Miracle-dz/UniFAR-FTUs huggingface dataset:
Insights into early molluscan neuronal development through studies of transmitter phenotypes in embryonic pond snails

Pond snails have long been the subject of intense scrutiny by researchers interested in general principles of development and also cellular and molecular neurobiology. Recent work has exploited both these fields of study by examining the ontogeny of the nervous system in these animals. Much of this work has focussed upon the development of specific transmitter phenotypes to provide vignettes of neuronal subpopulations that can be traced from early embryonic life through to adulthood. While such studies have generally confirmed previous explanations of gangliogenesis in gastropods, they have also indicated the presence of several neurons that appear earlier and in positions inconsistent with classical views of gastropods neurogenesis. The earliest of these cells contain FMRFamide‐related peptides and have anteriorly projections that mark the future locations of ganglia and interconnecting pathways that will comprise the postembryonic central nervous system. These posterior, peptidergic cells, as well as certain, apical, monoaminergic neurons, disappear and apparently die near the end of embryonic life. Finally, populations of what appear to be peripheral sensory neurons begin to express catecholamines by around midway through embryonic life. Like several of the neurons expressing a variety of transmitters in the developing central ganglia, the catecholaminergic peripheral cells persist into postembryonic life. Transmitter phenotypes, cell shapes and locations, and neuritic morphologies all suggest that many of the neurons observed in early embryonic pond snails have recognizable homologues across the molluscs. Such observations have profoundly altered our views of neurogenesis in gastropods over the last few years. They also suggest the promise for pond snails as fruitful models for studying the roles and mechanisms for pioneering fibres, cues triggering apoptosis, and contrasting origins and mechanisms employed for generating central vs. peripheral neurons within a single organism. Microsc. Res. Tech. 49:570–578, 2000. © 2000 Wiley‐Liss, Inc.
CALENDAR EFFECTS IN DAILY BOND RETURNS: CASE OF SELECTED EMERGING ECONOMIES by Mykhailo Bespalko A thesis submitted in partial fulfillment of the requirements for the degree of MA in Economics

This thesis investigates the existence of calendar effects on the bond market of selected emerging countries and conducts comparative analysis of these effects on the stock and bond markets. The empirical analysis for the bond markets show clear signs of Tuesday effect for most countries. This fact was confirmed by regression on dummies and bootstrap analysis. At the same time, stock market shows no evidence for any day-of-the-week-effect as a result of application of mentioned methods. Day-of-the-month effect, on the other hand, was found significant for both stock and bond markets: returns for the end of the month are higher than for the rest of the month. As it was expected the size of this effect was bigger for the stock market as equity is associated with higher risk.
Parametric study on the dielectric properties of biological tissues

A good comprehensive study of the electromagnetic properties of biological layers is important since we cannot discuss an implantable antenna design without investigating the interaction of electromagnetic radiation with the tissue. The human body is not an ideal medium for the transmission of radio waves which can be considered as a barrier degrading the performance of the transmission system that uses the human body as a propagation channel. This paper deals with some notions of electromagnetic characteristics of body tissues and their dependency to the frequency.
Look mother, virtual puzzling without buttons!

Not many virtual 3D puzzle applications have been researched. We present a solution using tangible objects and a reach-in set-up. The user can solve a puzzle using natural and tangible interaction. To provide realistic interaction, the usage of buttons was avoided by design. In a user experiment the solution proved to be natural and intuitive.
Aural Imaging from 3 D Vision by Jasper Fourways Vicenti

Dense stereo maps have many useful applications in computer vision. They can help in performing such tasks as background separation, segmentation, and object recognition. Despite the continued exponential advances in the computational capacity of microprocessors, current personal computers are limited in their ability to adequately solve the dense stereo vision problem in realtime. Modern processors now contain a SIMD instruction set architecture that can provide substantial improvements in performance when working with specific data types. This program demonstrates a stereo vision algorithm that implements commonly known methods in computer vision and takes advantage of the Altivec instruction set to achieve realtime performance. Once the stereo data has been processed, the depth map that is produced can be used to provide an additional dimension of data to the user. The software demonstrates a possible use for this data, as an aural aid to people that are blind or vision impaired. The system uses the depth information to identify obstacles in a user's path and alert the user with aural feedback. Thesis Supervisor: David Demirdjian Title: Research Scientist
Sentiment analysis of twitter data using machine learning approaches and semantic analysis

The wide spread of World Wide Web has brought a new way of expressing the sentiments of individuals. It is also a medium with a huge amount of information where users can view the opinion of other users that are classified into different sentiment classes and are increasingly growing as a key factor in decision making. This paper contributes to the sentiment analysis for customers' review classification which is helpful to analyze the information in the form of the number of tweets where opinions are highly unstructured and are either positive or negative, or somewhere in between of these two. For this we first pre-processed the dataset, after that extracted the adjective from the dataset that have some meaning which is called feature vector, then selected the feature vector list and thereafter applied machine learning based classification algorithms namely: Naive Bayes, Maximum entropy and SVM along with the Semantic Orientation based WordNet which extracts synonyms and similarity for the content feature. Finally we measured the performance of classifier in terms of recall, precision and accuracy.
Pro-p groups and towers of rational homology spheres

In the preceding paper, Calegari and Dunfield exhibit a sequence of hyperbolic 3-manifolds which have increasing injectivity radius, and which, subject to some conjectures in number theory, are rational homology spheres. We prove unconditionally that these manifolds are rational homology spheres, and give a sufficient condition for a tower of hyperbolic 3-manifolds to have first Betti number 0 at each level. The methods involved are purely pro-p group theoretical.
Area change detection in river mouthbars at the Mekong River delta using Synthetic Aperture Radar (SAR) data

We propose the use of SAR (Synthetic Aperture Radar) backscatter intensity data as a tool for monitoring coast. ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band SAR) data are analyzed to investigate the temporal changes in shape and area of mouthbars in the Mekong River distributaries. River mouthbars with strong backscatter, which is surrounded by the water, are successfully extracted using a histogram thresholding algorithm. Estimated areas of river mouthbars gradually increase on an annual time scale. Seasonal variations of areas were also recognized, and they appear to be related to the mean monthly sea level, discharge, and rainfall. Moreover, it is highly likely that tidal height at the time of SAR data acquisition clearly reflect the area of river mouthbar by examining over half-day intervals for ascending and descending images. This study shows that if appropriately calibrated, the SAR data is useful to quantifying long-term changes in river mouthbar.
SERP: Scalable Efficient Reservation Protocol for the Future Internet

The fast Internet growth has led to high demands requiring QoS provisioning mechanism to be implemented in the future Internet. This paper presents the development and implementation of a resource reservation scheme to allocate and manage resource in the future internet. We propose a scalable efficient reservation protocol (SERP) to efficiently allocate and manage resources in the future Internet. SERP takes into consideration the fact that the future Internet will accommodate both real time and non real time applications. Relevant design goals and principles were identified and these led to a formulation of a corresponding model. Simulation of the model was conducted to evaluate the performance of the developed scheme. The experimental results do show that SERP reduces the router load with less states information to be maintained. Use of aggregate-based reservation further reduces states information. Consequently SERP improves scalability. Results further demonstrate that request acceptance probability is high and more connections are established for end-to-end reservation.
Study on High Gain Patch Antenna with Metamaterial Cover

A new method to improve the gain of patch antenna with metamaterial composed of ring aperture lattice is presented. A comparison between the conventional patch antenna and the new metamaterial patch antenna is given. The experimental results show that this method is effective and metamaterial structure can realize congregating the radiation energy, so the gain of the antenna with metamaterial can greatly increase compared with the conventional one.
The Diagnosis and Treatment of Pseudoprogression, Radiation Necrosis and Brain Tumor Recurrence

Radiation therapy is an important modality used in the treatment of patients with brain metastatic disease and malignant gliomas. Post-treatment surveillance often involves serial magnetic resonance imaging. A challenge faced by clinicians is in the diagnosis and management of a suspicious gadolinium-enhancing lesion found on imaging. The suspicious lesion may represent post-treatment radiation effects (PTRE) such as pseudoprogression, radiation necrosis or tumor recurrence. Significant progress has been made in diagnostic imaging modalities to assist in differentiating these entities. Surgical and medical interventions have also been developed to treat PTRE. In this review, we discuss the pathophysiology, clinical presentation, diagnostic imaging modalities and provide an algorithm for the management of pseudoprogression, radiation necrosis and tumor recurrence.
Building reliable programs in a replicated environment using remote procedure calls

This paper addresses the problem of building reliable computing programs over unreliable remote procedure call (RPC) systems by using replication and transaction techniques. We rst establish the computation model: the RPC transactions. Based on this RPC transaction model, we present the design of our system for managing RPC transactions in the replicated-server environment. Finally we present some results of a correctness study on the system and an application example
Réformes et innovations comptables dans le secteur public local malgache – Etude des conditions de développement et d'adoption d'un système d'information simplifié

Dans les annees 1990, le processus de decentralisation malgache a connu une evolution telle qu'il a ete important pour les autorites de l'epoque de proceder a une serie de reformes du systeme comptable des collectivites locales. Inspirees des normes comptables internationales et des experiences etrangeres, l'objectif de ces reformes est de fournir un systeme comptable plus performant permettant aux collectivites locales de gerer les ressources ainsi que les competences qui leur sont devolues par les nouvelles lois de decentralisation. Toutefois, l'observation des pratiques comptables au niveau communal met en evidence que les reformes entreprises ne sont pas appliquees a cause de nombreuses lacunes liees principalement a des problemes de competence du personnel communal ainsi qu'a des manques de moyens financiers et technologiques. Face a cette situation, les bailleurs de fonds sont demandeurs d'un systeme d'information plus simple, robuste et pragmatique tenant compte de ces contraintes et du contexte local afin d'assurer le controle des fonds alloues aux communes. Pour repondre a cette demande des bailleurs de fonds, l'objectif de cette recherche est, dans un premier temps, de proposer un modele simplifie de systeme d'information comptable et budgetaire partant des besoins des principaux utilisateurs de l'information financiere produite par les communes. Dans un second temps, elle s'attache a l'etude des conditions d'adoption du systeme propose au niveau des communes rurales malgaches.
Emergence of leaders in virtual teams: what matters?

Leadership is currently viewed as a key though relatively unexplored variable influencing the effectiveness of virtual teams. This paper identifies and empirically examines potential factors explaining the emergence of leaders in cross-cultural ISD virtual teams. Results of the study indicate that factors such as performance, culture, cultural ability, trust, ISD ability, communication ability, and co-location with client explain the emergence of leaders in the initial stages of a project, while performance, culture, and ISD ability explain the emergence of a leader in later stages. Interestingly, in both initial and later stages, technical ability of an individual was,found to have a negative effect on leader emergence. Also, the extent of communication was,found to have no effect in both stages, thereby falsifying the "babble hypothesis. ".
TET2 Overexpression in Chronic Lymphocytic Leukemia Is Unrelated to the Presence of TET2 Variations

TET2 is involved in a variety of hematopoietic malignancies, mainly in myeloid malignancies. Most mutations of TET2 have been identified in myeloid disorders, but some have also recently been described in mature lymphoid neoplasms. In contrast to the large amount of data about mutations of TET2, some data are available for gene expression. Moreover, the role of TET2 in chronic lymphocytic leukemia (CLL) is unknown. This study analyzes both TET2 expression and mutations in 48 CLL patients. TET2 expression was analyzed by exon arrays and quantitative real-time polymerase chain reaction (qRT-PCR). Next-generation sequencing (NGS) technology was applied to investigate the presence of TET2 variations. Overexpression of TET2 was observed in B-cell lymphocytes from CLL patients compared with healthy donors (P = 0.004). In addition, in CLL patients, an overexpression of TET2 was also observed in the clonal B cells compared with the nontumoral cells (P = 0.002). However, no novel mutations were observed. Therefore, overexpression of TET2 in CLL seems to be unrelated to the presence of genomic TET2 variations.
BROWSING MODES FOR EXPLORING SONIFIED LINE GRAPHS

The research presented here addresses how line graphs can be made accessible to blind and visually impaired people through the use of non-speech audio. Previous research has focused on the sonification of a single data series. This paper describes a method of sonifying two data series, and the design of two modes (parallel mode and serial mode) for browsing the graphs. Quantitative evaluation showed that both browsing modes were successful, with the parallel mode being particularly effective.
Asynchronous Cellular Automaton-Based Neuron: Theoretical Analysis and On-FPGA Learning

A generalized asynchronous cellular automaton-based neuron model is a special kind of cellular automaton that is designed to mimic the nonlinear dynamics of neurons. The model can be implemented as an asynchronous sequential logic circuit and its control parameter is the pattern of wires among the circuit elements that is adjustable after implementation in a field-programmable gate array (FPGA) device. In this paper, a novel theoretical analysis method for the model is presented. Using this method, stabilities of neuron-like orbits and occurrence mechanisms of neuron-like bifurcations of the model are clarified theoretically. Also, a novel learning algorithm for the model is presented. An equivalent experiment shows that an FPGA-implemented learning algorithm enables an FPGA-implemented model to automatically reproduce typical nonlinear responses and occurrence mechanisms observed in biological and model neurons.
Lecture 5 : SV-robust Mechanisms and Bias-Control-Limited Source

We have seen that additive noise technique is not (SV (γ), ε)-DP. So, the question that we explore in todays class is whether differential privacy (DP) is achievable with SV sources. Interestingly, we give a differential private mechanism for approximate arbitrary “low sensitive” functions that works even with randomness coming from SV source, for any γ < 1. We conclude todays lecture with some key insights to a new imperfect random source, we call BCL source.
Computer Vision on Embedded Sensors for Traffic Flow Monitoring

Capillary monitoring of traffic in urban environment is key to a more sustainable mobility in smart cities. In this context, the use of low cost technologies is mandatory to avoid scalability issues that would prevent the adoption of monitoring solutions at the full city scale. In this paper, we introduce a low power and low cost sensor equipped with embedded vision logics that can be used for building Smart Camera Networks (SCN) for applications in Intelligent Transportation System (ITS), in particular, we describe an ad hoc computer vision algorithm for estimation of traffic flow and discuss the findings obtained through an actual field test.
A novel Rac-dependent checkpoint in B cell development controls entry into the splenic white pulp and cell survival

Rac1 and Rac2 GTPases transduce signals from multiple receptors leading to cell migration, adhesion, proliferation, and survival. In the absence of Rac1 and Rac2, B cell development is arrested at an IgD− transitional B cell stage that we term transitional type 0 (T0). We show that T0 cells cannot enter the white pulp of the spleen until they mature into the T1 and T2 stages, and that this entry into the white pulp requires integrin and chemokine receptor signaling and is required for cell survival. In the absence of Rac1 and Rac2, transitional B cells are unable to migrate in response to chemokines and cannot enter the splenic white pulp. We propose that loss of Rac1 and Rac2 causes arrest at the T0 stage at least in part because transitional B cells need to migrate into the white pulp to receive survival signals. Finally, we show that in the absence of Syk, a kinase that transduces B cell antigen receptor signals required for positive selection, development is arrested at the same T0 stage, with transitional B cells excluded from the white pulp. Thus, these studies identify a novel developmental checkpoint that coincides with B cell positive selection.
Calmodulin Activates Phosphatidylinositol 3-Kinase*

Calmodulin and phosphatidylinositol 3-kinase are vital components of a number of common intracellular events. Calmodulin, a ubiquitous Ca2+-dependent effector protein, regulates multiple processes in eukaryotic cells, including cytoskeletal organization, vesicular trafficking, and mitogenesis. Phosphatidylinositol 3-kinase participates in events downstream of the receptors for insulin and other growth factors. Here we demonstrate by coimmunoprecipitation and affinity chromatography that Ca2+/calmodulin associates with Src homology 2 domains in the 85-kDa regulatory subunit of phosphatidylinositol 3-kinase, thereby significantly enhancing phosphatidylinositol 3-kinase activity in vitro and in intact cells. Furthermore, CGS9343B, a calmodulin antagonist, inhibited basal and Ca2+-stimulated phosphorylation of phosphatidylinositol in intact cells. These data demonstrate a novel mechanism for modulating phosphatidylinositol 3-kinase and provide a direct link between components of two fundamental signaling pathways.
Trait Worry and Neural Correlates of Emotion Regulation

Pathological worrying is of high transdiagnostic relevance and is related to maladaptive emotion regulation processes. Dysfunctional emotion regulation and its underlying neural mechanisms might contribute to the maintenance of fear over time. Therefore, this functional magnetic resonance imaging (fMRI) study aims at investigating the association of trait worry with neural correlates of emotion regulation. Twenty-six healthy females were instructed to passively look at aversive pictures, to distract themselves with a neutral thought, or to down- and up-regulate negative feelings via cognitive reappraisal in response to repeatedly presented aversive pictures. Trait worry was not related to cognitive reappraisal but to distraction, which leads to a greater reduction of self-reported negative feelings and insula activation in individuals with higher trait worry. The current study indicates that the neural mechanisms underlying distraction seem to be altered in pathological worrying and may prevent adaptive emotional processing of aversive stimuli leading to the maintenance of fear.
Semantic based data collection for large scale cloud systems

Current tools for monitoring cloud systems are designed for physical servers and are not intended to handle rapid elasticity or dynamic behaviour while operating at scale. Though current monitoring tools can be applied to small cloud systems, the volume of data and computational overhead associated with their operation render them unsuitable for large scale cloud deployments. The metrics obtained by current solutions also lack a machine readable structure, limiting the ability of both software and humans to interpret the data. As cloud adoption continues, the scale and complexity of cloud systems will present significant challenges to current tools. This paper proposes a scalable distributed data collection system which forms the basis of a cloud monitoring system. Utilising technologies from the semantic web, our architecture generates a machine readable overview of a cloud system without the need for an additional dedicated monitoring system. We present an exemplar implementation of our architecture written using the Python programming language and perform an evaluation demonstrating its ability to provide scalable data collection services fit for cloud computing