Miracle-dz/UniFAR-FTUs huggingface dataset:
APP mouse models for Alzheimer's disease preclinical studies

Animal models of human diseases that accurately recapitulate clinical pathology are indispensable for understanding molecular mechanisms and advancing preclinical studies. The Alzheimer's disease (AD) research community has historically used first‐generation transgenic (Tg) mouse models that overexpress proteins linked to familial AD (FAD), mutant amyloid precursor protein (APP), or APP and presenilin (PS). These mice exhibit AD pathology, but the overexpression paradigm may cause additional phenotypes unrelated to AD. Second‐generation mouse models contain humanized sequences and clinical mutations in the endogenous mouse App gene. These mice show Aβ accumulation without phenotypes related to overexpression but are not yet a clinical recapitulation of human AD. In this review, we evaluate different APP mouse models of AD, and review recent studies using the second‐generation mice. We advise AD researchers to consider the comparative strengths and limitations of each model against the scientific and therapeutic goal of a prospective preclinical study.
Named Entity Recognition with Bilingual Constraints

Different languages contain complementary cues about entities, which can be used to improve Named Entity Recognition (NER) systems. We propose a method that formulates the problem of exploring such signals on unannotated bilingual text as a simple Integer Linear Program, which encourages entity tags to agree via bilingual constraints. Bilingual NER experiments on the large OntoNotes 4.0 Chinese-English corpus show that the proposed method can improve strong baselines for both Chinese and English. In particular, Chinese performance improves by over 5% absolute F1 score. We can then annotate a large amount of bilingual text (80k sentence pairs) using our method, and add it as uptraining data to the original monolingual NER training corpus. The Chinese model retrained on this new combined dataset outperforms the strong baseline by over 3% F1 score.
Combining Compositionality and Pagerank for the Identification of Semantic Relations between Biomedical Words

The acquisition of semantic resources and relations is an important task for several applications, such as query expansion, information retrieval and extraction, machine translation. However, their validity should also be computed and indicated, especially for automatic systems and applications. We exploit the compositionality based methods for the acquisition of synonymy relations and of indicators of these synonyms. We then apply pagerank-derived algorithm to the obtained semantic graph in order to filter out the acquired synonyms. Evaluation performed with two independent experts indicates that the quality of synonyms is systematically improved by 10 to 15% after their filtering.
Investor Attention and FX Market Volatility

We study the relationship between investors’ active attention, measured by a Google search volume index (SVI), and the dynamics of currency prices. Investor attention is correlated with the trading activities of large FX market participants. Investor attention comoves with contemporaneous FX market volatility and predicts subsequent FX market volatility, after controlling for macroeconomic fundamentals. In addition, investor attention is related to the currency risk premium. Our results suggest that investor attention is a priced source of risk in FX markets.
Fast Approximate Construction of Best Complex Antipodal Spherical Codes

Compressive Sensing (CS) theory states that real-world signals can often be recovered from much fewer measurements than those suggested by the Shannon sampling theorem. Nevertheless, recoverability does not only depend on the signal, but also on the measurement scheme. The measurement matrix should behave as close as possible to an isometry for the signals of interest. Therefore the search for optimal CS measurement matrices of size $m\times n$ translates into the search for a set of $n$ $m$-dimensional vectors with minimal coherence. Best Complex Antipodal Spherical Codes (BCASCs) are known to be optimal in terms of coherence. An iterative algorithm for BCASC generation has been recently proposed that tightly approaches the theoretical lower bound on coherence. Unfortunately, the complexity of each iteration depends quadratically on $m$ and $n$. In this work we propose a modification of the algorithm that allows reducing the quadratic complexity to linear on both $m$ and $n$. Numerical evaluation showed that the proposed approach does not worsen the coherence of the resulting BCASCs. On the contrary, an improvement was observed for large $n$. The reduction of the computational complexity paves the way for using the BCASCs as CS measurement matrices in problems with large $n$. We evaluate the CS performance of the BCASCs for recovering sparse signals. The BCASCs are shown to outperform both complex random matrices and Fourier ensembles as CS measurement matrices, both in terms of coherence and sparse recovery performance, especially for low $m/n$, which is the case of interest in CS.
Personal effectiveness as a function of psychological androgyny

Background: 'Think-manager, think-male' stereotype had lived its age and the time is ripe to give way to a Psychologically Androgynous manager, who is more personally effective. Irrespective of one's sex, he/she possesses both the masculine as well as feminine attributes and practices them as the situation so desires. Material & Method : 350 male management students were categorized under three groups viz. Typically Sex-typed, Androgynous and Undifferentiated by using Bem's Sex-role Inventory (1974). Their Personal Effectiveness scores were obtained using Pareek's Personal Effectiveness Scale(2001). Mean, S.D. , t-ratio and Pearson's Correlation was calculated. Results : Three groups were found to be significantly different in terms of their Personal Effectiveness. Psychologically Androgynous group was found to be most personally effective on the dimensions of self-disclosure, benefit from feedback & perceptiveness or sensitivity to others' feelings. Also, significant correlation existed between Psychological Androgyny and Personal Effectiveness vis-a-vis the other sex-role orientations. Conclusion : Androgynous sex-role orientation predicts personal effectiveness in management students.
Low-Cost High-Tech Robotics for Ambient Assisted Living: From Experiments to a Methodology

Abstract Aging of the population in developed countries is an important challenge to overcome. Robots have a role to play to offer solutions to old and dependent persons and also to their families and carers. We investigated low-cost high-tech robotics in order to offer affordable mobile robots that could be used in the context of ambient assisted living (AAL). We used a bottom–up approach and tried different technical solutions in order to propose an efficient prototype. Results of this experimental work are presented in the first part of this paper. From the different experiments we carried out, we felt the need to use a top–down approach that could be used to develop such robots and also any system that requires the use of mechanical, electronic, and software components. In the second part of this paper, we present the X-methodology and try to show its use in our AAL context.
Comparing Approaches to Integrating Refugee and Asylum-Seeking Healthcare Professionals in Canada and the UK

In this paper, we examine barriers to the integration of refugee doctors and nurses in Canada and the United Kingdom. Key obstacles impeding the integration of internationally trained health professionals are well documented, but less attention has been paid to the integration of refugee health professionals, particularly in Canada. Based on documentary analysis and semi-structured interviews with 46 Canadian and 34 UK stakeholders, our research shows
Von individuellen Wertedilemmata zu gesellschaftlichen Regeln: Möglichkeiten und Notwendigkeiten der Verbindung von Werte- und politischer Bildung

Zusammenfassung Moralische Dilemmata stellen Individuen vor die Entscheidung zwischen wichtigen Werten. Oft stellen solche Dilemmata zugleich die Gesellschaft vor die Aufgabe einer allgemeinen politischen Regelung. Drei didaktische Konsequenzen fur den Unterricht werden in diesem Beitrag mit Beispielen skizziert: Es bedarf einer Phase der Politisierung, als Theoriebezug und Analyseinstrument eignet sich Kohlbergs Stufenmodell, und fur die kooperativ-selbstandige Schulerarbeit wurde die „Moralstufenanalyse“ entwickelt. Die Trennung und Zusammenfuhrung von Moral und Politik finden eine Parallele in der Beziehung von sozialem und politischem Lernen. Schlagworter: Moralisches Dilemma, Individual-Ethik und politische Rahmensetzung, Didaktische Konsequenzen, Moralstufenanalyse, Soziales und politisches Lernen ----- From individual value dilemmas to societal rules: opportunities for a connection between value and political education Abstract Moral dilemmas ask individuals to decide for one side of conflicting values. Often society will or must decide on a political rule to render a general answer. Three didactical consequences for teaching are outlined and demonstrated by examples: Teaching must arrange for a separate phase of political questioning, Kohlberg’s stage model renders a theoretical frame for analyses and was transformed into the instrument of ‘moral-stage-analysis’ for cooperative learning. The relationship of ethics and politics (separation and combination are necessary) is the same as the relationship of social and political learning. Keywords: Moral dilemma, Personal ethics and political framing, Results for teaching, Analyses-bymoral-stages, Social and political learning
The Grammar of Society: The Nature and Dynamics of Social Norms, by Cristina Bicchieri

contradictions. Simplistic class analyses will turn them off, and in any event, don’t actually do much work in explaining the timing and content of neoliberal doctrines. For instance, while there has yet to be written a serious history of the Bank of Sweden Prize in Economic Science, I very much doubt it will be attributed to the class of Swedish corporate heads who “used their control over the Nobel Prize to consolidate neoliberalism within Swedish economic thinking” (p. 113). After all, back then even they felt the need to ‘balance’ the Prize given to Hayek with one to Myrdal; it is only now that such notions strike us as quaint. Returning to our own point of departure, the thing that turns out to be most striking about the MPS is the extent to which the neoliberals imagined their ideal market utopia long before there was much in the way of footsoldiers or patrons poised to carry off their revolution. It was not that disgruntled conservative philosophers and corporate movers and shakers knew precisely what sort of political economy would prove to coincide with their interests; rather, they had to be taught what it was they wanted. Here lies a lesson for all explanations rooted in self-interest.
Integrating Syntactic Priming into an Incremental Probabilistic Parser, with an Application to Psycholinguistic Modeling

The psycholinguistic literature provides evidence for syntactic priming, i.e., the tendency to repeat structures. This paper describes a method for incorporating priming into an incremental probabilistic parser. Three models are compared, which involve priming of rules between sentences, within sentences, and within coordinate structures. These models simulate the reading time advantage for parallel structures found in human data, and also yield a small increase in overall parsing accuracy.
ICP0 enables and monitors the function of D cyclins in herpes simplex virus 1 infected cells

The herpes simplex virus 1 ICP0 is a regulatory protein. Early in infection ICP0 localizes in ND10 bodies and performs two functions: As an E3 ligase in conjunction with E2 UbcH5a conjugating enzyme, it degrades the ND10 components PML and SP100. Concurrently, it suppresses the silencing of viral DNA by dispersing the HDAC1/CoREST/REST/LSD1 repressor complex. Subsequently, ICP0 is exported to the cytoplasm. In cells treated with HDAC inhibitors or transfected with irrelevant DNA, the export is delayed in a DNA dose-dependent fashion. Here, we follow up an observation that ICP0 binds cyclin D3 and that ICP0 mutants unable to bind cyclin D3 are not exported. Moreover, in infected cells cdk4 is activated, but cdk2 is not. We report that (i) cyclin D1, D2, or D3 colocalize with ND10 bodies and ICP0 early in infection and ultimately become incorporated into viral replication compartments, (ii) each of the D cyclins partially rescues ΔICP0 mutants, and (iii) inhibition of cdk4 by inhibitor I sequesters ICP0 in the nucleus. A key finding is that overexpression of cyclin D3 enables the transport of ICP0 to the cytoplasm. We conclude that (i) ICP0 facilitates the recruitment of cyclin D3 to the sites of viral DNA synthesis, (ii) until its functions are completed, ICP0 is retained in the nucleus, and (iii) a common signal that results in the export of ICP0 to the cytoplasm is the accumulation of a viral DNA-synthesis-dependent late protein.
A Vascular Model of Tsc1 Deficiency Accelerates Renal Tumor Formation with Accompanying Hemangiosarcomas

Tuberous sclerosis complex (TSC) is an autosomal disease caused by inactivating mutations in either of the tumor suppressor genes TSC1 or TSC2. TSC-associated tumor growth is present in multiple tissues and organs including brain, kidney, liver, heart, lungs, and skin. In the kidney, TSC angiomyolipomas have aberrant vascular structures with abnormal endothelial cells, suggesting a role for endothelial mTORC1 function. In the current report, a genetically engineered mouse model (GEMM) with a conditional knockout allele of Tsc1 with a Darpp32-Cre allele displayed accelerated formation of both kidney cystadenomas and paw hemangiosarcomas. All mutant mice developed hemangiosarcomas on multiple paws by 6 weeks of age. By 16 weeks of age, the average mutant hind paw was 4.0 mm in diameter, nearly double the size of control mice. Furthermore, the hemangiosarcomas and kidney cystadenomas were responsive to intraperitoneal rapamycin treatment. Immunoblotting and immunostaining for phospho-S6 (pS6) and phospho-CAD showed that the effect of rapamycin on tumor size was through inhibition of the mTOR signaling pathway. Finally, elevated VEGF mRNA levels were also observed in hemangiosarcoma specimens. Because paw hemangiosarcomas are easily detectable and scorable for size and growth, this novel mouse model enables accelerated in vivo drug testing for therapies of TSC-related tumors. Implications: These findings provide a strong rationale for simultaneous use of this conditional knockout mouse as an in vivo genetic model while seeking new cancer therapies for TSC-related tumors. Mol Cancer Res; 13(3); 548–55. ©2014 AACR.
A distributed time synchronization algorithm robust to traffic load for MANETs

As in wired network, time synchronization is also important for MANETs specially to support quality of service (QoS). It becomes extremely difficult in IEEE 802.11 DCF based MANETs due to the lack of predefined network infrastructure and dedicated control channel. We propose a distributed time synchronization algorithm (DTSR) for MANETs which is robust to traffic load variations. To achieve accurate synchronization, we evaluate initial time synchronization procedure, clock offset and drift estimation, and update conditions. When update conditions are not satisfied time synchronization is updated by assumption update. DTSR is implemented and tested on IEEE 802.11b based wireless testbed running on Linux operating system. The accuracy of algorithm is evaluated with and without traffic load condition. Test results show DTSR is suitable for time synchronization in MANETs and to measure end-to-end packet delay for QoS sensitive applications such as VoIP.
Making distinctiveness models of memory distinct

Roddy is well known for many different contributions to experimental psychology in general and to the study of memory in particular. Although not usually thought of as a modeler, he is well known for his SPAM ("Sponge Associative Memory") model. Given the distinctive nature of that model, we thought a history of distinctiveness models of memory, in which we describe, compare, and contrast different formulations of distinctiveness, would be an appropriate contribution to this volume in his honor.
From Sensors to Spikes: Evolving Receptive Fields to Enhance Sensorimotor Information in a Robot-Arm

In biological systems, instead of actual encoders at different joints, proprioception signals are acquired through distributed receptive fields. In robotics, a single and accurate sensor output per link (encoder) is commonly used to track the position and the velocity. Interfacing bio-inspired control systems with spiking neural networks emulating the cerebellum with conventional robots is not a straight forward task. Therefore, it is necessary to adapt this one-dimensional measure (encoder output) into a multidimensional space (inputs for a spiking neural network) to connect, for instance, the spiking cerebellar architecture; i.e. a translation from an analog space into a distributed population coding in terms of spikes. This paper analyzes how evolved receptive fields (optimized towards information transmission) can efficiently generate a sensorimotor representation that facilitates its discrimination from other "sensorimotor states". This can be seen as an abstraction of the Cuneate Nucleus (CN) functionality in a robot-arm scenario. We model the CN as a spiking neuron population coding in time according to the response of mechanoreceptors during a multi-joint movement in a robot joint space. An encoding scheme that takes into account the relative spiking time of the signals propagating from peripheral nerve fibers to second-order somatosensory neurons is proposed. Due to the enormous number of possible encodings, we have applied an evolutionary algorithm to evolve the sensory receptive field representation from random to optimized encoding. Following the nature-inspired analogy, evolved configurations have shown to outperform simple hand-tuned configurations and other homogenized configurations based on the solution provided by the optimization engine (evolutionary algorithm). We have used artificial evolutionary engines as the optimization tool to circumvent nonlinearity responses in receptive fields.
Table of Contents Storyline Detection and Tracking Using Dynamic Latent Dirichlet Allocation Richer Event Description: Integrating Event Coreference with Temporal, Causal and Bridging Annotation Workshop Program Bridging the Gap between Event Macro-structures and Event Micro-structures Storyline Det

at the heart of information sharing. Ever since people began to share their experiences, they have connected them to form narratives. The study of storytelling and the field of literary theory called narratology have developed complex frameworks and models related to various aspects of narrative such as plots structures, narrative embeddings, characters' perspectives, reader response, point of view, narrative voice, narrative goals, and many others. These notions from narratology have been applied mainly in Artificial Intelligence and to model formal semantic approaches to narratives (e.g. Plot Units developed by Lehnert (1981)). In recent years, computational narratology has qualified as an autonomous field of study and research. Narrative has been the focus of a number of workshops and conferences (AAAI Symposia, Interactive Storytelling Conference (ICIDS), Computational Models of Narrative). Furthermore, reference annotation schemes for narratives have been proposed (NarrativeML by Mani (2013)). The workshop aims to bring together researchers from different communities working on representing and extracting narrative structures in news, a text genre popular in NLP research but which has received little attention in research into narrative structure, representation and analysis. Current advances in NLP technology have made it possible to look beyond scenario-driven, atomic extraction of events from single documents and work towards extracting story structures from multiple documents, while these documents are published over time as news streams. Policy makers and information specialists are increasingly in need of tools that support them in finding salient stories in large amounts of information to more effectively implement policies, monitor actions of " big players " in society and check facts. Their tasks often revolve around reconstructing cases either with respect to specific entities (e.g. person or organisations) or events (e.g. the 2016 presidential elections). Storylines represent explanatory schemas that enable us to make better selections of relevant information but also projections for the future. They constitute a huge potential for exploiting news data in an innovative way. Of the 14 submissions we received, 8 were accepted that touch upon different aspects of narrative research in news. Three contributions describe approaches to detect storylines either from news (Brüggermann et al.), from Tweets (Krishnan and Eisenstein), or from news but with metadata added via Twitter (Poghosyan and Ifrim). Besides detecting storylines, different aspects of storylines such as diegesis and point of view are also addressed (Eisenberg and Finlayson). The second topic that is addressed is annotation and representation of storylines (Caselli and …
A New Subpixel Imaging Method for Image Super Resolution

The subpixel imaging technique for image super resolution can get a higher resolution image from two low resolution images which are observed from two linear array CCDs staggered half pixel both along the flight direction and perpendicular direction. In this paper, an adaptive weight interpolation method which considers the Euclidean distance information from two low resolution images for different size interpolation window is proposed. Compared with the traditional interpolation method, the experiment results show the effectiveness of the proposed method.
Collective intelligence for control of distributed dynamical systems

We consider the El Farol bar problem, also known as the minority game (W. B. Arthur, The American Economic Review, 84 (1994) 406; D. Challet and Y. C. Zhang, Physica A, 256 (1998) 514). We view it as an instance of the general problem of how to configure the nodal elements of a distributed dynamical system so that they do not “work at cross purposes”, in that their collective dynamics avoids frustration and thereby achieves a provided global goal. We summarize a mathematical theory for such configuration applicable when (as in the bar problem) the global goal can be expressed as minimizing a global energy function and the nodes can be expressed as minimizers of local free energy functions. We show that a system designed with that theory performs nearly optimally for the bar problem.