Miracle-dz/UniFAR-FTUs huggingface dataset:
Physiological effects of electroconvulsive therapy and transcranial magnetic stimulation in major depression

Major depressive episodes are associated with dysregulation of various physiologic systems. Antidepressant medications alter regulation of the hormonal and sleep systems. A thorough understanding of these changes may elucidate the pathophysiologic basis of the disorder [Amsterdam et al., 1989: Psychoneuroendocrinology 14:43–62], and interventions targeted directly at these systems are being increasingly recognized as possible treatments for depression [Wong et al., 2000: Proc Natl Acad Sci USA 97:325–330; Szuba et al., 1996: Proc Am Coll Neuropsychopharmacol Ann Meet]. These physiologic systems are regulated by the major neurotransmitters implicated in the etiology of mood disorders—norepinephrine, serotonin, and dopamine. Many of the hormones of import for this article also act as neurotransmitters and thus alter cerebral activity themselves [Owens and Nemeroff, 1993: Ciba Found Symp 172:296–308; Weitzner, 1998: Psychother Psychosom 67:125–132]. Parenteral infusion of hydrocortisone [DeBattista, 2000: Am J Psychiatry 157:1334–1337] and thyrotropin‐releasing hormone (TRH) [Prange et al., 1972: Lancet 2:999–1002; Marangell et al., 1997: Arch Gen Psychiatry 54:214–222; Szuba, 1996: Proc Am Coll Neuropsychopharmacol Ann Meet. ] produce acute antidepressant effects. Antagonists to corticotropin‐releasing hormone and repeated parenteral infusion of TRH may have antidepressant activity when given during several weeks [Wong, 2000: Proc Natl Acad Sci USA 97:325–330; Arborelius et al., 1999: J Endocrinol 160:1–12; Callahan et al., 1997: Biol Psychiatry 41:264–272]. Manipulations of the sleep system through sleep deprivation can ameliorate depression [Szuba et al., 1994: Psychiatry Res 51:283–295; see Wirz‐Justice et al., 1999: Biol Psychiatry 46:445–453 for review]. Sleep deprivation has been shown in more than three dozen studies published in the last three decades to produce marked, acute antidepressant effects in the majority of depressed individuals [Wirz‐Justice, et al., 1999: Biol Psychiatry 46:445–453]. Thus, examination of the effects the two nonpharmacologic treatments, electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS), produce in these physiologic systems may help elucidate their mechanisms of action, while enhancing understanding of the neurobiology of depressive illness. We will review these physiologic changes associated with depression, the effects that manipulations of these systems can have on depressive disorders, and then describe the effects the two techniques that can stimulate the human brain in vivo, ECT and TMS, exert on these systems. Depression and Anxiety 12:170–177, 2000. © 2000 Wiley‐Liss, Inc.
Circulating Progenitor Cells Identify Peripheral Arterial Disease in Patients With Coronary Artery Disease.

RATIONALE Peripheral arterial disease (PAD) is a clinical manifestation of extracoronary atherosclerosis. Despite sharing the same risk factors, only 20% to 30% of patients with coronary artery disease (CAD) develop PAD. Decline in the number of bone marrow-derived circulating progenitor cells (PCs) is thought to contribute to the pathogenesis of atherosclerosis. Whether specific changes in PCs differentiate patients with both PAD and CAD from those with CAD alone is unknown. OBJECTIVE Determine whether differences exist in PCs counts of CAD patients with and without known PAD. METHODS AND RESULTS 1497 patients (mean age: 65 years; 62% men) with known CAD were identified in the Emory Cardiovascular Biobank. Presence of PAD (n=308) was determined by history, review of medical records, or imaging and was classified as carotid (53%), lower extremity (41%), upper extremity (3%), and aortic disease (33%). Circulating PCs were enumerated by flow cytometry. Patients with CAD and PAD had significantly lower PC counts compared with those with only CAD. In multivariable analysis, a 50% decrease in cluster of differentiation 34 (CD34+) or CD34+/vascular endothelial growth factor receptor-2 (VEGFR2+) counts was associated with a 31% (P=0.032) and 183% (P=0.002) increase in the odds of having PAD, respectively. CD34+ and CD34+/VEGFR2+ counts significantly improved risk prediction metrics for prevalent PAD. Low CD34+/VEGFR2+ counts were associated with a 1.40-fold (95% confidence interval, 1.03-1.91) and a 1.64-fold (95% confidence interval, 1.07-2.50) increases in the risk of mortality and PAD-related events, respectively. CONCLUSIONS PAD is associated with low CD34+ and CD34+/VEGFR2+ PC counts. Whether low PC counts are useful in screening for PAD needs to be investigated.
A Feature Subset Selection Method based on Conditional Mutual Information and Ant Colony Optimization

Feature subset selection is one of the important problems in a number of fields namely data mining, machine learning, pattern recognition. It refers to the problem of opting for useful features that are neither irrelevant nor redundant. Since most of the data acquired through different sources are not in a proper shape to mine useful patterns from it therefore feature selection is applied over this data to filter out useless features. But since feature selection is a combinatorial optimization problem therefore exhaustively generating and evaluating all possible subsets is intractable in terms of computational cost, memory usage and processing time. Hence such a mechanism is required that intelligently searches for useful set of features in a polynomial time. In this study a feature subset selection algorithm based on conditional mutual information and ant colony optimization is proposed. The proposed method is a pure filter based feature subset selection technique that incurs less computational cost and proficient in terms of classification accuracy. Moreover, along with high accuracy it opts for less number of features. Extensive experimentation is performed based on thirteen benchmark datasets over a number of well known classification algorithms. Empirical results endorse efficiency and effectiveness of the proposed method.
Invasive weed optimization algorithm optimized fuzzy logic scaling parameters in controlling a lower limb exoskeleton

This paper describes a new modified versions of invasive weed optimization algorithm with exponential seeds-spread factor. The modified invasive weed optimization algorithm (MIWO) is employed to optimize the fuzzy input-output scaling factors of lower limb exoskeleton. A fuzzy logic control (FLC) system with the (MIWO) are evolved for reference tracking control. The exoskeleton is developed to enhance and upgrade the lower limb capability and augment the torque of knee and hip of elderly people during the walking cycle. Invasive weed optimization is a bio-inspired search algorithm that mimics how weeds colonize a certain area in nature. The algorithm is modified by applying local knowledge during distribution of seeds that depends on their cost function value in each generation to narrow the accuracy and improve the local search ability. The obtained results from the modified invasive weed optimization algorithm are compared with heuristic gain values to improve the performance of the exoskeleton system. The Visual Nastran 4D software is used to develop a simulation model of the humanoid and an exoskeleton for testing and verification of the developed control mechanism. Simulation results demonstrating the performance of the adopted approach are presented and discussed.
Study of Some Distance Measures for Language and Encoding Identification

To determine how close two language models (e.g., n-grams models) are, we can use several distance measures. If we can represent the models as distributions, then the similarity is basically the similarity of distributions. And a number of measures are based on information theoretic approach. In this paper we present some experiments on using such similarity measures for an old Natural Language Processing (NLP) problem. One of the measures considered is perhaps a novel one, which we have called mutual cross entropy. Other measures are either well known or based on well known measures, but the results obtained with them vis-avis one-another might help in gaining an insight into how similarity measures work in practice. The first step in processing a text is to identify the language and encoding of its contents. This is a practical problem since for many languages, there are no universally followed text encoding standards. The method we have used in this paper for language and encoding identification uses pruned character n-grams, alone as well augmented with word n-grams. This method seems to give results comparable to other methods.
Study on the Qualitative Defects Detection in Composites by Optical Infrared Thermography

In this paper, infrared thermography measurement technique has been used to develop standard measurement technique for nondestructive testing of composite materials which is widely used in aerospace industries. To increase the defect detection rate, the related experiment used the lock-in IR-thermographiy method. Therefore it is of considerable interest in the field of non-destructive testing for fast discontinuity detection by using ultrasonic lock-in infrared thermography. The result also shows that as the investigation period of light source is lengthened according to the thickness of specimen, the possibility of detecting defects gets higher as well. However, the reason why the result values were not favorable when less than 50 mHz of light source was provided is because it was difficult to detect defects as the defect parts became a state of thermal equilibrium in general when thermal diffusivity affects the entire materials.
Near-Index-Match refractive beam shapers

A method for designing and fabricating aspherical transmissive beam shaping elements for the visible and near-IR is described. Both rotationally symmetric and non-symmetric aspheres can be fabricated as Near-Index-MatchTM optics. The aspherical surface is machined or mastered using a conventional NC machine. A sandwich of two transmissive materials is formed, with the refractive phase the product of the surface relief and the index difference. Both far-field (Dickey, Romero, and Holswade) beam shapers and near-field (Rhodes and Shealy) beam shapers can be realized, as well as two-element systems with phase correction of the shaped beam. Design methodologies and results are presented.
Variable Sampling Period Filter PLL for Distorted Three-Phase Systems

This paper proposes a novel variable sampling period filter phase-locked loop (VSPF-PLL) for use in the general area of three-phase systems. It is based on the concept of variable sampling period, which allows to automatically adjust the sampling frequency to be NPLL times the line frequency. Conventional three-phase PLL are based on synchronous reference frames (SRFs) to estimate the phase error between the PLL and the input signals. However, SRF transform fail when the voltage waveforms are distorted. In this paper, a sliding-Goertzel-transform- based filter is used in the loop to reject disturbances, such as unbalanced voltage and harmonics. It allows to detect the positive sequence present in the systems without errors. Characteristics of VSPF-PLL, including its mathematical model as well as steady state and dynamic responses, are discussed in this paper. The method is implemented in a DSP and tested using typical disturbances, such as frequency steps, unbalances, harmonics, saturation, and line-to-ground fault. Comparative simulations are performed between the proposed VSPF-PLL and some of the most common three-phase PLL described in the literature. Advantages of the proposed system over the methods analyzed are also discussed. Structural simplicity, robustness, and harmonics rejection are other attractive features offered by the proposed system.
Towards continuous policy-driven demand response in data centers

Demand response (DR) is a technique for balancing electricity supply and demand by regulating power consumption instead of generation. DR is a key technology for emerging smart electric grids that aim to increase grid efficiency, while incorporating significant amounts of clean renewable energy sources. In today's grid, DR is a rare event that only occurs when actual peak demands exceed the expected peak. In contrast, smart electric grids incentivize consumers to engage in continuous policy-driven DR to 1) optimize power consumption for time-of-use pricing and 2) deal with power variations from non-dispatchable renewable energy sources. While data centers are well-positioned to exploit DR, applications must cope with significant, frequent, and unpredictable changes in available power by regulating their energy footprint. The problem is challenging since data centers often use distributed storage systems that co-locate computation and storage, and serve as a foundation for a variety of stateful distributed applications. As a result, existing approaches that deactivate servers as power decreases do not translate well to DR, since important application-level state may become completely unavailable. In this paper, we propose a DR-compatible storage system that uses staggered node blinking patterns combined with a balanced data layout and popularity-based replication to optimize I/O throughput, data availability, and energy-efficiency as power varies. Initial simulation results show the promise of our approach, which increases I/O throughput by at least 25% compared to an activation approach when adjusting to real-world wind and price fluctuations.
Combining Conventional Lithography with Molecular Self‐Assembly for Chemical Patterning

Chemical patterning can incorporate self-assembled molecules as basic building blocks and active components to develop functional films for applications ranging from sensor platforms to hierarchical structures. Reported here is a new method for the creation of chemical patterns that combines self-assembly, [1] lithographic resists, and photo-oxidation. [2] An important aspect of this process is the resist, which is robust enough to allow subsequent chemical processing involving UV-ozone oxidation and self-assembly deposition while acting as a shield to protect the components of the films from one another. In this way, we are able to exploit the parallel wafer-scale processing of conventional lithography in order to pattern chemical functionality. This opens a new avenue for directed chemical patterning of multicomponent self-assembled films.
Thermal issues in deep sub-micron FDSOI circuits

Self-heating effects became more prominent with the introduction of the modern devices like FDSOI and low thermal conductivity materials such as SiO2. Consequently, the design of high speed digital circuits which are the time-critical blocks of high performance processors started to be limited mainly by thermal issues. For observing the thermal behaviour of FDSOI structure on circuit level, a 64-bit Kogge-Stone parallel prefix adder is designed and implemented in 40nm bulk CMOS technology and thermal model of the circuit is extracted and simulated according to FDSOI design parameters. The implemented adder circuit has a critical path delay of 148ps under 900 mV power supply voltage with a power consumption of 12mW. The temperature profile of the designed circuit is extracted with thermal simulations and the peak temperature locations are examined in detail. The hot spot locations and their temperature values are correlated with the power density. It is shown that self-heating of high power density devices has a significant influence on the peak temperature of a design. Finally, a simple design solution is proposed which can significantly decrease the peak temperature.
H-Techsight - a Next Generation Knowledge Management Platform

A new breed of Knowledge Management Systems (KMS), referred to as the Next Generation of Knowledge Management (NGKM), aims at overcoming the limitations of existing KMS regarding the range and quality of supportable Knowledge Management activities. Therefore, AI-based technologies are employed to enable automated knowledge item processing instead of the information retrieval functionality provided by conventional KMS. This paper presents the Knowledge Management Platform (KMP) developed in the h-TechSight project as an NGKM solution. It is designed to support organizations in technology intensive industries in monitoring changes in their external environment as an important factor in competitiveness. Therefore, the KMP combines NGKM enabling technologies for automatically observation of information resources on the Internet in order to notify users whenever a change in their domain of interest occurs. The aim of this paper is to position the KMP as a KMS of the next generation and to delineate the lessons learned in KMS design in the h-TechSight project. Thus, we illustrate the idea of NGKM with special emphasis on enabling technologies and, on this basis, expose the functional design and technical realization of the h-TechSight KMP.
Neptune: a domain specific language for deploying hpc software on cloud platforms

In this paper, we present the design and implementation of Neptune, a domain specific language (DSL) that automates configuration and deployment of existing HPC software via cloud computing platforms. We integrate Neptune into a popular, open-source cloud platform, and extend the platform with support for user-level and automated placement of cloud services and HPC components. Such platform integration of Neptune facilitates hybrid-cloud application execution as well as portability across disparate cloud fabrics. Supporting additional cloud fabrics through a single interface enables high throughput computing (HTC) to be achieved by users who do not necessarily own grid-level resources but do have access to otherwise independent cloud technologies. We evaluate Neptune using different applications that employ a wide range of popular HPC packages for their implementation including MPI, X10, MapReduce, DFSP, and dwSSA. In addition, we show how Neptune can be extended to support other HPC software and application domains, and thus be used as a mechanism for many task computing (MTC).
Cosed-loop control impact on condition monitoring of high-resistance connections in PMSM based on power signature analysis

Permanent magnet synchronous motors (PMSMs) are used for large variety of applications in industry, mainly because of their high efficiency suitable for automotive and traction systems. In this context, diagnosing stator faults is crucial for ensuring high motor performance and reliability. The influence of the Closed-loop (CL) control scheme must be considered when the diagnosis of stator asymmetry is derived from the signature analysis of electrical quantities. Therefore, an examination of the spectral content of the investigated quantities for different bandwidths of CL regulators, under faulty conditions is needed to assess the efficiency of the fault indexes. In this paper, the performances of two different techniques, for detecting stator asymmetry are investigated. The first method is based on motor current signature analysis (CSA), and the second is based on power signature analysis (PSA). Results derived from numerical simulations and experimental tests are here presented showing the validity of the established comparative study.
Discovering popular routes from trajectories

The booming industry of location-based services has accumulated a huge collection of users' location trajectories of driving, cycling, hiking, etc. In this work, we investigate the problem of discovering the Most Popular Route (MPR) between two locations by observing the traveling behaviors of many previous users. This new query is beneficial to travelers who are asking directions or planning a trip in an unfamiliar city/area, as historical traveling experiences can reveal how people usually choose routes between locations. To achieve this goal, we firstly develop a Coherence Expanding algorithm to retrieve a transfer network from raw trajectories, for indicating all the possible movements between locations. After that, the Absorbing Markov Chain model is applied to derive a reasonable transfer probability for each transfer node in the network, which is subsequently used as the popularity indicator in the search phase. Finally, we propose a Maximum Probability Product algorithm to discover the MPR from a transfer network based on the popularity indicators in a breadth-first manner, and we illustrate the results and performance of the algorithm by extensive experiments.
Manipulation of deformable objects without modeling and simulating deformation

We present a method to manipulate deformable objects that does not require modeling and simulating deformation. Our method is based on the concept of diminishing rigidity, which we use to quickly compute an approximation to the Jacobian of the deformable object. This Jacobian is used to drive the points within the deformable object towards a set of targets. However, this Jacobian alone is insufficient to avoid stretching the object beyond its allowed length and to avoid gripper collision with obstacles. Thus a key part of our approach is incorporating techniques to avoid collision and excessive stretching. Our experiments show how to perform several interesting tasks for one and two-dimensional deformable objects using our method. They also show how the method can be applied to collaborative tasks, where the robot and a user simultaneously manipulate the deformable object. Our experiments are conducted in simulation but we emphasize that our method does not have access to the model of the deformable object used by the simulator, although we assume we are able to sense the geometry of the object. While our method is local, we find that it is quite versatile in the range of tasks it can perform, especially since it has no knowledge of the model of the deformable object.
Rossby number expansions, slaving principles, and balance dynamics

We consider the problem of constructing balance dynamics for rapidly rotating fluid systems. It is argued that the conventional Rossby number expansion—namely expanding all variables in a series in Rossby number—is secular for all but the simplest flows. In particular, the higher-order terms in the expansion grow exponentially on average, and for moderate values of the Rossby number the expansion is, at best, useful only for times of the order of the doubling times of the instabilities of the underlying quasi-geostrophic dynamics. Similar arguments apply in a wide class of problems involving a small parameter and sufficiently complex zeroth-order dynamics. A modified procedure is proposed which involves expanding only the fast modes of the system; this is equivalent to an asymptotic approximation of the slaving relation that relates the fast modes to the slow modes. The procedure is systematic and thus capable, at least in principle, of being carried to any order—unlike procedures based on truncations. We apply the procedure to construct higher-order balance approximations of the shallow-water equations. At the lowest order quasi-geostrophy emerges. At the next order the system incorporates gradient-wind balance, although the balance relations themselves involve only linear inversions and hence are easily applied. There is a large class of reduced systems associated with various choices for the slow variables, but the simplest ones appear to be those based on potential vorticity.