Miracle-dz/UniFAR-FTUs huggingface dataset:
Helical Tomotherapy for Inoperable Breast Cancer: A New Promising Tool

Background. We investigated the feasibility of helical tomotherapy (HT) for inoperable large breast tumors, after failing to achieve adequate treatment planning with conformal radiation techniques. Material and Methods. Five consecutive patients with locally advanced breast cancer (LABC) were treated by preoperative HT. All patients received up-front chemotherapy before HT. Irradiated volumes included breast and nodal areas (45–50 Gy) in 4 patients. One patient received a simultaneous integrated boost (55 Gy) to gross tumor volume (GTV) without lymph node irradiation. Acute toxicity was assessed with Common Toxicity Criteria for Adverse Events v.4. Patients were evaluated for surgery at the end of treatment. Results. Patients were staged IIB to IIIC (according to the AJCC staging system 2010). HT was associated in 4 patients with concomitant chemotherapy (5-fluorouracil and vinorelbine). Two patients were scored with grade 3 skin toxicity (had not completed HT) and one with grade 3 febrile neutropenia. One patient stopped HT with grade 2 skin toxicity. All patients were able to undergo mastectomy at a median interval of 43 days (31–52) from HT. Pathological partial response was seen in all patients. Conclusions. HT is feasible with acceptable toxicity profiles, potentially increased by chemotherapy. These preliminary results prompt us to consider a phase II study.
Learning and Knowledge Management Toolbox for Cognitive Radio Network Applications

experience and knowledge in cognitive radio (CR) systems, exposed to high dynamics with often unpredictable states. Such learning mechanisms can be associated with user and device profiles, context and decisions. This paper provides a synopsis of basic learning functionalities and relevant requirements for the collection and processing of information that can lead to exploitable knowledge. The paper also provides an overview of potential implementation approaches for these functionalities that exploit diverse machine learning techniques.
MinExp-card: limiting data collection using a smart card

Online services such as social care, tax services, bank loans and many others, request individuals to fill in application forms with hundreds of private data items, in order to calibrate their offer. In practice, far too much data is requested, leading to over data disclosure. As shown in our previous works, avoiding this problem would (1) improve the privacy of the applicants and (2) decrease costs for service providers. We demonstrate here a prototype designed and implemented in partnership with the General Council of Yvelines District in France. The prototype targets forms used to calibrate social care for dependant people. To maintain the privacy of the decision process used to calibrate the social care, we propose a smartcard implementation. We will show that a 50% reduction of the items exposed in application forms can be achieved, explore the quality and scalability of our smartcard implementation, and demonstrate its scope.
Research on a New Three-dimension Reconstruction and Visualization Technology of Concrete Based on CT Images

In recent years, the research of concrete based on CT Images has been popular. A new modified Ray-casting on VTK aims to solve the poor effect on 3-D reconstruction of concrete CT image, which has great influence on the construction of accurate 3-D meso-concrete numerical model. Owing to this result, A new tech-VTK system came into being to get improvement and development. What is more, it can achieve visualization. It is tested that the method in this dissertation is more effective and accurate meanwhile it will help to build the construction of concrete material numerical model.
Clustering Ad hoc Network Scheme and Classifications Based on Context-aware

In ad hoc network, the scarce energy management of the mobile devices has become a critical issue in order to extend the network lifetime. Current research activity for the Minimum Energy Multicast (MEM) problem has been focused on devising efficient centralized greedy algorithms for static ad hoc networks. In this paper, we consider mobile ad hoc networks(MANETs) that could provide the reliable monitoring and control of a variety of environments for remote place. Mobility of MANET would require the topology change frequently compared with a static network. To improve the routing protocol in MANET, energy efficient routing protocol would be required as well as considering the mobility would be needed. In this paper, we propose a new method, the CACH(Context-aware Clustering Hierarchy) algorithm, a hybrid and clustering-based protocol that could analyze the link cost from a source node to a destination node. The proposed analysis could help in defining the optimum depth of hierarchy architecture CACH utilize. The proposed CACH could use localized condition to enable adaptation and robustness for dynamic network topology protocol and this provide that our hierarchy to be resilient. As a result, our simulation results would show that CACH could find energy efficient depth of hierarchy of a cluster.
A distributed problem solving with contract net and case-based reasoning

Contractor net protocol (CNP) and case based reasoning (CBR) are wide-application distributed problem solving methods. The paper presents an interacted learning strategy based CNP and CBR to solve non-structural, nonlinear, and complex urban traffic control decision-making under multiagent system architecture. The manager agent (MA) decomposes a regional control task into several separable subtasks which single traffic agent (TA) could deal with independently and their specifications by knowledge with CBR. MA sends task announcement messages to selected agents and requires them finish bid document in expiration-time. MA analyzes bid messages, eliminates those conflict control schemes, and optimizes their specification and resend to TAs. Through finite cycles of interacted learning, MAS could get a group of best coordinating TAs and optimal control schema. Extended KQML is a tool to realize the distributed decision-making.
Inventory Sharing and Rationing in Decentralized Dealer Networks

An increasing number of manufacturers have started to pursue a strategy that promotes inventory sharing among the dealers in their distribution network. In this paper we analyze a decentralized dealer network in which each independent dealer is given the flexibility to share his inventory. We model inventory sharing as a multiple demand classes problem in which each dealer faces his own customer demand with high priority, and inventory-sharing requests from other dealers with low priority. Assuming that each dealer uses a base-stock and threshold-rationing policy for his inventory-stocking and inventory-sharing decisions, we explicitly model the interactions between the dealers through inventory sharing and obtain aclosed-form cost function for each dealer based on the steady-state distribution of the inventory levels at the two dealers. We then provide a detailed supermodularity analysis of the inventory-sharing and inventory-rationing game in which each dealer has a two-dimensional strategy set (stocking level and rationing level). We show that the full-sharing game (in which dealers precommit to sharing all of their on-hand inventory) and the fixed-sharing-level game (in which dealers precommit to sharing a portion of their on-hand inventory) are supermodular, and thus a pure-strategy Nash equilibrium is guaranteed to exist. For the rationing game (in which dealers precommit to their stocking levels), we show that there exists a dominant strategy equilibrium on the dealers' sharing (rationing) levels. Finally, a comprehensive computational study is conducted to highlight the impact of the manufacturer's incentives, subsidies, and/or transshipment fees on the dealers' sharing behavior.
Robot calibration based on multi-thread particle swarm optimization

Main contributions include: (1) A platform composed of a structure-light vision sensor and a industrial robot is established for robot calibration. (2) Transform the robot calibration to an optimization problem through measuring a fixed point at different hand poses and positions. (3) A multi-thread particle swarm optimization algorithm is proposed and applied in robot kinematic parameter estimation. The effectiveness of the proposed method is validated by simulation.
On the theory of magnetar QPOs

We consider torsional oscillations of magnetars. This problem features rich dynamics due to the strong interaction between the normal modes of a magnetar’s crust and a continuum of magnetohydrodynamic (MHD) modes in its fluid core. We study the dynamics using a simple model of a magnetar possessing a uniform magnetic field and a thin spherical crust. First, we show that global torsional modes only exist when one introduces unphysically large dissipative terms into the equations of motion; thus global modes are not helpful for understanding the magnetar quasi-periodic oscillations (QPOs). Secondly, we solve the initial-value problem by simulating the sudden release of an initially strained crust and monitoring the subsequent crustal motion. We find that the crustal torsional modes quickly exchange their energy with the MHD continuum in the core, and decay by several orders of magnitude over the course of ∼10 oscillation periods. After the initial rapid decay, the crustal motion is stabilized and several time-varying QPOs are observed. The dynamical spectrum of the simulated crustal motion is in qualitative agreement with that of the X-ray light curve in the tail of a giant magnetar flare. The asymptotic frequencies of some of the QPOs are associated with the special spectral points ‐ the turning points or edges ‐ of the MHD continuum, and are not related to those of the crust. The observed steady low-frequency QPO at 18 Hz is almost certainly associated with the lowest frequency of the MHD continuum, or its first overtone. We also find that drifting QPOs get amplified when they come near the frequencies of the crustal modes. This explains why some of the observed QPOs have frequencies close to the expected crustal frequencies, and why these QPOs are highly variable with time.
Identifications of SUMO-1 cDNA and Its Expression Patterns in Pacific White Shrimp Litopeanaeus vannamei

Small ubiquitin-like modifiers (SUMO) work in a similar way as ubiquitin to alter the biological properties of a target protein by conjugation. A shrimp SUMO cDNA named LvSUMO-1 was identified in Litopenaeus vannamei. LvSUMO-1 cDNA contains a coding sequence of 282 nucleotides with untranslated regions of 37 bp at 5'-end and 347 bp at 3'-end, respectively. The deduced 93 amino acids exhibit 83% identity with the Western Honeybee SUMO-1, and more than 65% homologies with human and mouse SUMO-1. LvSUMO-1 mRNA is expressed in most L. vannamei tissues with the highest level in hepatopancrease. The mRNA expression of LvSUMO-1 over development stages in L. Vammamei is distinguished by a low level in nauplius stage and relatively high level in postlarva stage with continuous expression until juvenile stage. The LvSUMO-1 protein and its conjugated proteins are detected in both cytoplasm and nucleus in several tissues. Interestingly, LvSUMO-1 mRNA levels are high in abdominal muscle during the premolt stage, wherein it has significant activities of protein degradation, suggesting its possible role in the regulation of shrimp muscle protein degradation.
A simulation tool for evaluating digital camera image quality

The Image Systems Evaluation Toolkit (ISET) is an integrated suite of software routines that simulate the capture and processing of visual scenes. ISET includes a graphical user interface (GUI) for users to control the physical characteristics of the scene and many parameters of the optics, sensor electronics and image processing-pipeline. ISET also includes color tools and metrics based on international standards (chromaticity coordinates, CIELAB and others) that assist the engineer in evaluating the color accuracy and quality of the rendered image.
Extended Parallelism Models for Optimization on Massively Parallel Computers

Single-level parallel optimization approaches, those in which either the simulation code executes in parallel or the optimiza- tion algorithm invokes multiple simultaneous single-processor analyses, have been investigated previously and been shown to be effective in reducing the time required to compute optimal solutions. However, these approaches have clear performance limita- tions that prevent effective scaling with the thousands of processors available in massively parallel supercomputers. In more recent work, a capability has been developed for multilevel parallelism in which multiple instances of multiprocessor simulations are coordinated simultaneously. This implementation employs a master-slave approach using the Message Passing Interface (MPI) within the DAKOTA software toolkit. Mathematical analysis on achieving peak efficiency in multilevel parallelism has shown that the most effective processor partitioning scheme is the one that limits the size of multiprocessor simulations in favor of concurrent execution of multiple simulations. That is, if both coarse-grained and fine-grained parallelism can be exploited, then preference should be given to the coarse-grained parallelism. This analysis was verified in multilevel paralIel computatiorud experiments on networks of workstations (NOWS) and on the Intel TeraFLOPS massively parallel supercomputer. In current work, methods for exploiting additional coarse-grained parallelism in optimization are being investigated so that fine-grained efficiency more » losses can be further minimized. These activities are focusing on both algorithmic coarse-grained parallel- ism (multiple independent function evaluations) through the development of speculative gradient methods and concurrent iterator strategies and on function evaluation coarse-grained parallelism (multiple separable simulations within a function evaluation) through the development of general partitioning and nested synchronization facilities. The net result is a total of four separate lev- els of parallelism which can minimize efficiency losses and achieve near linear scaling on massively parallel computers. « less
A Comparison of US and Hong Kong Cap-Floor Volatility Dynamics

In this paper we investigate the dynamics of Hong Kong cap-floor volatilities and compare their dynamics with the US cap-floor volatilities. We use linear and non-linear factor models and VARi¦s. The results show that the first principal components, both linear and non-linear, do a very good job in explaining the dynamics of the volatility curve and but there is not much to be gained by moving to non-linear models for the case of Hong Kong data. Secondly, we see that Hong Kong cap-floor volatilities cannot be obtained from the USD cap-floor volatilities by simply adding a volatility spread. The two sets of volatilities are non-trivially related to each other.
Pseudorandom Noise for Real-Time Volumetric Rendering of Fire in a Production System

This paper presents an effort at developing a robust, interactive framework for rendering 3D fire in real-time in a production environment. Many techniques of rendering fire in non real-time exist and are constantly employed by the movie industry and have directly influenced and inspired real-time fire rendering, including this paper. Macrolevel behavior of fire is characterized by wind fields, temperature and moving sources and is currently processed on the CPU while micro-level behavior like turbulence, flickering, separation and shape is created on the graphics hardware. This framework provides a set of tools for level designers to wield artistic and behavioral control over fire as part of the scene. The resulting system is able to scale well, to use as few processor cycles as possible, and to efficiently integrate into an existing production environment. We present performance statistics and assess the feasibility of achieving interactive frame rates within a 3D engine framework. The framerates we obtained vary from 42 to 168 depending on the rendering conditions, and indicate that the real-time procedural fire might not be far away.
Real-Time Implementation of Multiple Sub-array Beam-Space MUSIC Based on FPGA and DSP Array

Multiple sub-array beam-space MUSIC (MSB-MUSIC) is a new beam-space high resolution DOA estimation algorithm. In order to solve the problem of huge computation load of the algorithm, a real-time processing scheme based on FPGA and DSP array is proposed and implemented on the hardware. In the hardware platform MSB-MUSIC with 80 channels data is real-time implemented, where both the digital down conversion based on CORDIC and the eigenvalue decomposition using the two-side CORDIC based parallel Jacobi algorithm are implemented on the FPGA. The calculation of the covariance matrix and MUSIC angular spectra are implemented on DSP array, respectively. The parallel processing platform has been applied to the shallow water high resolution multi-beam echo sounder, and the lake test proves that the system can achieve the high performance.
MAPK signalling : ERK 5 versus ERK 1 / 2

Extracellular-signal-regulated kinase 5 (ERK5) is a member of the mitogen-activated protein kinase (MAPK) family and, similar to ERK1/2, has the Thr–Glu–Tyr (TEY) activation motif. Both ERK5 and ERK1/2 are activated by growth factors and have an important role in the regulation of cell proliferation and cell differentiation. Moreover, both the ERK5 and the ERK1/2 pathways are sensitive to PD98059 and U0126, which are two well-known inhibitors of the ERK pathway. Despite these similarities, recent studies have revealed distinctive features of the ERK5 pathway: ERK5 has a key role in cardiovascular development and neural differentiation; ERK5 nuclear translocation is controlled by its own nuclear localizing and nuclear export activities; and the carboxy-terminal half of ERK5, which follows its kinase catalytic domain, has a unique function.
Violencia Conyugal - comprensión e intervención en red / Conjugal violence - understanding and network intervention

ABSTRACT This article shows the results of therapeutic intervention performed two networks with men exercising conjugal violence against women. He set the foundations of the systemic approach of clinical psychology, with a qualitative type methodology through a categorical analysis of narratives. The process showed a decrease in aggressive behavior towards the couple where other forms of communication other than abuse were found. At the institutional level a process of therapeutic intervention was promoted through networking with batterer men; promoting the reconciliation process in family dynamics and relational. This study supports a new perspective on this problem as it arises from the position of the aggressor achieving a far-reaching impact on time and with a multiplier effect on their social context minimizing domestic violence. RESUMEN El presente articulo muestra los resultados de una investigacion mediante la intervencion terapeutica realizada a dos redes con hombres que ejercen la violencia conyugal contra la mujer. Partio de las bases del enfoque sistemico de la psicologia clinica, con una metodologia de tipo cualitativo a traves de un analisis categorial de narrativas. El proceso evidencio una disminucion en los comportamientos agresivos hacia la pareja donde se encontraron otras formas de comunicacion diferentes al maltrato. A nivel institucional se promovio un proceso de intervencion terapeutica mediante el trabajo en red con los hombres maltrantantes; el proceso fomento la conciliacion en las dinamicas familiares y relacionales. Este estudio admite una nueva perspectiva de esta problematica ya que se plantea desde la postura del agresor logrando un impacto de largo alcance en tiempo y con un efecto multiplicador en su contexto social minimizando la violencia conyugal.
Measuring the Effect of Queues on Customer Purchases

We conduct an empirical study to analyze how waiting in queue in the context of a retail store affects customers' purchasing behavior. Our methodology combines a novel data set with periodic information about the queuing system (collected via video recognition technology) with point-of-sales data. We find that waiting in queue has a nonlinear impact on purchase incidence and that customers appear to focus mostly on the length of the queue, without adjusting enough for the speed at which the line moves. An implication of this finding is that pooling multiple queues into a single queue may increase the length of the queue observed by customers and thereby lead to lower revenues. We also find that customers' sensitivity to waiting is heterogeneous and negatively correlated with price sensitivity, which has important implications for pricing in a multiproduct category subject to congestion effects. This paper was accepted by Martin Lariviere, operations management.
ON MARIAN SMOLUCHOWSKI'S LIFE AND CONTRIBUTION TO PHYSICS ∗ ,∗∗

The first part presents the life and historical contributions of Marian Smoluchowski to the foundations of atomic theory of matter. Remaining parts are devoted to the presentation of the original derivation and present applications of the Smoluchowski equations. Commonly used in various physical, chemical, etc., problems is the kinetic Smoluchowski equation, being the high-friction limit of the full Fokker-Planck equation. Of less use so far has been the functional Smoluchowski (called also Chapman-Enskog or Bachelier) equation. Within the scope of modern theory of stochastic processes this equation is an identity equivalent to the definition of a Markovian process. It is argued that, in the view of the growing interest in non-Markovian stochastic processes, the functional Smoluchowski equation may become the most natural and effective tool for checking the Markovian vs. non-Markovian character of a considered process, especially when applied to experimental data. Some examples are given.
Prevalence and Risk Factors of HCV/HIV Co-Infection and HCV Genotype Distribution in North-Eastern Poland

Background: HIV/HCV co-infection predisposes to accelerated liver damage and increased both liver-related and unrelated morbidity and mortality in patients with HIV infection. Objectives: The aim of this study was to evaluate the prevalence of HCV infection, seropositivity, risk factors and genotype distribution among treated HIV positive patients. Furthermore, the occurrence and causes of deaths were analyzed. Patients and Methods: Adult HIV-1 infected patients, with at least one antiHCV result, treated in one of Polish HIV/AIDS reference centers, participated in this cross-sectional study. Results: Four hundred and fifty seven patients with a median age of 38 years (ranged 23 - 72), and predominantly male (76.6%) were enrolled in the study. Anti-HCV antibodies were detected in 325 individuals (71.1%). HCV RNA was detected in 207 of the 233 patients tested (88%). The HCV genotype analysis (n = 193) demonstrated almost equal distribution with slight genotype 1 domination as 37.3%, mainly 1b, followed by genotypes 3 as 32.1% and 4 as 30.6%. No association was found between HCV genotype and route of HIV acquisition. In univariate analysis, higher HCV seropositivity was related to male sex, intravenous drug use (IDU), mode of HIV transmission, history of drug and alcohol abuse and imprisonment. In multivariate analysis, only being injection drug user (P = 0.0001), imprisonment (P = 0.310) and younger age at the HIV diagnosis per each year (P = 0.025) were identified as risk factors for HCV infection. Sixty three deaths were reported; no association was found between HCV seropositivity and death prevalence. Conclusions: HIV/HCV co-infection is an important medical problem in North-Eastern Poland. A history of incarceration and younger age at HIV diagnosis were additional to IDU risk factors for HCV seropositivity in this cohort.