Miracle-dz/UniFAR-FTUs huggingface dataset:
The Isolation Time of Poisson Brownian Motions

Let the nodes of a Poisson point process move independently in R^d according to Brownian motions. We study the isolation time for a target particle that is placed at the origin, namely how long it takes until there is no node of the Poisson point process within distance r of it. In the case when the target particle does not move, we obtain asymptotics for the tail probability which are tight up to constants in the exponent in dimension d ≥ 3 and tight up to logarithmic factors in the exponent for dimensions d = 1, 2. In the case when the target particle is allowed to move independently of the Poisson point process, we show that the best strategy for the target to avoid isolation is to stay put.
Extracting the Science from Scientific Publications

This is an edited version of the original project proposal. This proposal is for a collaboration between three groups in Cambridge. The Computer Laboratory (CL) group provides expertise in Natural Language Processing (NLP), the Chemistry group brings in a user-base as well as experience in application of NLP technology to eScience goals, while the Cambridge eScience Centre (CesC) will ensure scalability and integration of the technology. The project also involves three publishers as partners, who will support the project by supplying large corpora of scientific papers, providing informal feedback and facilitating dissemination activities: the Royal Society of Chemistry, Nature Publishing Group and the International Union of Crystallography. Project objectives:
Telomerase Activity in Cervical Smears

It is well known that almost all carcinoma cells including those of the uterine cervix have re‐established their telomerase activity. However, until now there is no conclusive picture on the telomerase activity in cervical dysplasias and about their relationship to HPV infection. To investigate this question, material from 34 patients (15 with normal epithelium, 11 with LGSIL, 8 with HGSIL) obtained by conventional cervical brushing was used and subjected to non‐radioactive TRAP‐ELISA (Boehringer Mannheim). The HPV analysis was performed by PCR on formalin‐fixed, paraffin‐embedded biopsy material obtained after cytological investigation. We could show that telomerase activity is detectable in normal cervical epithelium, and that an gradual increase exists for both telomerase activity and HPV positivity from normal epithelium to HGSIL. However, HPV infection and telomerase activity appear to be independent of each other. The high frequency of telomerase positivity in patients with normal cervical epithelium indicates that telomerase activity is not a useful differential diagnostic aid. Whether patients with telomerase‐positive dysplasias have a higher probability to progress into an invasive carcinoma remains to be clarified by follow‐up studies.
Learning From Observation and Practice Using Behavioral Primitives : Marble Maze

We explore how to enable robots to rapidly learn from watching a human or robot perform a task, and from practicing the task itself. A key component of our approach is to use small units of behavior, which we refer to as behavioral primitives. Another key component is to use the observed human behavior to define the space to be explored during learning from practice. In this paper we manually define task appropriate primitives by programming how to find them in the training data. We describe memory-based approaches to learning how to select, provide subgoals for, and perform behavioral primitives. We demonstrate both learning from observation and learning from practice on a marble maze task, Labyrinth. Using behavioral primitives greatly speeds up learning relative to learning using a direct mapping from states to actions.
Conditionning , halting criteria and choosing λ

We show the convergence of 1+λ-ES with standard step-size update-rules on a large family of fitness functions without any convexity assumption or quasi-convexity assumptions ([5, 6]). The result provides a rule for choosing λ and shows the consistency of halting criteria based on thresholds on the step-size. The family of functions under work is defined through a conditionnumber that generalizes usual condition-numbers in a manner that only depends on level-sets. We consider that the definition of this conditionnumber is the relevant one for evolutionary algorithms; in particular, global convergence results without convexity or quasi-convexity assumptions are proved when this condition-number is finite.
Voter and Politician Response to Political Communication in Sierra Leone Kelly Bidwell

Candidate debates have a rich history, offer a unique communication forum, and have become integral to contemporary campaign strategy. There is, however, no definitive evidence of whether they affect actual voting behavior. The relative scarcity of political information in the developing world offers an attractive testing ground, where the effects of debates could be larger and more directly linked to electoral outcomes. We experimentally manipulate citizen exposure to debates in Sierra Leone to measure their impacts on, and the interconnections among, voter behavior, campaign spending, and the performance of elected politicians. We find positive impacts on citizen political knowledge, policy alignment, openness to candidates, and votes cast on Election Day. We then document an endogenous response by participating candidates, who increased campaign expenditure in communities where debate videos were screened in large public gatherings. Over the longer term, we find that debate participation enhanced the subsequent accountability of elected Parliamentarians, who demonstrated greater constituency engagement and development expenditure over their first year in offi ce. To explore mechanisms, individual treatments disentangle the effects of general political knowledge from the information conveyed about candidate persona, and find that both matter. The results speak to the central political economy question of whether elections effectively discipline politicians, and show how political communication—via interparty debates—can trigger a chain of events that ultimately influences policy. JEL codes D72, D83, O17. [Total words 14,884] ∗Corresponding author: 655 Knight Way, Stanford CA 94305, +1 650 725 2167, kecasey@stanford.edu. We thank Ambrose James and Search for Common Ground, Innovations for Poverty Action and their Freetown team, the National Electoral Commission of Sierra Leone, and members of our expert panel for their collaboration. We are grateful for comments from Laurent Bouton, Steve Callander, Pascaline Dupas, Thomas Fujiwara, Maggie Penn, Cyrus Samii, Francesco Trebbi, Barry Weingast, and especially Melissa Dell in her discussion at NBER. We thank Allyson Barnett, Fatu Emilia Conteh, Nick Eubank, Abdulai Kandeh, Agnes Lahai, Osman Nabay, Isaac Nwokocha, Katie Parry, and Catherine Wright for excellent research assistance. Seminar participants at Bristol University, Center for Effective Global Action, Experiments in Governance and Politics, International Growth Centre (IGC) Growth Week, NBER Summer Institute, Political Institutions and Economic Policy Conference at Princeton, Stanford GSB, University of British Columbia, University of California Berkeley, University of Michigan, Wellesley, and the Working Group on African Political Economy provided insightful comments. We gratefully acknowledge financial support from the Governance Initiative at J-PAL, the IGC, NBER, and Stanford Institute for Innovation in Developing Economies. All errors are our own.
Embedded Implicatures as Pragmatic Inferences under Compositional Lexical Uncertainty

How do comprehenders reason about pragmatically ambiguous scalar terms like some in complex syntactic contexts? In many pragmatic theories of conversational implicature, local exhaustification of such terms (‘only some’) is predicted to be difficult or impossible if the result does not entail the literal meaning, whereas grammatical accounts predict such construals to be robustly available. Recent experimental evidence supports the salience of these local enrichments, but the grammatical theories that have been argued to account for this evidence do not provide explicit mechanisms for weighting such construals against others. We propose a probabilistic model that combines previous work on pragmatic inference under ‘lexical uncertainty’ with a more detailed model of compositional semantics. We show that this model makes accurate predictions about new experimental data on embedded implicatures in both non-monotonic and downward-entailing semantic contexts. In addition, the model’s predictions can be improved by the incorporation of neo-Gricean hypotheses about lexical alternatives. This work thus contributes to a synthesis of grammatical and probabilistic views on pragmatic inference.
Loss of phospholipase D2 impairs VEGF-induced angiogenesis

Vascular endothelial growth factor (VEGF) is a key mediator of angiogenesis and critical for normal embryonic development and repair of pathophysiological conditions in adults. Although phospholipase D (PLD) activity has been implicated in angiogenic processes, its role in VEGF signaling during angiogenesis in mammals is unclear. Here, we found that silencing of PLD2 by siRNA blocked VEGF-mediated signaling in immortalized human umbilical vein endothelial cells (iHUVECs). Also, VEGF-induced endothelial cell survival, proliferation, migration, and tube formation were inhibited by PLD2 silencing. Furthermore, while Pld2-knockout mice exhibited normal development, loss of PLD2 inhibited VEGF-mediated ex vivo angiogenesis. These findings suggest that PLD2 functions as a key mediator in the VEGF-mediated angiogenic functions of endothelial cells. [BMB Reports 2016; 49(3): 191-196]
Access method concurrency with recovery

Providing high concurrency in B+-trees has been studied extensively. But few efforts have been documented for combining concurrency methods with a recovery scheme that preserves well-formed trees across system crashes. We describe an approach for this that works for a class of index trees that is a generalization of the Blink-tree. A major feature of our method is that it works with a range of different recovery methods. It achieves this by decomposing structure changes in an index tree into a sequence of atomic actions, each one leaving the tree well-formed and each working on a separate level of the tree. All atomic actions on levels of the tree above the leaf level are independent of database transactions, and so are of short duration.
Influence of the Direction of Elemental Luminance Gradients on the Responses of V4 Cells to Textured Surfaces

The texture of an object provides important cues for its recognition; however, little is known about the neural representation of texture. To investigate the representation of texture in the visual cortex, we recorded single-cell activities in area V4 of macaque monkeys. To distinguish the sensitivity of the cells to texture parameters such as density and element size from that to spatial frequency, we used texture stimuli mimicking shaded granular surfaces. We varied the size and density of the texture elements and the direction of elemental luminance gradients (apparent shadings) as stimulus parameters. Most macaque V4 cells (151 of 170; 89%) exhibited sensitivity to the texture parameters. Interestingly, 21of these cells were tuned to single shading directions (unidirectional tuning). This unidirectional tuning cannot be explained by complex-cell-like tuning for spectral power of spatial frequency, because texture stimuli with a shading direction and its opposite have almost the same spectral power. Unidirectional tunings of these cells were invariant for the position of the texture elements. Thus, this tuning cannot be explained by simple-cell-like phase-dependent spatial frequency tuning or selectivity to a particular arrangement of the elements. Moreover, the unidirectional tuning had a bias toward vertical directions, consistent with an anisotropy in the perception of three-dimensional shape from shading. This novel spatial property suggests that V4 cells are involved in extracting texture features from objects, including their three-dimensionality.
An Image Retrieval Interface Based On Dynamic Knowledge

Focus of this work is the presentation of an interface for an image retrieval system that makes users aware of the overall organization of the image database. The main features of this system are the multi-images query approach and the use of a dynamic knowledge base in order to improve the system performances. The multi-images query is utilized because often a single image does not fully cover the semantic query idea of the user, so, this work presents a system that allows the user to submit multi query images. Another relevant feature of the proposed system is the use of a dynamic knowledge based approach. This knowledge base is composed of two sets of clusters: the first one is obtained with an automatic clustering algorithm and the second one is built dynamically by the user when using the system. The results presented in this paper demonstrate that this approach provides accurate retrieval results showing acceptable interaction speed that can be compared with existing methods
A Web entity activity recognition approach based on k-nearest neighbors classifier

Based on the traditional information extraction, this paper puts forward an approach to recognizing entity activity form Web. Entity activity which describes the behaviour or action information about the entity is valuable to recognize for search engine, business intelligence, data integration and so on. Since Web entity activities, as multi-relationships, are contained in unstructured text in the Web, recognizing entity activities is a difficult problem in current information extraction area. In this paper, we rigorously define the recognition task firstly and propose a novel recognition framework to extract entity activities form Web. Firstly, this paper proposes a k-nearest neighbors classifier based on sentence similarity to discover the sentences which contain web entity activity. Then, according to dependency parsing feature, we use a set of heuristic rules to extract the information from sentences. Experimental results demonstrate the feasibility and effectiveness of our proposed approach and it can adapt to multi-domains.
Lemmatising Serbian as Category Tagging with Bidirectional Sequence Classification

We present a novel tool for morphological analysis of Serbian, which is a low-resource language with rich morphology. Our tool produces lemmatisation and morphological analysis reaching accuracy that is considerably higher compared to the existing alternative tools: 83.6% relative error reduction on lemmatisation and 8.1% relative error reduction on morphological analysis. The system is trained on a small manually annotated corpus with an approach based on Bidirectional Sequence Classification and Guided Learning techniques, which have recently been adapted with success to a broad set of NLP tagging tasks. In the system presented in this paper, this general approach to tagging is applied to the lemmatisation task for the first time thanks to our novel formulation of lemmatisation as a category tagging task. We show that learning lemmatisation rules from annotated corpus and integrating the context information in the process of morphological analysis provides a state-of-the-art performance despite the lack of resources. The proposed system can be used via a web GUI that deploys its best scoring configuration
Further Steps Towards a Standard Testbed for Optical Music Recognition

Evaluating Optical Music Recognition (OMR) is notoriously difﬁcult and automated end-to-end OMR evaluation metrics are not available to guide development. In “To-wards a Standard Testbed for Optical Music Recognition: Deﬁnitions, Metrics, and Page Images”, Byrd and Simon-sen recently stress that a benchmarking standard is needed in the OMR community, both with regards to data and evaluation metrics. We build on their analysis and definitions and present a prototype of an OMR benchmark. We do not, however, presume to present a complete so-lution to the complex problem of OMR benchmarking. Our contributions are: (a) an attempt to deﬁne a multi-level OMR benchmark dataset and a practical prototype implementation for both printed and handwritten scores, (b) a corpus-based methodology for assessing automated evaluation metrics, and an underlying corpus of over 1000 qualiﬁed relative cost-to-correct judgments. We then assess several straightforward automated MusicXML evaluation metrics against this corpus to establish a baseline over which further metrics can improve.
Worst-case to average-case reductions based on Gaussian measures

We show that solving modular linear equation on the average is at least as hard as approximating several lattice problems in the worst case within a factor almost linear in the rank of the lattice. The lattice problems we consider are the shortest vector problem, the shortest independent vectors problem and the covering radius problem. The approximation factor we obtain is O(n) for all three problems. This greatly improves on all previous work on the subject starting from Ajtai's seminal paper (STOC, 1996), up to the strongest previously known results by Micciancio (STOC, 2002). Our results also bring us closer to the limit where the problems are no longer known to be in NP /spl cap/ coNP. Our main tools are Gaussian measures on lattices and the high dimensional Fourier transform. We start by defining a new lattice parameter which determines the amount of Gaussian noise that one has to add to a lattice in order to get close to a uniform distribution, in addition to yielding quantitatively much stronger results, the use of this parameter allows us to simplify many of the complications in previous work. Our technical contributions are two-fold. First, we show tight connections between this new parameter and existing lattice parameters. One such important connection is between this parameter and the length of the shortest set of linearly independent vectors. Second, we prove that the distribution that one obtains after adding Gaussian noise to the lattice has the following interesting property: the distribution of the noise vector when conditioning on the final value behaves in many respects like the original Gaussian noise vector. In particular, its moments remain essentially unchanged.
Robust Formation Adaptation for Mobile Platforms with Noisy Sensor Information

In this paper stability and formation adaptation of mobile multi-agent systems with limited sensor information is studied. A globally stable control for line formations with varying separations and bearing angles between the agents is evaluated in simulations and experiments with Khepera robots. The control algorithm only requires information available from on-board sensors, although stability is improved if communication and sharing of information between the agents is possible. In addition, the control only needs a coarse estimation of the actual target speed
Digital Inpainting on the Basis of Exemplar Based Method

— Digital image inpainting refers to a technique used for ﬁlling in the missing or corrupted regions of an image using information from the surrounding area. Inpainting techniques have found widespread use in applications that include, but are not limited to error recovery, red-eye removal, multimedia editing. This paper will discuss inpainting techniques in the context of digital artwork restoration. Notwithstanding the potentially different approaches, the goal of any digital image inpainting algorithm is to reconstruct the missing or damaged regions in a visually plausible way.
DECENTRALIZED COORDINATION WITH CRASH FAILURES

ACKNOWLEDGMENTS I thank my adviser, Professor Gul Agha, and the members of the Open Systems Laboratory for supporting my work with their time, resources and ideas. The study described in this thesis is a continuation of a project done in collaboration with Together we built all the infrastructure used in developing this thesis, I have made only relatively small improvements. Since the original project ended several conversations with Amr and Predrag Tosic have been fruitful. Myeong-Wuk Jang generously found time for me to run my own experiments when his computers were idle. I also acknowledge the unceasing moral and grammatical support of Stephanie Jensen.
Manuscript in preparation : I . Aging in Rats Promotes Alzheimer ’ s Disease β-amyloid Aggregation and Toxicity by Metallostasis of Extraneuronal Zinc

IV. A novel and simple fluorescence method for the measurement of presynaptic vesicular zinc release in acute hippocampal slices with a fluorescence plate reader. II. Membrane-lipid therapy in operation: the Hsp co-inducer BGP-15 activates stress signal transduction pathways by remodeling plasma membrane rafts. III. Hydroximic acid derivatives: pleiotrophic Hsp co-inducers restoring homeostasis and robustness. Abbreviations αSN Alpha-synuclein protein Aβ Amyloid-beta peptide ACSF Artificial cerebrospinal fluid AD Alzheimer " s disease ADDLs Aβ-derived diffusible ligands APP Amyloid precursor protein ASPD Native-amylospheroids BCA Bicinchoninic acid CDK5 Cyclin-dependent kinase 5 DLBD Diffuse Lewy body disease DMSO Dimethyl-sulfoxide DNP 2,4-dinitrophenol FBS Fetal bovine serum fEPSP Field excitatory postsynaptic potentials GSK-3β Glycogen synthase kinase 3 beta HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid LBD Lewy body diseases LBV Lewy body variant of Alzheimer " s disease LDH Lactate dehydrogenase LTP Long-term potentiation MAP Microtubule associated protein MEM Minimal essential medium NAC Non-amyloid component of Alzheimer " s disease amyloid NACP NAC precursor = alpha-synuclein NFTs Neurofibrillary tangles NMDA N-methyl-D-aspartate NMDAR N-methyl-D-aspartate receptor NR2B Subunit of NMDAR PBS Phosphate buffered saline PD Parkinson " s disease PI Propidium iodide PP-1 Protein phosphatase 1 PP-2A Protein phosphatase 2A RT Room temperature SDS-PAGE Sodium dodecyl sulphate-polyacrylamide gel electrophoresis SEM Standard error of mean TBS Theta-burst stimulation TEM Transmission electron microscopy upH 2 O MilliQ ultrapure water ZEN Zinc-enriched neuron ZnT Zinc transporter Alzheimer " s disease (AD) is a heterogeneous, progressive neurodegenerative disorder representing the most common cause of cognitive failure and dementia in older human patients. Extracellular deposition of beta amyloid peptide, intracellular formation of neurofibrillar tangles (NFT) caused by hyperphosphorylated tau protein and oxidative stress induced by impaired metabolic pathways and metals are the hallmarks of the disease primary theory for the cause of AD is the overproduction and/or impaired clearance of amyloid-beta (Aβ) peptides derived from amyloid precursor protein (APP), especially the The secondary hypothesis is the " metal hypothesis " which proposes the interaction of Aβ with specific metal ions that could enhance Aβ aggregation, pathogenicity and finally cause Brain tissues of AD patients after autopsy contain two main characteristic lesions: extracellular amyloid plaques and intracellular neurofibrillary tangles which are formed by hyperphosphorylated tau protein (Goedert and Crowther, 1989, Selkoe, 2003). There are two main forms of amyloid depositions: senile (or neuritic) and diffuse plaques. Senile plaques (originally observed by Alois Alzheimer) are extracellular spherical structures around 50–200 µm in diameter which contain a central amyloid core enriched …