Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Structural Fingerprints for Graph Attention Networks

Many real-world data sets are represented as graphs, such as citation links, social media, and biological interaction. The volatile graph structure makes it non-trivial to employ convolutional neural networks (CNN's) for graph data processing. Recently, graph attention network (GAT) has proven a promising attempt by combining graph neural networks with attention mechanism, so as to achieve massage passing in graphs with arbitrary structures. However, the attention in GAT is computed mainly based on the similarity between the node content, while the structures of the graph remains largely unemployed (except in masking the attention out of one-hop neighbors). In this paper, we propose an `````````````````````````````"ADaptive Structural Fingerprint" (ADSF) model to fully exploit both topological details of the graph and content features of the nodes. The key idea is to contextualize each node with a weighted, learnable receptive field encoding rich and diverse local graph structures. By doing this, structural interactions between the nodes can be inferred accurately, thus improving subsequent attention layer as well as the convergence of learning. Furthermore, our model provides a useful platform for different subspaces of node features and various scales of graph structures to ``cross-talk'' with each other through the learning of multi-head attention, being particularly useful in handling complex real-world data. Encouraging performance is observed on a number of benchmark data sets in node classification.
Optimization of Diagnostic Process in Assessing the Extent of Dental Hard Tissue Defects after Endodontic Treatment

The selection of an optimal treatment is one of the problems when restoring the defects of dental hard tissues after endodontic treatment. The work aims at studying the percentage ratio of the volume of the coronal portion of the tooth to its crown that will allow us to optimize the determination of the extent of dental hard tissue defect after endodontic treatment as well as to choose the optimal method of treatment.The objective of the research was to optimize the diagnostic process when treating damaged coronal portion of the tooth after endodontic treatment through the determination of the percentage ratio of the volume of the coronal portion of the tooth to the total volume of tooth crown for different groups of teeth.Materials and methods. 42 extracted teeth with preserved coronal portions served as the material for our study. The volume of the coronal potion of the tooth as well as the total volume of tooth crown was determined using the method developed by us. Having calculated the ratio of the volume of the coronal portion of the tooth to the volume of tooth crown, we received the volume which is occupied by the coronal cavity of the tooth.Results. We obtained the percentage ratio of the volume which is occupied by the coronal cavity of the tooth compared to its crown for different groups of teeth.Conclusions. To estimate the extent of damage to the coronal portion of the tooth after endodontic treatment, it is recommend using the obtained data, namely, in the maxillary and mandibular front teeth, the coronal portion of the tooth occupies up to 10% of tooth crown volume, while in the maxillary and mandibular grinding teeth, the coronal portion of the tooth occupies up to 5% of tooth crown volume.
Audiovisual narratives about the case Spain’s stolen babies

The critical discourse analysis is the tool used in this article, to study how audiovisual media have constructed mental representation about the historical facts occurred in Spain between the final stage of the Spanish Civil War (1936–1939) and the late 1980s: the theft of newborn babies. The State has failed in an attempt to establish policies that support truth, justice and reparation as it has been recalled by United Nations experts to the Government of Spain, and the reports and documentaries have become vehicles to capture and recover memories. Our objective is to analyze how this collective awareness has been realized and the contribution of reports and documentaries. Our results show that the Spanish television channels silence the Francoist context to depict the thefts as the product of economical mobs focused on child trafficking. The international channels, however, put the origin of the dictatorship at the center of the discourse.
IGF-I Governs Cortical Inhibitory Synaptic Plasticity By Astrocyte Activation

Insulin-like growth factor-I (IGF-I) signaling plays key regulatory roles in multiple processes of brain physiology and pathology. While the direct effects of IGF-I in neurons have been extensively studied, the astrocyte involvement in IGF-I signaling and the consequences on synaptic plasticity and animal behavior remain unknown. Here we show that IGF-I induces the long-term depression (LTD) of inhibitory synaptic transmission in the mouse barrel cortex. This LTD requires the activation of the IGF-I receptor (IGF-IR) in astrocytes, which stimulates astrocyte Ca2+ signaling and the release of ATP/adenosine that in turn activates A2A adenosine receptors at presynaptic inhibitory terminals. Specific deletion of IGF-IR in cortical astrocytes (IGF-IR-/-) impaired the behavioral performance in a whisker discrimination task. These results show novel mechanisms and functional consequences of IGF-I signaling on cortical inhibitory synaptic plasticity and animal behavior, revealing astrocytes as key elements in these processes.
Pancreatic Dysfunction in Shwachman-Diamond Syndrome

Shwachman-Diamond syndrome (SDS) is an autosomal recessive ribosomopathy caused by loss of the ancillary translation factor Shwachman-Bodian-Diamond syndrome (SBDS) protein, which functions in ribosome subunit joining and protein synthesis. SDS is typified by exocrine pancreatic dysfunction, skeletal abnormalities, and bone marrow failure with leukemia
Checklist-based techniques with gamification and traditional approaches for inspection of interaction models

Interaction models specify the structure and content of the user interface, the allowed user actions, and the corresponding system responses. There is a need to inspect interaction models, as it avoids the propagation of defects to other artefacts. We created two inspection techniques for interaction models, called MoLVERIC Cards (MCards) and MoLVERIC Check (MCheck). MCards employs a gamification mechanism to motivate practitioners during the inspection. MCheck is a simple technique to be used by practitioners in a traditional way. Both techniques have questions, whose answers assist in identifying defects. We performed three studies to verify whether these techniques support the inspection of interaction models. In the first and second studies, we evaluated MCards and MCheck in comparison with an ad-hoc technique supported by the conventional inspection approach based on defect types. The results of these studies showed that both techniques support the inspection of interaction models. In the third study, we evaluated MCard in comparison with MCheck to understand the participants'; perceptions of both techniques. The study results showed that MCards was considered more suitable for practitioners interested in using dynamic activities, while MCheck was considered more suitable for practitioners who want to use a more traditional technique.
Development of sugarcane and trash identification system in sugar production using hyperspectral imaging

Classification and differentiation of clean sugarcane from trash (green sugarcane leaf, dry sugarcane leaf, stone, and soil) are important for the sugar payment system at a sugar mill. Currently, the methods used to do this are manual and subjective. Therefore, this study is aimed at accurately differentiating clean sugarcane from trash by using hyperspectral imaging with multivariate analyses. Samples containing sugarcane billets and trash mixed in a ratio of 18:38 were analyzed in this study. The reflectance data of the samples were analyzed in the wavelength range of 400–1000 nm via principal component analysis (PCA). The PCA model was capable of identifying all of the clean sugarcane and trash samples. The spectral loadings of the PCA model show that the sugarcane and trash samples are easily identifiable based on the color (visible light) of each class, water absorption (approximately 970 nm), and chlorophyll absorption (approximately 680 nm). Based on the characteristic wavelengths of the PCA loading peaks, over 90% of the sugarcane and trash samples were differentiated using a multiple linear regression model. Sugarcane and trash are classified by using partial least-squares discriminant analysis and support vector machine models. For all wavelengths, the classification rate is 92.9% and 98.2%, respectively. This shows that sugarcane and trash can be accurately classified and differentiated by using hyperspectral imaging and multivariate analyses.
The effect of prebiotics on intestinal digestion of carbohydrates in lead intoxicated rats

It has been shown the lead intoxication of growing rats result in increase the cavity and membrane carbohydrate hydrolysis and glucose absorption from small intestine which leads to hyperglicemiya. The oral treatment of intoxicated rats with inulin or lactulose results in decrease of carbohydrate assimilation in small intestine and content glucose level in blood. The correcting effect of lactulose on normalization of carbohydrate assimilation is more expressed in compare with inulin. So, inulin and/or lactulose take part in improving of adaptation of the carbohydrate assimilation system in the small intestine during intoxication with lead ions in growing rats. This suggests the prospect of their use as physiologically acceptable additives to stabilize carbohydrate digestion and blood glucose levels in lead and, possibly, other heavy metal intoxication in the growing organism.
Experimental study of the multiphase flow in a pore doublet model

The paper presents the results of an experimental study of the properties of single-and multiphase flows in a “pore doublet model” (PDM) using microfluidic and optical microscopy techniques. Polymer based microfluidic devices containing pore doublet were fabricated using soft lithography methods. The average cross-section of the microchannels was in the order of 100 μm, and the length reached several millimeters. A bubble generator in the form of a T-junction microchannel was fabricated to study the multiphase flows. High speed imaging and tracer visualization methods were used to study the flow patterns. The properties of multiphase flows were studied during liquid-gas displacement and bubbly liquid flow through pore doublet. The flow patterns were visualized using polymer micro particles suspended in flowing liquids.
Empirical essays on public and media attitudes to conflict

The lens through which people observe and form judgements upon conflict and terrorism depends heavily on the media they consume as well as their personal circumstances. This thesis is comprised of three empirical studies; the first two investigate how media reporting of armed conflict affects both the perceptions of news consumers and the completeness of media-based datasets, the third analyses the determinants of public support for terrorism. Chapter 1 studies the factors that drive variation in the intensity of media coverage that violent events receive and the impact this will have upon consumers of news media. This is achieved by using the unique Iraq Body Count (IBC) database. Conflict events accruing intense media coverage are those that have higher numbers of fatalities and injuries, use more newsworthy weapons (e.g. explosive violence) and occur on weekdays. Events occurring further from Baghdad receive a reporting intensity penalty, particularly among the international media. Chapter 2 considers the impact of heterogenous reporting on media-based conflict event datasets. Founders of such datasets select a subset of sources from the universe of news media outlets to be monitored. This source selection affects both the overall body count as well as the dataset’s event type composition. The chapter also applies multiple systems estimation (MSE) techniques to the Iraq case finding that IBC is likely missing a substantial number of events and that these are not randomly distributed across event types. The third chapter considers how an individual’s support for terrorism against civilians is determined by their socio-economic and religious characteristics. The study uses 11 rounds of Pew’s Global Attitudes Survey in five Muslim countries. Results show that support for terrorism generally declines as household income or religious commitment rises. Increased levels of education, however, may significantly increase support for terrorism in some countries. Finally, a concluding chapter draws out the implications from these three studies as well as the synergies between them.
Dynamics of sphingolipids and the serine palmitoyltransferase complex in rat oligodendrocytes during myelination[S]

Myelin is a unique lipid-rich membrane structure that accelerates neurotransmission and supports neuronal function. Sphingolipids are critical myelin components. Yet sphingolipid content and synthesis have not been well characterized in oligodendrocytes, the myelin-producing cells of the CNS. Here, using quantitative real-time PCR, LC-MS/MS-based lipid analysis, and biochemical assays, we examined sphingolipid synthesis during the peak period of myelination in the postnatal rat brain. Importantly, we characterized sphingolipid production in isolated oligodendrocytes. We analyzed sphingolipid distribution and levels of critical enzymes and regulators in the sphingolipid biosynthetic pathway, with focus on the serine palmitoyltransferase (SPT) complex, the rate-limiting step in this pathway. During myelination, levels of the major SPT subunits increased and oligodendrocyte maturation was accompanied by extensive alterations in the composition of the SPT complex. These included changes in the relative levels of two alternative catalytic subunits, SPTLC2 and -3, in the relative levels of isoforms of the small subunits, ssSPTa and -b, and in the isoform distribution of the SPT regulators, the ORMDLs. Myelination progression was accompanied by distinct changes in both the nature of the sphingoid backbone and the N-acyl chains incorporated into sphingolipids. We conclude that the distribution of these changes among sphingolipid family members is indicative of a selective channeling of the ceramide backbone toward specific downstream metabolic pathways during myelination. Our findings provide insights into myelin production in oligodendrocytes and suggest how dysregulation of the biosynthesis of this highly specialized membrane could contribute to demyelinating diseases.
Human Subjects Testing of Sweat Stimulation Technologies

i ACKNOWLEDGEMENTS iv TABLE OF CONTENTS v LIST OF TABLES vi LIST OF FIGURES vi (1) INTRODUCTION 1 (1.1) ULTRASTRUCTURE OF THE ECCRINE SWEAT GLAND 1 (1.2) SWEAT SECRETION AND mM-pM SOLUTE PARTITIONING 3 (1.3) CURRENT SWEAT STIMULATION AND SENSING TECHNOLOGIES 10 (2) HYPOTHESIS AND SPECIFIC AIMS 13 (3) AN EXAMINATION OF INTRAAND INTERSUBJECT SWEAT VARIATIONS USING COMMERCIALLY AVAILABLE SWEAT STIMULATION TECHNOLOGIES 14 (3.1) INTRODUCTION 14 (3.2) MATERIALS AND METHODS 15 (3.2.1) PARTICIPANT DEMOGRAPHICS AND ELIGIBILITY 15 (3.2.2) NANODUCT® IONTOPHORESIS 16 (3.2.3) MACRODUCT® IONTOPHORESIS 17 (3.2.4) STATISTICAL ANALYSIS 18 (3.2.5) STUDY APPROVAL AND INFORMED CONSENT 18 (3.3) RESULTS 18 (3.3.1) NANODUCT® 18 (3.3.2) MACRODUCT® 19 (3.3.3) DUPLICATION TESTS 20 (3.4) DISCUSSION 21 (3.5) ETHICAL APPROVAL 23 (3.6) CONFLICT OF NTEREST 23 (4) EXPLORATORY STUDIES 24 (4.1) IONTOPHORETIC SUDOMOTOR AXON REFLEX PATCH 24 (4.2) EXERCISE PATCH 26 (5) CONCLUSIONS AND RECOMMENDATIONS 28 BIBLIOGRAPHY 31 APPENDIX A: TESTING THE MICROFLUIDICS OF ON-SKIN TECHNOLOGIES 34 APPENDIX B: TESTING OF A NOVEL IONTOPHORETIC SWEAT STIMULATION PATCH 42 APPENDIX C: TESTING OF NOVEL ON-SKIN SWEAT PATCH THROUGH METABOLIC SWEAT INDUCTION 47
Dual-Source Transformer Model for Neural Machine Translation with Linguistic Knowledge

Incorporating source-side linguistic knowledge into the neural machine translation (NMT) model has recently achieved impressive performance on machine translation tasks. One popular method is to generalize the word embedding layer of the encoder to encode each word and its linguistic features. The other method is to change the architecture of the encoder to encode syntactic information. However, the former cannot explicitly balance the contribution from the word and its linguistic features. The latter cannot flexibly utilize various types of linguistic information. Focusing on the above issues, this paper proposes a novel NMT approach that models the words in parallel to the linguistic knowledge by using two separate encoders. Compared with the single encoder based NMT model, the proposed approach additionally employs the knowledge-based encoder to specially encode linguistic features. Moreover, it shares parameters across encoders to enhance the model representation ability of the source-side language. Extensive experiments show that the approach achieves significant improvements of up to 2.4 and 1.1 BLEU points on Turkish→English and English→Turkish machine translation tasks, respectively, which indicates that it is capable of better utilizing the external linguistic knowledge and effective improving the machine translation quality.
Out of Control: Causes of Individual Differences in Self-Control

Self-control plays a significant role in positive youth development. Although numerous self-control challenges occur during adolescence, some adolescents control themselves better than others. Parenting is considered a critical factor that distinguishes adolescents with good self-control from those with poor selfcontrol, but existing findings are inconsistent. This meta-analysis summarizes the overall relationship between parenting and self-control among adolescents aged 10 to 22. The analysis includes 191 articles reporting 1,540 effect sizes (N=164,459). The results show that parenting is associated with adolescents’ self-control both concurrently (r=.204, p<.001) and longitudinally (r=.157, p<.001). Longitudinal studies also reveal that adolescents’ self-control influences subsequent parenting (r=.155, p<.001). Moderator analyses show that the effect sizes are largely invariant across cultures, ethnicities, age of adolescents, and parent and youth gender. Our results point to the importance of parenting in individual differences in adolescent self-control and vice versa.
Grasp Pose Detection Based On Point Cloud Shape Simplification

In the robot grasping environment, grasping unknown objects that have neither model data nor RGB data is very important, we present a new approach for grasping unknown objects. Firstly, depth camera is used to obtain the partial 3D data of target object. Then, we perform 3D segmentation and the segmented parts are simplified to a cylinder, a sphere, an ellipsoid or a parallelepiped based on the geometric and semantic shape characteristic. Grasping constraints are used to obtain grasp candidates based on the simplified shape. The grasp descriptions are used to describe each candidates and CNN is used for grasping training. We evaluate our grasp networks both in simulation and robotic experiment, and the experiment result shows that the grasp quality score using simplified constraints is more robust than without simplified constraint when the gripper posture is uncertain.
Contrasting Hydroclimatic Model‐Data Agreements Over the Nordic‐Arctic Region

Rapid changes in high‐latitude hydroclimate have important implications for human societies and environment. Previous studies of different regions have indicated better agreement between climate model results and observation data for the thermodynamic variable of surface air temperature (T) than for the water variables of precipitation (P), evapotranspiration (ET), and runoff (R). Here we compare climate model output with observations for 64 Nordic and Arctic hydrological basins of different sizes, and for the whole region combined. We find an unexpectedly high agreement between models and observations for R, about as high as the model‐observation agreement for T and distinctly higher than that for P or ET. Model‐observation agreement for R and T is also consistently higher on the whole‐region scale than individual basin scales. In contrast, model‐observation agreement for P and ET is overall lower, and for some error measures also lower for the whole region than for individual basins of various scales. Region‐specific soil freeze–thaw bias of climate models can at least partly explain the low model‐observation agreement for P and ET, while leaving modeled R relatively unaffected. Thereby, model projections for this region may be similarly reliable and directly useful for large‐scale average conditions of R as of T.
Representative Solutions for Bi-Objective Optimisation

Bi-objective optimisation aims to optimise two generally competing objective functions. Typically, it consists in computing the set of nondominated solutions, called the Pareto front. This raises two issues: 1) time complexity, as the Pareto front in general can be infinite for continuous problems and exponentially large for discrete problems, and 2) lack of decisiveness. This paper focusses on the computation of a small, “relevant” subset of the Pareto front called the representative set, which provides meaningful trade-offs between the two objectives. We introduce a procedure which, given a pre-computed Pareto front, computes a representative set in polynomial time, and then we show how to adapt it to the case where the Pareto front is not provided. This has three important consequences for computing the representative set: 1) does not require the whole Pareto front to be provided explicitly, 2) can be done in polynomial time for bi-objective mixed-integer linear programs, and 3) only requires a polynomial number of solver calls for bi-objective problems, as opposed to the case where a higher number of objectives is involved. We implement our algorithm and empirically illustrate the efficiency on two families of benchmarks.
Segmented-Rotor Modular Switched Reluctance Motor With High Torque and Low Torque Ripple

This article delves into simultaneously applying the modular stator and segmented rotor to switched reluctance motors (SRMs). In this regard, a new double-stator segmented-rotor modular SRM (DSSR-MSRM) with a new pole combination is proposed. First, the motor topology is introduced and the magnetic circuit model of the motor is analyzed. Next, the electromagnetic performances of the machine are analyzed using a finite-element analysis (FEA). The superiority of the DSSR-MSRM in terms of flux linkage and torque is illustrated based on a comparative study with five various types of SRMs with modular/nonmodular and segmented/nonsegmented structures with the same dimensions and parameters. The simulation results indicate that the DSSR-MSRM has higher torque compared to the other structures. Moreover, the dynamic performances of the proposed motor in terms of current, torque, and power waveforms are obtained. In addition, it is shown that the proposed motor has low torque ripple. Finally, the prototype motor is built, the mechanical considerations are discussed, and the experimental results are obtained, which are in a good agreement with those predicted from the FEA.