Miracle-dz/UniFAR-FTUs huggingface dataset:
Pore Structure of Calcium Silicate Hydrate in Hydrated Tricalcium Silicate

Adsorption of N2 and water vapor was studied in completely hydrated tricalcium silicate and in fully hydrated tricalcium silicate from which Ca(OH)2 had been extracted. Compared with results obtained using N2, water vapor adsorption led to increased values for small-pore volume, peak shifts to smaller sizes, and decreased values for large-pore volume. Marked hysteresis was observed in the case of water vapor adsorption; the resorption branch apparently represents the true pore structure. Extraction of Ca(OH)2 from the paste increased the calculated volume of small pores strikingly, suggesting that adsorption is hindered by Ca(OH)2; this tendency is more obvious in water vapor adsorption. The adsorption measurements indicate the existence of two kinds of pores, i.e. a wider intergel-particle pore and a smaller pore existing within the gel particle. The latter pore was further classified into intercrystallite and intracrystallite pores.
complexFuzzy: A novel clustering method for selecting training instances of cross-project defect prediction

Over the last decade, researchers have investigated to what extent cross-project defect prediction (CPDP) shows advantages over traditional defect prediction settings. These works do not take training and testing data of defect prediction from the same project. Instead, dissimilar projects are employed. Selecting proper training data plays an important role in terms of the success of CPDP. In this study, a novel clustering method named complexFuzzy is presented for selecting training data of CPDP. The method is developed by determining membership values with the help of some metrics which can be considered as indicators of complexity. First, CPDP combinations are created on 29 different data sets. Subsequently, complexFuzzy is evaluated by considering cluster centers of data sets and comparing some performance measures including area under the curve (AUC) and F-measure. The method is superior to other five comparison algorithms in terms of the distance of cluster centers and prediction performance.
Alterations in Quality Parameters of Mastitic Milk

Quality milk production in modern dairy systems is facing many challenges. Salient in them is mastitis which is responsible for decline in milk production, altered milk composition and compromised udder health. The malaise consists of multiple bacterial etiologies which can be broadly classified into contagious pathogens and environmental pathogens S. aureus is being isolated invariably in all epidemiological studies, followed by E. coli. Pathogenic virulence in mastitis is often accounted due to microbial ability of producing wide array of virulence factors that enhances pathogenicity and sustainment potential in the epithelial linings of udder. Mastitis affects quality parameters of milk i.e. constitutional as well as mineral profile due to local damage and inflammatory mediators. It decreases the lactose secretion because of oxidative stress generated due to the formation of free radicals in the milk. In mastitic milk, IgG2 becomes the predominant antibody which is thought to be the main opsonin supporting neutrophil phagocytosis in the bovine mammary gland. Therefore, it plays a significant role in the battle against mastitis pathogens. Mastitis infected cow shows a notable elevated level of the sodium and chlorine and demoted level of calcium, potassium and inorganic phosphorus. In micro minerals, mastitis affects are pretty much same as in most macro minerals i.e. lower down their concentration in milk secretion. Consistent preventive strategy alongside strict surveillance and biosecurity is recommended for combating this challenge.
Dimensionality reduction for efficient hand tracking, pose estimation and classification

Pose recovery and tracking of articulated objects based on visual observations is a theoretically interesting and challenging problem. One of its instances, human hand pose estimation, has a number of diverse applications including but not limited to human-computer interaction, robot learning by demonstration, human hand motion analysis etc. The problem is associated with many challenges that are introduced because of its high dimensionality, the severe hand self-occlusions, the potentially fast hand motions and the uncontrolled environments in which hands are observed. Some of these difficulties can be alleviated by employing specialized motion capture hardware or visual markers. However, such methods interfere with the observed scene and/or require a costly hardware setup. This work is built upon an existing model-based method that tracks and recovers the 3D position, orientation and 20 DOF articulation of a human hand from markerless visual observations obtained by an RGB-D sensor. According to this baseline method, hand pose estimation is formulated as an optimization problem, seeking for the hand model parameters that minimize the discrepancy between the appearance of hypothesized hand configurations and the actual hand observation. The optimization problem is handled by a variant of Particle Swarm Optimization (PSO), which searches the parametric space of hand configurations. The high dimensionality of this space affects the computational performance of this method. More specifically, a computational performance of 20 fps is achieved, but only thanks to an elaborate GPU implementation on a high end computer. A closer study of the problem reveals that the parametric space of hand configurations is highly redundant. For example, it can represent implausible hand poses. Additionally, when a human hand is known to be engaged in specific activities (e.g., grasping, sign language, etc), its configurations are known to lie in a much lower dimensional manifold. In this work, we employ Principal Component Analysis (PCA) to create a space of reduced dimensionality that describes effectively the human hand articulation, by implicitly modeling relevant constraints. By doing so one needs to solve a much simpler optimization problem, requiring less computational effort to find the optimal hand configuration. Multiple variants of the proposed methodology are formed for the problems of hand pose recovery, pose tracking and pose classification. Extensive experimental results study the relationships among the proposed method’s accuracy, the dimensionality of the search space and the computational budget required to solve the pose recovery, tracking and classification problems. The obtained results demonstrate that the proposed approach achieves better accuracy in pose recovery compared to the baseline method using only 1/4 of the latter’s computational budget. Moreover, the method classified hand postures into the 10 classes of the Chinese numbers signs with an accuracy of 87% to 100%, depending on the employed computational budget.
Structures and energies of compression twin boundaries in hcp Ti and Zr

Abstract Using a combination of first-principles and embedded-atom techniques, we have calculated the structure and energy of compression twin boundaries in hcp Zr and Ti, the most ductile of the hcp elements. These calculations are important tests of classical nucleation theory, which predicts that the energy of these structures controls the nucleation rate. Our results contradict this: the {1122} twin boundary, which is prevalent at low temperatures, is significantly higher in energy than the competing {1011} twin which is only formed at higher temperatures.
Stress-Testing Net Trading Income: The Case of European Banks

Net trading income is an important but volatile source of income for many euro area banks, highly sensitive to changes in financial market conditions. Using a representative sample of European banks, we study the distribution of net trading income (normalized by total assets) conditional to changes in key macro-financial risk factors. To map the linkages of net trading income with financial risk factors and capture non-linear effects, we implement a dynamic fixed effects quantile model using the method of moments approach. We use the model to empirically estimate and forecast the conditional net trading income distribution from which we quantify tail risk measures and expected losses across banks. We find a heterogeneous and asymmetric impact of the risk factors on the distribution of net trading income. Credit and interest rate spreads affect lower quantiles of the net trading income distribution while stock returns are an important determinant of the upper quantiles. We also find that the onset of the Covid-19 pandemic resulted in a significant increase in the 5th and 10th percentile expected capital shortfall. Moreover, adverse scenario forecasts show a wide dispersion of losses and a long-left tail is evident especially in the most severe scenarios. Our findings highlight strong inter-linkages between financial risk factors and trading income and suggest that this tractable methodology is ideal for use as an additional tool in stress test exercises.
Making use of transcription data from qualitative research within a corpus-linguistic paradigm: issues, experiences and recommendations

In this paper, we reflect on the process of re-operationalising transcript data generated in an ethnographic study for the purposes of corpus analysis. We present a corpus of patient–provider interactions in the context of Emergency Departments in hospitals in Australia, to discuss the process through which ethnographic transcripts were manipulated to generate a searchable corpus. We refer to the types of corpus analysis that this conversion enables, facilitated by the rich metadata collected alongside the transcribed audio recordings, augmenting the findings of prior qualitative analyses. Subsequently, we offer guidance for spoken data transcription, intended to ‘future proof’ such data for subsequent reformatting for corpus linguistic analysis.
Towards an AI-Based Tailored Training Planning for Road Cyclists: A Case Study

In a world where the data is a central piece, we provide a novel technique to design training plans for road cyclists. This study exposes an in-depth review of a virtual coach based on state-of-the-art artificial intelligence techniques to schedule road cycling training sessions. Together with a dozen of road cycling participants’ training data, we were able to create and verify an e-coach dedicated to any level of road cyclists. The system can provide near-human coaching advice on the training of cycling athletes based on their past capabilities. In this case study, we extend the tests of our empirical research project and analyze the results provided by experts. Results of the conducted experiments show that the computational intelligence of our system can compete with human coaches at training planification. In this case study, we evaluate the system we previously developed and provide new insights and paths of amelioration for systems based on artificial intelligence for athletes. We observe that our system performs equal or better than the control training plans in 14 and 24 week training periods where it was evaluated as better in 4 of our 5 test components. We also report a higher statistical difference in the results of the experts’ evaluations between the control and virtual coach training plan (24 weeks; training load: X2 = 4.751; resting time quantity: X2 = 3.040; resting time distance: X2 = 2.550; efficiency: X2 = 2.142).
Modeling Leptin Receptor Insensitivity by Comparing How Leptin or Leptin Receptor Mutations in Mice Affect Body Weight, Basal Metabolism, Body Temperature and Feeding Behaviors

Abstract. Leptin, a protein hormone produced principally in adipose tissue, plays a major role in the regulation of food intake, hunger, satiety and metabolism. Most obesity is likely the result of the body's resistance to leptin. The purpose of this experiment was to model leptin receptor insensitivity by comparing how the lack of leptin or the leptin receptor in mutant mice would affect body weight, basal metabolism, body temperature and feeding behaviors. Eighteen mice were used: 6 controls, 6 mutant ob/ob (defective for the expression of leptin), and 6 mutant db/db (defective for the expression of the leptin receptor). After 24 weeks of free access to food and water, the ob/ob mice weighed more than the control and db/db mice (P=0.0012). Both the ob/ob and db/db mice had lower metabolic rates (P = 0.0194) and body temperatures (P < 0.0001). As expected, the db/db mice had the greatest water intake (P=0.0060) and cage waste (P=0.0499) reflective of their diabetic state. The normal mice ate more than the other mice, but the increases were not significant; the ob/ob mice had much less food debris. These results indicate that mutations in the leptin protein or receptor interrupt normal metabolism in a manner similar to what may be experienced by individuals resistant to leptin. If a chronic intake of excessive calories results in increased adipose depositions, then over a lifetime, cell signaling activities may act to protect the leptin receptor from over bombardment by leptin, attenuate leptin's regulatory function, and promote obesity.
Synthesis and Characterization of Polyindole–NiO-Based Composite Polymer Electrolyte with LiClO4

There has been an increasing interest in synthesizing the novel composite polymer electrolyte (CPE) for use in lithium batteries in recent years. This paper describes the preparation and characterization of CPE containing lithium perchlorate based on polyindole–NiO nanocomposite. NiO nanoparticles were added to the monomer solution before the polymer formation in the presence of a surfactant to get the PInNiO nanocomposite. The thermal properties, surface morphology, and structural studies of the electrolyte were investigated by TGA, SEM, TEM, and XRD. An enhanced conductivity of 2.62 × 10−4 S cm−1 at 45°C for the composite polymer electrolyte was determined from impedance studies.
Etiology and Management of Complications Associated with Sinus Augmentation Procedures

Abstract Sinus floor elevation is a predictable procedure for vertical bone augmentation in the atrophic posterior maxilla. As with most surgical procedures, complications can be encountered during sinus floor elevation/augmentation. A clinician should have a thorough knowledge of factors that can lead to complications and possible ways to manage. Presurgical evaluation of the sinus is a prerequisite in identifying the concomitant presence of systemic disease and maxillary sinus disease that may lead to postoperative complications. Despite the best efforts, one may encounter adverse events. Complications can broadly be divided into intraoperative, acute, and chronic complications based on the timing of its occurrence. The most commonly encountered complications include membrane perforation and excessive bleeding. Evaluation of anatomic deviations and sound surgical skill is required to reduce intraoperative complications. Prevention is better than cure. It is always better to know how and when a complication might occur so that the clinician might take the necessary steps to avoid it. This article reviews the management of most commonly encountered complications and the best possible ways to manage them.
Keeping Secrets from Ourselves: Understanding Self-deception Through Theory, Evidence and Application

Self-deception is a difficult concept to share with students. Although few students find it implausible that they are capable of keeping secrets from themselves, the social theory, application, and practical demonstration of self-deception is far from straightforward. This work offers a three-step approach to teach a theoretically-grounded, evidence-based, and application-reinforced understanding of self-deception. Rooted in work on identity by Mead (1934), the approach outlined here engages with interdisciplinary case studies derived from social psychology (Greenwald, McGhee and Schwartz 1998) and behavioral economics (Ariely 2012). The theory and case studies build toward a peer evaluation that offers students a concrete demonstration of self-deception with implications at the individualand group-level.
ZEF-Discussion Papers on Development Policy No. 331

In many developing countries, food environments are changing rapidly. One emblematic trend is the proliferation of supermarkets and other modern retailers. While changing food environments likely influence the types of foods supplied and consumed, research on the implications for people’s diets and nutrition is still scant. Here, we analyze the effects of supermarkets on child diets and nutrition in China. We use nationally representative panel data that include information on households’ access to supermarkets and individual -level anthropometric and dietary indicators. Results show that improved access to supermarkets leads to higher child dietary diversity and nutrient intakes, especially among children in rural areas and from low-income households. Supermarkets are also found to increase child height, but not weight. Estimates with different model specifications and placebo tests confirm the results’ robus tness. The effects are mediated through supermarkets contributing to more variety in local food supplies and lower average food prices. Our findings suggest that the spread of supermarkets improves child dietary quality and nutrition in China.
Blockchain in Insurance: Exploratory Analysis of Prospects and Threats

Ever since the first generation of blockchain technology became very successful and the FinTech enormously benefited from it with the advent of cryptocurrency, the second and third generations championed by Ethereum and Hyperledger have explored the extension of blockchain in other domains like IoT, supply chain management, healthcare, business, privacy, and data management. A field as huge as the insurance industry has been underrepresented in literature. Therefore, this paper presents how investments in blockchain technology can profit the insurance industry. We discuss the basics of blockchain technology, popular platforms in use today, and provide a simple theoretical explanation of the insurance sub-processes which blockchain can mutate positively. We also discuss hurdles to be crossed to fully implement blockchain solutions in the insurance domain.
Rheological characterization of concentrated cellulose solutions in 1‐allyl‐3‐methylimidazolium chloride

The rheological properties of high concentrated wood pulp cellulose 1-allyl-3-methy-limidazolium Chloride ([Amim]Cl) solutions were investigated by using steady shear and dynamic viscoelastic measurement in a large range of concentrations (10–25 wt %). The measurement reveals that cellulose may slightly degrade at 110°C in [Amim]Cl and the Cox–Merz rule is valid for 10 wt % cellulose solution. All of the cellulose solutions showed a shear thinning behavior over the shear rate at temperature from 80 to 120°C. The zero shear viscosity (ηo) was obtained by using the simplified Cross model to fit experimental data. The ηo values were used for detailed viscosity-concentration and activation energy analysis. The exponent in the viscosity-concentration power law was found to be 3.63 at 80°C, which is comparable with cellulose dissolved in other solvents, and to be 5.14 at 120°C. The activation energy of the cellulose solution dropped from 70.41 to 30.54 kJ/mol with an increase of concentration from 10 to 25 wt %. The effects of temperature and concentration on the storage modulus (G′), the loss modulus (G″) and the first normal stress difference (N1) were also analyzed in this study. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012
Fe–N/C catalysts synthesized by heat-treatment of iron triazine carboxylic acid derivative complex for oxygen reduction reaction

4,4′,4′′-s-Triazine-1,3,5-triyltri-p-aminobenzoic acid (H3TATAB) was used as a ligand to prepare an iron–TATAB (Fe–TATAB) complex for the development of an effective oxygen reduction reaction (ORR) catalyst. The activity of the catalyst depended on weight ratios between the Fe–TATAB complex and carbon black and heat-treated temperatures. The results showed that the Fe–N70%/C-800 catalyst (the weight ratio of Fe complex to carbon black was 70 : 30 and the catalyst was pyrolyzed at 800 °C) had good catalytic activity toward ORR with the onset potential at 0.91 V vs. RHE and a kinetic current density of 4.3 mA cm−2 at 0.6 V vs. RHE in alkaline medium. Moreover, the Fe–N70%/C-800 catalyst had better tolerance to methanol crossover effect in comparison with commercial Pt/C (20%). The morphology and composition of the catalysts were characterized by high resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD) as well as X-ray photoelectron spectroscopic (XPS). The electrocatalytic activities were demonstrated by cyclic voltammetry (CV), linear sweep voltammetry (LSV), chronoamperometric measurements and stability accelerated tests. According to rotating disk electrode (RDE) measurements and Koutecky–Levich analysis, the overall electron transfer number in the catalyzed ORR was found to be 3.7–3.9 and the ORR process was mainly a four-electron pathway. The results indicate that the Fe–N70%/C-800 catalyst may be a promising cathode catalyst for ORR.
Dietary control and lipid profiles of Type 2 diabetes mellitus patients in Yaounde, Cameroon

This study was conducted to compare the dietary and blood lipids between type 2 diabetes subjects and non diabetes subjects living in Cameroon. Dietary intakes were significantly higher in non diabetic men compared to diabetic men but not significantly higher in diabetic women compared to diabetic women. Dietary fiber was significantly higher in diabetic men and women compared to non diabetic subjects. Type 2 diabetic patients of both sexes had a triglyceridemia level higher than non diabetic patients. However Type 2 diabetic men had a cholesterolemia level lower than non diabetic men and there was no difference between cholesterolemia of type 2 diabetic women and non diabetic women. It was concluded that type 2 diabetic subjects are consuming diets that are varied and nutritionally adequate for a healthy adult. To optimize nutrition therapy of type 2 diabetic subjects in Cameroon, recommendations should emphasize on traditional dishes which are mainly constitutes of tubers, fruits, cereals and green leaf vegetables.
Guest‐Inclusion Behavior of Double‐Strand 1D Coordination Polymers Based on N,N′‐Type Schiff Base Ligands

Four double-strand one-dimensional (1D) coordinationpolymers, namely, {[Ni(N3Py)2(NO3)2]·(C6H6)x·C2H5OH}n (1), [Cd(ImBNN)2(CH3C6H4SO3)2]n (2), {[Co(N3OPy)2(H2O)2](ClO4)2·C6H6·H2O}n (3), and {[Co(N3OPy)2(H2O)2](ClO4)2·(C8H10)x}n (4) were obtained from the assembly of three N,N′-type Schiff base ligands, 1,4-bis(3-pyridyl)-2,3-diaza-1,3-butadiene (N3Py), 2,5-bis(4′-(imidazol-1-yl)benzyl)-3,4-diaza-2,4-hexadiene (ImBNN), and bis[4-(3-pyridylmethylenemino)phenoxy]methane (N3OPy), with transition-metal ions. All complexes were characterized by single-crystal X-ray diffraction, X-ray powder diffraction, and FTIR measurements. The guest-inclusion behavior of these complexes were investigated by thermogravimetric and X-ray powder diffraction analyses. The structural relationship between the ligands and the cavity sizes and packing fashions have been discussed to elucidate the distinctive guest-inclusion behavior of these complexes. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2008)