Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel lead design enables selective deep brain stimulation of neural populations in the subthalamic region

Objective. The clinical effects of deep brain stimulation (DBS) of the subthalamic nucleus (STN-DBS) as a treatment for Parkinson’s disease are sensitive to the location of the DBS lead within the STN. New high density (HD) lead designs have been created which are hypothesized to provide additional degrees of freedom in shaping the stimulating electric field. The objective of this study is to compare the performances of a new HD lead with a conventional cylindrical contact (CC) lead. Approach. A computational model, consisting of a finite element electric field model combined with multi-compartment neuron and axon models representing different neural populations in the subthalamic region, was used to evaluate the two leads. We compared ring-mode and steering-mode stimulation with the HD lead to single contact stimulation with the CC lead. These stimulation modes were tested for the lead: (1) positioned in the centroid of the STN, (2) shifted 1 mm towards the internal capsule (IC), and (3) shifted 2 mm towards the IC. Under these conditions, we quantified the number of STN neurons that were activated without activating IC fibers, which are known to cause side-effects. Main results. The modeling results show that the HD lead is able to mimic the stimulation effect of the CC lead. Additionally, in steering-mode stimulation there was a significant increase of activated STN neurons compared to the CC mode. Significance. From the model simulations we conclude that the HD lead in steering-mode with optimized stimulation parameter selection can stimulate more STN cells. Next, the clinical impact of the increased number of activated STN cells should be tested and balanced across the increased complexity of identifying the optimized stimulation parameter settings for the HD lead.
Molecular Epidemiology of Neisseria gonorrhoeae in Amsterdam, The Netherlands, Shows Distinct Heterosexual and Homosexual Networks

ABSTRACT Molecular typing, added to epidemiological data, can better identify transmission patterns of gonorrhea in Western countries, where the incidence has recently been rising. From September 2002 to September 2003, patients with a laboratory-confirmed diagnosis of gonorrhea at the Clinic for Sexually Transmitted Infections in Amsterdam, The Netherlands, were subjected to a questionnaire pertaining to sexual risk behavior and sexual partners in the 6 months prior to the diagnosis. The Neisseria gonorrhoeae isolates were all genotyped using PCR-restriction fragment length polymorphism of the porin and opacity genes. All patients with a completed questionnaire and genotyped isolates were included in the study. We obtained 885 N. gonorrhoeae isolates from 696 patients that revealed 88 clusters and 46 unique genotypes. Patients infected at multiple anatomical sites with one or more strains and patients infected several times during the study period were shown to pursue high-risk sexual behavior and were considered core groups. There were 11 clusters of ≥20 patients; in seven clusters, 81% to 100% of patients were men who have sex with men (MSM), three clusters contained 87 to 100% heterosexual men and women, and one cluster was formed by equal proportions of MSM and heterosexual male and female patients. However, the various clusters differed in characteristics such as types of coinfections, numbers of sexual partners, Internet use to seek sexual partners, and locations of sexual encounters. Molecular epidemiology of gonococcal isolates in Amsterdam revealed core groups and clusters of MSM and heterosexual patients that probably indicate distinct transmission networks.
Possessed Robot: How to Find Original Nonverbal Communication Style in Human-robot Interaction

We propose an alternative approach called the Possessed Robot method to find each robot's unique communication strategies. In this approach, the human manipulator behaves as if she/he possesses the robot and finds the optimal communication strategies based on each robot's shape and modalities. We implement the Possessed Robot system (PoRoS) including a reconfigurable body robot, an easier manipulation system, and a recording system to evaluate the validity of our method. We evaluate a block-assembling task by PoRoS by turning on and off the modality of the robot's head. Subsequently, the robot's motion during player's motion significantly increases whereas the ratio of confirmatory behaviour significantly decreases in the head-fixed design. Based on the results, we find an example case for the optimal communication strategy in the head-fixed design. In this case, the robot leads the users and the user follows the robot as in the turn-taking communication style of the humanlike condition. This result shows the feasibility of the Possessed Robot method to make appropriate strategy adjustments based on the robot design.
Comparison of two three-dimensional gated SPECT methods with thallium in patients with large myocardial infarction

BackgroundTwo different commercially available gated single photon emission computed tomography (GSPECT) methods were compared in a population of patients with a major myocardial infarction.MethodsRest thallium GSPECT was performed with a 90-degree dual-detector camera, 4 hours after injection of thallium-201 (Tl-201; 185 MBq) in 43 patients (mean age, 62±12 years) with a large myocardial infarction (mean defect size, 33%±16%). End-diastolic volume (EDV), end-systolic volume (ESV), and left ventricular ejection fraction (LVEF) were calculated by using QGS (Cedars Sinai) and MultiDim (Sopha Medical Vision International, Buc, France). Images were reconstructed by using a 2.5 zoom and a Butterworth filter (order, 5; cut-off frequency, 0.20). LVEF was calculated in all patients by using equilibrium radionuclide angiocardiography (ERNA). EDV, ESV, and LVEF were also measured by using left ventriculography (LVG). ResultsCompared with LVG, QGS underestimated LVEF by means of an underestimation of mean EDV. MultiDim overestimated EDV and ESV. GSPECT EDV and ESV overestimation was demonstrated by means of Bland-Altman analysis to increase with left ventricular volume size (P<.05). The difference between LVG and GSPECT volumes was demonstrated by means of regression analysis to be correlated with infarction size. This effect was particularly important with MultiDim (P<.0001). ConclusionIn Tl-201 GSPECT, LVEF and volume measurements will vary according to the type of software used.
Distributed generation dispatch optimization by artificial neural network trained by particle swarm optimization algorithm

Distributed power generation is a small-scale power generation technology that provides electric power at a site closer to customers than the central generating stations. The Distributed Generation (DG) has been created a challenge and an opportunity for developing various novel technologies in power generation. The proposed work discusses the primary factors that have lead to an increasing interest in DG. DG reduces line losses, increases system voltage profile and hence improves power quality. The proposed work finds out the optimal generation dispatch of the DG by artificial neural network. This ANN has been trained by optimal values of power generation by each DG at different status of network. In order to get over the insufficiency of back-propagation (BP) algorithm, after analyses of particle swarm optimization (PSO) a continuous version of PSO algorithm is proposed. The objective function of PSO algorithm is a combination of cost of loss and cost of power generation by each DG with considering different load state. The feasibility of the proposed method is demonstrated for typical distribution network, and it is compared with the other researches.
Modeling of Transaction Level SystemC modules and transactional channels with Petri nets

Currently, Transaction Level Modeling (TLM) is being used in the industry to solve a variety of practical problems during the design and deployment of electronic systems. TLM and SystemC gain popularity partly due to their simulation capabilities. However, formal models associated to SystemC designs and TLM descriptions are less developed. This paper describes how to translate SystemC modules defined at transactional level to formal Petri Net models. These models offer help in understanding the behaviour of third party modules used in component-based system. This paper focuses mainly on the translation of blocking and non-blocking Interface Method Calls which are the basis of TLM.
Serum levels of G‐CSF, M‐CSF and GM‐CSF in a patient with cyclic neutropenia

To the Editor: Cyclic neutropenia is a unusual disorder characterized by regularly recurring episodes of severe neutropenia, approximately every 21 days (1). The etiology of the disease is not known. In order to elucidate the pathogenesis of the disease, it is essential to examine serum levels of granulopoietic stimulating factors such as granulocyte colonystimulating factor (G-CSF), macrophage colonystimulating factor (M-CSF) and granulocytemacrophage colony-stimulating factor (GM-CSF). Until now, such factors have been investigated with a bioassay using colony-forming methods. However, it is thought that the results of bioassay indicate the summation of the granulopoietic stimulating activities of various cytokines in serum. In the present study we have measured serum levels of G-CSF, M-CSF and GM-CSF in a patient with cyclic neutropenia, using a newly developed enzyme-linked immunosorbent assay (ELISA). A 17-year-old female patient was admitted for therapy of a suppurative eruption in July 1983 and in April 1987. She had the hematological feature that severe neutropenia recurred approximately every 22 d but the number of red blood cells and platlets was within normal ranges. Serum samples from venous blood of the patient at that time were stored at 20°C until assay. Methods of ELISA for G-CSF (2,3) and M-CSF (4) are described in detail elsewhere. Serum GMCSF levels were estimated by human GM-CSF ELISA kit (Genzyme Corporation, Boston, MA) which could measure a concentration of 101000 pg/ml of GM-CSF. Serum G-CSF levels of 50 healthy adults were below the sensitivity of assay (60 pg/ml). Serum M-CSF levels of 10 healthy adults were 3.26 1.04 ng/ml (mean standard deelevated from the normal level with an increase in the number of monocytes during the neutropenic phase and returned to the normal level with the recovery of neutrophils. However, serum GM-CSF was not detectable on any day. Our data concerning serum G-CSF levels are in accordance with the report of Watari et al. (3), although there are no reports concerning serum M-CSF and GM-CSF levels in cyclic neutropenia. These data indicate that there is no primary role for the production of G-CSF and M-CSF in the pathogenesis of cyclic neutropenia. On the other hand, the reason GM-CSF was not detected may be because GM-CSF is produced locally within the bone marrow (5) . The present results suggest the possibility that inhibitory factors to granulopoiesis are important in the pathogenesis of cyclic neutropenia (6, 7).
A fuzzy neural network based on fuzzy hierarchy error approach

This paper presents a novel fuzzy neural network which consists of an antecedent network and a consequent network. The antecedent network matches the premises of the fuzzy rules and the consequent network implements the consequences of the rules. In the network learning and training phase, a concise and effective algorithm based on the fuzzy hierarchy error approach is proposed to update the parameters of the network. This algorithm is simple to implement and it does not require as many calculations as some other classic neural network learning algorithms. A model reference adaptive control structure incorporating the proposed fuzzy neural network is studied. Simulation results of a cart-pole balancing system demonstrate the effectiveness of the proposed method.
Matched sibling donor hematopoietic stem cell transplantation for thalassemia

Purpose of reviewBone marrow transplantation is the only curative treatment for severe thalassemia. Since its successful first report in 1981, more than 4000 patients with this disease worldwide underwent bone marrow transplantation. The purpose of this review is to update the most recent reports of matched sibling donor hematopoietic stem cell transplantation in thalassemia. Recent findingsAdvanced and improved transplant techniques result in the improved outcomes in those transplants from a matched sibling donor with transplant-related mortality less than 5%. Class 3 patients aged at least 7 years and liver enlargement at least 5 cm have a very high risk of graft rejection and regimen-related toxicity. This subset of patients require innovative approaches to overcome the morbidity and mortality. Those include the addition of hydroxyurea, azathioprine, and fludarabine as preconditioning to busulfan, thiotepa, and cyclophosphamide. Novel conditioning consisting of pretransplant immunosuppression with two cycles of fludarabine and dexamethasone followed by reduced intensity conditioning with fludarabine, busulfan, and thymoglobulin has been developed. SummaryBone marrow transplantation in young low-risk (class 1 and 2) patients should be performed as soon as possible. For class 3 severe thalassemia, novel conditioning regimens have been developed to overcome graft rejection and regimen-related toxicity. Hematopoietic stem cell transplantation in adults who have been well chelated should be offered with clinical trials.
GSPNs versus SPNs: what is the actual role of immediate transitions?

Stochastic Petri nets (SPNs) and generalized stochastic Petri nets (GSPNs) are compared in order to investigate the role of immediate transitions. The comparison is based on the ability of the two formalisms to define models that can be 'scalable' with respect to the initial marking. An intermediate model between (G)SPN structures and (G)SPN systems called 'family' is introduced as a reference for the comparison. It is shown that GSPN families exist that do not have SPN counter- parts. An algorithm is given to reduce GSPN to SPN families in the cases in which this is possible. The application of this structural reduction algorithm allows a more efficient generation of the state space of GSPN systems. <<ETX>>
Bridging the gap between TCAD and ECAD methodologies in deep sub-micron interconnect extraction and analysis

Dominance of interconnect parasitics in impacting functionality, performance and reliability in deep sub-micron (DSM) designs is a well known topic. Reduced metal pitches, process variations, new materials for metallization/dielectrics emphasizes an increased need for "accurate" technology modeling of interconnect. In the mean time, continued design integration, increased chip sizes and market pressures call for faster but "accurate" EDA methodologies and tools. This tutorial provides a complete perspective of the TCAD interconnect modeling issues and how these could be addressed in ECAD methodologies and tools.
Effect of Temperature Variation and Packaging on SOI MEMS Inductor With DRIE Trench on Low-Resistivity Substrate

This paper reports the implementation and wafer-level mechanical and RF testing of three types of MEMS inductor-octagonal, square, and circular; the latter over a temperature range -30°C to 150 °C. The devices were fabricated using a silicon on insulator process with deep reactive ion etching (DRIE) trench on a low-resistivity substrate (ρ = 1-10 Ω cm) and contains gold bond wire overpass to complete the inductance loop. The three inductors exhibited nominal inductance of 3.36, 12.15, and 3.29 nH with peak quality factor of 9.51, 6.91, and 7.26, respectively, and self-resonance frequency more than 10 GHz. Afterward, the inductors were packaged in a pin grid array package and postpackaging RF testing was carried out to analyze the effect of packaging on RF performance of the inductors.
Vision for Mobile Robot Navigation

Vision is a very important sense for humans. Robots also need to be aware of their environment for working in it. This is even more important for mobile robots that operate in unknown environments that are not prepared for robots. In this paper, we focus on the aspect of navigation of mobile robots for applications in search and rescue as well as planetary exploration. We discuss a typical vision pipeline and navigation stack that has been developed at the Institute of Robotics and Mechatronics of the German Aerospace Center (DLR). In recent years, we have successfully applied the solution to a number of crawling, driving and flying robots. We present mobile systems in several applications and also discuss the relation between computer vision and photogrammetry.
Use of an anterior chamber maintainer in the surgical management of traumatic hyphaemas

Surgical intervention in traumatic hyphaemas becomes necessary when high intraocular pressure (IOP) is intractable and there is persistent corneal staining. Anterior chamber (AC) washout and elimination of blood clots have been described previously using one paracentesis. We describe the value of creating two paracenteses. The first one is made in the lower temporal quadrant and accommodates a 20‐gauge anterior chamber maintainer (ACM) that is connected to a bottle of Balanced Salt Solution. The second paracentesis is made in an upper quadrant and serves to evacuate liquefied blood and blood clots. With an ACM in place, the fluctuations of intraoperative IOP are minimized and the AC depth is stabilized throughout the operation. The risk of renewed bleeding is reduced because of the continuous positive intraoperative IOP. The ACM is an important tool in the surgical management of traumatic hyphaemas because it facilitates AC washout and reduces iatrogenic damage to the iris and corneal endothelium.
Optimal temporal path on spatial decaying networks

We introduce temporal effect to the classical Kleinberg model and study how it affects the spatial structure of optimal transport network. The initial network is built from a regular d-dimensional lattice added by shortcuts with probability p(rij) r ij , where rij is the geometric distance between node i and j. By assigning each shortcut an energy E = r , a link with length r survives within period , which leads the network to a decaying dynamics of constantly losing long-range links. We find new optimal transport in the dynamical system for = 3 d , in contrast to any other result in static systems. The conclusion does not depend on the information used for navigation, being based on local or global knowledge of the network, which indicates the possi- bility of the optimal design for general transport dynamics in the time-varying network.
Wrapper and Filter Metrics for PSO-based Class Balance Applied to Protein Subcellular Localization

Recent advances in proteomic research have generated an unprecedented amount of stored data. Given the size of current databases, manual annotation has become an almost intractable process, paving the way to the use of computational methods. In this context, considering that a single protein can belong to several functional classes, a multi-label classification problem is generated. The most common way to cope with these problems is by training a number of classifiers equal to the number of classes that will allow taking independent decisions on the membership of proteins. Nevertheless, this methodology leads to a high degree of imbalance between classes, magnifying the disparity already present in their size. Current balancing techniques are based on the optimization of criteria leading to a better subset that represent the data. Moreover, most of the sample selection criteria are based on the Wrapper type metrics. However, Wrapper metrics are computationally quite expensive. This work presents a comparative analysis between the Wrapper and Filter metrics as the sample selection criteria in balance techniques. In order to accomplish this task, a subsampling technique based on the Particle Swarm Optimization method to obtain the optimal balance subset is used. The results show that filter metrics notably improved the computational cost obtaining a similar performance when compared with the Wrapper type metrics.
Unsupervised classification of vineyard parcels using SPOT5 images by utilizing spectral and textural features

In order to support agricultural management of vineyards, high spatial resolution remote sensing images (less than 1 meter) enables textural representation of their periodic plantation pattern which helps for delineation. Even though this texture analysis may provide highly accurate delineation of vineyards, it may be infeasible at national scale, due to the computational complexity of texture extraction. In addition, particularly for Turkey, plantation practices for vineyards deviate from common periodic pattern, which can make those textures insufficient. In this study, we used SPOT5 images to explore their capabilities for delineation of vineyard parcels, without any a priori parcel information. As the inter-row distance and the spacing between the individual vine plants are less than the used 2.5m panchromatic, which is generated from 2×5m scenes (nadir) for panchromatic and 10m (nadir) spatial resolutions for multi-spectral bands, currently used periodicity based (Fourier) texture analysis may be vague. Therefore, we used Gabor textures (with different scales and directions) to define texture characteristics at this relatively coarse resolution, and we integrated these textures with image bands (visible, near infrared and shortwave infrared) which hold the ability to spectrally distinguish the vine plants from the remaining crops. For the vineyards parcels recognition, we classified the extracted features by a recent hierarchical clustering method based on self-organizing neural networks. We compared the performance of this proposed method to the object-based image analysis (by eCognition) which depends on multi-scale image segmentation and user-defined decision rules with corresponding thresholds.
Planar-Integrated Magnetics (PIM) Module in Hybrid Bidirectional DC–DC Converter for Fuel Cell Application

In most power electronics converters, the overall volume is mainly determined by the number of parts and the size of passive components. Integrated magnetics and planar magnetics techniques, therefore, have been an excellent option in order to reduce the counts and the size of magnetic components, hereby increasing the power density of converters. In this paper, a new planar-integrated magnetics (PIM) module for a phase-shift plus duty-cycle-controlled hybrid bidirectional dc-dc converter is proposed, which assembles one boost inductor and two transformers into an E-I-E core geometry, reducing the number of parts, the total volume of converter, as well as the total core loss of the magnetic components. AC losses in the windings and leakage inductance of the transformers are kept low by interleaving the primary and secondary turns of the transformers. To verify the validity of the design approach and theoretical analysis, a laboratory prototype employing the PIM module is implemented for a fuel cell application with 20-40-V input voltage and 400-V output voltage. Detailed results from the experimental comparisons demonstrate that the PIM module is fully functional and electromagnetically equivalent to the discrete magnetics and a significant reduction of size can be achieved by using the PIM module.