-Arroyo Carmen , Manzano-Redondo Fernando , Gómez-Campos Rossana , Adsuar José Carmelo
Published: February 2021

In recent decades, tourism is an activity in continuous growth and generates a significant impact in the social, economic, and environmental fields. Adventure tourism mainly takes place in natural settings, where tourist immersion will generate, in addition to profits, an impact on nature and the conservation of natural areas. The purpose of this work is to analyze the sociodemographic characteristics of tourists who choose to carry out adventure activities, as well as the means of transport used. For this, we have carried out this study through analysis of the 2019 data file of tourists from the National Statistics Institute with a sample of adventure tourists of 380 people. The results of the analysis show that the type of tourist who does adventure sports is single people with a higher educational level and a stable professional situation. The most frequently used means of transport to a destination is private transport, and lodging accounts for the majority of accommodation. It should be noted that significant gender differences were found in the level of studies, professional status in the job performed, and type of accommodation. Finally, the profile of the adventure tourist will be very useful for planning sustainable tourism.
Economic Analysis of Measures for GHG Emission Reduction
Authors: Ćetković Jasmina , Lakić Slobodan , Živković Angelina , Žarković Miloš , Vujadinović Radoje
Published: February 2021

The European Union, as a signatory to the Paris Agreement, has approached the action against greenhouse gas (GHG) emissions and climate change quite ambitiously, striving to achieve climate neutrality by 2050. Extension of the European Green Deal policy implementation to the Western Balkans can only increase the chances of the climate neutral agenda. Expectations from Montenegro in the coming period are transposable to other Western Balkans countries as they are urged to start implementing the Paris Agreement by establishing appropriate policies and measures. In this regard, this paper presents the analysis of the financial and economic analysis results of measures to reduce GHG emissions in Montenegro. With this respect, least cost analysis—cost effectiveness analysis and cost–benefit analysis were conducted. The analysis results indicated that due to the thermal power plant reconstruction, increased use of renewable energy sources and measures to increase energy efficiency, the largest reduction in GHG emissions in Montenegro in the next 10 years is expected in the energy sector.
Learning Resilience in Local Livestock Breeds from COVID-19 Pandemic
Authors: Turri Federica , Pizzi Flavia , Gandini Gustavo
Published: February 2021

In situ conservation of local breeds requires populations in economically sustainable and resilient production systems. In those countries where the market recognizes the quality of the products of local breeds, the traditional relationship between local breeds and products can be used to improve breed profitability. We analyze sales data from year 2020 of five dairy products associated with endangered local breeds farmed in northern Italy, in order to understand the potential resilience of these production systems, in terms of ability to persist and to adapt to disturbances associated with the COVID-19 pandemic. All breed-cheese systems showed good capacity to persist during the COVID-19 pandemic, with four systems even increasing sales with respect to the period 2017–2019. Three breed-cheese systems showed rapid adaptation to the new conditions by modifying sales channels, including the introduction of e-commerce.
Toward an Evaluation of Cultural Ecosystem Services Delivered by Urban Micro-Farms
Authors: Giacchè Giulia , Consalès Jean-Noël , Grard Baptiste J-P. , Daniel Anne-Cécile , Chenu Claire
Published: February 2021

Since two decades, urban agriculture has been booming and a wide range of forms, from urban allotment gardens to rooftop farming under greenhouse, is developing. Various benefits are recognized for urban agriculture integration within the city and a specific consideration is dedicated to ecosystem services. In this article, we have focused on cultural ecosystem services provided by urban micro-farms. The state of the art reveals that urban agriculture delivers cultural ecosystem services that are well perceived and evaluated by users, but there are still few studies on this topic. Based on the analysis of specific literature on cultural ecosystems and micro-farms in parallel to a period of observation and documentary research of five urban micro-farms either on rooftop or at soil level, located in Paris and its surroundings, we proposed a specific methodology. This methodology aimed at quantitative and qualitative evaluation of the cultural ecosystem services provided by urban micro-farms and is based on a framework, which distinguishes exogenous and endogenous cultural ecosystem services.
New Challenges for Sustainable Organizations in Light of Agenda 2030 for Sustainability
Authors: Morea Donato , Gebennini Elisa , Mazzitelli Andrea , Andreano Maria Simona , Basile Gianpaolo , Dominici Gandolfo
Published: February 2021

Sustainability is one of humanity’s most daunting issues at present [...]
The Defining Characteristics of Agroecosystem Living Labs
Authors: McPhee Chris , Bancerz Margaret , Mambrini-Doudet Muriel , Chrétien François , Huyghe Christian , Gracia-Garza Javier
Published: February 2021

In response to environmental, economic, and social challenges, the living labs approach to innovation is receiving increasing attention within the agricultural sector. In this paper, we propose a set of defining characteristics for an emerging type of living lab intended to increase the sustainability and resilience of agriculture and agri-food systems: the “agroecosystem living lab”. Drawing on first-hand knowledge of case studies of large initiatives from Canada and France and supported by eight other cases from the literature, we highlight the unique nature of agroecosystem living labs and their distinct challenges with respect to their aims, activities, participants, and context. In particular, these living labs are characterized by exceptionally high levels of scientific research; long innovation cycles with high uncertainty due to external factors; and the high number and diversity of stakeholders involved. Both procedurally and conceptually, we link to earlier efforts undertaken by researchers seeking to identify urban living labs and rural living labs as distinct, new types of living labs. By highlighting what makes agroecosystem living labs unique and their commonalities with other types of living labs, we hope to encourage their further study and help practitioners better understand their implementation and operational challenges and opportunities.
Urban Planning as a Strategy to Implement Social Sustainability Policy Goals? The Case of Temporary Housing for Immigrants in Gothenburg, Sweden
Authors: Stepanova Olga , Romanov Magdalena
Published: February 2021

Planning is one of the envisioned strategies for reaching policy goals of urban social sustainability. However, the practical realization of this vision faces a number of challenges not least due to conflicts of interests and goals that arise in the planning process. There also seems to be a lack of understanding of the relationship between formal planning and social sustainability goals that are often normative and visionary. In order to bridge this knowledge gap, this paper investigates how urban social sustainability can be implemented in urban planning in the context of conflicts of interests and goals. In particular, we explore two questions: (i) whether and how planning procedures are interconnected with local policy goals for social sustainability; (ii) whether and how conflict affects the implementation of these goals through planning. The paper presents a qualitative case study of planning of temporary housing for immigrants in Gothenburg, Sweden, where a conflict of interests developed in conjunction with the planning. The local social sustainability goals are operationalized through the specific sub-goals of accessible and more equal living conditions, distribution of and equal access to housing for all groups in the community, and reduced social and ethnic segregation and discrimination in regard to housing. We identify shortcomings in the integration of local urban social sustainability goals into planning procedures and find that conflicts of interests as well as conflicts of priorities within and between the policy goals complicate their integration into formal planning procedures. More attention needs to be given to improved operationalization of the questions of priority and conflict resolution, both in planning and in urban social sustainability policy, if planning is to be considered a viable strategy for implementation of social sustainability goals.
Does Emotional Intelligence Influence Academic Performance? The Role of Compassion and Engagement in Education for Sustainable Development
Authors: Estrada Marta , Monferrer Diego , Rodríguez Alma , Moliner Miguel Ángel
Published: February 2021

Education must guide students’ emotional development, not only to improve their skills and help them achieve their maximum performance, but to establish the foundations of a more cooperative and compassionate society. Achieving the Sustainable Development Goals, therefore, implies focusing on emotional aspects as well as financial, social, environmental, and scientific objectives. In this line, the goal of this study is to show how emotional intelligence, which is an essential dimension in the development and management of emotional competences required to build sustainable societies, plays a key role in optimising student’s academic performance in the classroom through compassion and academic commitment. The research model was tested with a questionnaire addressed to 550 students from four higher education institutions and one secondary school. The results of a structural equation analysis confirmed the study hypotheses. Emotional intelligence was shown to be positively related to compassion and higher levels of commitment, which, consequently, led to better academic performance. This finding will encourage interest in developing emotional intelligence, not only for its long-term value in training healthy citizens, but also for its short-term results in the classroom.
Multi-Stroke Thai Finger-Spelling Sign Language Recognition System with Deep Learning
Authors: Pariwat Thongpan , Seresangtakul Pusadee
Published: February 2021

Sign language is a type of language for the hearing impaired that people in the general public commonly do not understand. A sign language recognition system, therefore, represents an intermediary between the two sides. As a communication tool, a multi-stroke Thai finger-spelling sign language (TFSL) recognition system featuring deep learning was developed in this study. This research uses a vision-based technique on a complex background with semantic segmentation performed with dilated convolution for hand segmentation, hand strokes separated using optical flow, and learning feature and classification done with convolution neural network (CNN). We then compared the five CNN structures that define the formats. The first format was used to set the number of filters to 64 and the size of the filter to 3 × 3 with 7 layers; the second format used 128 filters, each filter 3 × 3 in size with 7 layers; the third format used the number of filters in ascending order with 7 layers, all of which had an equal 3 × 3 filter size; the fourth format determined the number of filters in ascending order and the size of the filter based on a small size with 7 layers; the final format was a structure based on AlexNet. As a result, the average accuracy was 88.83%, 87.97%, 89.91%, 90.43%, and 92.03%, respectively. We implemented the CNN structure based on AlexNet to create models for multi-stroke TFSL recognition systems. The experiment was performed using an isolated video of 42 Thai alphabets, which are divided into three categories consisting of one stroke, two strokes, and three strokes. The results presented an 88.00% average accuracy for one stroke, 85.42% for two strokes, and 75.00% for three strokes.
An Experimental Investigation on the Effect of Ferrous Ferric Oxide Nano-Additive and Chicken Fat Methyl Ester on Performance and Emission Characteristics of Compression Ignition Engine
Authors: Suhel Ameer , Abdul Rahim Norwazan , Abdul Rahman Mohd Rosdzimin , Bin Ahmad Khairol Amali , Teoh Yew Heng , Zainal Abidin Noh
Published: February 2021

In recent years, industries have been investing to develop a potential alternative fuel to substitute the depleting fossil fuels which emit noxious emissions. Present work investigated the effect of ferrous ferric oxide nano-additive on performance and emission parameters of compression ignition engine fuelled with chicken fat methyl ester blends. The nano-additive was included with various methyl ester blends at different ppm of 50, 100, and 150 through the ultrasonication process. Probe sonicator was utilized for nano-fuel preparation to inhibit the formation of agglomeration of nanoparticles in base fuel. Experimental results revealed that the addition of 100 ppm dosage of ferrous ferric oxide nanoparticles in blends significantly improves the combustion performance and substantially decrease the pernicious emissions of the engine. It is also found from an experimental results analysis that brake thermal efficiency (BTE) improved by 4.84%, a reduction in brake specific fuel consumption (BSFC) by 10.44%, brake specific energy consumption (BSEC) by 9.44%, exhaust gas temperature (EGT) by 19.47%, carbon monoxides (CO) by 53.22%, unburned hydrocarbon (UHC) by 21.73%, nitrogen oxides (NOx) by 15.39%, and smoke by 14.73% for the nano-fuel B20FFO100 blend. By seeing of analysis, it is concluded that the doping of ferrous ferric oxide nano-additive in chicken fat methyl ester blends shows an overall development in engine characteristics.
An Efficient Applications Cloud Interoperability Framework Using I-Anfis
Authors: Ramalingam Chithambaramani , Mohan Prakash
Published: February 2021

Cloud interoperability provides cloud services such as Software as a Service (SaaS) or customer system to communicate between the cloud providers. However, one of the most important barriers for existing researches was to adopt the application’s or data’s in cloud computing environments so as to obtain efficient cloud interoperability. This paper focuses on reliable cloud interoperability with a heterogeneous cloud computing resource environment with the objective of providing unilateral provision computing capabilities of a cloud server without the help of human interaction and allowing proper utilization of applications and services across various domains by using an effective cloud environment available at runtime. Moreover, the framework uses hybrid squirrel search genetic algorithm (HSSGA) to select the relevant features from a set of extracted features in order to eliminate irrelevant data which provides advantages of low computational time and less memory usage. Thereafter, for a proper selection of cloud server with respect to the selected features, the system has developed the improved adaptive neuro-fuzzy inference system (I-ANFIS) which provides accurate server selection and helps against uncertainties caused by servers or applications. Hence, the experimental result of the proposed framework gives an accuracy of 94.24% and remains more efficient compared to existing frameworks.
Supramolecular Chirogenesis in Bis-Porphyrin: Crystallographic Structure and CD Spectra for a Complex with a Chiral Guanidine Derivative
Authors: Osadchuk Irina , Konrad Nele , Truong Khai-Nghi , Rissanen Kari , Clot Eric , Aav Riina , Kananovich Dzmitry , Borovkov Victor
Published: February 2021

The complexation of (3aR,7aR)-N-(3,5-bis(trifluoromethyl)phenyl)octahydro-2H-benzo[d]imidazol-2-imine (BTI), as a guest, to ethane-bridged bis(zinc octaethylporphyrin), bis(ZnOEP), as a host, has been studied by means of ultraviolet-visible (UV-Vis) and circular dichroism (CD) absorption spectroscopies, single crystal X-ray diffraction, and computational simulation. The formation of 1:2 host-guest complex was established by X-ray diffraction and UV-Vis titration studies. Two guest BTI molecules are located at the opposite sides of two porphyrin subunits of bis(ZnOEP) host, which is resting in the anti-conformation. The complexation of BTI molecules proceed via coordination of the imine nitrogens to the zinc ions of each porphyrin subunit of the host. Such supramolecular organization of the complex results in a screw arrangement of the two porphyrin subunits, inducing a strong CD signal in the Soret (B) band region. The corresponding DFT computational studies are in a good agreement with the experimental results and prove the presence of 1:2 host-guest complex as the major component in the solution (97.7%), but its optimized geometry differs from that observed in the solid-state. The UV-Vis and CD spectra simulated by using the solution-state geometry and the TD-DFT/ωB97X-D/cc-pVDZ + SMD (CH2Cl2) level of theory reproduced the experimentally obtained UV-Vis and CD spectra and confirmed the difference between the solid-state and solution structures. Moreover, it was shown that CD spectrum is very sensitive to the spatial arrangement of porphyrin subunits.
Investigation on Combined Inhalation Exposure Scenarios to Biocidal Mixtures: Biocidal and Household Chemical Products in South Korea
Authors: Kim Sunmi , Seo Myungwon , Na Minju , Kim Jongwoon
Published: February 2021

Global regulations of biocides have been continuously enhanced for protecting human health and the environment from potentially harmful biocidal products. Such regulations consider the combined toxicity caused by mixture components in a biocidal product of which approval and authorization are to be enhanced. Although the combined exposure scenarios of components in mixtures are firstly needed to conduct the mixture risk assessment, systematic combined exposure scenarios are still lacking. In this study, combined inhalation exposure scenarios of biocides in household chemical and biocidal products marketed in South Korea were investigated based on the European Union (EU) and Korean chemical product databases and various data sources integration. The information of 1058 biocidal products and 675 household chemical products that are likely to cause inhalation exposure with two or more biocides was collected, and mixture combination patterns were investigated. Binary mixtures occupied 72% in biocidal products. The most frequently appearing binary mixture was phthalthrin and d-phenothrin. Based on the frequency of use, we suggested a priority list of biocide mixture combinations which need to be firstly evaluated for identifying their combined toxicity for the mixture risk assessment. This study highlights that the derived combined inhalation exposure scenarios can support and facilitate further studies on priority settings for mixture risk assessment and management of potentially inhalable biocides.
Cannabis: A Toxin-Producing Plant with Potential Therapeutic Uses
Authors: Breijyeh Zeinab , Jubeh Buthaina , Bufo Sabino A. , Karaman Rafik , Scrano Laura
Published: February 2021

For thousands of years, Cannabis sativa has been utilized as a medicine and for recreational and spiritual purposes. Phytocannabinoids are a family of compounds that are found in the cannabis plant, which is known for its psychotogenic and euphoric effects; the main psychotropic constituent of cannabis is Δ9-tetrahydrocannabinol (Δ9-THC). The pharmacological effects of cannabinoids are a result of interactions between those compounds and cannabinoid receptors, CB1 and CB2, located in many parts of the human body. Cannabis is used as a therapeutic agent for treating pain and emesis. Some cannabinoids are clinically applied for treating chronic pain, particularly cancer and multiple sclerosis-associated pain, for appetite stimulation and anti-emesis in HIV/AIDS and cancer patients, and for spasticity treatment in multiple sclerosis and epilepsy patients. Medical cannabis varies from recreational cannabis in the chemical content of THC and cannabidiol (CBD), modes of administration, and safety. Despite the therapeutic effects of cannabis, exposure to high concentrations of THC, the main compound that is responsible for most of the intoxicating effects experienced by users, could lead to psychological events and adverse effects that affect almost all body systems, such as neurological (dizziness, drowsiness, seizures, coma, and others), ophthalmological (mydriasis and conjunctival hyperemia), cardiovascular (tachycardia and arterial hypertension), and gastrointestinal (nausea, vomiting, and thirst), mainly associated with recreational use. Cannabis toxicity in children is more concerning and can cause serious adverse effects such as acute neurological symptoms (stupor), lethargy, seizures, and even coma. More countries are legalizing the commercial production and sale of cannabis for medicinal use, and some for recreational use as well. Liberalization of cannabis laws has led to increased incidence of toxicity, hyperemesis syndrome, lung disease cardiovascular disease, reduced fertility, tolerance, and dependence with chronic prolonged use. This review focuses on the potential therapeutic effects of cannabis and cannabinoids, as well as the acute and chronic toxic effects of cannabis use on various body systems.
Limits on Magnetized Quark-Nugget Dark Matter from Episodic Natural Events
Authors: VanDevender J. Pace , VanDevender Aaron P. , Wilson Peter , Hammel Benjamin F. , McGinley Niall
Published: February 2021

A quark nugget is a hypothetical dark-matter candidate composed of approximately equal numbers of up, down, and strange quarks. Most models of quark nuggets do not include effects of their intrinsic magnetic field. However, Tatsumi used a mathematically tractable approximation of the Standard Model of Particle Physics and found that the cores of magnetar pulsars may be quark nuggets in a ferromagnetic liquid state with surface magnetic field Bo = 1012±1 T. We have applied that result to quark-nugget dark matter. Previous work addressed the formation and aggregation of magnetized quark nuggets (MQNs) into a broad and magnetically stabilized mass distribution before they could decay and addressed their interaction with normal matter through their magnetopause, losing translational velocity while gaining rotational velocity and radiating electromagnetic energy. The two orders of magnitude uncertainty in Tatsumi’s estimate for Bo precludes the practical design of systematic experiments to detect MQNs through their predicted interaction with matter. In this paper, we examine episodic events consistent with a unique signature of MQNs. If they are indeed caused by MQNs, they constrain the most likely values of Bo to 1.65 × 1012 T +/− 21% and support the design of definitive tests of the MQN dark-matter hypothesis.
Holocene Millennial-Scale Solar Variability and the Climatic Responses on Earth
Authors: Zhao Xinhua , Soon Willie , Velasco Herrera Victor M.
Published: February 2021

The solar impact on Earth’s climate is both a rich and open-ended topic with intense debates. In this study, we use the reconstructed data available to investigate periodicities of solar variability (i.e., variations of sunspot numbers) and temperature changes (10 sites spread all over the Earth) as well as the statistical inter-relations between them on the millennial scale during the past 8640 years (BC 6755–AD 1885) before the modern industrial era. We find that the variations of the Earth’s temperatures show evidence for the Eddy cycle component, i.e., the 1000-year cyclicity, which was discovered in variations of sunspot numbers and believed to be an intrinsic periodicity of solar variability. Further wavelet time-frequency analysis demonstrates that the co-variation between the millennium cycle components of solar variability and the temperature change held stable and statistically strong for five out of these 10 sites during our study interval. In addition, the Earth’s climatic response to solar forcing could be different region-by-region, and the temperatures in the southern hemisphere seemed to have an opposite changing trend compared to those in the northern hemisphere on this millennial scale. These findings reveal not only a pronounced but also a complex relationship between solar variability and climatic change on Earth on the millennial timescale. More data are needed to further verify these preliminary results in the future.
Correction: Mashhoon, B. Critical Tidal Currents in General Relativity. Universe 2020, 6, 104
Authors: Mashhoon Bahram
Published: February 2021

In writing out the tidal equation for X in my recent paper [...]
HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles
Authors: Coelho Antonio Victor Campos , Gratton Rossella , Melo João Paulo Britto de , Andrade-Santos José Leandro , Guimarães Rafael Lima , Crovella Sergio , Tricarico Paola Maura , Brandão Lucas André Cavalcanti
Published: February 2021

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.
Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes
Authors: Mathkar Pranav , Chen Xun , Sulovari Arvis , Li Dawei
Published: February 2021

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. Almost half of HCC cases are associated with hepatitis B virus (HBV) infections, which often lead to HBV sequence integrations in the human genome. Accurate identification of HBV integration sites at a single nucleotide resolution is critical for developing a better understanding of the cancer genome landscape and of the disease itself. Here, we performed further analyses and characterization of HBV integrations identified by our recently reported VIcaller platform in recurrent or known HCC genes (such as TERT, MLL4, and CCNE1) as well as non-recurrent cancer-related genes (such as CSMD2, NKD2, and RHOU). Our pathway enrichment analysis revealed multiple pathways involving the alcohol dehydrogenase 4 gene, such as the metabolism pathways of retinol, tyrosine, and fatty acid. Further analysis of the HBV integration sites revealed distinct patterns involving the integration upper breakpoints, integrated genome lengths, and integration allele fractions between tumor and normal tissues. Our analysis also implies that the VIcaller method has diagnostic potential through discovering novel clonal integrations in cancer-related genes. In conclusion, although VIcaller is a hypothesis free virome-wide approach, it can still be applied to accurately identify genome-wide integration events of a specific candidate virus and their integration allele fractions.
Visualizing HIV-1 Capsid and Its Interactions with Antivirals and Host Factors
Authors: Wilbourne Morganne , Zhang Peijun
Published: February 2021

Understanding of the construction and function of the HIV capsid has advanced considerably in the last decade. This is due in large part to the development of more sophisticated structural techniques, particularly cryo-electron microscopy (cryoEM) and cryo-electron tomography (cryoET). The capsid is known to be a pleomorphic fullerene cone comprised of capsid protein monomers arranged into 200–250 hexamers and 12 pentamers. The latter of these induce high curvature necessary to close the cone at both ends. CryoEM/cryoET, NMR, and X-ray crystallography have collectively described these interactions to atomic or near-atomic resolutions. Further, these techniques have helped to clarify the role the HIV capsid plays in several parts of the viral life cycle, from reverse transcription to nuclear entry and integration into the host chromosome. This includes visualizing the capsid bound to host factors. Multiple proteins have been shown to interact with the capsid. Cyclophilin A, nucleoporins, and CPSF6 promote viral infectivity, while MxB and Trim5α diminish the viral infectivity. Finally, structural insights into the intra- and intermolecular interactions that govern capsid function have enabled development of small molecules, peptides, and truncated proteins to disrupt or stabilize the capsid to inhibit HIV replication. The most promising of these, GS6207, is now in clinical trial.
Molecular Epidemiology of Group A Streptococcus Infections in The Gambia
Authors: Jabang Sona , Erhart Annette , Darboe Saffiatou , Baldeh Aru-Kumba , Delforge Valerie , Watson Gabriella , Foster-Nyarko Ebenezer , Salaudeen Rasheed , Lawal Bolarinde , Mackenzie Grant , Botteaux Anne , Antonio Martin , Smeesters Pierre ,   on behalf of The MRCG StrepA Study Group
Published: February 2021

Molecular epidemiological data on Group A Streptococcus (GAS) infection in Africa is scarce. We characterized the emm-types and emm-clusters of 433 stored clinical GAS isolates from The Gambia collected between 2004 and 2018. To reduce the potential for strain mistyping, we used a newly published primer for emm-typing. There was considerable strain diversity, highlighting the need for vaccine development offering broad strain protection.