Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure and interaction of weakly charged polyelectrolyte brushes: Self-consistent field theory

A self-consistent field analytical theory is developed to analyze the equilibrium structure of weakly charged polyelectrolyte brushes in salt-free solutions. In contrast to previous studies based on the local electroneutrality approximation valid for sufficiently strongly charged or densely grafted (“osmotic”) brushes, we consider a general case comprising both limits of weakly and strongly charged systems without any a priori assumptions about the distribution of counterions. The analytical expressions for various structural properties of free and confined polyelectrolyte brushes are obtained and compared to existing scaling predictions. The elastic response and structural rearrangement in the polyelectrolyte brush under compression are analyzed.
Structure of dense liquids at solid interfaces

Detailed calculations of dense fluids of hard spheres, soft repulsive spheres and Lennard‐Jones molecules between hard, soft repulsive and attractive solid walls reveals a pronounced stratification of the fluid’s density profile. The calculations have been performed using the NVT Monte Carlo method with about 200 fluid molecules. The results indicate that a very significant role is played by the attractive component in the intermolecular potentials, which suggests that the usual hard‐sphere perturbation theories are not applicable in their present form.
EFFECT OF FEED SUPPLEMENTATION OF PROBIOTIC AND DIGESTIVE ENZYMES IN PRODUCTION PERFORMANCE AND INTESTINAL BIOMETRICS OF LAYING HENS

This study aimed to determine the effect of feed supplementation of the probiotic, digestive enzymes and their combination on productive performance, biometrics of small intestine and humoral immunity of laying hens. It was using 144 laying hens 23 week-old Lohmann Brown, be distributed in 12 ground pens, 12 hens/pen (Rep.), were randomly divided into four treatments (3 Rep./ treat.). Hens in the first treatment were fed a standard layer diet (control), hens in second treatment were fed a standard layer diet was added with 0.5g/kg probiotic, hens in third treatment were fed a standard layer diet was added with 0.75 g/kg digestive enzymes, hens in forth treatment were fed a standard layer diet was added with combination 0.5 g/kg probiotic and 0.75 g/kg digestive enzymes. The results showed a significant (P  0.05) improved in egg production, egg weight, egg mass, accumulative egg production and feed conversion ratio of supplementation treatments of the probiotic, digestive enzymes and their combination, In addition, probiotic treatment and combination treatment led to a significant increase in weight, length, villi length and crypts depth of small intestine, as well as humoral immunity. The results suggested that adding the probiotic or digestive enzymes improved the productive performance of laying hens, the probiotic was the best in the results, while the combination of the probiotic and digestive enzymes did not have improved results compared to the probiotic.
Redescription of Entomophthora muscae (Cohn) Fresenius

Entomophthora muscae (Zygomycetes, Entomophthoraceae) is redescribed from its type host, the house fly (Musca domestica L.), based on several collections from Switzerland and from Denmark. The species has subspherical, ellipsoidal, kidney-shaped or rounded hyphal bodies measuring 24-54 x 17-41 î m with 10-24 nuclei (average 15-19). Conidiophores are unbranched and contain 10-27 nuclei (average 15-20). The primary conidia measure on average 27-31 x 20-24 îm with a length/diameter ratio of 1.20-1.32 and 10-27 nuclei (average 15-20). The secondary conidia measure on average 19-24 x 15-19 urn with a length/diameter ratio of 1.201. 33. These data correspond with the type material deposited in herbaria. They do not correspond with the data given in the original description which is assumed to concern E. schizophorae, which was also found as a pathogen of M. domestica during these investigations. Detailed data on morphology, including intraspecific variability of E. muscae are given.
USING AFLP TO IDENTIFYGENETIC RELATIONSHIPS IN CASSIA SPECIES

Several species of Cassia are used in Thai folk medicine as a laxative and a treatment for skin infections. However, the taxonomy of the GenusCassia is quite complex and intriguing. Thus, the correct identification of the species of this genus is necessary for efficacy and safety. The phylogenetic relationships among the 16 species of Cassiagenus existing in Thailand were evaluated using Amplified Fragment Length Polymorphism (AFLP) technique. Combinations of 70 primers were screened and eleven primer combinations produced a total of 849 distinct and reproducible bands ranging from 60 to 100 bands with an average of 77.18 bands per primer combination. The genetic distances were calculated based on the AFLP bands that had been amplified using the eleven primer combinations. The similarity indices (SI) ranged from 0.25 to 0.78. The dendrogram was created using the Unweighted Pair Group Method of the Arithmetic Average (UPGMA) and the genotypes were divided into two major groups. The results indicate that the phylogenetic relationships are associated with the morphological characterization. In conclusion, an AFLP marker could be an efficient and reliable tool for the identification of a Cassia species.
MOLECULAR PHYLOGENY AND SYSTEMATICS OF GLOMEROMYCOTA : METHODS AND LIMITATIONS

Arbuscular Mycorrhiza (AM) fungi are symbiotically associated with more than 80% of terrestrial plant. AM fungi provide multiple benefits to plant by increasing uptake of nutrients from soil and also enhance level of soil fertility. Currently AM fungi have being used as a potential biofertilizers for sustainable agriculture production. However, AM fungi is ultimate biological organism for organic agricultural practices in cultivated land but identification, screening and mass scaling of specific genotype of AM fungi with desirable function is very tedious and time consuming. Therefore, present study revealed application and limitation of modern molecular tool and suggested some reliable molecular marker with broad taxonomic range for accurate detection of AM fungi from complex environment. Present study may future used as reference data sets for molecular systematics and community analyses in AM fungi collected from complex environmental soil. Key word: Arbuscular Mycorrhiza fungi (AMF), small subunits (SSU), Glomeromycota, internal transcribed spacer (ITS)
Variations in sustainable development goal interactions: Population, regional, and income disaggregation

Funding information Bundesministerium für Bildung und Forschung, Grant/Award Number: 01DP17035; Bundesministerium für Umwelt, Naturschutz, Bau und Reaktorsicherheit, Grant/Award Number: 42206-6157 Abstract To fulfill the 2030 Agenda, the complexity of sustainable development goal (SDG) interactions needs to be disentangled. However, this understanding is currently limited. We conduct a cross-sectional correlational analysis for 2016 to understand SDG interactions under the entire development spectrum. We apply several correlation methods to classify the interaction as synergy or trade-off and characterize them according to their monotony and linearity. Simultaneously, we analyze SDG interactions considering population, location, income, and regional groups. Our findings highlight that synergies always outweigh trade-offs and linear outweigh non-linear interactions. SDG 1, 5, and 6 are associated with linear synergies, SDG 3, and 7 with non-linear synergies. SDG interactions vary according to a country's income and region along with the gender, age, and location of its population. In summary, to achieve the 2030 Agenda the detected interactions and inequalities across countries need be tracked and leveraged to “leave no one behind. ”
Rating Prediction Method for Item-based Collaborative Filtering Recommender Systems Using Formal Concept Analysis

The recommender systems are used to mainly suggest recommendations to the online users by utilizing the user preferences recorded during the item purchase. No matter how, the performance of the recommendation quality seems to be inevitable and far satisfactory. In this paper, a new approach based on the mathematical model, Formal Concept Analysis (FCA) is used to improve the rating prediction of the unknown users which can certainly overcome the issues of the existing approaches like data sparsity, high dimensionality of data, performance of the recommendation generated for top n recommendation. The FCA method is applied using Boolean Matrix Factorization (ie. optimal formal concepts) in predicting the rating of the unknown users in the available user-item interaction matrix which proves to be more efficient in tackling the problem of computational complexity managing the high dimensionality of data. The proposed method is applied using item-based collaborative filtering technique and the experiment is conducted on the Movielens dataset which shows the satisfactory results. The experiments results are evaluated using the related error metrics and performance metrics. The experimental results are also compared with existing item-based Collaborative Filtering techniques which demonstrate that the performance of recommendation quality gradually improved with state-of-the-art existing techniques.
A MONOGRAPH ON MRI IMAGES RECONSTRUCTION USING GENERATIVE ADVERSARIAL NETWORK

This paper introduces a Magnetic Resonance Imaging (MRI) reconstruction, which gives rapid achievement and it is more advantageous for many clinical application. This reduces the scanning cost as well as image reconstructed in very less time, this will be advantage for real time technology. This paper confer a deep learning based plan for reconstruction of MRI images. In our Generative Adversarial Network (GAN) designed a generator which gives the better enhancement like texture smoothness, and high resolution to MRI images, Also find the ` In addition including the frequency domain information to embed similarity in both the images using parameter Structural Similarity Index (SSIM). Also performed radon transform to find the structural similarity of images with enhancement, accuracy and test whether the images are real or fake. Compared to other method, our GAN method provides superior reconstruction. A group of two images gives a reconstructed image using radon transform. Once the reconstruction is done, after applying radon transform on reconstructed images get the image same as it is.
Méthode de contribution de groupes pour la représentation des propriétés d'équilibre dans les solutions aqueuses

Un modele physico-chimique predictif a ete developpe pour representer les proprietes d'equilibre dans des solutions aqueuses simples et mixtes. La partie physique du modele utilise le modele de contribution de groupes UNIFAC modifie par Larsen et al (1987), associe a un terme electrostatique issu du modele Pitzer Debye-Huckel (Achard, 1992). La partie chimique, qui constitue l'originalite de ce travail, tient compte des interactions chimiques entre les molecules par un equilibre d'hydratation conduisant a la formation en une seule etape d'une nouvelle espece n-hydratee dans le melange. N, le nombre d'hydratation et K, la constante d'equilibre d'hydratation de l'espece hydratee, sont les deux parametres independants de cette partie chimique. La representation des proprietes thermodynamiques des solutions aqueuses electrolytiques et non electrolytiques a conduit, dans un premier temps, a identifier les deux parametres n et K ainsi que les parametres d'interaction entre les ions et l'eau. Les valeurs des parametres d'interaction et les groupes fonctionnels d'origine des especes non electrolytiques n'ont pas ete modifies. De plus il n'y a pas eu d'introduction de nouveaux groupes fonctionnels. Dans un deuxieme temps, le modele developpe a ete utilise pour predire d'autres proprietes d'equilibre, telles que le pH, l'activite de l'eau, les temperatures de fusion et d'ebullition et la solubilite des solutes dans des melanges aqueux binaires ternaires ou mixtes, contenant des especes neutres (sucres, polyols) et/ou electrolytiques (sels, acides, bases)
RESPONSE OF WHEAT CULTIVAR (SABER BEG) TO INOCULATION WITH NITROGEN FIXING AZOSPIRILLUM SPECIES (LOCAL ISOLATES)

Investigating the impact of the inoculant Azospirillum spp. isolate on wheat plant (Triticum aestivum cv. Saber Beg) root hair deformation, growth parameters and detecting host-specificity phenomenon. The nitrogenase activity (C2H2 reduction) of Azospirillum Spp. isolate was measured using gas chromatography method, and the impact of these isolate on the wheat cultivar (Saber Beg) were studied using hydroponic culture experiments. Emphasis was attempted on the impact of inoculation on the root hair deformation, root length, root fresh weight, and location of bacteria in infected root, also the response of the green part (fresh, dry weight and total nitrogen). Results showed that all isolate of Azospirillum spp. used could fix nitrogen and deform wheat root hair cv. Saber Beg forming forks or unequal branching phenomenon. Also, almost all isolates produce a significant increase in the root mass of Triticum aestivum cv Saber Beg. The same patterns of affect were found in the root length. Considering the green part of inoculated plant, positive response in early growth stage was observed, which was enhancing the shoot giving rise to a significant increase in fresh and dry weight and height of plant compared with the noninoculated control. Microscopic examination of cross section of infected roods showed that the bacterial cells was localized in the cortex layer.
Accent based speech recognition: A critical overview

An incredible amount of research has been conducted in speech recognition and accent-based speech recognition during recent decades. Automatic Speech Recognition in various dialects in any natural language is examined as one among the most complicated domains in Automatic Speech Recognition (ASR). The increasing signiﬁcance of speech recognition in any dialect is attributable to the ever-developing interest for applications that handle human-machine interaction through geographically inﬂuenced natural languages. The objective of this paper is to provide an overview of recent developments in dialect or accent-based speech processing. This paper concentrates on the study of accent-based speech recognition techniques in various languages and the technologies used for the same
Incorporating Labeled Features into Image Classification using Generalized Expectation

approved: Weng-Keen Wong Image classification is a difficult problem, often requiring large training sets to get satisfactory results. However this is a task that humans perform very well, and incorporating user feedback into these learning algorithms could help reduce the dependency on large amounts of labeled training data. This process has already been leveraged in text classification, through the incorporation of labeled features. Labeling features provides a much more informative form of feedback than existing vision feedback systems like active learning and relevance feedback. In this paper, I adapt the Generalized Expectation Criteria to incorporate labeled features into the more complex CRF model used for images. Experiments are performed using oracle selected features as a first step towards showing the potential benefits of this kind of user feedback for image classification. c ©Copyright by Travis Moore November 21, 2013 All Rights Reserved Incorporating Labeled Features into Image Classification using Generalized Expectation
EFFECT OF NORMAL AND SYNTHETIC ANTI MYCOTOXIN ON LEVELS OF NEUROTRANSMITTER HORMONES AND IMMUNE STATE IN BROILER CHICKENS

Mycotoxins one of major problems in poultry industry had wide different of harmful impact to birds. The study investigate the role of natural (Bentonite) and synthetic (Mycofix® Plus) antimycotoxin substance on levels of neurotransmitter hormones (Dopamine and Serotonin) and immune state (CD4, CD8) levels with contaminated diet with aflatoxin in broiler, A total of 180 broiler chicks were divided randomly into six groups T1-Control +ve chick’s given contaminated diet by mycotoxins only. T2-chick’s given Bentonite at a dose (5 kg / ton of feed) with contaminated diet by mycotoxins. T3-chick’s given Mycofix® Plus at a dose (1.5 kg / ton of feed) with contaminated diet by mycotoxins. T4-Active control chick’s given Bentonite® at a dose (5 kg / ton of feed) with not contaminated diet (free mycotoxins). T5-chick’s given Mycofix® Plus at a dose (1.5 kg / ton of feed) with not contaminated diet (free mycotoxins). T6-chick’s given not contaminated diet only (free mycotoxins). The result of Dopamine was significantly (P<0.05) higher in (T5) and no significant difference at (P<0.05) in (T2,T3,T6) respectively, then at T1 finally, T4 had less significant difference at (P<0.05) at 40 days old. The results of serotonin in 20 and 40 days old were recorded increased with significant difference at (P<0.05) in T5 then no significant difference at (P<0.05) between (T2,T3) respectively, followed (T4,T6) respectively. Finally T1 had less value. Results of CD4 in 20 and 40 days old were recorded increased with significant difference at (P<0.05) in (T4,T5) respectively and no significant difference between (T2,T3,T6) respectively. Then T1 had less value with significant difference at (P<0.05). The results of CD8 in 20 and 40 days old was recorded increased with significant difference at (P<0.05) in T5 among all groups. There were no significant difference at (P<0.05) between (T4,T6) respectively, then also between (T2,T3) respectively. Finally T1 had less value with significant difference at (P<0.05). In Conclusion mycotoxin had harmful impact on different biological and immunological parameters. Natural and synthetic anti-mycotoxin reduce mycotoxin levels in diet within the time. Natural and synthetic anti-mycotoxin maintains the immunological response by improved (CD4,CD8) levels, as well as improved levels of dopamine and serotonin (neurotransmitter hormones).
Causes of Outcome Learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome

Nearly all diseases can be caused by different combinations of exposures. Yet, most epidemiological studies focus on the causal effect of a single exposure on an outcome. We present the Causes of Outcome Learning (CoOL) approach, which seeks to identify combinations of exposures (which can be interpreted causally if all causal assumptions are met) that could be responsible for an increased risk of a health outcome in population sub-groups. The approach allows for exposures acting alone and in synergy with others. It involves (a) a pre-computational phase that proposes a causal model; (b) a computational phase with three steps, namely (i) analytically fitting a non-negative additive model, (ii) decomposing risk contributions, and (iii) clustering individuals based on the risk contributions into sub-groups based on the predefined causal model; and (c) a post-computational phase on hypothesis development and validation by triangulation on new data before eventually updating the causal model. The computational phase uses a tailored neural network for the non-negative additive model and Layer-wise Relevance Propagation for the risk decomposition through this model. We demonstrate the approach on simulated and real-life data using the R package "CoOL". The presentation is focused on binary exposures and outcomes but can be extended to other measurement types. This approach encourages and enables epidemiologists to identify combinations of pre-outcome exposures as potential causes of the health outcome of interest. Expanding our ability to discover complex causes could eventually result in more effective, targeted, and informed interventions prioritized for their public health impact.
Mechanically assisted walking training during inpatient rehabilitation after stroke: perceptions of physiotherapists.

Background and Purpose: Despite evidence supporting the use of mechanically assisted walking training in stroke rehabilitation, it is not extensively used. The purpose of this study was a to explore the perceptions of physiotherapists regarding their use of mechanically assisted walking training, specifically treadmill training, during inpatient rehabilitation after stroke. Better understanding of physiotherapist perceptions can inform the development of translation strategies. Methods: A qualitative study using focus groups comprising 14 phsyiotherapists (including students) working in stroke inpatient rehabilitation at two sites was conducted. Transcripts were analysed using an inductive approach to thematic analysis. Results: Physiotherapists perceived two main themes related to using mechanically assisted walking training during inpatient rehabilitation; therapeutic consequences e.g. patients able to walk earlier, further, longer; less fatiguing for therapist, ability to manipulate walking parameters) and practical considerations (eg safety, efficiency, staff skill, access to equipment, weight and level of disability of patient, fear of treadmill). Discussion: Therapists perceptions of using mechanically assisted walking training during inpatient rehabilitation after stroke were mixed. There is a need to educate physiotherapy staff about the evidence of therapeutic value as well as how to perform mechanically assisted walking training.
What positives can be taken from the COVID-19 pandemic in Australia?

Objective: To investigate whether Australians have experienced any positive effects during the COVID-19 pandemic, despite the disruption to society and daily life. Methods: National online longitudinal survey. As part of a June 2020 survey, participants (n=1370) were asked "In your life, have you experienced any positive effects from the COVID-19 pandemic" (yes/no), with a free-text explanation if yes, and also completed the WHO-Five well-being index. Differences were explored by demographic variables. Free-text responses were thematically coded. Results: 960 participants (70%) reported experiencing at least one positive effect during the COVID-19 pandemic. Living with others (p=.045) and employment situation (p<.001) at baseline (April), were associated with experiencing positive effects. Individuals working for pay from home were more likely to experience positive effects compared to those who were not working for pay (aOR=0.45, 95%CI: 0.32, 0.63, p<.001), or who were working for pay outside the home (aOR=0.40, 95%CI: 0.28, 0.58, p<.001). Age and education were not associated with positive effects when controlling for employment and household numbers. There was an overall effect of gender (p=.001), where those identifying as female were more likely than males (aOR=1.62, 95%CI: 1.25, 2.09) to report experiencing a positive effect. 54.2% of participants reported a sufficient level of wellbeing, 23.2% low wellbeing and a further 22.6% very low wellbeing. Of those experiencing positives, 945/960 (98%) provided an explanation. The three most common themes were "Family time" (33%), "Work flexibility" (29%), and "Calmer life" (19%). Conclusion: A large proportion of surveyed Australians reported positive effects resulting from changes to daily life due to the COVID-19 pandemic in Australia. Enhancing these aspects may build community resilience to cope with future pandemic responses. The needs of people living alone, and of those having to work outside the home or who are unemployed, should be considered by health policy makers and employers in future pandemic preparedness efforts, as these groups were least likely to report positive experiences and may be more vulnerable.