Miracle-dz/UniFAR-FTUs huggingface dataset:
A framework for studying design thinking through measuring designers’ minds, bodies and brains

This paper presents a framework for studying design thinking. Three paradigmatic approaches are described to measure design cognitive processes: design cognition, design physiology and design neurocognition. Specific tools and methods serve each paradigmatic approach. Design cognition is explored through protocol analysis, black-box experiments, surveys and interviews. Design physiology is measured with eye tracking, electrodermal activity, heart rate and emotion tracking. Design neurocognition is measured using electroencephalography, functional near infrared spectroscopy and functional magnetic resonance imaging. Illustrative examples are presented to describe the types of results each method provides about the characteristics of design thinking, such as design patterns, design reasoning, design creativity, design collaboration, the co-evolution of the problem solution space, or design analysis and evaluation. The triangulation of results from the three paradigmatic approaches to studying design thinking provides a synergistic foundation for the understanding of design cognitive processes. Results from such studies generate a source of feedback to designers, design educators and researchers in design science. New models, new tools and new research questions emerge from the integrated approach proposed and lay down future challenges in studying design thinking.
Allometric and trait-based patterns in parasite stoichiometry

We measured the elemental content (%C, N and P) and ratios (C:N, C:P, N:P) of a diverse assemblage of parasitic helminths to ask whether taxonomy or traits were related to stoichiometric variation among species. We sampled 27 macroparasite taxa, spanning four phyla, infecting vertebrate and invertebrate hosts from freshwater ecosystems in New Jersey. Macroparasites varied widely in elemental content, exhibiting 4.7‐fold variation in %N, 4.6‐fold variation in %P, and 11.5‐fold variation in N:P. Across all species, parasite %P scaled negatively and C:P scaled positively with body size. Similar relationships between parasite P content and body size occurred at the phylum level and within individual species. The allometric scaling of P across species supports the growth rate hypothesis, which predicts that smaller taxa require more P to support relatively higher growth rates. Life cycle stage was related to %N and C:N, with non‐reproductive parasite stages lower in %N and higher in C:N than actively reproducing parasites. Parasite phylum, functional feeding group, and trophic level did not explain elemental variation among species. Organismal stoichiometry is linked to ecological function, and wide variation in macroparasite stoichiometry likely generates diverse patterns in host–parasite nutrient dynamics and variable relationships between parasitism and nutrient cycling.
Untersuchung von Diesel-Einspritzkonzepten unter Berücksichtigung von zukünftigen Anforderungen

In order to achieve the goals of the positive influence on the increase in performance, the reduction of fuel consumption, noise and pollutant emissions, higher demands are placed on the diesel direct injection system. This leads to a conflict of costs, complexity and benefits between the injection systems and the exhaust aftertreatment equipment. For future developments, new requirements are derived from the goals set, which must be identified and clarified theoretically and experimentally in the early phase of the product development process. In the context of this work, a list of requirements for today’s and future injection systems has been compiled from relevant literature. In particular, the focus has been placed on the flexibility of the injection system for the realisation of a freely selectable injection rate shaping. With experimental tests their flexibility in injection rate generation via needle seat throttling and pressure modulation for passenger car applications could be shown. It has been detected that also in passenger car applications with small spray holes during injection rate shaping „Boot“ by using the needle seat throttling, disadvantages in the spray jet characteristic are produced. Furthermore, the limitations of different pressure modulation systems with respect to their response, efficiency and flexibility have become apparent. With the help of flow simulations of internal nozzle flows, a targeted positive influence could be achieved by geometry variations on the flow guidance with dynamic needle stroke movement, whereby a directly comparable level with the pressure modulation could be produced during a injection rate shaping profile. Furthermore, a simulation model known from the literature was implemented on the basis of thermodynamic and phenomenological combustion model approaches. By means of a recalculation under specification of an ideal cylinder pressure or combustion curve, a first estimation of an injection strategy for a highly flexible injection system by means of needle seat throttling could be predicted at selected operating points.
A Robust Design Methodology for Synchronous Reluctance Motors

The improvement of the robustness of the performance of electrical machines in presence of neglected features, such as manufacturing tolerances and deviations in material properties and parameters, is increasingly demanded. The available optimization procedures do not account for manufacturing tolerances, leaving the decision process incomplete. The article proposes a methodology for the selection of the more robust design towards manufacturing tolerances among the best candidates, detected by an optimization procedure. Statistical tools for tolerance analysis and worst-case analysis are discussed and adopted for the scope. The proposed methodology is used to select a robust design with respect to torque ripple deviations due to geometric tolerances in the laminations of a Synchronous Reluctance Motor with fluid shaped barriers. The statistical performance analysis and the worst-case analysis provide an estimation of the performance deterioration in the presence of the tolerances in the manufacturing process.
Towards a Classification of Neoclassical Objects in Interior Scenes

Digitale Forschungsinstrumente sind disruptive Technologien mit dem Potential, grundlegend die Art und Weise zu verändern, wie wir in den historischen Bildwissenschaften, in der Architekturund Designgeschichte oder den Material Culture Studies forschen, ja welche Vorstellungen wir von unseren Disziplinen entwerfen. Künstliche Intelligenz und Verfahren maschinellen Lernens werden in den bildbezogenen Digitalen Geisteswissenschaften zum Zweck der Bildanalyse sowie der Klassifizierung visueller Merkmale genutzt. Waren Methoden im Bereich der Bildanalyse lange Zeit von niedrigschwelligen Methoden wie der Bildung von Clustern auf der Grundlage von Farbverteilungen oder lokalen Kontrasten für diesen Bereich bestimmend, zielen Forschungsinstrumente nunmehr darauf ab, Bildmerkmale zu identifizieren, zu klassifizieren oder gar semantisch zu segmentieren. Sie bieten also, anders ausgedrückt, erstmals informatisch halbautomatischen Zugang zur dem Bild eigenen Ebene der Repräsentation. Das Neoclassica-Projekt hat zum Ziel, Forschenden einen Zugang zu Instrumenten und Methoden zu bieten, die eine computergestützte Analyse materieller Kultur, genauer struktureller Merkmale und ästhetischer Formen klassizistischer Artefakte bieten. Wir möchten damit sowohl mehr hypothesen-getriebene, als auch explorative Zugänge zum Medium Bild unterstützen. Gegenwärtig konzentrieren wir uns dabei auf Raumkunst, insbesondere Mobiliar und Innenräume, aber auch Architektur und deren jeweilige bildliche Darstellung. In diesem Beitrag stellen wir unseren Zugang zur Analyse von Zimmerbildern vor, angefangen mit der Klassifizierung in Darstellungen von Einzelartefakten bis hin zur Identifizierung von Objekten in komplexen zeitgenössischen Interieurdarstellungen. Abschließend zeigen wir Anwendungsmöglichkeiten der Technologie und Perspektiven der weiteren Forschung auf.
A Dataset for Non-Intrusive Load Monitoring: Design and Implementation

A NILM dataset is a valuable tool in the development of Non-Intrusive Load Monitoring techniques, as it provides a means of evaluation of novel techniques and algorithms, as well as for benchmarking. The figure of merit of a NILM dataset includes characteristics such as the sampling frequency of the voltage, current, or power, the availability of indications (ground-truth) of load events during recording, the variety and representativeness of the loads, and the variety of situations these loads are subject to. Considering such aspects, the proposed LIT-Dataset was designed, populated, evaluated, and made publicly available to support NILM development. Among the distinct features of the LIT-Dataset is the labeling of the load events at sample level resolution and with an accuracy and precision better than 5 ms. The availability of such precise timing information, which also includes the identification of the load and the sort of power event, is an essential requirement both for the evaluation of NILM algorithms and techniques, as well as for the training of NILM systems, particularly those based on Machine Learning.
Diverse tuning underlies sparse activity in L2/3 vibrissal cortex of awake mice

It is widely reported that superficial layers of the somatosensory cortex exhibit sparse firing. This sparseness could reflect weak feedforward sensory inputs that are not sufficient to generate action potentials in these layers. Alternatively, sparseness might reflect tuning to unknown or higher-level complex features that are not fully explored in the stimulus space. Here, we examined these hypotheses by applying a range of vibrotactile and manual vibrissal stimuli in awake, head-fixed mice while performing loose-seal cell-attached recordings from the vibrissal primary somatosensory (vS1) cortex. A high-velocity stimulus delivered by a piezo-electric actuator evoked activity in a small fraction of regular spiking supragranular neurons (29%) in awake condition. However, a majority of the supragranular regular spiking neurons (84%) were driven by manual stimulation of whiskers. Our results suggest that most neurons in the superficial layers of vS1 cortex contribute to coding in awake conditions when neurons may encounter their preferred feature(s) during whisker-object interactions.
Phenolics and carotenoids contents and radical scavenging capacity of some selected solanaceous medicinal plants

Plants being an important source of medicine play significant role in human health. The aim of the present study was to evaluate thetotal phenolics and carotenoids contents, and free radical scavenging capacity of leaves and fruits of selected five solanaceous medicinal plants, namely Solanum melongena (brinjal ), Solanum torvum ( tit begun) , Solanum virginianum (kantikari ), Solanum sisymbrifolium (sada kantikari ) and Solanum nigrum (futi begun). Carotenoids content in the leaves and fruits of solanaceous plants varied significantly among the species. Leaf phenolics content ranged between 147.40 ( S. melongena) and 585.15 ( S. virginianum ) mg gallic acid equivalent (GAE)/100 g fresh weight, while fruit phenolics content varied from 50.52 ( S. nigrum ) to 105.02 ( S. virginianum ) mg GAE/100 g fresh weight. IC 50 values for scavenging 2, 2-diphenyl-1-picrylhydrazyl radical (DPPH) radical ranged between 31.52 ( S. nigrum ) and 33.55 ( S. melongena ) mg mL −1 in leaf, while in fruit it ranged between 27.90 ( S. virginianum ) and 33.11 ( S. melongen a) mg mL −1 . The highest carotenoids content (0.370 mg g −1 fresh weight) was measured from Solanum nigrum leaf. S. virginianum leaf contained about 4−fold high phenolics content than that in S. melongena . S. nigrum leaf had about 15−fold high carotenoids content (0.370 mg g −1 fresh weight). compared to S. torvum and S. virginianum fruits (0.024 mg g −1 FW in each). Because of the highest fruit phenolics and carotenoids content along with the lowest IC 50 values for scavenging DPPH, S. virginianum fruit can be considered as superior for its health beneficial biochemical constituents J. Bangladesh Agril. Univ. 16(1): 56-61, April 2018
Effects of zinc deficiency on concentrations of lipids in liver and plasma of rats

The present paper reviews the effects of zinc deficiency on concentrations of lipids in liver and plasma of rats. Results originate either from classical zinc deficiency experiments or from experiments with force-fed rats. Classical zinc deficiency experiments have the disadvantage that zinc-deficient rats largely reduce food intake, and therefore the effects of zinc deficiency on lipid metabolism are confounded by low food intake. This disadvantage can be overcome by force-feeding rats sufficient quantities of a zinc-deficient diet. Experiments with force-fed rats have shown that the effect of zinc deficiency on concentrations of hepatic lipids depends on the type of dietary fat. Feeding a zinc-deficient diet with predominately coconut oil causes a fatty liver characterized by largely elevated concentrations of triglycerides with saturated and monounsaturated fatty acids compared with control rats. In contrast, feeding zinc-deficient diets with linseed oil or fish oil does not produce a fatty liver. Since zinc deficiency also affects the regulation of hepatic lipogenic enzymes it is probable that the fatty liver in zinc-deficient rats is due to increased lipogenesis. Additionally, experimental data indicate that secretion of lipids from liver into blood may be impaired by zinc deficiency. Zinc-deficient rats force-fed different types of dietary fat develop hyperlipidemia which may be a compensatory way to avoid triglyceride accumulation in the liver. In contrast to force-fed rats, rats consuming a zinc-deficient diet ad libitum do not gain a fatty liver. This may be due to the low food intake in those rats which suppresses hepatic lipogenic enzymes. The results about the effects of zinc deficiency on concentrations of lipids in plasma of rats fed ad libitum zinc-deficient diets are not consistent. However, most of the studies point to a hypolipidemia in zinc-deficient rats which is in contradiction to results in force-fed rats.
Vehicle Target Detection Method Based on Improved SSD Model

When we use traditional computer vision Inspection technology to locate the vehicles, we find that the results were unsatisfactory, because of the existence of diversified scenes and uncertainty. So, we present a new method based on improved SSD model. We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model. Meanwhile, the new method optimizes the loss function, such as the loss function of predicted offset, and makes the loss function drop more smoothly near zero points. In addition, the new method improves cross entropy loss function of category prediction, decreases the loss when the probability of positive prediction is high effectively, and increases the speed of training. In this paper, VOC2012 data set is used for experiment. The results show that this method improves average accuracy of detection and reduces the training time of the model.
X-SVM: An Extension of C-SVM Algorithm for Classification of High-Resolution Satellite Imagery

The accurate land cover mapping of the Earth’s surface using Earth observation data is one of the most studied, but yet the most challenging tasks of remote sensing field, particularly when it comes to urban areas. The large spectral variability of man-made structures, as well as the mixed pixel phenomenon, imposes the use of computational demanding techniques, which are not always effective for real case applications. Support vector machines (SVMs) are supervised learning models with associated learning algorithms, which are mainly used for classification and regression analysis. Specifically, a support vector classifier (SVC) constructs a hyperplane or a set of hyperplanes in a high-dimensional space, which separates the training data into different classes. These are then used to classify a whole image, or series of images. The current standard SVM algorithm for classification used by the most popular mapping software (e.g., ENVI, EnMAP) is the C-SVC. The parameterization of a C-SVC strongly affects the final classification result. Yet, there is no rule of thumb to choose the optimal parameters when classifying satellite imagery. Optimal parameterization totally depends on the training data, and to determine it for a specific case, a time-consuming trial-and-error process is inevitable. In this work, advancements for the C-SVC algorithm are proposed to enhance its performance when used to classify remote sensing data, eliminating the need for a part of manual parametrization, while ensuring increasing its performance.
Clinicopathological associations and prognostic values of IDH1 gene mutation, MGMT gene promoter methylation, and PD-L1 expressions in high-grade glioma treated with standard treatment

Introduction the objective was to evaluate the impact of IDH1 R132H mutation, MGMT methylation and PD-L1 expression in high grade glioma that received standard therapy (surgery, radiation and chemotherapy) to overall survival (OS). Methods this is a retrospective study of 35 high grade glioma cases. Genotyping of IDH1 gene alteration on the mutation hotspot R132 (Sanger sequencing method with Applied Biosystems 3500 Genetic Analyzer), EZ DNA Methylation-Gold kit (Zymo Research) is used to study the methylation, Cell line BT549 (ATCC HTB-122) and HCT-116 (ATCC CCL-247) were used as unmethylated control and partially methylated control respectively. Anti-human PD-L1 antibody clone E1L3N®from Cell Signalling Technology (USA) and Rabbit XP®were used to see PDL-1 expression. Results anaplastic astrocytoma cases had more MGMT promoter methylation (50%) than glioblastoma multiforme (GBM) (20%), more IDH1 R132H mutation (42%) than GBM (4.3%). Immunohistochemistry tumor proportion score method (TPS) identified 17% and 8.7% were PD-L1 positive in AA and GBM groups, respectively. Cases with IDH1 R132H mutation and MGMT methylation still showed better OS although with high PD-L1 expression. Conclusion IDH1 R132H mutation and MGMT methylation were good prognostic markers. High expression of PD-L1 apparently might not indicate poor overall survival in the presence of IDH1 R132 mutation and MGMT methylation.
Increasing the Learning Efficiency in Decision-Making Field using the Workshop Activity in Moodle

The decision-making field is one of the most critical fields in education for entrepreneurs. Students must adopt different concepts, methods, and tools that improve both - their analytic and intuitive decision making. One of the most used decision-making methods is the analytic hierarchy process (AHP). Students must know how to recognize that a specific problem requires AHP analysis and to apply it correctly. This study presents the implementation of AHP education using the Workshop activity supported by the learning management system Moodle. In the first part of this activity, the students have to make a paper of AHP analysis of one real strategic or tactical problem related to any organization they choose: they have to structure the problem using the structuring methods, collect pairwise comparisons from decision-makers, calculate the group priorities and make the sensitivity analysis. In the second part of the activity, the students do peer assessment – they evaluate other students’ projects using the rubrics and qualitative assessment. The analysis reveals better results in understanding the AHP when compared to traditional ways of learning (direct assessment of papers by teachers without peer assessment). The different ways of learning are evaluated by comparing the points achieved for the AHP papers, points achieved for the AHP test, and using a short survey – all of them are implemented in Moodle as well.
Troglitazone Inhibits Atherosclerosis in Apolipoprotein E–Knockout Mice

Abstract—Atherosclerotic coronary heart disease is a common complication of the insulin resistance syndrome that can occur with or without diabetes mellitus. Thiazolidinediones (TZDs), which are insulin-sensitizing antidiabetic agents, can modulate the development of atherosclerosis not only by changing the systemic metabolic conditions associated with insulin resistance but also by exerting direct effects on vascular wall cells that express peroxisome proliferator–activated receptor-γ (PPAR-γ), a nuclear receptor for TZDs. Here we show that troglitazone, a TZD, significantly inhibited fatty streak lesion formation in apolipoprotein E–knockout mice fed a high-fat diet (en face aortic surface lesion areas were 6.9±2.5% vs 12.7±4.7%, P<0.05; cross-sectional lesion areas were 191 974±102 911 μm2 vs 351 738±175 597 μm2, P<0.05; n=10). Troglitazone attenuated hyperinsulinemic hyperglycemia and increased high density lipoprotein cholesterol levels. In the aorta, troglitazone markedly increased the mRNA levels o.
Étude sur le résumé comparatif grâce aux plongements de mots

Dans cet article, nous presentons une nouvelle methode de resume automatique comparatif. Ce type de resume a pour objectif de permettre de saisir rapidement les differences d’information entre deux jeux de documents. En raison de l’absence de ressources disponibles pour cette tâche, nous avons compose un corpus d’evaluation. Nous presentons a la fois la methodologie de son elaboration ainsi que le corpus lui-meme. Notre methode utilise les avancees recentes dans le calcul de similarite entre phrases afin de detecter les informations comparatives. Nous montrons que sur ce corpus, notre methode est comparable en termes de qualite de resultats a une methode de l’etat de l’art, tout en reduisant d’un facteur dix le temps de calcul, la rendant donc exploitable dans le cadre de l’aide a l’analyse de documents.
Synthesis of LiNbO sub 3 by hydrolysis of metal alkoxides

Very fine LiNbO{sub 3} powders can be prepared by the hydrolysis of metal alkoxides. The coordination states of metal alkoxides in alcohol were examined by ir and NMR spectroscopy; double alkoxides were formed during controlled refluxing. Under optimum conditions the fine powder can be prepared, crystallizing at lower temperatures, 250{degree}C. Crystallization and removal of the carbonate ion proceeded efficiently by heating the as-precipitated powder in a flow of water vapor and oxygen gas.
Condition of animals on arrival at the abattoir and their management during lairage.

Abstract This chapter presents guidelines on how to assess fitness for transport, undertake on-farm euthanasia for animals not fit for transport; and develop on-farm policies to avoid transporting animals in a deteriorated and compromised condition. Also, how lairage conditions and the management of animals in a lairage may or may not mitigate the condition of the animals on arrival and avoiding deterioration of their welfare during lairage were discussed. Resting behaviour and the importance of physical and social environmental factors in meeting the behavioural and physiological requirements of the animals while in a lairage were also emphasized.
Classical Economic Theory and the Modern Economy

Economic theory reached its zenith of analytical power and depth of understanding in the middle of the nineteenth century among John Stuart Mill and his contemporaries. This book explains what took place in the ensuing Marginal Revolution and Keynesian Revolution that left economists less able to understand how economies operate. It explores the false mythology that has obscured the arguments of classical economists, providing a pathway into the theory they developed.