Miracle-dz/UniFAR-FTUs huggingface dataset:
Perspectives on the role of serotonergic mechanisms in the pharmacology of schizophrenia

Sirs, Busatto and Kerwin (1997) remind us we have progressed far toward a clearer understanding of the nature of neurochemical dysfunction in the brains of schizophrenic patients since the initial serendipitous observations describing the pharmacological efficacy of antipsychotic medications. Nonetheless, the remarkable story of the discovery and recent rediscovery of antipsychotics, including the careful demonstration of medication-responsive classes of symptoms to atypical agents still leaves a gnawing dissatisfaction about how much
Expectation-Maximization as lower bound maximization

The Expectation Maximization algorithm given by Dempster et al has enjoyed considerable popularity for solving MAP estimation problems This note derives EM from the lower bounding viewpoint Luttrell which better illustrates the convergence properties of the algorithm and its variants The algorithm is illustrated with two examples pooling data from multiple noisy sources and tting a mixture density
Cumulant based Teager energy operator for ECG signal modeling

In this paper a cumulant based Teager energy operator (TEO) method is proposed to enhance the morphological features of noisy stress ECG signals which are corrupted with Gaussian noise, and other artifacts like baseline wander. It uses higher order statistical (HOS) cumulants in combination with nonlinear TEO required for the analysis of nonlinear and non stationary signals. Higher order cumulants suppress the Gaussian noise and TEO derives an energy from nonlinear components in time and frequency domains. It exhibits an attractive feature of retrieving a clean ECG from noisy recordings with extremely poor SNR of up to 10 dB. The mean of Teager energy (TE) in time as well as frequency domains and improvement in signal to noise ratio (SNRI) are the statistical measures used for classification. Results reveal the efficacy of the proposed method in improving the signal to noise ratio and computing the energy in time and frequency domains.
A rare case of paratesticular pleomorphic rhabdomyosarcoma diagnosed by fine needle aspiration: A case report

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of children and young adults. It represents 6.5% of all malignant tumors in pediatrics with an annual incidence of 4 to 7 cases per million children. Embryonal RMS arising in paratesticular region in young males is a common entity, however pleomorphic RMS in such location is quite rare. An eighteen year old male presented with painless right scrotal mass measuring 7× 6 × 5 cm of two year duration, which was reported on ultrasonography as extratesticular tumor. Fine needle aspiration showed cellular smears comprising of pleomorphic population of mostly singly scattered cells and few cell aggregates. Few isolated large cells with whip like cytoplasmic processes and faint cross‐striations were also seen. A diagnosis of paratesticular malignant mesenchymal tumor probably RMS was made. Tumor was removed surgically with right sided orchidectomy. On histopathology, it was reported as pleomorphic RMS. There was focal lymphatic invasion and involvement of rete testis. Immunostaining of tumor cells revealed myogenin and desmin positivity. The case is being presented because of diagnosis of RMS on Fine needle aspiration and rare occurrence of pleomorphic RMS in paratesticular location. Diagn. Cytopathol. 2010. © 2009 Wiley‐Liss, Inc.
hNMP 200: a novel human common nuclear matrix protein combining structural and regulatory functions.

Previously we have reported about human nuclear matrix proteins (hNMPs) with increased reassembling and potential filament-forming capability [C. Gerner et al., 1999, J. Cell. Biochem. 74, 145-151]. Here, we cloned the cDNA of one of these proteins, hNMP 200, following partial amino acid sequencing of the novel 56-kDa nuclear protein. Sequence alignments show hNMP 200-related proteins in metazoans, plants, and yeast, the homologous Saccharomyces cerevisiae protein prp19 being an accessory, but essential, factor for pre-mRNA processing. Evidence for any enzymatic activity was not detected. However, the hNMP 200 primary sequence contained five consensus WD-repeat sequences, indicative of participation and regulatory function in larger protein assemblies. Northern blot analysis and 2D protein electrophoresis showed ubiquitous expression of hNMP 200 in a variety of cell types. (35)S labeling studies indicated a high metabolic stability of the protein. The hNMP 200 gene was assigned to chromosomal region 11q12.2. Confocal laser scanning microscopy revealed that the intracellular localization conformed with that reported for other structural nuclear proteins. In interphase cells, green fluorescent protein-tagged hNMP 200 was predominantly nucleoplasmic. Structures with speckled appearance extended through several sections of in situ-isolated nuclear matrices. During cell division hNMP 200 became irregularly distributed in prophase, sparing regions of condensing chromatin. In anaphase it was concentrated in the spindle midzone. The putative dual function of the novel NMP is discussed. Being a component of the nuclear framework, it may provide structural support for components of the RNA-processing machinery, thereby also modulating splicing activities.
Visuospatial Working Memory in ADHD Patients, Unaffected Siblings, and Healthy Controls

Objective: The aim of this study was to (a) test the usefulness of visuospatial working memory (VSWM) as an endophenotype for ADHD and (b) study the developmental trajectory of VSWM in ADHD. Method: A total of 110 ADHD patients, 60 unaffected siblings, and 109 controls, aged 8 to 29 years, were assessed on VSWM functioning. Multilevel analyses were carried out to account for the correlation between measurements within families. Results: ADHD patients showed impaired VSWM performance compared with unaffected siblings and controls, with comparable performance between unaffected siblings and controls. Impaired VSWM in ADHD patients was not more pronounced on higher memory loads, signifying executive rather than storage deficits as an underlying mechanism. ADHD patients, unaffected siblings, and controls showed parallel developmental trajectories of VSWM. Conclusion: Current findings question the usefulness of VSWM as a neurocognitive endophenotype for ADHD and provide unique insights into the developmental trajectory of VSWM in ADHD.
Examination criteria and calibration procedures for prevention trials of the Early Childhood Caries Collaborating Centers.

OBJECTIVES To summarize diagnostic criteria and examiner training and calibration of the National Institute of Dental and Craniofacial Research-funded Early Childhood Caries Collaborating Centers (EC4) and report examiner calibration results from 2010 to 2014. The EC4 at Boston University, University of Colorado, and University of California San Francisco are performing randomized controlled early childhood caries (ECC) prevention trials with caries as the main outcome measure. METHODS The EC4 with University of Iowa consultants developed standardized tooth and tooth surface status examination criteria for use in field conditions, examiner training materials, and examiner calibration and re-calibration methodologies. Calibration and re-calibration were performed with 1- to 5-year-old children in the San Francisco Mission District in which assessments from each examiner to be calibrated were compared with those from a single gold standard examiner from 2010 to 2014. Cohen's kappa statistic was used to determine inter-examiner agreement. RESULTS A total of seven examiners were successfully (re)calibrated during that period, examining a total of 231 children. Overall unweighted Cohen's kappas for 10 surface conditions exceeded the criterion of 0.70. However, separate agreement for assessment of noncavitated lesions, as in other studies, was lower. CONCLUSIONS An experienced multidisciplinary and multi-institutional team was able to develop criteria and training materials to anticipate situations and field conditions the main trials would encounter. Examiners were successfully trained and (re)calibrated.
Reference curves based on non‐parametric quantile regression

Reference curves which take time into account, such as those for age, are often required in medicine, but simple systematic and efficient statistical methods for constructing them are lacking. Classical methods are based on parametric fitting (polynomial curves). Semi‐parametric methods are also widely used especially in Europe. Here, we propose a new methodology for the estimation of reference intervals for data sets, based on non‐parametric estimation of conditional quantiles. The derived methods should be applicable to all clinical (or more generally biological) variables that are measured on a continuous quantitative scale. As an example, we analyse a data set collected to establish reference curves for biophysical properties of the skin of healthy French women. The results are compared to those obtained with Royston's polynomial parametric method and the semi‐parametric LMS approach. Copyright 2002 John Wiley & Sons, Ltd.
Motion reconstruction with a low-cost MEMS IMU for the automation of human operated specimen manipulation

We consider the problem of automating the motion performed by a human operator when manipulating a specimen in tasks such as visual inspections for defects. This is a typical situation in which the trajectory of the manipulated object is hardly described by analytical functions, since the actual movements are suggested more by the operator's experience, rather than a standardized protocol. In principle, traditional motion capture systems based on computer vision methods could be employed to reconstruct the motion: however, especially when manipulating small specimens, visual occlusions caused by the operator's hand prevent the correct tracking of the moving object. In this paper, we investigate the possibility of reconstructing the motion by using the information provided by a low-cost MEMS Inertial Measurement Unit (IMU) attached to the specimen. For simple manipulating tasks such as shaking and rotations, we show that the motion capture system based on inertial measurements can be effectively used.
Interactive object segmentation in digital images by foreground/background region classification with hierarchical queues

Abstract In this paper, we present work on interactive object segmentation in digital images. The user can employ the proposed work to separate the target object from the background easily. After marker drawing of foreground and background from a user, the user interface shows the target object in original color and the background in some other specific color, respectively. Compared with the tedious steps of Adobe Photoshop, the user can interactively approximate the contour of the target object with more efficiency. Our proposed algorithm is based on Foreground/Background region classification by comparing the similarity of color information. At first, the user interface processes the input image by watershed segmentation to produce the segmented regions. Then, some unlabeled regions are assigned as foreground regions or background regions by marker drawing. After marker drawing, the remaining unlabeled regions are processed by Foreground/Background region classification. In our implementation, we also introduce hierarchical queues to store the unlabeled regions during the procedure of region classification. The target object is segmented after Foreground/Background region classification. In our experiments, the proposed algorithm provides output with high accuracy and low effort.
The paradox of hypnosis and pain: From the power of the hypnotherapist to the patient's sense of control

One of the main advantages of hypnosis in the management of chronic pain is its holistic approach, which centers on the patient-doctor relationship and the sense of control perceived by the patient. Researchers have been interested in the cognitive aspects of pain, including attention, sense of control and pain coping strategies. Paradoxically, hypnosis is often considered a mix of influence, suggestion, and the power of the hypnotist over the hypnotized patient. To better understand the apparent paradox created by hypnosis, in terms of power and control, we examine the aspects of power in the relationship between the patient and doctor and examine how hypnosis redistributes this power to help patients better manage pain.
Methods For Collecting Myoelectric Signals From Individuals With Lower Limb Amputations

Technological advancements in lower limb prostheses have resulted in actuated motors in both knees and ankles. Currently, these components are controlled by information measured from various electromechanical sensors attached to the prosthesis. Our aim is to enhance the control information provided to powered prosthetic components by including input from the user via interpreted myoelectric signals (MESs). To extract useful control information, it is imperative that consistent, high-quality MESs be collected from patients each time they don the socket. In this work, we present approaches to maintaining consistent electrode placements on individuals with transfemoral and transtibial amputations during static non-weight-bearing conditions and dynamic weight-bearing activities. Our results show that a variety of methods, similar to those used in upper limb fittings, may be used to collect high-quality MESs during static non-weight-bearing conditions. MES collection during dynamic weight-bearing activities is more challenging. The type, size, shape, and placement of electrodes must be carefully chosen to maintain contact with the skin without compromising comfort during weightbearing activity.
Consensus of k-NNs for Robust Neighborhood Selection on Graph-Based Manifolds

Propagating similarity information along the data manifold requires careful selection of local neighborhood. Selecting a "good" neighborhood in an unsupervised setting, given an affinity graph, has been a difficult task. The most common way to select a local neighborhood has been to use the k-nearest neighborhood (k-NN) selection criterion. However, it has the tendency to include noisy edges. In this paper, we propose a way to select a robust neighborhood using the consensus of multiple rounds of k-NNs. We explain how using consensus information can give better control over neighborhood selection. We also explain in detail the problems with another recently proposed neighborhood selection criteria, i.e., Dominant Neighbors, and show that our method is immune to those problems. Finally, we show the results from experiments in which we compare our method to other neighborhood selection approaches. The results corroborate our claims that consensus of k-NNs does indeed help in selecting more robust and stable localities.
An Efficient SRA Based Isomorphic Task Allocation Scheme for k - ary n - cube Massively Parallel Processors

A good task allocation algorithm should find available processors for incoming jobs, if they exist, with minimum overhead. Due to its topological generality and flexibility the k-ary n-cube architecture has been chosen for the task allocation problem. We propose a fast and efficient isomorphic processor allocation scheme for k-ary n-cube systems by using isomorphic partitioning where the processor space is partitioned into higher dimensional isomorphic subcube and by using subcube recognition ability algorithm (SRA) which uses simple coordinate calculation and spatial subtraction. Thus the proposed scheme seeks to reduce the search space drastically, and hence can locate a free subcube very quickly providing scalable, faster, processor allocation, complete recognition ability with minimal overhead and minimizes the fragmentation
FAST‐TRACK: A southern California freeway is a physical and social barrier to gene flow in carnivores

Roads present formidable barriers to dispersal. We examine movements of two highly mobile carnivores across the Ventura Freeway near Los Angeles, one of the busiest highways in the United States. The two species, bobcats and coyotes, can disappear from habitats isolated and fragmented by roads, and their ability to disperse across the Ventura Freeway tests the limits of vertebrates to overcome anthropogenic obstacles. We combine radio‐telemetry data and genetically based assignments to identify individuals that have crossed the freeway. Although the freeway is a significant barrier to dispersal, we find that carnivores can cross the freeway and that 5–32% of sampled carnivores crossed over a 7‐year period. However, despite moderate levels of migration, populations on either side of the freeway are genetically differentiated, and coalescent modelling shows their genetic isolation is consistent with a migration fraction less than 0.5% per generation. These results imply that individuals that cross the freeway rarely reproduce. Highways and development impose artificial home range boundaries on territorial and reproductive individuals and hence decrease genetically effective migration. Further, territory pile‐up at freeway boundaries may decrease reproductive opportunities for dispersing individuals that do manage to cross. Consequently, freeways are filters favouring dispersing individuals that add to the migration rate but little to gene flow. Our results demonstrate that freeways can restrict gene flow even in wide‐ranging species and suggest that for territorial animals, migration levels across anthropogenic barriers need to be an order of magnitude larger than commonly assumed to counteract genetic differentiation.
Changing Network Behavior

The security of computer networks has been in the focus of research for years. While several sophisticated systems had been developed in the area of Intrusion Detection, new challenges arised. Pattern matching systems are not able to cope with high bandwidth (10 Gbps +) when analyzing the whole payload. Furthermore, new attack schemes arise by increasingly complex software and systems. New approaches like Network Behavior Analyses (NBA) Systems show promise for being able to cope with the new threats. These systems evaluate statistical flow data generated from the traffic of the monitored network. While originally designed for optimising traffic handling and accounting in the network, flow data appeared to be powerful for intrusion detection. NBA Systems based on machine learning techniques are able to evaluate these data and to recognize anomalies in the network. However, these systems suffer from a long-lasting learning phase and are susceptible to manipulations during that time. To overcome these shortcomings, we are introducing a fast-learning modular neural network based on pre-processed components. For the development of the new system, the possible attacks on NBA systems have to be investigated and understood in depth.
Hot-Spot Blob Merging for Real-Time Image Segmentation

— One of the major, difficult tasks in automated video surveillance is the segmentation of relevant objects in the scene. Current implementations often yield inconsistent results on average from frame to frame when trying to differentiate partly occluding objects. This paper presents an efficient block-based segmentation algorithm which is capable of separating partly occluding objects and detecting shadows. It has been proven to perform in real time with a maximum duration of 47.48 ms per frame (for 8x8 blocks on a 720x576 image) with a true positive rate of 89.2%. The flexible structure of the algorithm enables adaptations and improvements with little effort. Most of the parameters correspond to relative differences between quantities extracted from the image and should therefore not depend on scene and lighting conditions. Thus presenting a performance oriented segmentation algorithm which is applicable in all critical real time scenarios.
Nanofibers and their applications in tissue engineering

Developing scaffolds that mimic the architecture of tissue at the nanoscale is one of the major challenges in the field of tissue engineering. The development of nanofibers has greatly enhanced the scope for fabricating scaffolds that can potentially meet this challenge. Currently, there are three techniques available for the synthesis of nanofibers: electrospinning, self-assembly, and phase separation. Of these techniques, electrospinning is the most widely studied technique and has also demonstrated the most promising results in terms of tissue engineering applications. The availability of a wide range of natural and synthetic biomaterials has broadened the scope for development of nanofibrous scaffolds, especially using the electrospinning technique. The three dimensional synthetic biodegradable scaffolds designed using nanofibers serve as an excellent framework for cell adhesion, proliferation, and differentiation. Therefore, nanofibers, irrespective of their method of synthesis, have been used as scaffolds for musculoskeletal tissue engineering (including bone, cartilage, ligament, and skeletal muscle), skin tissue engineering, vascular tissue engineering, neural tissue engineering, and as carriers for the controlled delivery of drugs, proteins, and DNA. This review summarizes the currently available techniques for nanofiber synthesis and discusses the use of nanofibers in tissue engineering and drug delivery applications.
Microarray‐based Analysis of Anti‐angiogenic Activity of Demethoxycurcumin on Human Umbilical Vein Endothelial Cells: Crucial Involvement of the Down‐regulation of Matrix Metalloproteinase

cDNA microarray‐based gene expression analysis has been successfully employed to explore the action mechanism and to validate the targets of several drugs. In the present study, we evaluated anti‐angiogenic activity of demethoxycurcumin (DC), a structural analog of curcumin, isolated from Curcuma aromatica, and investigated the effect of DC on genetic reprogramming in cultured human umbilical vein endothelial cells (HUVECs) using cDNA microarray analysis. Of 1024 human cancer‐focused genes arrayed, 187 genes were up‐regulated and 72 genes were down‐regulated at least 2‐fold by DC. Interestingly, 9 angiogenesis‐related genes were down‐regulated over 5‐fold in response to DC, suggesting that the genetic reprogramming was crucially involved in anti‐angiogenesis by the compound. To verify the results obtained from cDNA microarray analysis, matrix metalloproteinase‐9 (MMP‐9), the product of one of the angiogenesis‐related genes down‐regulated over 5‐fold by DC, was investigated using gelatin zymography. DC potently inhibited the expression of MMP‐9, yet showed no direct effect on its activity. These data show that gene expressional change of MMP‐9 is a major mediator for angiogenesis inhibition by DC. All genes identified and microarray data are available on the web at http://dasan.sejong. ac.kr/bioprobe/.