Miracle-dz/UniFAR-FTUs huggingface dataset:
DDL.1: a formal description of a constraint representation language for physical domains

This paper describes a domain description language DDL.1 able to represent physical domains to solve planning and scheduling problems. DDL.1 uses a representation, inspired by classical control theory, based on state-variables to represent the relevant features of a domain. Each state variable is meant to represent a set of plausible temporal evolutions those features may have. DDL.1 allows to specify constraints on the sequence of values that a state variable may assume over time. For the language a syntactic specification, and a model theoretic semantic are given. The problem of temporal planning using a DDL.1 specification is also addressed and a planning algorithm named TP-SV introduced. The paper tries to show how this kind of description languages may generate a methodology to gracefully model the relevant constraints in physical domains, and how a formally specified planner may be associated to this description.
VIEW-BASED 3 D OBJECT RECOGNITION WITH SUPPORT VECTOR MACHINES

Support Vector Machines have demonstrated excellent results in pattern recognition tasks and 3D object recognition. In this contribution, we confirm some of the results in 3D object recognition and compare it to other object recognition systems. We use different pixel-level representations to perform the experiments, while we extend the setting to the more challenging and practical case when only a limited number of views of the object are presented during training. We report high correct classification of unseen views, especially considering that no domain knowledge is including into the proposed system. Finally, we suggest an active learning algorithm to reduce further the required number of
5-HT receptor-induced long-lasting changes in reflex function 2 Abstract Dorsal root-evoked stimulation of sensory afferents in the hemisected in vitro rat spinal cord produces reflex output, recorded on the ventral roots. Transient spinal 5-HT2C receptor activation induces a long-lasting facilitati

Dorsal root-evoked stimulation of sensory afferents in the hemisected in vitro rat spinal cord produces reflex output, recorded on the ventral roots. Transient spinal 5-HT2C receptor activation induces a long-lasting facilitation of these reflexes (LLFR) by largely unknown mechanisms (Machacek et al., 2001). Two Sprague-Dawley substrains were used to characterize network properties involved in this serotonin (5-HT) receptor-mediated reflex plasticity. Serotonin more easily produced LLFR in one substrain and a long-lasting depression of reflexes (LLDR) in the other. Interestingly, LLFR and LLDR were bi-directionally interconvertible using 5-HT2A/2C and 5HT1A receptor agonists respectively, regardless of substrain. LLFR was predominantly Aβ afferent fiber-mediated consistent with prominent 5-HT2C receptor expression in the Aβ fiber projection territories (deeper spinal laminae). Reflex facilitation involved an unmasking of polysynaptic pathways and an increased receptive field size. LLFR emerged even when reflexes were evoked 3-5 times/hour indicating an activity independent induction. Both the NMDA and AMPA/kainate receptor-mediated components of the reflex could be facilitated, and facilitation was dependent upon 5-HT receptor activation alone, not upon coincident reflex activation in the presence of 5-HT. Selective blockade of GABAA and/or glycine receptors also did not prevent reflex amplification and so are not required for LLFR. Indeed, a more robust response was seen after blockade of spinal inhibition indicating that inhibitory processes serve to limit reflex amplification. Overall we demonstrate that the serotonergic system has the capacity to induce long-lasting bidirectional changes in reflex strength in a manner that is non-associative, and independent of evoked activity or activation of ionotropic excitatory and inhibitory receptors. 5-HT receptor-induced long-lasting changes in reflex function 3
CD163 is a predictive biomarker for prognosis of classical Hodgkin's lymphoma in Saudi patients

Hodgkin's lymphoma (HL) is a hematological malignancy characterized by a minority of neoplastic cells outnumbered by tumor-associated macrophages (TAMs). The overexpression of the CD163 antigen by TAMs is considered to be a significant predictive biomarker for risk stratification. This is likely caused by a genetic single-nucleotide polymorphism (SNP) at the gene promoter. The aim of the present retrospective case-control study was to establish a gene expression profile of a specific biomarker for classical HL (CHL) in order to predict the outcome and survival of CHL patients in Saudi Arabia. The protein expression of CD163 on TAMs was studied using immunohistochemistry (IHC). A prognosis index was calculated for the CD163 protein to assess the risk stratification of CHL. Genotyping of selected SNPs of this antigen was performed for 100 CHL cases and controls. The analysis revealed that the CD163 protein expression level was significantly correlated with disease relapse (DR) and overall survival (OS). In addition, the CD163 index threshold (15.0) was found to be significantly correlated with the relapse rate. Among the studied CD163 SNPs, rs75608120 exhibited a significant correlation with the DR rate of CHL patients, but not with OS. The findings of the present study confirmed that CD163 is a specific marker for TAMs, and its overexpression by TAMs is significantly associated with relapse and reduced survival post-therapy. In addition, a new methodology of indexing CD163 protein expression for HL risk stratification was proposed. Thus, the present study identified a specific predictive molecular and antigenic biomarker for CHL prognosis.
El consumo móvil de las generaciones futuras

El comercio movil es un indicador de la brecha economica y la consecuente, brecha digital entre los paises desarrollados economicamente y los paises con economias emergentes. En tal sentido, se exponen los fundamentos de una teoria para explicar las consecuencias del comercio movil a partir de los determinantes economicos, tecnologicos, mercadotecnicos y psicologicos que llevan a una persona a adquirir productos a traves de protocolos moviles
Amyloid Pathology Is Associated with Progressive Monoaminergic Neurodegeneration in a Transgenic Mouse Model of Alzheimer's Disease

β-Amyloid (Aβ) pathology is an essential pathogenic component in Alzheimer's disease (AD). However, the significance of Aβ pathology, including Aβ deposits/oligomers and glial reactions, to neurodegeneration is unclear. In particular, despite the Aβ neurotoxicity indicated by in vitro studies, mouse models with significant Aβ deposition lack robust and progressive loss of forebrain neurons. Such results have fueled the view that Aβ pathology is insufficient for neurodegeneration in vivo. In this study, because monoaminergic (MAergic) neurons show degenerative changes at early stages of AD, we examined whether the APPswe/PS1ΔE9 mouse model recapitulates progressive MAergic neurodegeneration occurring in AD cases. We show that the progression forebrain Aβ deposition in the APPswe/PS1ΔE9 model is associated with progressive losses of the forebrain MAergic afferents. Significantly, axonal degeneration is associated with significant atrophy of cell bodies and eventually leads to robust loss (∼50%) of subcortical MAergic neurons. Degeneration of these neurons occurs without obvious local Aβ or tau pathology at the subcortical sites and precedes the onset of anxiety-associated behavior in the mice. Our results show that a transgenic mouse model of Aβ pathology develops progressive MAergic neurodegeneration occurring in AD cases.
Negotiation coalitions in group-choice multi-agent systems

In Group-Choice Decision Making (GCDM) where a number of stakeholders are involved in choosing a single solution from a set of available solution options, it is common for the stakeholders to form coalitions during negotiations in order to increase their individual welfare. It is also common to use Multi-Agent Systems (MAS) to automate GCDM processes. In such MAS, agents have to form coalitions like their human counterparts. Within each coalition, the individual agents behave according to the strategies of their clients. In this paper we present a coalition formation model which can employ multiple coalition formation algorithms. The model is motivated by a real-world group-choice multi-agent system that we developed; in the system, agents can form coalitions dynamically based on the similarity between their preferences, and based on the ownership criteria. Finally, this paper presents simulation results that illustrate the operational effectiveness of our coalition formation model.
An Iterative Method for Solving Complex-Symmetric Systems Arising in Electrical Power Modeling

We propose an iterative method for solving a complex-symmetric linear system arising in electric power networks. Our method extends Gremban, Miller, and Zagha's [in Proceedings of the International Parallel Processing Symposium, IEEE Computer Society, Los Alamitos, CA, 1995] support-tree preconditioner to handle complex weights and vastly different admittances. Our underlying iteration is a modification to transpose-free QMR to enhance accuracy. Computational results are described.
Exploring the bird mind: A review of episodic memory and metacognition studies of western scrub-jays

The view that episodic memory and metacognition are human-unique abilities has been challenged over the recent decades. While much of the focus of nonhuman studies has been on primates, western scrub-jays contributed extensively towards the understanding of these abilities. Western scrub-jays demonstrate episodic-like memory by remembering what, where, and when they cached food items and by using this information flexibly during recovery to change their behaviour according to the situation. In addition to episodic-like memory, recent studies suggest that these birds are also capable of self-reflection in a form of metacognition. Further investigation of their self-reflective ability may be the critical approach in deepening our understanding of episodic memory in nonhuman animals.
DAVM Distributed Asynchronous Data Versioning Mechanism for Replicas

We present a distributed and asynchronous versioning mechanism (DAVM) in this paper to identify consistent replicas for each encoding block in BW-RAID, which uses "mirroring and RAID4" encoding scheme to improve the system performance and disk space utilization. DAVM has three advantages: Firstly, it is distributed and asynchronous in management. Secondly, it is correct and workable in any running status of the storage system, including normal status, recovery status. Thirdly, it is independent of standard storage protocols. On the basis of DAVM, we implement an asynchronous and low overhead BW-RAID scheme. Experiments show that DAVM can identify consistent replicas for all logical blocks normal state and recovery states. In sequential write tests, compared to synchronous scheme, our asynchronous scheme improves the average bandwidth by 25.58% in average, and improves the system throughput stability by 25.10% in average, with the storage overhead less than 0.5%. In real workloads replays, our scheme improves the average IOPS by 42.23% in average and reduces the average write latency by 31.76% in average.
AP1 Transcription Factors in Epidermal Differentiation and Skin Cancer

AP1 (jun/fos) transcription factors (c-jun, junB, junD, c-fos, FosB, Fra-1, and Fra-2) are key regulators of epidermal keratinocyte survival and differentiation and important drivers of cancer development. Understanding the role of these factors in epidermis is complicated by the fact that each protein is expressed, at different levels, in multiple cells layers in differentiating epidermis, and because AP1 transcription factors regulate competing processes (i.e., proliferation, apoptosis, and differentiation). Various in vivo genetic approaches have been used to study these proteins including targeted and conditional knockdown, overexpression, and expression of dominant-negative inactivating AP1 transcription factors in epidermis. Taken together, these studies suggest that individual AP1 transcription factors have different functions in the epidermis and in cancer development and that altering AP1 transcription factor function in the basal versus suprabasal layers differentially influences the epidermal differentiation response and disease and cancer development.
Using Fuzzy System to Establish Regional Economy Input-Output Model

The relation of input factors and output in regional economy is complicated, this paper introduces the fuzzy system into the economic field, using the Sugeon fuzzy model to construct the mapping relation between production factors and economic output. Taking China as an example, firstly, selects capital asserts and human capital as economic input factors, GDP as economic output, and then establishes the system structure, finally determines the final parameters by BP algorithm. The case study shows that the fuzzy model has better performance than regression, and the fuzzy if-then rules can give valuable economic decision-making macroscopically.
Integrative approach to cognitive parameters in decision making

Decisions are pervasive phenomena in everyday life. Two predominant factors in decision-making theory are uncertainty and risk. Nevertheless, there are other cognitive aspects whose roles have recently gained attention in the literature. Those aspects include information acquisition strategies, scenario complexity, the dynamic and/or static aspect of choice scenarios, and the time-frame for the tasks. We propose a selective review and an integrative account as a way to argue for the theoretical importance of logically combining those different factors. The main argument is that the factors involved do not play independent roles, rather they can modulate each other´s influence given varying levels of the interactions between factors. The importance of better understanding such interactions lays on the choice of strategies that decision makers use to choose. Finally, theoretical, methodological and managerial contributions and implications relating to such approach are discussed.
Influence of the PCB Manufacturing Process on the Measurement Error of Planar Relative Permittivity Sensors Up To 100 GHz

Accurate and precise knowledge of the relative permittivity of printed circuit board (PCB) materials is essential for the reliable design of high-frequency circuits. For simplicity reasons, planar, resonant permittivity sensors, which are directly integrated on the unknown PCB material, are widely used. However, the sensors are affected by the nonidealities of the copper-clad laminate and PCB manufacturing process, e.g., the difference in roughness between the top and bottom sides of each metal layer. This paper analyzes the influence of these nonidealities on the extracted relative permittivity values of different sensor geometries in microstrip and substrate integrated waveguide (SIW) technology up to 100 GHz. Microstrip resonators are very sensitive against the investigated nonidealities. Additional roughness measurements and more detailed simulation models cannot noticeably reduce the uncertainties. SIW cavity sensors are more robust, and simple modeling approaches lead to low uncertainties smaller than 0.05 for the whole frequency range from 10 to 100 GHz.
Thyroid Hormones in Male Reproduction and Fertility

Thyroid hormones, previously thought not to affect spermatogenesis and male fertility, are now being recognized as having important role in spermatogenesis. The identification of thyroid hormone receptors on Sertoli cells, the nurturing cells for sperm in the testis, has embarked further research to investigate the role of thyroid hormones in male reproduction. Since spermatogenesis occurs in close contact with the Sertoli cells, the thyroid hormones must exert significant regulatory role in sperm production. Therefore, disturbances in the thyroid function could affect spermatogenesis and male fertility. Studies on human subjects and animals models are now revealing further insights into the effect of thyroid hormones on male fertility and infertility. The present review provides an update on the role of thyroid hormones in spermatogenesis and male fertility.
The Service Adaptation Machine

The reuse of software services often requires the introduction of adapters. In the case of coarse-grained services, and especially services that engage in long-running conversations, these adapters must deal not only with mismatches at the level of individual interactions, but also across interdependent interactions. Existing techniques support the synthesis of adapters at design-time by comparing pairs of service interfaces. However, these techniques only work under certain restrictions. This paper explores a runtime approach to service interface adaptation. The paper proposes an adaptation machine that sits between pairs of services and manipulates the exchanged messages according to a repository of mapping rules. The paper formulates an operational semantics for the adaptation machine, including algorithms to compute rule firing sequences and criteria for detecting deadlocks and information loss. The adaptation machine has been implemented as a prototype and tested on common business processes.
Applying GreenLab Model to Adult Chinese Pine Trees with Topology Simplification

This paper applied the functional structural model GreenLab to adult Chinese pine trees (pinus tabulaeformis Carr.). Basic hypotheses of the model were validated such as constant allometry rules, relative sink relationships and topology simplification. To overcome the limitations raised by the complexity of tree structure for collecting experimental data, a simplified pattern of tree description was introduced and compared with the complete pattern for the computational time and the parameter accuracy. The results showed that this simplified pattern was well adapted to fit adult trees with GreenLab.
A way to improve graph-based keyword extraction

Keyword extraction aims to find representative phrases for a document. Graph-based keyword extraction represent the input document as a graph and rank its nodes according to their score using graph-based ranking method. In this paper, we propose a method to compute importance of co-occurrence word in document and apply it in graph approach to find more representative phrases; introduce words correlation degree in document language network to improve performance when extracting average number of keyword in document. The experiment results show the effectiveness of proposed approach.
Integer linear programming for speaker diarization and cross-modal identification in TV broadcast

Most state-of-the-art approaches address speaker diariza- tion as a hierarchical agglomerative clustering problem in the audio domain. In this paper, we propose to revisit one of them: speech turns clustering based on the Bayesian Information Cri- terion (a.k.a. BIC clustering). First, we show how to model it as an integer linear programming (ILP) problem. Its resolu- tion leads to the same overall diarization error rate as standard BIC clustering but generates significantly purer speaker clus- ters. Then, we describe how this approach can easily be ex- tended to the audiovisual domain and TV broadcast in particu- lar. The straightforward integration of detected overlaid names (used to introduce guests or journalists, and obtained via video OCR) into a multimodal ILP problem yields significantly better speaker diarization results. Finally, we explain how this novel paradigm can incidentally be used for unsupervised speaker identification (i.e. not relying on any prior acoustic speaker models). Experiments on the REPERE TV broadcast corpus show that it achieves performance close to that of an oracle ca- pable of identifying any speaker as long as their name appears on screen at least once in the video.
3-D finite-element analysis of fiber-reinforced soft bending actuator for finger flexion

Towards the development of a safe, small, lightweight and human-friendly finger exoskeleton, device made from high elasticity material driven by pneumatic source; or simply known as soft actuator is currently being paid to attention. The study is to determine the optimum fiber-reinforced elastic soft actuator model to be employed in an exoskeleton for finger rehabilitation. Bending motion anticipated from a 3-D finite element actuator model is verified in the nonlinear finite element software, MARC™. The effectiveness of the proposed model is discussed based on the displacement data obtained from the large strain finite element analysis. Specific geometric properties, material properties, contact and boundary conditions related to the real experimental testing were applied to the analysis. Based on the results, the proposed model shows a good presentation of bending motion at applied pressure of 150 kPa. The behavior of bending motion which is greatly influenced by the angle of the fiber reinforced to the actuator is also discussed.
Interacting with digital cultural heritage collections via annotations: the CULTURA approach

This paper introduces the main characteristics of the digital cultural collections that constitute the use cases presently in use in the CULTURA environment. A section on related work follows giving an account on efforts on the management of digital annotations that are pertinent and that have been considered. Afterwards the innovative annotation features of the CULTURA portal for digital humanities are described; those features are aimed at improving the interaction of non-specialist users and general public with digital cultural heritage content. The annotation functions consist of two modules: the FAST annotation service as back-end and the CAT Web front-end integrated in the CULTURA portal. The annotation features have been, and are being, tested with different types of users and useful feedback is being collated, with the overall aim of generalising the approach to diverse document collections and not only the area of cultural heritage.
An Efficient Fault Tolerant Approach to Resource Discovery in P2p Networks an Efficient Fault Tolerant Approach to Resource Discovery in P2p Networks

Current research into resource discovery in peer-to-peer networks is largely focussed on the use of Distributed Hash Tables and multi-layered topologies. In this paper we present a resource discovery system capable of resolving keyword-value pair queries, based on a two-layered Chord ring architecture. We show how the base topology augmented with shortcuts between layers and selection of ring member nodes provides performance benefits and the potential for increased fault tolerance over other similar resource discovery systems.