Miracle-dz/UniFAR-FTUs huggingface dataset:
How Environmental Awareness relates to Green Purchase Intentions can affect Brand Evangelism? Altruism and Environmental Consciousness as Mediators

The idea behind our research model was to analyse environmental awareness impact on green purchase intention and ultimate impact on brand evangelism through indirect role of customers’ altruism and environmental consciousness. Green consumers become more conscious to environment as the awareness spreads. Thus, consumers more leaned toward environmentally friendly products. The Theory of Planned Behaviour was employed to portray a clear analytical foundation of our research model. The respondents of green customers were gathered through survey from the online social-media sources particularly e-mails, WhatsApp and Facebook. In focused group, respondents were those which were active buyers of green products and must had past green purchase experience. Our analysis concludes the environmental awareness positively influence green purchase intention moreover the altruism and environmental consciousness partially mediates the indirect relationship. Finally, the brand evangelism has most significant influence on green purchase intention. The governance and managers of developing countries should invest on evangelists to spread the green message to delicate the environmental sustainability. The future researchers can examine a combination can be modelled into the influence of environmental awareness on brand evangelism while considering green purchase intentions as mediator.
Modeling and characterization of inter-individual variability in CD8 T cell responses in mice

To develop vaccines it is mandatory yet challenging to account for inter-individual variability during immune responses. Even in laboratory mice, T cell responses of single individuals exhibit a high heterogeneity that may come from genetic backgrounds, intra-specific processes (e.g. antigen-processing and presentation) and immunization protocols. To account for inter-individual variability in CD8 T cell responses in mice, we propose a dynamical model coupled to a statistical, nonlinear mixed effects model. Average and individual dynamics during a CD8 T cell response are characterized in different immunization contexts (vaccinia virus and tumor). On one hand, we identify biological processes that generate inter-individual variability (activation rate of naive cells, the mortality rate of effector cells, and dynamics of the immunogen). On the other hand, introducing categorical covariates to analyze two different immunization regimens, we highlight the steps of the response impacted by immunogens (priming, differentiation of naive cells, expansion of effector cells and generation of memory cells). The robustness of the model is assessed by confrontation to new experimental data. Our approach allows to investigate immune responses in various immunization contexts, when measurements are scarce or missing, and contributes to a better understanding of inter-individual variability in CD8 T cell immune responses.
The Effects of Wet-Milled Wood Flour on the Mechanical Properties of Wood Flour/Polypropylene Composites

Abstract The sizes and shapes of wet ball-milled wood flour were investigated based on their average particle size, size distribution, their solution viscosity, and scanning electron microscopy images. The ball-milling conditions were combinations of rotational speed (150, 200, and 250 rpm) and milling time (1 to 16 h). The average diameter of the wood flours decreased and the degree of fibrillation of the wood fibers increased with the ball-milling time at each rotational speed. Ball-milled wood flours having the same average particle size had similar surface fibrils that were tens to hundreds of nanometers wide. Ball-milling at 200 or 250 rpm could pulverize just as effectively as that at 150 rpm because the size reduction and fibrillation progressed more quickly. Tensile and bending properties of the composites prepared from the ball-milled wood flour (4 wt% in polypropylene) were evaluated. Morphological changes in the wood fillers had little effect on the properties of the composites. The tensile and bending properties of the composites containing the wood filler were 10% higher than those for the unfilled resin.
Check List

Angola has experienced an incredible increase of the knowledge of its herpetofauna over the past decade. However, accurate biodiversity inventories remain deficient for certain regions of particular conservation interest. We therefore provide an updated checklist of Iona National Park’s herpetofauna, with 75 recorded species, including five amphibians and 70 reptiles, 40 of these recorded for the first time in Iona National Park. These species comprise ~80% of the reptile diversity of Namibe Province. Therefore, this work recognises Iona National Park as the most reptile-diverse protected area in Angola and is potentially one of the richest in southern Africa. Consequently, this work enhances the importance of specific conservation plans in the area and the need for further investigation into the hidden biodiversity of this region.
Well-being and Psychopathology: A Deep Exploration into Positive Emotions, Meaning and Purpose in Life, and Social Relationships

For decades, researchers and practitioners have theorized psychological disorder and health as opposite ends of a single continuum. We offer a more nuanced, data driven examination into the various ways that people with psychological disorders experience well-being. We review research on the positive emotions, meaning and purpose in life, and social relationships of people diagnosed with major depressive disorder, bipolar disorder, social anxiety disorder, schizophrenia, and trauma-related disorders. We also discuss when and how friends, family members, and caregivers of these people are adversely impacted in terms of their well-being. Throughout, we highlight important, often overlooked findings that not all people with mental illness are devoid of well-being. This review is meant to be illustrative as opposed to comprehensive, synthesizing existing knowledge and inspiring explorations of unclear or undiscovered territory.
THE SAUDI MONARCHY @KINGSALMAN: EMOTIONAL CHOICE ON VIRTUAL SPACE

The purpose of this study is to explore how social media can provide leaders an emotional choice for virtual expression online. The study's case is the Saudi Monarchy, presented in the Twitter account of Saudi King Salman. It addresses the emotional aspects of communication via a Twitter account with local and international audiences while exploring the dark emotional choice of expression that the Monarchy wants to convey in different mediums. The research design builds on the dramaturgical approach and Lasswell's communication model to explore King Salman's Twitter posts, both on the frontstage (traditional media) and the backstage (Twitter). The systematic review indicates that social media, from emotional expression, lapse in the literature. The analysis considers the emotional communication of the significant events in Saudi Arabia from January 2015 to December 2015. The findings depict that the social media platform (Twitter) provides an emotional expression for lighter shades of dark emotions, while darker shades of emotions are expressed more visibly on traditional media outlets. This paper discusses a new perspective to review leadership identity via virtual communication and explores their emotional choices through Twitter posts. The paper concludes with some justifications for the leadership’s emotional choices directed by emotional intelligence.
Theories, models and frameworks in men's health studies: A scoping review

Background and Objectives: Men's health has been acknowledged as a broad ﬁeld that comprises not only of male speciﬁc diseases, but involves widely differing disciplines. While a signiﬁcant number of studies have looked into the deﬁnition of men's health, there is a lack of concerted attempts to collectively review the theories, models and frameworks in men's health studies. This paper presents an overview of theories, models and frameworks used in past men's health studies. Material and Methods: A scoping review was conducted using the Arksey and O'Malley framework. Publications were searched in three electronic databases. Two independent researchers performed publications' selection and data charting. Any disagreement was resolved by consultation with a third researcher. Results: One hundred and forty publications were included in this review. Within these publications, 87 theories, models and frameworks were identiﬁed. They were found to be generic to either health sciences or social sciences, or speciﬁc to men's health. Three type of processes were observed among the theories, models and frameworks, namely, behavioural, cognitive and gender processes. The ﬁndings also indicated a lack of publications about theories, models and frameworks in men's health studies from developing countries and outside the western world. Conclusion: The results revealed the multidisciplinary nature of men's health. However, due to the fragmentation of theoretical understanding by separate disciplines, an interdisciplinary approach is necessary for this ﬁeld.
The Effect of Accruals Quality On Return and Capital Cost

The present study aims to investigate the effect of accruals on return and cost of capital. Accordingly, by analyzing information of 92 companies over a period of 8 years from 2008 to 2015, the researcher seeks to study the effect of accruals quality on the returns and capital cost of the companies listed in Tehran Stock Exchange. Tadbirpardaz, Rah Avard-e Novin, Eviews and SPPS were used for analyzing the hypotheses. The results of hypothesis analysis indicate that accruals quality has different impacts on the capital cost components. Accruals have a positive and significant effect on the cost of equity, which increases the cost of internal resources provision, while there is no significant relationship between the accruals quality and costs. Moreover, the findings show that the quality of accruals leads to increased return on the companies’ market and the relationship between these two factors is positive and significant. Finally, the results of the Fama-French three-factor model analysis demonstrate that accruals quality cannot explain stock returns (equity premium) to assess companies’ returns, and statistically, there is no meaningful relationship between accruals quality and risk premium in the Fama-French three-factor model.
CDFF-Net: Cumulative Dense Feature Fusion for Single Image Specular Highlight Removal

Specular highlights are everywhere in our daily lives. However, they are often undesirable in the photography community, as they can severely bury the details of objects in the scene and degrade the image qualities. Existing high-light removal methods primarily rely on strict assumptions and can easily fail in scenes with complex backgrounds and illumination conditions. Although the success of deep learning techniques has been witnessed in many low-level vision areas, such as image denoising and image super-resolution, there is still few explorations of deep learning in the highlight removal area. This is partly due to the fact that there exists no large scale datasets of high-quality training data. In this paper, we propose to address the single image highlight removal problem from the following aspects. First, to facilitate the learning process for highlight removal, we construct a large scale synthetic dataset, which contains 11000 pairs of images with/without highlights. It will be made publicly available for future research. Second, we propose a novel Cumulative Dense Feature Fusion network, called CDFF-Net, to take full advantages of low-level features for producing high-quality highlight-free images. Moreover, a cascaded learning scheme is applied to ﬁrst learn the residual specular layer, and then remove the corresponding specular highlights according to the specular prediction. We conduct extensive evaluations on both synthetic and real data to verify the superiority of the proposed method against the state-of-the-art highlight removal methods. We also demonstrate the potential of the proposed network for other low-level vision tasks such as single image deraining.
Descending neocortical output critical for skilled forelimb movements is distributed across projection cell classes

Motor cortex is a key node in the forebrain circuits that enable flexible control of limb movements. The influence of motor cortex on movement execution is primarily carried by either pyramidal tract neurons (PT), which project directly to the brainstem and spinal cord, or intratelencephalic neurons (IT), which project within the forebrain. The logic of the interplay between these cell types and their relative contribution to the coordination and scaling of forelimb movements remains unclear. Here we combine large-scale neural recordings across all layers of motor cortex with cell-type specific perturbations in a cortex-dependent mouse behavior: kinematically-variable manipulation of a joystick. Our data demonstrate that descending neocortical motor commands are distributed across projection cell classes. IT neuron activity, in comparison to PT neurons, carries a larger fraction of information about gross movement kinematics. We find that forelimb movements are robust to optogenetic silencing of PT output, but substantially impaired by silencing Layer 5a IT projection neurons. Dorsal striatum is the unique extracortical integration point for IT and PT output pathways and its activity was more dependent upon IT input than PT input during movement execution. These data indicate that forebrain extrapyramidal pathways can be critical for regulating kinematics of motor skills.
Deep Reinforcement Learning in Starcraft II

Over the past decade, machine learning has become a popular subject in academia. With the emergence of technologies such as cars that can drive themselves, many academics and entrepreneurs have become interested in the practical applications of these algorithms. Reinforcement learning, a subset of machine learning, has seen several prominent breakthroughs. Unlike supervised or unsupervised machine learning, reinforcement learning aims to maximize a reward value by taking an action based upon a given state. For our research, we looked to apply deep reinforcement learning algorithms to the video game StarCraft II using the DeepMind PySC2 Python library. The library contains several mini-games that were developed specifically to be used as simulation environments for reinforcement learning research. In our case, we aimed to create deep reinforcement algorithms to play the mineral collection mini game; a game where two marines, which the AI controls, seeks to collect as many crystals as possible in an allotted time frame.
Enhancement of Suppressive Effect of Compost on Faba Bean Root Rot and Wilt Diseases by Yeast Seed Treatment

Effect of soil amendment with two composts (CMS) types (Planta Rich and Rich) alone or incombination with seed coating with the antagonistic yeast Pichia gluilliermondi on severity of Rhizoctonia root rot, Fusarium root rot and wilt diseases of faba bean were tested under greenhouse and field conditions. Application of CMS at the rates equivalent to 2, 7, 10 and 14 ton/feddan (T/F) in greenhouse and 7 and 10 T/F in the field reduced % of diseases and increased plant fresh weight. Combined CMS treatments with yeast seed treatment enhanced the suppressive effect of CMS on the tested diseases and increased percentage of plant growth. The potential of the tested composts on disease severity and plant growth was similar.
The Formation of Silicon Nanoparticles on Silicon-on-insulator Substrate by Thermal Anneal

THE FORMATION OF SILICON NANOPARTICLES ON SILICON-ON-INSULATOR SUBSTRATE BY THERMAL ANNEALING by Benedict Anyamesem-Mensah, B.S. Texas State University-San Marcos May 2007 SUPERVISING PROFESSOR: GREGORY F. SPENCER In this study, we investigated the formation of silicon nanoparticles on a silicon-oninsulator (SOI) substrate that were created with a simple thermal treatment using temperatures ranging from 600 o C to 900 C under atmospheric pressure in an inert gas (Ar). We studied the nanoparticle formation process versus the temperature of the thermal anneal, the thickness of the top silicon layer and we determined the variation of the particle size distribution with these parameters. The post-anneal substrate morphology is studied using ex situ atomic force microscopy (AFM). It was found that nanoparticle size increases with an increase in both the temperature and thickness of the top silicon layer. From a technological point of view, this study opens up a simpler way to synthesize silicon nanoparticles on an insulator.
METAZOÁRIOS PARASITOS DA CABRINHA Prionotus punctatus (BLOCH, 1793) (OSTEICHTHYES: TRIGLIDAE) DO LITORAL DO ESTADO DO RIO DE JANEIRO, BRASIL

BICUDO, A.J.A. ; TAVARES, L.E. R. ; LUQUE, J.L. [Metazoan parasites of the bluewing searobin Prionotus punctatus (Bloch, 1793) (Osteichthyes: Triglidae) from the coastal zone of the State of Rio de Janeiro, Brazil. ] Metazoários parasitos da cabrinha Prionotus punctatus Bloch, 1797 (Osteichthyes: Triglidae) do litoral do estado do Rio de Janeiro, Brasil. Revista Brasileira de Parasitologia Veterinária, v. 14, n. 1, p. 27-33, 2005. Departamento de Parasitologia Animal, Universidade Federal Rural do Rio de Janeiro, BR 465, Km 7, Seropédica, RJ 23890000, Brazil. E-mail: jlluque@ufrrj.br Eighty specimens of P. punctatus from Angra dos Reis, coastal zone of the State of Rio de Janeiro (23°01’S, 44°19’W), were necropsied between May 2002 to August 2003 to study their infracommunities of metazoan parasites. Were collected 23 species of metazoan parasites: 4 digenean, 2 monogeneans, 2 cestodes, 2 acantocephalans, 6 nematodes, 3 copepods, 2 branchiura, 1 isopod and 1 hirudinean. All fishes were parasitized by two or more parasites species. The nematodes was the predominant taxon (58.6% of parasites collected). Hysterothylacium sp. was the most prevalent, abundant and dominant species. The total of parasites collected and the parasites species richness were significantly correlated with host’s total length. Ten species of parasites showed significantly correlation between parasites abundance and total length of P. punctatus. The sex of the host showed positive influence on abundance and prevalence of Hysterothylacium sp. , Progrillotia dollfusi Carvajal and Rego, 1983 and Dolops sp. Four pairs of adult endoparasites, one pair of endoparasites larval stages and two pairs of ectoparasites presented association and/or covariation between its prevalences and abundances, respectively. Quantitative dominance of endoparasites in the parasite community of P. punctatus could be related with the predatorious behavior of this fish.
Entity-Based Information Retrieval System: A Graph-Based Document and Query Model

: Named Entity has been playing an important role in information seeking and retrieval. Many queries in web search are related to entities. Several knowledge bases contain valuable information about named entities and their relations, such as Wikipedia, Freebase, DBpedia and YAGO. Most existing works, about entity-based search, propose exploiting knowledge about entities and their relationships for expanding or reformulating a user query. Query expansion and reformulation yield effective retrieval performance on average, but results a performance inferior to that of using the original query for many information needs. In this paper, we propose to differently investigate knowledge about named entities and their relations. Therefore, we ﬁrst present an entity-based document and query model. Then, we suggest a retrieval model based on language models to match between document and query models.
A NOVEL APPROACH FOR DETECTING FAKE NEWS THROUGH MULTI LAYER PERCEPTRON INCLUDING SENTIMENTS

-Fake news is a kind of false information to intentionally mislead or manipulate public opinion, through conventional mass media and ongoing social media. In recent years, due to explosive growth of online social media, fake news for different political agenda and commercial gains has been coming out in wide spread online. The main objective of the proposed method is to effectively detect fake news and prevent its diffusion on social media which has gained much attention in recent years. Here we also include latent sentiments hidden in user comments which can help to distinguish fake news from reliable content. We incorporate these latent sentiments into deep embedding framework (Multi-Layer Perceptron) for detecting fake news. First, we use multi modal networks to deal with heterogeneous data modalities. Second, to learn semantically meaningful spaces per data source, an adversarial mechanism is adopted. Third, we characterize a novel regularization loss to bring embeddings of relevant pairs closer. The real-world dataset used is PolitiFact, demonstrates the effectiveness in detecting fake news.
Interaction of Building Frame with Pile Foundation

The study deals with physical modeling of a typical building frame resting on a pile group embedded in cohesive soil mass using complete three-dimensional finite element analysis. The elements of the superstructure frame and that of the pile foundation are discretized using twenty node isoparametric continuum elements. The interface between the pile and pile cap is idealized using sixteen node isoparametric surface elements. The more improved finite element mesh is used for modeling soil element as compared to the one used in the study reported in the literature. The soil elements are discretized using eight node, nine node and twelve node continuum elements. Both the elements of superstructure and substructure (i.e., foundation) including soil are assumed to remain in elastic state at all the time. The interaction analysis is carried out using sub-structure approach to attempt a parametric study. The effect of the parameter such as spacing between the piles in a group and diameter of pile is evaluated on the response of superstructure. The response includes the displacement at the top of the frame. The effect of the soil-structure interaction is observed to be significant for the type of foundation and soil considered in the present study.
Physicochemical properties and oxidative stability of oils from samrong (Sterculia foetida) seed

Samrong seed kernel consisted of 5.91 ± 0.12% moisture, 2.80 ± 0.17% ash, 46.09 ± 0.44% oil, 11.68 ± 0.16% protein and 33.52 ± 0.07% carbohydrate. The crude oil was extracted from samrong seed kernel using cold hexane as solvent. The oil from samrong seed kernel contained 27.32% saturated fatty acid (SFA), 5.30% monounsaturated fatty acid (MUFA) and 55.95% poly-unsaturated fatty acid (PUFA). Gammalinolenic acid (47.80%) was the dominant fatty acid, followed by palmitic acid (16.49%) and steric acid (10.45%). The physicochemical properties including color, viscosity, tocopherol content, total phenolic content, acid value, free fatty acid, peroxide value (PV), thiobarbituric acid reactive substances (TBARS) and ρ-anisidine value of kernel oil were determined. When kernel oil was stored at 30°C for 48 days, the oxidative stability of kernel oil was also examined. The kernel oil had the increase in PV and TBARS within the first 36 days of storage (P < 0.05). Subsequently, a decrease in PV and TBARS were noticeable up to day 48 (P < 0.05). Oil from samrong seed kernel showed high quality and oxidative stability during storage. Thus, samrong seed kernel could be used as a potential source of edible oil for use in the food industrial.