Miracle-dz/UniFAR-FTUs huggingface dataset:
International sourcing: a must or a choice? A perspective on the role of local supplier relationships in the Italian mechanical industry

Studies on international sourcing strategies and practices are mainly concerned with the behaviour of large firms, which are able to interact with various supply sources in different markets and detain organisational capabilities to engage in such activities. Only a few studies enter into the detail of SME’s international sourcing behaviour. Therefore the main goal of this paper is to investigate whether mid-sized companies might choose to remain closely integrated within the local supply network and which are the main conditions influencing their approach. The research methodology is qualitative and based on the investigation of three case-studies of Italian companies selected among the leading firms in specific subsectors of the mechanical industry in the light of their size, performance and international profile. The empirical analysis shows that the three companies under examination pursue a gradual and balanced approach toward international sourcing opportunities, which are exploited mainly for commercial parts and only to a limited extent for customized parts and components. Local suppliers have been playing the role of “sources” of value in different ways in distinct historical phases, contributing actively in terms of knowledge and competence development, production flexibility and delivery performance, and price efficiency. Within such context, the three companies over time have shown a capacity to adapt their supply management approach to changing market conditions, with the emergence of hybrid and segmented buyer-supplier relations in different historical phases.
Differences in Long- and Short-Term Memory Performance and Brain Matter Integrity in Seniors With Different Physical Activity Experience

Abstract Due to increasing changes in demographics, maintaining cognitive functioning later in life has become both economic and social concerns, and thus finding a cost-effective solution is one of the priorities in research. Factors like physical and intellectual activities have been associated with better cognitive performance in later life. While several studies have considered the impact of short-term physical activity interventions on cognitive functioning, retrospective research focusing on life-time physical activity experience has been sparse. The aim of the study was to determine the relationship between memory performance and whole brain matter integrity in seniors with different regular life-long physical activity experience. Fifty-three Latvian seniors aged 65–85 (M = 72.25, SD = 5.03, 83% female) with no self-reported chronic disease participated in the study. Measures of memory, physical activity and whole brain matter integrity were obtained and analysed. The obtained results indicated no significant relationship between physical activity experience and short and long-term memory and whole brain matter integrity; however, brain matter integrity was significantly correlated with demographic factors like age and education. These results might be related to inadequate physical activity measures, as well as unequal physical activity experience in participants. In the future, more detailed assessment of physical activity experience should be considered.
Using Czech-English Parallel Corpora in Automatic Identiﬁcation of It

In this paper we have two goals. First, we want to present a part of the annotation scheme of the recently released Prague Czech-English Dependency Treebank 2.0 related to the annotation of personal pronoun it on the tectogrammatical layer of sentence representation. Second, we introduce experiments with the automatic identiﬁcation of English personal pronoun it and its Czech counterpart. We design sets of tree-oriented rules and on the English side we combine them with the state-of-the-art statistical system that altogether results in an improvement of the identiﬁcation. Furthermore, we design and successfully apply rules, which exploit information from the other language.
Prediction of retweet cascade size over time

Retweet cascades play an essential role in information diffusion in Twitter. Popular tweets reflect the current trends in Twitter, while Twitter itself is one of the most important online media. Thus, understanding the reasons why a tweet becomes popular is of great interest for sociologists, marketers and social media researches. What is even more important is the possibility to make a prognosis of a tweet's future popularity. Besides the scientific significance of such possibility, this sort of prediction has lots of practical applications such as breaking news detection, viral marketing etc. In this paper we try to forecast how many retweets a given tweet will gain during a fixed time period. We train an algorithm that predicts the number of retweets during time T since the initial moment. In addition to a standard set of features we utilize several new ones. One of the most important features is the flow of the cascade. Another one is PageRank on the retweet graph, which can be considered as the measure of influence of users.
SentiFul: A Lexicon for Sentiment Analysis

In this paper, we describe methods to automatically generate and score a new sentiment lexicon, called SentiFul, and expand it through direct synonymy and antonymy relations, hyponymy relations, derivation, and compounding with known lexical units. We propose to distinguish four types of affixes (used to derive new words) depending on the role they play with regard to sentiment features: propagating, reversing, intensifying, and weakening. Besides derivation, we considered important process of finding new words such as compounding, which is a highly productive process, especially in the case of nouns and adjectives. We elaborated the algorithm for automatic extraction of new sentiment-related compounds from WordNet using words from SentiFul as seeds for sentiment-carrying base components and applying the patterns of compound formations. In the paper, the importance of considering modifiers, contextual valence shifters, and modal operators, which are integral parts of the SentiFul lexicon for robust sentiment analysis, is also discussed.
Simple approach to the angular momentum distribution in the ground states of many-body systems

We propose a simple approach to predict the angular momentum I ground state (I g.s.) probabilities of many-body systems that does not require the diagonalization of hamiltonians with random interactions. This method is found to be applicable to {\bf all} cases that have been discussed: even and odd fermion systems (both in single-j and many-j shells), and boson (both sd and sdg) systems. A simple relation for the highest angular momentum g.s. probability is found. Furthermore, it is suggested for the first time that the 0g.s. dominance in boson systems and in even-fermion systems is given by two-body interactions with specific features.
Mindful “Servants:” Reflective Practices in a High School Service-Learning Classroom

Increasingly, public school teachers, administrators, and students are turning towards including reflective practices, such as “mindfulness” activities, in their daily teaching and learning experiences. This article shows the importance of how practitioners and students use and experience these practices, especially in a service-learning program aimed at pushing students to change habits and ways of thinking. This qualitative study explores reflective techniques applied to a high school service-learning course that was created and maintained to push students out of their “comfort zones” and further into community exploration and self-reflection. Results of the study conclude that reflective activities were effective in class and service contexts, supported personal growth and connection, and that students experienced “buy-in,” embracing weekly journal assignments, one-one-one-conversations, and meditation. Keywords: Mindfulness, service-learning, reflection, meditation, adolescents, high school
Feature-Oriented Reflexion Modelling

Reflexion Modelling is an industrially proven and well-established technique for the reconstruction of software architectures. Studies have shown, users of this technique not only envisage it as a means of recovering the logical module structure of the system but also envisage it as a means of modelling a high-level functional view on the system, in which architectural entities represent user-observable functionality. In this case, the challenging task of manual mapping source code to modules in the reflexion model becomes the task of feature location. In this article, we describe the idea of Feature-Oriented Reflexion Modelling in which just-in-time Reflexion Modelling is combined with automatic Feature Location techniques, helping the system expert define that mapping efficiently and thus subsequently analyse, explore, and model the inter-feature dependencies in systems. Feature Location techniques are applied to suggest mapping extensions to the reflexion model to the user, leading to an incremental and interactive mapping process. Furthermore, we outline a research agenda towards an industrially applicable realisation.
On the Role of Reflection and Representation in Environmental Decision Support Systems

Donald Norman describes how reflection enables us to critically analyse and review details, compare and contrast situational outcomes, and aid in our general decision- making abilities. Furthermore, he explains how through reflection, we increase our awareness - become smarter - which inevitably enables us to conduct more satisfying decision-making analyses. In a day and age where information is abundant, the activity of reflection may prove more difficult. This is particularly the case for evaluating alternatives for health and environmentally preferable product selection. Key in supporting consumers in such regard is the design of the user interface, one where the interactions provide satisfying user experiences through support for reflective activities supplemented by high quality representations. This paper will discuss the importance of reflection and representation in such regard by describing a framework for system design. A detailed description of the framework is provided along with a discussion describing qualitative results from a recent usability evaluation. Future work is also provided.
Functional Genomic Analyses of Two Morphologically Distinct Classes of Drosophila Sensory Neurons: Post-Mitotic Roles of Transcription Factors in Dendritic Patterning

Background Neurons are one of the most structurally and functionally diverse cell types found in nature, owing in large part to their unique class specific dendritic architectures. Dendrites, being highly specialized in receiving and processing neuronal signals, play a key role in the formation of functional neural circuits. Hence, in order to understand the emergence and assembly of a complex nervous system, it is critical to understand the molecular mechanisms that direct class specific dendritogenesis. Methodology/Principal Findings We have used the Drosophila dendritic arborization (da) neurons to gain systems-level insight into dendritogenesis by a comparative study of the morphologically distinct Class-I (C-I) and Class-IV (C-IV) da neurons. We have used a combination of cell-type specific transcriptional expression profiling coupled to a targeted and systematic in vivo RNAi functional validation screen. Our comparative transcriptomic analyses have revealed a large number of differentially enriched/depleted gene-sets between C-I and C-IV neurons, including a broad range of molecular factors and biological processes such as proteolytic and metabolic pathways. Further, using this data, we have identified and validated the role of 37 transcription factors in regulating class specific dendrite development using in vivo class-specific RNAi knockdowns followed by rigorous and quantitative neurometric analysis. Conclusions/Significance This study reports the first global gene-expression profiles from purified Drosophila C-I and C-IV da neurons. We also report the first large-scale semi-automated reconstruction of over 4,900 da neurons, which were used to quantitatively validate the RNAi screen phenotypes. Overall, these analyses shed global and unbiased novel insights into the molecular differences that underlie the morphological diversity of distinct neuronal cell-types. Furthermore, our class-specific gene expression datasets should prove a valuable community resource in guiding further investigations designed to explore the molecular mechanisms underlying class specific neuronal patterning.
Self-diffusion in sheared suspensions by dynamic simulation

The behaviour of the long-time self-diffusion tensor in concentrated colloidal dispersions is studied using dynamic simulation. The simulations are of a suspension of monodisperse Brownian hard spheres in simple shear flow as a function of the Péclet number, Pe, which measures the relative importance of shear and Brownian forces, and the volume fraction, ϕ. Here, Pe = &γdot;a2/D0, where &γdot; is the shear rate, a the particle size and D0 = kT/6πηa is the Stokes–Einstein diffusivity of an isolated particle of size a with thermal energy kT in a solvent of viscosity η. Two simulations algorithms are used: Stokesian Dynamics for inclusion of the many-body hydrodynamic interactions, and Brownian Dynamics for suspensions without hydrodynamic interactions. A new procedure for obtaining high-quality diffusion data based on averaging the results of many short simulations is presented and utilized. At low shear rates, low Pe, Brownian diffusion due to a random walk process dominates and the characteristic scale for diffusion is the Stokes–Einstein diffusivity, D0. At zero Pe the diffusivity is found to be a decreasing function of ϕ. As Pe is slowly increased, O(Pe) and O(Pe3/2) corrections to the diffusivity due to the flow are clearly seen in the Brownian Dynamics system in agreement with the theoretical results of Morris & Brady (1996). At large shear rates, large Pe, both systems exhibit diffusivities that grow linearly with the shear rate by the non-Brownian mechanism of shear-induced diffusion. In contrast to the behaviour at low Pe, this shear-induced diffusion mode is an increasing function of ϕ. Long-time rotational self-diffusivities are of interest in the Stokesian Dynamics system and show similar behaviour to their translational analogues. An off-diagonal long-time self-diffusivity, Dxy, is reported for both systems. Results for both the translational and rotational Dxy show a sign change from low Pe to high Pe due to different mechanisms in the two regimes. A physical explanation for the off-diagonal diffusivities is proposed.
Real-World Scene Representations in High-Level Visual Cortex: It's the Spaces More Than the Places

Real-world scenes are incredibly complex and heterogeneous, yet we are able to identify and categorize them effortlessly. In humans, the ventral temporal parahippocampal place area (PPA) has been implicated in scene processing, but scene information is contained in many visual areas, leaving their specific contributions unclear. Although early theories of PPA emphasized its role in spatial processing, more recent reports of its function have emphasized semantic or contextual processing. Here, using functional imaging, we reconstructed the organization of scene representations across human ventral visual cortex by analyzing the distributed response to 96 diverse real-world scenes. We found that, although individual scenes could be decoded in both PPA and early visual cortex (EVC), the structure of representations in these regions was vastly different. In both regions, spatial rather than semantic factors defined the structure of representations. However, in PPA, representations were defined primarily by the spatial factor of expanse (open, closed) and in EVC primarily by distance (near, far). Furthermore, independent behavioral ratings of expanse and distance correlated strongly with representations in PPA and peripheral EVC, respectively. In neither region was content (manmade, natural) a major contributor to the overall organization. Furthermore, the response of PPA could not be used to decode the high-level semantic category of scenes even when spatial factors were held constant, nor could category be decoded across different distances. These findings demonstrate, contrary to recent reports, that the response PPA primarily reflects spatial, not categorical or contextual, aspects of real-world scenes.
Human Motion De-noising via Greedy Kernel Principal Component Analysis Filtering

Kernel principal component analysis (KPCA) has been shown to be a powerful non-linear de-noising technique. A disadvantage of KPCA, however, is that the storage of the kernel matrix grows quadratically, and the evaluation cost grows linearly with the number of exemplars. The size of the training set composing of these exemplars is therefore vital in any real system incorporating KPCA. Given long human motion sequences, we show how the greedy KPCA algorithm can be applied to filter exemplar poses to build a reduced training set that optimally describes the entire sequence. We compare motion de-noising between standard KPCA using all poses in the original sequence as training exemplars and de-noising using the reduced set filtered by the greedy algorithm. We show how both have superior de-noising qualities over PCA, whilst Greedy KPCA results in lower evaluation cost due to the reduced training set
Some results on interval edge colorings of ( α , β )-biregular bipartite graphs

A bipartite graph G is called (α, β)-biregular if all vertices in one part of G have the degree α and all vertices in the other part have the degree β. An edge coloring of a graph G with colors 1, 2, 3, . , t is called an interval t-coloring if the colors received by the edges incident with each vertex of G are distinct and form an interval of integers and at least one edge of G is colored i, for i = 1, . , t. We show that the problem to determine whether an (α, β)-biregular bipartite graph G has an interval t-coloring is NP-complete in the case when α > β ≥ 3 and β is a divisor of α. It is known that if an (α, β)-biregular bipartite graph G on m vertices has an interval t-coloring then α+β−gcd(α, β) ≤ t ≤ m−1, where gcd(α, β) is the greatest common divisor of α and β. We prove that if an (α, β)-biregular bipartite graph has m ≥ 2(α + β) vertices then the upper bound can be improved to m − 3. We also show that this bound is tight by constructing, for every integer n ≥ 1, a connected (α, β)-biregular bipartite graph G which has m = n(α + β) vertices and admits an interval t-coloring for every t satisfying α + β − gcd(α, β) ≤ t ≤ m − 3.
Viewpoint normalized images for feature based landmark detection

Image feature based landmark detection is widely used in machine vision for mobile robotics applications. Advanced image feature extraction algorithms offer robust keypoint detection as being invariant to numerous transformations such as translation, rotation, scale change. Even slight changes in brightness, contrast or viewpoint do not affect feature point matching abilities. The most widely used advanced image feature extraction algorithms such as SIFT (Scale Invariant Feature Transform) and SURF (Speeded Up Robust Feature) both have these features. Both algorithms implement feature point detection and descriptor generation. Descriptor vectors are calculated around feature points to distinguish and match these points based on the image content. In the application of mobile robotics viewpoint invariance is essential. As the robot moves in its environment it must detect landmarks from widely different viewpoints to improve efficiency of SLAM algorithms. This is essential in loop closing situations. In this paper we evaluate a method to improve viewpoint invariance based on the additional data provided by range image sensors to supplement traditional feature extraction algorithms. Planes are extracted from range images based on local surface normal histograms and feature point matching is evaluated in viewpoint normalized image planes. We present a simulation framework and results for the selected algorithm. We compare feature point matching with and without the improvement.
Hierarchical Semantic Role Labeling

We present a four-step hierarchical SRL strategy which generalizes the classical two-level approach (boundary detection and classification). To achieve this, we have split the classification step by grouping together roles which share linguistic properties (e.g. Core Roles versus Adjuncts). The results show that the non-optimized hierarchical approach is computationally more efficient than the traditional systems and it preserves their accuracy.
Factors Influencing Academic Achievement of Undergraduate Computing Students

Undergraduate computing students may face some problems, complications and worries in attaining respectable academic performance due to some disturbing factors. Detecting these factors is crucial to ring the bell and raise the alertness of the students and guide them to modify their behavior for better achievement. This study examines the factors affecting the academic achievement of computing students of faculty of computers and information technology (FCIT), University of Tabuk. 320 computing students from both male and female campuses responded to a self-administered questionnaire. The results report 21 affecting factors ordered by their importance. General Terms Computer Science, Principle Component Analysis PCA.
Quantitative and qualitative measures of decomposition: is there a link?

Decomposition rates of loblolly pine coarse woody debris (CWD) were determined by mass loss and wood density changes for trees that differed in source of mortality (natural, girdle-poison, and felling). Specifically, three treatments were examined: (1) control (CON): natural mortality; (2) CD: 5-fold increase in CWD compared with the CON; and (3) CS: 12-fold increase in snags compared with the CON. The additional CWD in the CD treatment plots and the additional snags in the CS plots were achieved by felling (for the CD plots) or girdling followed by herbicide injection (for the CS plots) select trees in these plots. Consequently,mortality on the CD plots is due to natural causes and felling. Likewise, mortality on the CS plots is due to natural causes and girdle-poison. In each treatment plot, mortality due to natural causes was inventoried since 1997, whereas mortality due to girdle-poison and felling were inventoried since 2001. No significant difference was detected between the rates of decomposition for the CWD on these treatment plots, indicating that source of the tree mortality did not influence rates of decomposition once the tree fell. These experimental measures of decomposition were compared with two decay classification systems (three- and five-unit classifications) tomore » determine linkages. Changes in wood density did not correlate to any decay classification, whereas mass loss had a weak correlation with decay class. However, the large degree of variation limits the utility of decay classification systems in estimating mass loss. « less