Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequency Noise Suppression of a Single Mode Laser with an Unbalanced Fiber Interferometer for Subnanometer Interferometry

We present a method of noise suppression of laser diodes by an unbalanced Michelson fiber interferometer. The unstabilized laser source is represented by compact planar waveguide external cavity laser module, ORIONTM (Redfern Integrated Optics, Inc.), working at 1540.57 nm with a 1.5-kHz linewidth. We built up the unbalanced Michelson interferometer with a 2.09 km-long arm based on the standard telecommunication single-mode fiber (SMF-28) spool to suppress the frequency noise by the servo-loop control by 20 dB to 40 dB within the Fourier frequency range, remaining the tuning range of the laser frequency.
Secondary cancer in a survivor of Hodgkin’s lymphoma: A case report and review of the literature

Hodgkin’s lymphoma (HL) is one of the most curable malignant diseases in adults. However, HL patients have a higher risk of developing second malignancies compared with the general population. The population of adult cancer survivors is growing, thus, the long-term effects of cancer treatment, including secondary cancer development, have become an increasingly important concern in the field of oncology. The current study presents the case of a female HL survivor who developed two secondary malignancies within 29 years of follow-up. Furthermore, a review of the literature was conducted, which focused on secondary breast and gastrointestinal cancers in HL survivors.
Rôle des adipokines dans la physiopathologie de l'arthrose : exemple de la leptine et de l'adiponectine

L'arthrose est une maladie degenerative des articulations et represente la deuxieme cause d'invalidite en France. En raison des liens entre l'obesite et l'arthrose concernant a la fois les articulations portantes et non portantes, nous faisons l'hypothese que des proteines produites par le tissu adipeux, les adipokines, constituent des facteurs cles impliques dans cette arthropathie. En premier lieu, nous avons montre que l'expression de la leptine, de l'adiponectine et de leurs recepteurs evolue de facon inverse et depend fortement de l'etat de differenciation des chondrocytes. Dans une seconde etude, nous avons compare la production des adipokines par le ligament adipeux de Hoffa a celle mesuree dans la graisse sous-cutanee et avons ainsi mis en evidence des differences entre les 2 tissus adipeux. Les travaux realises ensuite ont permis de preciser le role des adipokines dans l'arthrose. Ainsi, la production d'adiponectine par les chondrocytes augmente lorsque le cartilage se degrade et apparait directement reliee a celle de la MMP-13 et du TGF-[beta]. En revanche, l'expression de son recepteur AdipoR1 est associee a l'expression d'elements matriciels et d'un facteur de transcription specifique du cartilage implique dans la synthese de ces elements. Le traitement des chondrocytes a l'adiponectine a permis de confirmer in vitro les donnees observees in vivo chez les patients atteints d'arthrose, a savoir que l'adiponectine induit l'expression du TGF-[beta] et de la MMP-13. Les resultats obtenus avec la leptine indiquent par ailleurs que l'obesite influence fortement la reponse des chondrocytes a cette adipokine. Elle semble ainsi proteger le cartilage chez les patients non obeses en stimulant l'expression de l'IGF-1, du collagene de type 2 et du TIMP-2, mais contribue au processus degeneratif chez les patients obeses en augmentant l'expression de la MMP-13. Enfin l'induction d'une arthrose experimentale chez le rat Zucker n'ayant pas de recepteur fonctionnel a la leptine a montre que cette adipokine est susceptible de preserver l'articulation des modifications du cartilage et surtout de l'os sous-chondral.
Scalable audience targeted models for brand advertising on social networks

People are using social media to generate, share, and communicate information with each other. Finding actionable insights from such big data has attracted a lot of research attentions on, for example, finding targeted user groups based on their historical on-line activities. However, existing ma- chine learning algorithms fail to keep up with the increasing large data volume. In this paper, we develop a scalable regression-based algorithm called distributed iterative shrinkage-thresholding algorithm (DISTA) that can identify potential users. Our experiments conducted on Facebook data containing billions of users and associated activities show that DISTA with feature selection not only enables on-line audience-targeted approach for precise marketing but also performs efficiently on parallel computers.
Adaptive Nonlinear Tracking Control Algorithm for Quadcopter Applications

This paper presents a nonlinear tracking controller including the cutoff frequency adaptation algorithm for quadcopters without the use of true plant parameters. This study makes two contributions. First, an adaptation algorithm automatically updates the closed-loop cutoff frequency by updating the feedback gains. Second, a nonlinear control law renders the closed-loop system to guarantee the exponential performance recovery and offset-free properties, while only using the proportional component of tracking errors. The numerical verifications are performed to verify the closed-loop performance improvement from the proposed controller with MATLAB/Simulink.
Evolution of a Mobile Robot's Neurocontroller on the Grasping Task - Is Genetic also Generic?

This paper presents a survey on the generic evolution of mobile robot’ neurocontrollers with a particular focus on the capacity to adapt these controllers in several environments. Several experiments on the example of the grasping task (autonomous vacuum cleaner for example) are performed and the results show that the produced neurocontroller is dedicated to the trained conditions and cannot be considered as generic. The last part of the paper discusses of the necessary changes in the fitness function in order to produce generic neurocontrollers.
Identification and characterization of a specific sensory epithelium in the rat larynx

A specific laryngeal sensory epithelium (SLSE), which includes arrays of solitary chemoreceptor cells, is described in the supraglottic region of the rat. Two plates of SLSE were found, one on each side of the larynx. The first plate was located in the ventrolateral wall of the larynx, and the second was located in the interarytenoidal region. In SLSE, immunoblotting showed the presence of α‐gustducin and phospholipase C β2 (PLCβ2), which are two markers of chemoreceptor cells. At immunocytochemistry, laryngeal immunoreactivity for α‐gustducin was localized mainly in solitary chemosensory cells. Double‐label immunocytochemistry using confocal microscopy demonstrated that α‐gustducin–expressing cells in large part colocalize type III IP3 receptor (IP3R3), another key molecule in bitter taste perception. However, some IP3R3–expressing cells do not colocalize α‐gustducin. At ultrastructural immunocytochemistry, these cells showed packed apical microvilli, clear cytoplasmic vesicles, and cytoneural junctions. SLSE was characterized by high permeability to a tracer due to poorly developed junctional contacts between superficial cells. Junctions were short in length and showed little contact with the terminal web. Ultrastructural analysis showed deep pits among the superficial cells. In SLSE, high density of intraepithelial nerve fibers was found. The lamina propria of the SLSE appeared thicker than that in other supraglottic regions. It was characterized by the presence of a well‐developed subepithelial nerve plexus. The immunocytochemical and ultrastructural data suggested that SLSE is a chemoreceptor located in an optimal position for detecting substances entering the larynx from the pharynx or the trachea. J. Comp. Neurol. 475:188–201, 2004. © 2004 Wiley‐Liss, Inc.
Hidden Markov Model Based Graph Construction Process for DNA Sequence Assembly

Through using next-generation sequencers to decode DNA symbols has been a majorly breakthrough in the area of genomic research for decades. A plenty of current approaches of next-generation sequencers with high throughput rates as well as relatively low costs, but it is still challenged for the assembly of the reads which those sequencers produces. We proposed, in this paper, a novel Hidden Markov Model based (HMM-based) approach for next-generation genome sequence assembly programs. The paper introduces the major challenges that currently existed assemblers encounter in the next-generation environment, and four basic stages included in our proposed method: a) pre-processing filtering, b) a graph construction process, c) a graph simplification process, d) post-processing filtering. Experimental results prove the performance of the new approach meets or exceeds the state-of-art by testing a number of DNA open-source datasets.
A particle swarm optimization based simultaneous learning framework for clustering and classi fi cation

A particle swarm optimization based simultaneous learning framework for clustering and classification (PSOSLCC) is proposed in this paper. Firstly, an improved particle swarm optimization (PSO) is used to partition the training samples, the number of clusters must be given in advance, an automatic clustering algorithm rather than the trial and error is adopted to find the proper number of clusters, and a set of clustering centers is obtained to form classification mechanism. Secondly, in order to exploit more useful local information and get a better optimizing result, a global factor is introduced to the update strategy update strategy of particle in PSO. PSOSLCC has been extensively compared with fuzzy relational classifier (FRC), vector quantization and learning vector quantization (VQþLVQ3), and radial basis function neural network (RBFNN), a simultaneous learning framework for clustering and classification (SCC) over several real-life datasets, the experimental results indicate that the proposed algorithm not only greatly reduces the time complexity, but also obtains better classification accuracy for most datasets used in this paper. Moreover, PSOSLCC is applied to a real world application, namely texture image segmentation with a good performance obtained, which shows that the proposed algorithm has a potential of classifying the problems with large scale. & 2014 Elsevier Ltd. All rights reserved.
Geometric Concept Acquisition in a Dueling Deep Q-Network

Explaining how intelligent systems come to embody knowledge of deductive concepts through inductive learning is a fundamental challenge of both cognitive science and artificial intelligence. We address this challenge by exploring how a deep reinforcement learning agent, occupying a setting similar to those encountered by early-stage mathematical concept learners, comes to represent ideas such as rotation and translation. We first train a Dueling Deep Q-Network on a shape sorting task requiring implicit knowledge of geometric properties, then we query this network with classification and preference selection tasks. We demonstrate that scalar reinforcement provides sufficient signal to learn representations of shape categories. After training, the model shows a preference for more symmetric shapes, which it can sort more quickly than less symmetric shapes, supporting the view symmetry preferences may be acquired from goal-directed experience.
Overview of Membrane Protein Solubilization

The solubilization of membrane proteins (i.e., extraction of the protein from the membrane in a disperse state in aqueous solution) in a stable state that retains the native activity of the membrane‐bound form is more an empirical art than a protocol‐driven science. Although a large number of molecules have been invented that display detergent properties, selection of the proper solubilizing agent is largely a matter of trial and error that depends on the protein of interest and the particular goals of the investigator. The purpose of this overview is to describe the methodology for finding the optimal conditions for detergent solubilization and to relate the selection of a specific detergent to explicit experimental goals.
Uveitis Related to Juvenile Idiopathic Arthritis: Familial Cases and Possible Genetic Implication in the Pathogenesis

Purpose: To describe four cases of familial Juvenile Idiopathic Arthritis (JIA) associated uveitis. Design: Retrospective observational case series. Methods: Clinical data from patients who present familial JIA-associated uveitis are described and possible genetic influence in disease etiology is reviewed. Results: Two sisters, 6- and 7-year-old, developed bilateral anterior uveitis related to oligoarticular JIA. Arthritis in both began by the age of 18 months; uveitis developed simultaneously in one of them and less than one year after arthritis in the other one. Both received topical and systemic treatment to control the ocular disease. Glaucoma occurred in both cases and bilateral cataract in one case. In the other family, a 2-year-old girl developed unilateral uveitis in the context of oligoarticular JIA which was diagnosed by 1-year-old. The disease became soon bilateral and she received topical and systemic immunosuppressive treatment. Her mother suffered from bilateral anterior uveitis associated to oligoarticular inflammatory disease during her infancy, later diagnosed as JIA-associated uveitis. Conclusions: Familial cases of JIA uveitis, although not very common, support the possible role of genetic influence in the pathogenesis of the disease, with horizontal and vertical inheritance being possible. The evolution of ocular disease is similar to the non-familial cases, except for an earlier age of onset.
A computational framework for labeling spatiotemporal remote sensing datasets

Remote sensing instruments and sensors have made significant progress over the last several decade in spatial, spectral and temporal resolutions. These improvements have led to the collection of synoptic scale data and enabled a variety of new applications. For example, improvements in temporal resolution allows monitoring biomass on a daily basis. Improvements in spatial resolution allows fine-grained classification of urban settlements, damage assessments, and critical infrastructure monitoring. Remote sensing applications have the following characteristics: • Spatio-temporal Grid: The underlying data sets are gridded—with the grid dimensions ranging across 2D (images, 2D flow fields), 3D (volumetric data) and 4D (spatiotemporal data). Unlike standard machine learning approaches where the data is usually only available in the form of high dimensional feature vectors, the presence of a grid affords us the potential to develop techniques that can interpolate each of the features (using differentiable splines) and generate new feature vectors with different (and more desirable) nearest neighbor properties. • Large Volume and Velocity: The underlying volume (terabytes to petabytes) and velocity (gigabytes to terabytes per day) of these applications is very large and are responsible for carrying us into the bigdata regime. Effective processing requires low complexity and multiscale algorithms that can exploit modern parallel architectures with deep memory hierarchies.
Head Morphology and Degree of Variation in Lacerta bilineata, Podarcis muralis and Podarcis sicula

La morfologia de las escamas cefalicas en Lacertidos se organiza en estructuras geometricas bien definidas. La variacion de estos elementos esta relacionada con el crecimiento y la morfogenesis del hueso subyacente, pero esta tambien es asociada con el sistema muscular y sutural dinamico. En este trabajo, son comparados los patrones de variacion de las escamas cefalicas de tres especies mediterraneas comunes: Podarcis muralis, Podarcis sicula y Lacerta bilineata. El morfoespacio generado por las relaciones morfologicas con el sistema cefalico en estas tres especies se investigo con el fin de examinar su grado de variacion y sus peculiaridades anatomicas. En general, Lacerta es 64% mas grande que Podarcis, muestra una reduccion relativa de la escama frontal, alargamiento de la estructura fronto-parietal, y estrechamiento del area occipital. L. bilineata muestra el menor grado de variacion en la forma del espacio, mientras que P. muralis muestra los valores mas altos. La morfologia de los dos generos es diferente principalmente debido a variaciones alometricas. Diferencias no alometricas entre las tres especies son sutiles pero detectables. El grado y el patron de variacion son interpretados en terminos de las posibles presiones del medio ambiente y la dinamica funcional craneal asociada a la sutura fronto-parietal, respectivamente. En este sentido, las relaciones estructurales entre los huesos y las escamas son de particular interes para seguir investigando ontogenia y filogenia de los reptiles.
Concept for Human Robot Co-operation Integrating Artificial Haptic Perception

Human robot co-operation becomes more and more important when using robots in daily life and is a key note in the design of humanoid robots. The authors are members of the newly founded centre of excellence “Humanoid robots – cooperating and learning systems” at the University of Karlsruhe. Our group of researchers is responsible for the human robot co-operation, a haptic sensor system and the control of a robot hand. All three topics closely co-operate as the human robot co-operation (using a robot arm and a robot hand attached to it) is mainly based on the haptic sensor system within the first phase of the project. In this paper we present our first classifications for human robot co-operation and contacts between a robot and a human or an object, which both form the basis for our practical work. The control concept of our robotic system is depicted as well.
Study of antecedent and consequences of work group learning

The organizational and individual levels of analysis dominate most research about learning in organizations. Group level learning has generally been neglected. In this paper, we first study group learning modes, the extent and frequency with which group learning processes are used. Then, antecedents of work group learning are presented. Finally, we study consequences of work group learning.
Indoor Air Quality Investigation at Primary Classrooms in Hamirpur, Himachal Pradesh, India

Two schools in Hamirpur (Himachal Pradesh, India) having hybrid ventilation (ceiling fan) were selected for indoor and outdoor air quality investigation. Investigated parameters include temperature, relative humidity, CO2, and PM2.5 for both indoor and outdoor air quality. The average concentrations of CO2, and PM2.5 are estimated for indoor and outdoor air quality. Result shows that adopted building performance is not good in comparison with designed ones. The indoor concentrations of various pollutants are found to be higher in comparison with outdoor, so there is an urgent need to reduce the levels of pollutants inside the primary classrooms.
Off-Road Terrain Traversability Analysis and Hazard Avoidance for UGVs

Abstract : To achieve complete autonomy of unmanned ground vehicles (UGVs) in off-road terrain at high speeds, a robot must understand and analyze the terrain it is driving on in real-time just as a human analyzes the terrain and makes decisions of where to drive. Much research has been done in the way of obstacle avoidance, terrain classification, and path planning, but there has yet to be seen a system that can accurately traverse offroad environments at high speeds in an autonomous fashion. We present algorithms that analyze the off-road terrain using a point cloud produced by a 3D laser range finder, determine potential hazards both above ground and those where the ground cover has a negative slope, then plan safe routes around those hazards. We take into account problems such as high-centering, tip-over and overhanging obstacles. In this paper we discuss a real-time approach to analyzing the traversability of off-road terrain for UGVs considering positive and negative obstacles using multilevel surface maps and planning paths to a goal state.
A fully integrated two-channel A/D interface for the acquisition of cardiac signals in implantable pacemakers

This work presents an input stage for a cardiac pacemaker fully integrated in 0.35-/spl mu/m CMOS technology. The system can acquire and digitize to 8 bits both atrial and ventricular electrical activity. Log-domain circuits are exploited to amplify and filter the input signal, while /spl Sigma//spl Delta/ modulation is exploited to convert it. The design is power optimized, indeed the current consumption is limited to 2.9 /spl mu/A, while the power supply ranges from 2.8 to 1.8 V. The total area is 2.2 mm/sup 2/ and experimental data prove correct filtering and a total dynamic range of at least 47 dB.
Regional Estimates of Breast Cancer Burden in Italy

Aims and background Breast cancer is the most common cancer and the leading cause of cancer death among women. Knowledge of the present and future burden of the disease at a regional and national scale is a major issue in Italy, where the frequency and coverage of screening programs vary considerably across the country. This study presents estimates and projections of the female breast cancer incidence, prevalence and mortality for Italy and all Italian regions in the period 1970-2010. Methods The estimates were obtained by applying the MIAMOD method, a statistical back-calculation approach to derive incidence and prevalence figures from mortality and relative survival data. Published data from the Italian cancer registries were modelled to obtain regional and national estimates of breast cancer survival. Results Breast cancer mortality has been declining from the late 1980s in the northern-central regions and from the mid 1990s in the southern regions Puglia, Sicilia and Sardegna. Stable mortality rates are estimated for the other southern regions in the 2000's first decade. The incidence rate in Italy is estimated as increasing until the late 1990s, and stable thereafter (93 per 100,000). The incidence curve is also estimated to flatten in many northern-central regions from the late 1990s or later. Rising incidence trends are estimated in all southern regions, with the exception of Puglia. About 8,500 deaths, 37,000 new diagnoses and 416,000 prevalent cases for breast cancer are estimated among Italian women in 2005. In the same year, the proportion of prevalent cases in the northern area (1,221 per 100,000) is about twice that estimated in the South (685 per 100,000). Discussion The geographical variation in female breast cancer burden can be explained by the unequal distribution of screening. A more widespread screening activity in the southern regions would help to bridge the gap between northern-central and southern regions. Continuous monitoring of regional epidemiological indicators for breast cancer is crucial to evaluate the effect of different health measures taken to control breast cancer in Italy.