Miracle-dz/UniFAR-FTUs huggingface dataset:
Levels of modeling of mechanisms of visually guided behavior

Abstract Intermediate constructs are required as bridges between complex behaviors and realistic models of neural circuitry. For cognitive scientists in general, schemas are the appropriate functional units; brain theorists can work with neural layers as units intermediate between structures subserving schemas and small neural circuits. After an account of different levels of analysis, we describe visuomotor coordination in terms of perceptual schemas and motor schemas. The interest of schemas to cognitive science in general is illustrated with the example of perceptual schemas in high-level vision and motor schemas in the control of dextrous hands. Rana computatrix, the computational frog, is introduced to show how one constructs an evolving set of model families to mediate flexible cooperation between theory and experiment. Rana computatrix may be able to do for the study of the organizational principles of neural circuitry what Aplysia has done for the study of subcellular mechanisms of learning. Approach, avoidance, and detour behavior in frogs and toads are analyzed in terms of interacting schemas. Facilitation and prey recognition are implemented as tectal-pretectal interactions, with the tectum modeled by an array of tectal columns. We show how layered neural computation enters into models of stereopsis and how depth schemas may involve the interaction of accommodation and binocular cues in anurans.
Next‐generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan)

Summary To map resistance genes for Fusarium wilt (FW) and sterility mosaic disease (SMD) in pigeonpea, sequencing‐based bulked segregant analysis (Seq‐BSA) was used. Resistant (R) and susceptible (S) bulks from the extreme recombinant inbred lines of ICPL 20096 × ICPL 332 were sequenced. Subsequently, SNP index was calculated between R‐ and S‐bulks with the help of draft genome sequence and reference‐guided assembly of ICPL 20096 (resistant parent). Seq‐BSA has provided seven candidate SNPs for FW and SMD resistance in pigeonpea. In parallel, four additional genotypes were re‐sequenced and their combined analysis with R‐ and S‐bulks has provided a total of 8362 nonsynonymous (ns) SNPs. Of 8362 nsSNPs, 60 were found within the 2‐Mb flanking regions of seven candidate SNPs identified through Seq‐BSA. Haplotype analysis narrowed down to eight nsSNPs in seven genes. These eight nsSNPs were further validated by re‐sequencing 11 genotypes that are resistant and susceptible to FW and SMD. This analysis revealed association of four candidate nsSNPs in four genes with FW resistance and four candidate nsSNPs in three genes with SMD resistance. Further, In silico protein analysis and expression profiling identified two most promising candidate genes namely C. cajan_01839 for SMD resistance and C. cajan_03203 for FW resistance. Identified candidate genomic regions/SNPs will be useful for genomics‐assisted breeding in pigeonpea.
Photogrammetric grading of oil palm fresh fruit bunches

 Abstract— Conventional grading of oil palm Fresh Fruit Bunches (FFB) is still currently manually carried out in palm oil producing industries. The most critical part of the grading process is the categorization of the oil palm fruit bunches according to their ripeness. This paper presents a computer assisted photogrammetric methodology which correlates the color of the palm oil fruits to their ripeness and eventually sorts them out physically. The methodology consists of five main phases, i.e. image acquisition, image pre-processing, image segmentation, calculation of color Digital Numbers (DN) and finally the classification of the fresh fruit bunches according to their ripeness. The software and hardware essential s for the implementation of the methodology have been developed and tested. The design of system is geared towards four main characteristics: (i) affordable in comparison to the labor cost in palm oil mills, (ii) reliable grading process equivalent to the task carried out by a skilled grader, (iii) sufficiently robust to withstand the oil palm mill environment without human intervention and (iv) synergistic integration of hardware and software systems. The system and the methodology formulated in this work have developed a complete automation grading system of oil palm FFB and thus drastically increased the grading productivity.
Attentional blink in young people with high-functioning autism and Asperger’s disorder

The aim of the study was to examine the temporal characteristics of information processing in individuals with high-functioning autism and Asperger’s disorder using a rapid serial visual presentation paradigm. The results clearly showed that such people demonstrate an attentional blink of similar magnitude to comparison groups. This supports the proposition that the social processing difficulties experienced by these individuals are not underpinned by a basic temporal-cognitive processing deficit, which is consistent with Minshew’s complex information processing theory. This is the second study to show that automatic inhibitory processes are intact in both autism and Asperger’s disorder, which appears to distinguish these disorders from some other frontostriatal disorders. The finding that individuals with autism were generally poorer than the comparison group at detecting black Xs, while being as good in responding to white letters, was accounted for in the context of a potential dual-task processing difficulty or visual search superiority.
Region-based automatic web image selection

We propose a new Web image selection method which employs the region-based bag-of-features representation. The contribution of this work is (1) to introduce the region-based bag-of-features representation into an Web image selection task where training data is incomplete, and (2) to prove its effectiveness by experiments with both generative and discriminative machine learning methods. In the experiments, we used a multiple-instance learning SVM and a standard SVM as discriminative methods, and pLSA and LDA mixture models as probabilistic generative methods. Several works on Web image filtering task with bag-of-features have been proposed so far. However, in case that the training data includes much noise, sufficient results could not be obtained. In this paper, we divide images into regions and classify each region instead of classifying whole images. By this region-based classification, we can separate foreground regions from background regions and achieve more effective image training from incomplete training data. By the experiments, we show that the results by the proposed methods outperformed the results by the whole-image-based bag-of-features.
The Impact of Previous LMX Relationship on Current LMX Relationship: A Social Cognitive Model of Transference

Based on the social-cognitive model of transference, this paper discusses the transference effect of the leader-member exchange (LMX) relationship between the follower and the previous leader. The results show that the LMX between follower and the previous leader influences the follower's LMX with the current leader. The study identifies two moderators: both the traits difference between the previous leader and the current leader and the follower's individual transition resistance negatively moderate the main effect between the previous LMX and the current LMX.
AVENUE: Automated site modeling in urban environments

This paper is an overview of the AVENUE project at Columbia University. AVENUE's main goal is to automate the site modeling process in urban environments. The first component of AVENUE is a 3-D modeling system which constructs complete 3-D geometric models with photometric texture mapping acquired from different viewpoints. The second component is a planning system that plans the Next-Best-View for acquiring a model of the site. The third component is a mobile robot we have built that contains an integrated sensor suite for automatically performing the site modeling task. We present results for modeling buildings in New York City.
RELATIONSHIP BETWEEN OBSERVED COMPONENTS OF VARIANCE AND CAUSAL COMPONENTS OF VARIANCE IN A SPLIT‐FAMILY, HALF‐SIB, FULL‐SIB ANALYSIS

In the first of two papers presenting a quantitativegenetic analysis of larval performance by the fly, Liriomyza sativae, on two different host plants, Via (1984) used a split-family, half-sib, full-sib design to calculate causal components of variance (additive genetic, nonadditive genetic plus maternal effect, and residual environmental) using "the usual theoretical relationships between genetic variance and the observed variance among halfand full-sib families" (p. 885). To remove additive genetic variance from nonadditive genetic plus maternal-effect variance, Via used the equation,
Some notes on the Acquisition of Relative Clauses : New Data and Open Questions

This paper presents new experimental evidence on the relevance of feature mismatch between the head noun and the embedded noun in the comprehension of relative clauses. Exp. 1 shows that number mismatch determines an amelioration of both subjectand object-extracted relatives in English children. Exp. 2 shows that animacy mismatch per se does not play a role in German but 4-year-olds show a frequency effect, which disappears in older children and adults. The implications of these findings for recent approaches to the acquisition of relative clauses are discussed.
Differential Responses of Corticotropin-Releasing Hormone Receptor Type 1 Variants to Protein Kinase C Phosphorylation

Corticotropin-releasing hormone (CRH) regulates diverse biological functions in mammals, through activation of two types of specific G protein-coupled receptors that are expressed as multiple mRNA spliced variants. In most cells, the type 1α CRH receptor (CRH-R1α) preferentially activates the Gs-adenylyl cyclase signaling cascade. CRH-R1α-mediated signaling activity is impaired by insertion of 29 amino acids in the first intracellular loop, a sequence modification that is characteristic of the human-specific CRH-R1β variant. In various tissues, CRH signaling events are regulated by protein kinase C (PKC). The CRH receptors contain multiple putative PKC phosphorylation sites that represent potential targets. To investigate this, we expressed recombinant CRH-R1α or CRH-R1β in human embryonic kidney 293 cells and analyzed signaling events after PKC activation. Agonist (oxytocin) or phorbol 12-myristate 13-acetate-induced activation of PKC led to phosphorylation of both CRH-R1 variants. However, CRH-R1α and CRH-R1β exhibited different functional responses to PKC-induced phosphorylation, with only the CRH-R1β susceptible to cAMP signaling desensitization. This was associated with a significant decrease of accessible CRH-R1β receptors expressed on the cell surface. Both CRH-R1 variants were susceptible to homologous desensitization and internalization following treatment with CRH; however, PKC activation increased internalization of CRH-R1β but not CRH-R1α in a β-arrestin-independent manner. Our findings indicate that CRH-R1α and -R1β exhibit differential responses to PKC-induced phosphorylation, and this might represent an important mechanism for functional regulation of CRH signaling in target cells.
Cluster consensus of discrete-time multi-agent systems with fixed topology

Nowadays, multi-agent systems (MAS) are ubiquitous in the real world. Over the last decade, consensus has been received an increasing attention from various disciplines. This paper aims to further investigate a novel kind of cluster consensus of MAS with several different subgroups and fixed topology. Based on the theories of Markov chains and nonnegative matrix analysis, several cluster consensus criteria were obtained. Moreover, numerical simulations are also given to validate the effectiveness of the proposed cluster consensus criteria.
Towards a Socially Intelligent ECA

Embedding the HCI technology with human preferences and behaviour justifies the attempt of implementing emotional and social intelligence aimed at exceeding the single ability to help the user. In this paper we present an Embodied Conversational Agent’s (ECA’s) architecture and methods useful to interpret the user affective attitude during her dialog with an ECA and behaving ‘believably’in its turn. In particular, we present an agent architecture that is general enough to be applied in several application domains and that can employ several ECA’s bodies according to the context requirements.
A Literacy Exercise: An Extracurricular Reading Program as an Intervention to Enrich Student Reading Habits in Qatar

This paper evaluates an extracurricular reading activity in Qatari schools. The paper presents a two-month extracurricular reading program designed for fourth grade students. The methodology used triangulation of the data to analyze, in detail, the students’ primary perceptions towards reading, teacher self-efficacy, teacher instructional behavior and home literacy measures. The program was implemented in four randomly selected schools. The reading program was announced to each school, and students in the four schools were asked whether they wished to enroll contingent upon receiving parental consent. There were 248 students in the treatment group (students enrolled in the English and Arabic reading program), and 176 students were recruited for the control group (not enrolled in the reading program). The main design was a randomized subjects pretest-posttest control group design and analytical split-plot analysis of variance (ANOVA) design. The findings of this study suggested that students in the reading program demonstrated greater interest in reading than those who did not enroll in the reading program, even when factoring out the effects of parents and home environments. The extracurricular program was significant to the extent that it has improved students’ reading habits. An increase in breadth and depth of such programs shall increase language literacy and numeracy in schools and can improve the school culture towards a more student-teacher interactions and engaging activities.
Cannabidiol inhibits THC-elicited paranoid symptoms and hippocampal-dependent memory impairment

Community-based studies suggest that cannabis products that are high in Δ9-tetrahydrocannabinol (THC) but low in cannabidiol (CBD) are particularly hazardous for mental health. Laboratory-based studies are ideal for clarifying this issue because THC and CBD can be administered in pure form, under controlled conditions. In a between-subjects design, we tested the hypothesis that pre-treatment with CBD inhibited THC-elicited psychosis and cognitive impairment. Healthy participants were randomised to receive oral CBD 600mg (n=22) or placebo (n=26), 210 min ahead of intravenous (IV) THC (1.5 mg). Post-THC, there were lower PANSS positive scores in the CBD group, but this did not reach statistical significance. However, clinically significant positive psychotic symptoms (defined a priori as increases ≥3 points) were less likely in the CBD group compared with the placebo group, odds ratio (OR)=0.22 (χ2=4.74, p<0.05). In agreement, post-THC paranoia, as rated with the State Social Paranoia Scale (SSPS), was less in the CBD group compared with the placebo group (t=2.28, p<0.05). Episodic memory, indexed by scores on the Hopkins Verbal Learning Task-revised (HVLT-R), was poorer, relative to baseline, in the placebo pre-treated group (-10.6±18.9%) compared with the CBD group (-0.4%±9.7 %) (t=2.39, p<0.05). These findings support the idea that high-THC/low-CBD cannabis products are associated with increased risks for mental health.
Orchestrating bacterial cell morphogenesis

MreB proteins are bacterial homologues of actin that directly determine cell shape and are involved in a range of other cellular processes in non‐spherical bacteria. Like F‐actin in eukaryotes, MreBs self‐assemble into dynamic filamentous structures that are essential for cell viability. Recent studies have demonstrated that the MreB cytoskeletal scaffold governs shape determination by controlling functions related to the bacterial cell wall (probably by recruiting and directing peptidoglycan‐synthesizing and modifying proteins). Here I consider general implications for bacterial morphogenesis, and the basis for differences in wall expansion and cylindrical cell shape, based on recent studies aimed to determine the role of MreBs in bacteria with different modes of growth.
UoY: Graphs of Unambiguous Vertices for Word Sense Induction and Disambiguation

This paper presents an unsupervised graph-based method for automatic word sense induction and disambiguation. The innovative part of our method is the assignment of either a word or a word pair to each vertex of the constructed graph. Word senses are induced by clustering the constructed graph. In the disambiguation stage, each induced cluster is scored according to the number of its vertices found in the context of the target word. Our system participated in SemEval-2010 word sense induction and disambiguation task.
A Displacement Driven Real-Time Deformable Model For Haptic Surgery Simulation

We present a deformable graphical model for interactive modeling of three-dimensional objects representing organs and tissues in surgery simulations. The proposed model is a physically-based model, generating real-time deformations using a high resolution triangular surface mesh with minimal pre-processing of mesh data. The surface mesh of an object is modeled by a spring network according to the connectivity of mesh nodes. Object deformations are simulated by computing nodal deformations based on a force equation at each mesh node. A deformed node index table (DNIT) is proposed to model the deformation propagation driven by the displacement at a surface contact point (SCP). Surface nodes that undergo a deformation are added to the current DNIT according to the triangular mesh topology. A PHANToM device is integrated in the simulator to provide haptic feedback. Coupled with the real-time visual feedback generated by the proposed model, the simulator allows users to interactively manipulate virtual organs utilizing the PHANToM device. Results of a virtual kidney biopsy simulation are presented to illustrate the deformations.
Distance-based computational models for facilitating robot interaction with children

Sensing and interpreting the user's activities and social behavior, monitoring the dynamics of the social context, and selecting and producing appropriate robot action are the core challenges involved in using robots as social tools in interaction scenarios. In social human-robot interaction, speech and gesture are the commonly considered interaction modalities. In human-human interactions, interpersonal distance between people can contain significant social and communicative information. Thus, if human-robot interaction reflects this human-human interaction property, then human-robot distances also convey social information. If a robot is to be an effective social agent, its actions, including those relating to interpersonal distance, must be appropriate for the given social situation. This becomes a greater challenge in playful and unstructured interactions, such as those involving children. This paper demonstrates the use of a distance-based model for the recognition and expression of spatial social behavior. The model was designed to classify averse social behavior of a child engaged in playful interaction with a robot and uses distance-based features to autonomously identify interaction/play, avoidance, wall-hugging, and parent-proximity behavior with 94% accuracy. The same methodology was used to model the spatial aspects of a person following a robot and use the model as part of a modified navigation planner to enable the robot to exhibit socially-aware goal-oriented navigation behavior. The model-based planner resulted in robot navigation behavior that was more effective at allowing a partner to follow the robot. This effect was demonstrated using quantitative measures of navigation performance and observer rating of the robot's behavior. These two uses of spatial models were implemented on complete robot systems and validated in evaluation studies with children with autism spectrum disorders and with neurotypical adults.
Parsing Some Constrained Grammar Formalisms

In this paper we present a scheme to extend a recognition algorithm for Context-Free Grammars (CFG) that can be used to derive polynomial-time recognition algorithms for a set of for-malisms that generate a superset of languages generated by CFG. We describe the scheme by developing a Cocke-Kasami-Younger (CKY)-like pure bottom-up recognition algorithm for Linear Indexed Grammars and show how it can be adapted to give algorithms for Tree Adjoining Grammars and Combinatory Categorial Grammars. This is the only polynomial-time recognition algorithm for Combinatory Categorial Grammars that we are aware of.The main contribution of this paper is the general scheme we propose for parsing a variety of formalisms whose derivation process is controlled by an explicit or implicit stack. The ideas presented here can be suitably modified for other parsing styles or used in the generalized framework set out by Lang (1990).
TCP over Second (2.5G) and Third (3G) Generation Wireless Networks

This document describes a profile for optimizing TCP to adapt so that it handles paths including second (2.5G) and third (3G) generation wireless networks. It describes the relevant characteristics of 2.5G and 3G networks, and specific features of example deployments of such networks. It then recommends TCP algorithm choices for nodes known to be starting or ending on such paths, and it also discusses open issues. The configuration options recommended in this document are commonly found in modern TCP stacks, and are widely available standards-track mechanisms that the community considers safe for use on the general Internet.
Fault detection combining interacting multiple model and multiple solution separation for aviation satellite navigation system

In civil aviation applications, satellite failures yield unacceptable positioning errors when using the Global Positioning System (GPS). To ensure the user security, the navigation system has to fulfill stringent performance requirements. Thus, detecting and excluding the faulty GPS measurements is necessary prior to estimating the mobile location. Classical fault detection algorithms based on Kalman filters (KF) are sensitive to the choice of an appropriate motion model for the mobile. To overcome this difficulty, we propose in this paper a new fault detection algorithm wherein the KF are replaced by multiple model algorithms. In this way, both the false alarm rate and the position mean square error are shown to be decreased.
Evaluating a Complex and Uncertain Future

Social systems are emergent complex systems that are prone to uncertainty and change. Complexity and uncertainty increase the difficulty of evaluating for sustainability. However, backcasting from visions of sustainability using indicators that are positively correlated to principles of sustainability allows for congruence and complexity in achieving the vision. This article presents a model of how this can be done using Causal Layered Analysis and the Ecological Framework. Reiterating the evaluation and visioning process allows for indicators to accommodate change while remaining relevant to sustainability principles.