Miracle-dz/UniFAR-FTUs huggingface dataset:
Polystyrene nanocomposite materials by in situ polymerization into montmorillonite–vinyl monomer interlayers

A different series of new polystyrene–clay nanocomposites have been prepared by grafting polymerization of styrene with vinyl-montmorillonite (MMT) clay. The synthesis was achieved through two steps. The first step is the modification of clay with the vinyl monomers, such as N,N-dimethyl-n-octadecyl-4-vinylbenzyl-ammonium chloride, n-octadecyl-4-vinylbenzyl-ammonium chloride, triphenyl-4-vinylbenzyl-phosphonium chloride, and tri-n-butyl-4-vinylbenzyl-phosphonium chloride. The second step is the polymerization of styrene with different ratios of vinyl-MMT clay. The materials produced were characterized by different physical and chemical methods: (1) IR spectra, confirming the intercalation of the vinyl-cation within the clay interlayers; (2) thermogravimetric analysis (TGA), showing higher thermal stability for PS–nanocomposites than polystyrene (PS) and higher thermal stability of nanocomposites with of phosphonium moieties than nanocomposites with ammonium moieties; (3) swelling measurements in different organic solvents, showing that the swelling degree in hydrophobic solvents increases as the clay ratio decreases; (4) X-ray diffraction (XRD), illustrating that the nanocomposites were exfoliated at up to a 25 wt % of organoclay content; and (5) scanning electron microscopy (SEM), showing a complete dispersion of PS into clay galleries. Also, transmission electron microscopy (TEM) showed nanosize spherical particles of ∼ 150–400 nm appearing in the images. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 3739–3750, 2007
Docking by Monte Carlo minimization with a solvation correction: Application to an FKBP—substrate complex

A Monte Carlo docking procedure that combines random displacements of the substrate and protein side chains with minimization of the enzyme—substrate complex is described and applied to finding the binding mode of the blocked tetrapeptide N‐acetyl‐Leu‐Pro‐Phe‐methylamide to the FK506 binding protein (FKBP). The tetrapeptide, an analog of the preferred FKBP substrate, and the FKBP binding site are flexible during the docking procedure. The twisted‐imide transition‐state form of the substrate is used during docking. The enzyme charges are scaled individually to account for solvent screening of specific binding site residues during the Monte Carlo sampling. To evaluate the relative binding free energies of the resulting structures, a rapid method for calculating polar and nonpolar solvation effects is introduced. Accurate electrostatic solute—solvent energies are calculated by solving the finite‐difference linearized Poisson—Boltzmann equation; nonpolar contributions to the stability of the different conformers are estimated by the free energy of cavity formation, which is obtained from the molecular surface, and the solute—solvent van der Waals energy, which is calculated with a continuum approach. In the conformation of the enzyme—substrate complex with the lowest free energy, the tetrapeptide is bound as a type VIa proline turn with solvent accessible ends to permit longer polypeptide chains to act as substrates. Except for the imide carbonyl, which is involved in polar interactions with aromatic side chains of the FKBP binding site, all of the seven potential hydrogen bond donors or acceptors of the tetrapeptide are satisfied. The FKBP binding site has a similar conformation in the substrate complex as in the FKBP‐FK506 cocrystal structure, except for the predicted reorientation of the Tyr 82 hydroxyl, which plays an important role in substrate binding. The present model for the FKBP—substrate complex is in agreement with the recently determined crystal structure of a cyclic peptide—FK506 hybrid bound to FKBP and supports the structure obtained previously by iterative model building. In addition, it is consistent with the observed effects of FKBP point mutations on the enzyme activity. The approach described here should be useful, in general, for the prediction of the structure of a molecule in solution or as part of a complex. It provides for the effective sampling of conformational space and for the inclusion of solvent effects. © 1997 by John Wiley & Sons, Inc.
Ce(IV)-initiated graft polymerization of acrylic acid onto poly(ethylene terephthalate) fiber

Graft copolymerization of acrylic acid onto poly(ethylene terephthalate) (PET) fiber by a redox system using ceric (IV) initiator was studied with regard to various parameters of importance: acrylic acid concentration, ceric (IV) concentration, nitric acid concentration, reaction temperature, and reaction time. Based on the morphology of the PET fiber, it could be concluded that ceric (IV) in dilute nitric acid is a redox initiator for the surface graft copolymerization of the acrylic acid/PET system. The grafted PET fiber showed an increase in improved moisture regain to reach 900% at 39.5% graft yield. The dyeability with the basic dye and disperse dye significantly increased by 100 and 22%, respectively, as a result of the grafting onto PET fiber. Both tenacity and elongation gradually decreased by 51.2 and 28.9%, respectively, with increasing graft yield, which reduced the fiber service lifespan. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 1952–1958, 2003
Software Testing as A Problem of Machine Learning -- A Survey and Critical Review

This paper reviews the research on employing machine learning (ML) to solve software testing problems. Existing works can be classified into four categories according to the type of testing problems addressed: (a) adequacy problem, i.e. how to measure test adequacy, (b) oracle problem, i.e. how to determine the correctness of software’s outputs on test cases, (c) design problems, i.e. how to generate, prioritise and optimise test cases, and (d) testability problem, i.e. how to measure software’s testability. For each of these problems, various approaches proposed and studied in the literature are identified, summarised and critically analysed. Three observations are made on the current state of art and future research directions are identified: (1) No easy money . Applying ML techniques to testing is labour intensive and expensive. It is not economically viable as a practical technique, yet. (2) No free lunch . Wolpert’s No-Free-Lunch theorem is observed; that is, there is no single ML algorithm that consistently performed better than other ML techniques. (3) No silver bullet . Existing ML techniques cannot deal with the complexity confronted software engineers in current practices. Although ML in its current state is still far from a practically applicable testing technique, it can potentially bring significant and profound impacts on both research and practice. In particular, it is worth further exploring a novel theoretical model of software testing in parallel with the PAC learning theory by treating testing as inductive inference. A break through in this direction could foster a paradigm shift in testing and reliability assessment.
Integrating soil phosphorus testing into environmentally based agricultural management practices

Soil testing has been an accepted agricultural management practice for decades. Interpretations and fertility recommendations based on soil analyses and the information obtained with soil samples on cropping systems, tillage practices, soil types, manure use, and other parameters have contributed to the increased efficiency of agricultural production. Recently, however, analyses of long-term trends in soil test P values have shown that soil P in many areas of the world is now excessive, relative to crop P requirements. The role of P in the eutrophication of surface waters and emerging concerns about the human health impacts of toxic algal/dinoflagellate blooms have heightened public awareness of nonpoint source pollution by agricultural P. The greatest concerns are with animal-based agriculture, where farm and watershed-scale P surpluses and over-application of P to soils are common. The need for nutrient-management plans based on N and P is now an issue of intense debate in the U.S. and Canada. This paper addresses three issues: Should the applications of organic wastes and fertilizers be based on soil P and, if so, what is the most appropriate testing method to assess environmental risk? How can our knowledge of soil P chemistry be integrated with the expertise of hydrologists, agronomists, aquatic ecologists, and others to assess the risks that P in agricultural soils poses to surface waters? And, finally, how can we use soil P testing to evaluate new best management practices (BMPs) now being developed to reduce P transport from soil to water?
Steroid Eluting Esophageal-Targeted Drug Delivery Devices for Treatment of Eosinophilic Esophagitis

Eosinophilic esophagitis (EoE) is a chronic atopic disease that has become increasingly prevalent over the past 20 years. A first-line pharmacologic option is topical/swallowed corticosteroids, but these are adapted from asthma preparations such as fluticasone from an inhaler and yield suboptimal response rates. There are no FDA-approved medications for the treatment of EoE, and esophageal-specific drug formulations are lacking. We report the development of two novel esophageal-specific drug delivery platforms. The first is a fluticasone-eluting string that could be swallowed similar to the string test “entero-test” and used for overnight treatment, allowing for a rapid release along the entire length of esophagus. In vitro drug release studies showed a target release of 1 mg/day of fluticasone. In vivo pharmacokinetic studies were carried out after deploying the string in a porcine model, and our results showed a high local level of fluticasone in esophageal tissue persisting over 1 and 3 days, and a minimal systemic absorption in plasma. The second device is a fluticasone-eluting 3D printed ring for local and sustained release of fluticasone in the esophagus. We designed and fabricated biocompatible fluticasone-loaded rings using a top-down, Digital Light Processing (DLP) Gizmo 3D printer. We explored various strategies of drug loading into 3D printed rings, involving incorporation of drug during the print process (pre-loading) or after printing (post-loading). In vitro drug release studies of fluticasone-loaded rings (pre and post-loaded) showed that fluticasone elutes at a constant rate over a period of one month. Ex vivo pharmacokinetic studies in the porcine model also showed high tissue levels of fluticasone and both rings and strings were successfully deployed into the porcine esophagus in vivo. Given these preliminary proof-of-concept data, these devices now merit study in animal models of disease and ultimately subsequent translation to testing in humans.
Learning from Shared News:

We study learning via shared news. Each period agents receive the same quantity and quality of first-hand information and can share it with friends. Some friends (possibly few) share selectively, generating heterogeneous news diets across agents akin to echo chambers. Agents are aware of selective sharing and update beliefs by Bayes’ rule. Contrary to standard learning results, we show that beliefs can diverge in this environment leading to polarization. This requires that (i) agents hold misperceptions (even minor) about friends’ sharing and (ii) information quality is sufficiently low. Polarization can worsen when agents’ social connections expand. When the quantity of first-hand information becomes large, agents can hold opposite extreme beliefs resulting in severe polarization. Our results hold without media bias or fake news, so eliminating these is not sufficient to reduce polarization. When fake news is included, we show that it can lead to polarization but only through misperceived selective sharing. News aggregators can curb polarization caused by shared news. JEL codes: D82, D83, D90
Collaborative Product Portfolio Design Based on the Approach of Multichoice Goal Programming

Product portfolio optimization is a typical multiobjective problem. The multichoice goal programming method becomes a popular means of resolving multiobjective decision problems. However, the classic multichoice goal programming method treats the product portfolio optimization in isolation and does not consider the mutual influence between portfolio products. Researchers should consider the interaction between products in portfolio optimization so that they can be adjusted to “real world” problems. The interaction between products can be explained by population dynamics. Logistic model is a classical method to analyze the population interaction. The equilibrium point of logistic model can show the ideal state of product population coordinated development. The combination of logistic and multichoice goal programming method is an effective approach to analyze the interaction of product portfolio. This paper therefore proposes a new alternative method to formulate the multiobjective problem and also uses an illustrative example to demonstrate the usefulness of the proposed method. The comparative analysis of model optimization results shows that logistic multichoice goal programming model can take into account resource constraints, product collaboration, and output maximization. Logistic multichoice goal programming model shows good performance in the aspects of operation complexity, operation time, sensitivity analysis, and collaborative entropy evaluation.
A Meta-Analysis of the Effect of Parental Involvement on Students’ Academic Achievement

This study aims to examine the effect of parental involvement on students’ academic achievement at pre-school, elementary and secondary levels by using the meta-analysis method with respect to home-based and school-based parental involvement strategies. Data consisted of 55 independent research studies in English published between 2010 and 2019, and accessed through ERIC, Academic Search Complete, Science Direct, Wiley Online Library, and PsycNet databases. Findings revealed that the effect of parental involvement on academic achievement was positive but small. Parental expectations had the biggest effect on academic achievement and parental control had a negative and small effect. The mean effect of parental involvement on students’ academic achievement does not differ significantly according to moderator variables of education level, measurement type or measurement area but differs by developmental level of the country. The results are discussed using available related meta-analysis studies in the literature.
Sustainable Competitive Advantage in Creative Industry Small and Medium Enterprises: The Context of Thailand

Intense competition in today's business world has made it increasingly difficult for firms to exist, and survival has become a primary business goal. Some entrepreneurs have struggled to compete, and some have eventually failed; therefore, how firms create and sustain their competitive advantage provides a sound basis for the firms’ existence. This study’s objective is to explore the resources that enhance a sustainable competitive advantage within the context of small and medium enterprises (SMEs) in creative industries. The state of competition within industries is presented using the resource-based view (RBV) and social capital, and we specify three essential competitive determinants: market orientation, collaborative external network, and managerial ties. This study used a questionnaire survey and structural equation modelling to evaluate the conceptual model. We found that market orientation and collaboration external networks can lead to sustainable competitive advantage. In addition, managerial ties as a mediator between market orientation and collaborative external network lead to sustainable competitive advantage.
Effect of temperature on the rates of dissolution of gibbsite and boehmite

The effect of temperature on the rate of dissolution of gibbsite and boehmite in caustic soda solutions was studied in the temperature range 25-100°C. The results fitted the Arrhenius rate equation and the activation energy was found to be 30.6 ± 0.9 k. cal/g-mole for the gibbsite reaction and 29.4 ± 1.3 k. cal/g-mole for the boehmite reaction. While the effect of temperature on the boehmite dissolution has not been reported before, the value of the activation energy for gibbsite was higher than previously reported values. Reasons for these differences are given and a consistent value of the activation energy was obtained which agreed both with experimental data for different gibbsite samples and with modified forms of the previously published data.
Design Space-Based Pattern Representation

As knowledge of solutions to recurring design problems, a large number of software design patterns (DP) has been identiﬁed, catalogued and formalised in the past decades. Tools have been developed to support the application and recognition of patterns. However, although the notions of pattern in different subject domains carry a great deal of similarity, we are in lack of a general pattern representation approach that applies to all types of design patterns. Based on our previous work on formalisation of OO DPs and an algebra of pattern compositions, this paper proposes a generalisation of the approach so that it can be applied to other types of DPs. In particular, a pattern is deﬁned as a set of points in a design space that satisfy certain conditions. Each condition speciﬁes a property of the instances of the pattern in a certain view of the design space. The patterns can then be composed and instantiated through applications of operators deﬁned on patterns. The paper demonstrates the feasibility of the proposed approach by examples of patterns of enterprise security architecture.
Comparative Study of Microwave-Assisted Vacuum Evaporation, Microwave-Assisted Evaporation, and Conventional Evaporation Methods on Physicochemical Properties of Barberry Juice

This study was conducted to evaluate the efficiency of Microwave-Assisted Vacuum Evaporation (MAVE) and Microwave-Assisted Evaporation (MAE) techniques for production of barberry juice concentrate in comparison to the conventional evaporation techniques. The barberry juice was concentrated by two different methods (indirect heating and the microwave evaporation under pressures of 100 and 30 kPa) to reach 60 °Brix. The results showed that the evaporation rates of MAVE and MAE methods were, respectively, 48.86 and 48.27% higher than indirect heating. The minimum changes in color parameters of barberry juice concentrate (L*, a*, b*, ΔE) were observed for vacuum-microwave evaporation. In addition, applying this method could better preserve anthocyanin content, antioxidant activity, and total phenol content of barberry juice compared to the conventional method.
What Do We Want From Explainable Artificial Intelligence (XAI)?

Previous research in Explainable Artificial Intelligence (XAI) suggests that a main aim of explainability approaches is to satisfy specific interests, goals, expectations, needs, and demands regarding artificial systems (we call these ‘stakeholders’ desiderata’) in a variety of contexts. However, the literature on XAI is vast, spreads out across multiple largely disconnected disciplines, and it often remains unclear how explainability approaches are supposed to achieve the goal of satisfying stakeholders’ desiderata. This paper discusses the main classes of stakeholders calling for explainability of artificial systems and reviews their desiderata. Work on this paper was funded by the Volkswagen Foundation grants AZ 95143, 98509, 98510, 98511, 98512, 98513, and 98514 “Explainable Intelligent Systems” (EIS), by the DFG grant 389792660 as part of TRR 248, and by the ERC Advanced Grant 695614 (POWVER). The authors thank the anonymous reviewers for feedback on initial drafts of this paper. 1Markus Langer, Daniel Oster, and Timo Speith have contributed equally to this article and share the first authorship. Preprint submitted to Artificial Intelligence February 17, 2021 We provide a model that explicitly spells out the main concepts and relations necessary to consider and investigate when evaluating, adjusting, choosing, and developing explainability approaches that aim to satisfy stakeholders’ desiderata. This model can serve researchers from the variety of different disciplines involved in XAI as a common ground. It emphasizes where there is interdisciplinary potential in the evaluation and the development of explainability approaches.
A Comparative Analysis of Structural and Electrochemical Properties of Graphene Oxide (GO) and Reduced Graphene Oxide (rGO) Synthesized by Using Hummer’s and Modified Hummer’s Method.

Graphene oxide (GO) and reduced graphene oxide (rGO) is a semiconductor device which finds many applications in the various electronic devices. In the present study GO and rGO thin sheets have been grown over Si wafers using Hummer’s and modified Hummer’s methods and a comparison in the properties of the coatings have been carried out. The morphology of the sheets characterized by SEM revealed similar transparent sheet like structure for both methods of synthesis. The diffraction patterns of GO and rGO prepared with modified Hummer’s method showed peak shift to lower diffraction angle from 9.96 ̊ to 9.63 ̊ and 26.4 ̊ to 26.3 ̊ respectively. The diffraction peaks were observed at diffraction phase of 001 and 002 crystal plane. FTIR spectra revealed presence of oxygen functional groups in GO thin sheets whereas peaks for oxygen functionalities were absent in rGO. The polarization curve indicated similar corrosion resistance of GO and rGO thin sheets grown under Hummer’s and modified Hummer’s. Capacitive property of rGO is better than GO as observed by the electrochemical analysis of GO and rGO.
A Genome-Wide Association Study of Survival to Unexpected Acute Heat Stress in a F2 Chicken Population

Heat stress, or hyperthermia, can have a serious effect on chicken performance in poultry industry in many parts of the world. Both genetics and environment play key role in the performance of a chicken and, therefore, it is important to consider both factors in addressing heat stress. On genetics level, genome-wide association studies have become a popular method for studying heat stress in recent years. A population of 202 F2 chickens was reared for 84 days to find genes and genomic regions affecting growth traits and immune system. But, due to unexpected acute increase in temperature at day 83, 182 birds died (case) and 20 birds remained alive (control). At the age of 70 days, blood sample of all birds was collected to extract their DNA, using modified salting out method. All samples were genotyped by a 60 K Single Nucleotide Polymorphism (SNP) chip. Genome-wide association study was carried out by GCTA to identify gene and genomic regions associated with heat stress tolerance. Results indicated a close relationship between 28 SNPs, located on chromosomes 2, 3, 5, 6, 7, 12, 19, 20, and 21 and heat stress tolerance at the level of suggestive significance. Two suggestively significant markers on chromosome 5, namely, GGaluGA273356 and Gga_rs16479429, were located within and 52 Kb downstream of two genes, including MAPKBP1and SPON1, respectively. Gene ontology analysis indicated that the resistance of chickens to acute increase of temperature might be linked to the function of MAPKBP1 and SPON1 genes and their biological pathways. These results will be useful for understanding the molecular mechanisms of SNPs and candidate genes for heat stress tolerance in chickens and provide a basis for increasing genetic resistance in breeding programs.