Miracle-dz/UniFAR-FTUs huggingface dataset:
Paroxetine, Panorama and user reporting of ADRs: Consumer intelligence matters in clinical practice and post-marketing drug surveillance

We systematically analysed two complementary samples of emails relating to patients' problems with the popular SSRI antidepressant, paroxetine. These mainly concerned serious mood disorders and drug withdrawal symptoms. 1,374 emails were immediate responses to a major BBC-TV documentary programme. These were contrasted with 862 messages on similar themes sent to a website discussion forum over a period of nearly three years. Despite the limitations of most individual email reports, we judged their collective weight to be profound. We also suggest that the value of "immersion" in a large body of such data may be greater than continuing exposure to a variable trickle of reports. We discuss the significance of these data in relation to the patient-prescriber relationship and pharmacovigilance. We suggest that the Internet offers unparalleled opportunities for soliciting and monitoring patients' reports of adverse drug reactions, and propose practical initiatives to capture peoples' experiences and thereby promote safer and more effective drug use.
Peroxisome deficient invertebrate and vertebrate animal models

Although peroxisomes are ubiquitous organelles in all animal species, their importance for the functioning of tissues and organs remains largely unresolved. Because peroxins are essential for the biogenesis of peroxisomes, an obvious approach to investigate their physiological role is to inactivate a Pex gene or to suppress its translation. This has been performed in mice but also in more primitive organisms including D. melanogaster, C. elegans, and D. rerio, and the major findings and abnormalities in these models will be highlighted. Although peroxisomes are generally not essential for embryonic development and organogenesis, a generalized inactivity of peroxisomes affects lifespan and posthatching/postnatal growth, proving that peroxisomal metabolism is necessary for the normal maturation of these organisms. Strikingly, despite the wide variety of model organisms, corresponding tissues are affected including the central nervous system and the testis. By inactivating peroxisomes in a cell type selective way in the brain of mice, it was also demonstrated that peroxisomes are necessary to prevent neurodegeneration. As these peroxisome deficient model organisms recapitulate pathologies of patients affected with peroxisomal diseases, their further analysis will contribute to the elucidation of still elusive pathogenic mechanisms.
Characterization of high performance CNT-based TSV for high-frequency RF applications

In this paper, we present modeling and characterization of CNT-based TSVs to be used in high-frequency RF applications. We have developed an integrated model of CNT-based TSVs by incorporating the quantum confinement effects of CNTs with the kinetic inductance phenomenon at high frequencies. Substrate parasitics have been appropriately modeled as a monolithic microwave capacitor with the resonant line technique using a two-polynomial equation. Different parametric variations in the model have been outlined as case studies. Furthermore, electrical performance and signal integrity analysis on different cases have been used to determine the optimized configuration for CNT-based TSVs for high frequency RF applications.
Tractography for Arteriovenous Malformations near the Sensorimotor Cortices Materials and Methods

We sought to use diffusion-tensor imaging– based tractography to assess the relationship between the arteriovenous malformations (AVM) and the sensorimotor cortices/tracts. Three patients who had an AVM closely situated to the sensorimotor tracts were studied. The relationship between the sensorimotor tracts and the AVM was well demonstrated in all patients. Tractography was also helpful in identifying the location of the motor cortex in some of the cases. Surgical management of arteriovenous malforma-tion (AVM) has a high risk when eloquent areas of the brain are involved (1). Therefore, knowing the precise location of these areas and their axonal pathways would enable safer surgery. Fiber-tracking method is a relatively new neuroimaging technique that visualizes 3D macroscopic fiber orientation in the brain (2– 4). We applied this technique to patients with nonhemorrhagic AVMs that were in close proximity to the sensorimotor cortices to examine its clinical impact. Patient Population This study was approved by an institutional review board, and written informed consent was obtained from each patient. We performed MR imaging on 18 consecutive patients who presented to our institute with nonhemorrhagic intra-cranial AVM, during the study period between August 2001 and December 2002. Among these 18 consecutive patients, three patients had lesions closely situated to the sensorimo-tor cortices. All three patients had been conservatively followed because of their high scores on the Spetzler-Martin grading system (1). The demographic data of the patients are summarized in Table 1. Imaging Methods Thin-section diffusion-tensor imaging was performed at the end of our routine brain protocol. The diffusion-tensor image acquisition time was 4 minutes and 24 seconds. Images were obtained by using a 1.5-T whole-body scanner (Gyroscan In-tera, Philips Medical Systems, Best, the Netherlands). A single-shot echo-planar imaging (EPI) technique was used for the diffusion-tensor image (repetition time/echo time ϭ 6000/88 ms) with a motion-probing gradient in six orientations, a b value of 800 s/mm 2 , and image averaging of six times. The recorded data points were 128 ϫ 53 by using the parallel imaging technique. The parallel imaging technique allows for image reconstruction by using half the encoding steps, the advantage of which lies in its reduction of the geometric image distortion that is unique to EPI. The true resolution of the acquired images was equivalent to 128 ϫ 106. The data were zero filled to generate images with 128 ϫ 128 resolution. A total of 36 sections were obtained with a thickness of …
Determining Optimum Structure for Artificial Neural Networks

Artificial Neural Networks (ANNs) have attracted increasing attention from researchers in many fields, including economics, medicine and computer processing, and have been used to solve a wide range of problems. In remote sensing research, ANN classifiers have been used for many investigations such as land cover mapping, image compression, geological mapping, and meteorological image classification, and have generally proved to be more powerful than conventional statistical techniques, especially when the training data are not normally distributed. The use of ANNs requires some critical decisions on the part of the user, which may affect the accuracy of the resulting classification. In this study, determination of the optimum network structure, which is one of the most important attributes of a network, is investigated. The structure of the network has a direct effect on training time and classification accuracy. Although there is some discussion in the literature of the impact of network structure on the performance of the network, there is no certain method or approach to determine the best structure. Investigations of the relationship between the network structure and the accuracy of the classification are reported here, using a MATLAB tool-kit to take the advantage of scientific visualisation. The effect of the composition of the training data on network structure is also investigated.
Portable acoustic myography – a realistic noninvasive method for assessment of muscle activity and coordination in human subjects in most home and sports settings

Muscle sound gives a local picture of muscles involved in a particular movement and is independent of electrical signals between nerve and muscle. Sound recording (acoustic myography) is a well‐known noninvasive technique that has suffered from not being easily applicable, as well as not being able to register at sufficient sampling speed. With modern amplifiers and digital sound recording this has changed, and such assessment during movement outside a laboratory setting may be possible. Our aim was to develop a setup for muscle‐sound assessment, which could be reliably applied in any local setting. A group of healthy subjects were assessed during standing, stair climbing, walking, and running. Piezoelectric microphones were applied to the skin using contact gel. A digital sound recorder enabled sampling speeds of around 96,000 Hz. Surface electromyography was measured in parallel as a comparison. The recorded signals were assessed and described in terms of signal frequency (Hz) and peak‐to‐peak amplitude (mV) using Chart software. Bioimpedance of the involved muscles was measured. Sound recording was shown to be an easy noninvasive method for assessment of muscle function during movement with the possibility of being applied in most clinical, sports, and home settings. Muscle sound gives a representation of the work of each muscle group during a complex movement, illustrated here by a step test, which revealed both concentric and eccentric activity. The method in the presented new setup has great potential for assessment of function in patients with musculoskeletal complaints in out‐of‐clinic settings, as well as in sports.
Five (or so) challenges for species distribution modelling

Species distribution modelling is central to both fundamental and applied research in biogeography. Despite widespread use of models, there are still important conceptual ambiguities as well as biotic and algorithmic uncertainties that need to be investigated in order to increase confidence in model results. We identify and discuss five areas of enquiry that are of high importance for species distribution modelling: (1) clarification of the niche concept; (2) improved designs for sampling data for building models; (3) improved parameterization; (4) improved model selection and predictor contribution; and (5) improved model evaluation. The challenges discussed in this essay do not preclude the need for developments of other areas of research in this field. However, they are critical for allowing the science of species distribution modelling to move forward.
Is the use of pedometers feasible for identifying the volume and intensity of a balance specific exercise programme for older adults

Background: ‪Exercise programmes consisting of stepping were found to significantly reduce incidence of falls in the elderly. The aim of this case study was to evaluate the feasibility of step counts and to identify a specific dose, i.e. the amount and intensity of stepping during a multicomponent balance specific exercise programme. Material and methods: ‪Thirty fit community-dwelling older adults (69.7 ±6.2 years) participated in the study. The number of steps and the intensity of stepping per training unit was recorded with StepWatch pedometers. Results: ‪The average recorded number of steps per one-hour training unit was 1100 ±215. The intensity level of the activity was on average high for 43.6 ±16.6% of the unit time and moderate for 45.9 ±14.2% of the unit time, whereas only 9.9% ±3.9 of the unit time was in the low level range. Conclusions: ‪The use of pedometers, i.e. step counts, is feasible to monitor the intensity of the training as well as the volume and progression if needed for the balance specific exercise programmes. Additionally, this case study demonstrates that balance specific exercise programme can be organised in the way to facilitate balance by means of volitional and reactive stepping.
A Linear Approach of 3 D Face Shape and Texture Recovery using a 3 D Morphable Model

In this paper, we present a robust and efficient method to statistically recover the full 3D shape and texture of faces from single 2D images. We separate shape and texture recovery into two linear problems. For shape recovery, we learn empirically the generalization error of a 3D morphable model using out-of-sample data. We use this to predict the 2D variance associated with a sparse set of 2D feature points. This knowledge is incorporated into a parameter-free probabilistic framework which allows 3D shape recovery of a face in an arbitrary pose in a single step. Under the assumption of diffuseonly reflectance, we also show how photometric invariants can be used to recover texture parameters in an illumination insensitive manner. We present empirical results with comparison to the state-of-the-art analysis-by-synthesis methods and show an application of our approach to adjusting the pose of subjects in oil paintings.
MedicCyc: a biochemical pathway database for Medicago truncatula

MOTIVATION There is an imperative need to integrate functional genomics data to obtain a more comprehensive systems-biology view of the results. We believe that this is best achieved through the visualization of data within the biological context of metabolic pathways. Accordingly, metabolic pathway reconstruction was used to predict the metabolic composition for Medicago truncatula and these pathways were engineered to enable the correlated visualization of integrated functional genomics data. RESULTS Metabolic pathway reconstruction was used to generate a pathway database for M. truncatula (MedicCyc), which currently features more than 250 pathways with related genes, enzymes and metabolites. MedicCyc was assembled from more than 225,000 M. truncatula ESTs (MtGI Release 8.0) and available genomic sequences using the Pathway Tools software and the MetaCyc database. The predicted pathways in MedicCyc were verified through comparison with other plant databases such as AraCyc and RiceCyc. The comparison with other plant databases provided crucial information concerning enzymes still missing from the ongoing, but currently incomplete M. truncatula genome sequencing project. MedicCyc was further manually curated to remove non-plant pathways, and Medicago-specific pathways including isoflavonoid, lignin and triterpene saponin biosynthesis were modified or added based upon available literature and in-house expertise. Additional metabolites identified in metabolic profiling experiments were also used for pathway predictions. Once the metabolic reconstruction was completed, MedicCyc was engineered to visualize M. truncatula functional genomics datasets within the biological context of metabolic pathways. AVAILABILITY freely accessible at http://www.noble. org/MedicCyc/
Trends in Disability Rates in the United States, 1970-1994. Disability Statistics Abstract, Number 17.

T proportion of the U.S. population with disabilities has risen markedly during the past quarter-century. As the data presented in this abstract show, two distinct trends have contrib­ uted to the increasing overall prevalence of disability: a gradual rise, due largely to demographic shifts associated with an aging population, as well as a rapid increase that has taken place during the past several years. This recent change seems to be due not to demographics, but to greater numbers of children and young adults reported as having disabili­ ties.
Climate and development economics: Balancing science, politics and equity

The interaction of climate and development threatens to create a paradox: economic development could accelerate climate change, which in turn could block further development, locking the world into existing patterns of inequality as the natural environment deteriorates. The solution to this paradox is far from obvious. What analytical tools are needed to chart a path that leads toward sustainable, low-carbon economic development? This article reviews the implications for climate policy of the climate economics and development literature, focusing on three key areas of judgments and assumptions that are built into a number of leading climate-economics models: 1) the treatment of climate science, risk, and uncertainty in climate-economics models; 2) questions of abatement technologies and costs, including a focus on the cost effectiveness method of economic analysis; and 3) ethical issues surrounding the distribution of the costs of emission reductions and adaptation measures. The article concludes that since climate and development goals are inextricably linked, there is a need for a new economic analysis that can help interpret and guide the creation of an innovative, low-carbon path to economic development.
Teacher Misbehaviors at Elementary Schools in Turkey

The purpose of this study is to investigate teacher misbehaviors, their causes and consequences, and what can be done to eliminate them. The sample for the study was chosen according to accessible sampling methods from the elementary schools in the Malatya Province. The sample includes elementary teachers (n = 25), administrators (n = 16), students (n = 25), and parents (n = 19). This research is qualitatively designed and uses a descriptive model. The data was collected using a semistructured interview protocol. After analyzing and categorizing the data, themes emerged. According to the results, the following teacher misbehaviors emerged: lack of business ethics, pedagogical incompetence, and behavioral problems.
Parametric Verification of Hybrid Automata Using the Inverse Method

Hybrid systems combine continuous and discrete behavior. Hybrid Automata are a powerful formalism for the modeling and verification of such systems. A common problem in hybrid system verification is the good parameters problem, which consists in identifying a subset of parameters which guarantee a certain behavior of a system. Recently, a method has been presented for attacking this problem for Timed Automata. In this report, we show the extension of this methodology for hybrid automata with linear and affine dynamics. The method is demonstrated with a distributed temperature control system and several other hybrid system benchmarks from the literature.
Quantized Indexing Tree for Frequent Updates over Data Streams

Emerging hardware and communication technologies enable new data stream applications that deal efficiently with very high rates of data updates. In this paper, we propose a novel index structure, termed the QDM-tree (quantized R*-tree with double memos), to support efficient similarity search over data streams. We integrate quantized minimum bounding spheres (QMBSs) and quantized minimum bounding rectangles (QMBRs) which can improve the cache behavior of QDM-tree due to effectively pack more entries in a node and reduce the tree height. Two compact main memory memos (Insert Memo and Delete Memo) can accelerate the speed of insert operations and convert the cost of update to the cost of insert. Therefore, the RamDisk technique reduces the cost of disk accesses to the cost of memory accesses. Theoretical analysis and experimental evaluation demonstrate that the QDM-tree significantly outperforms other state of the art R-tree variants with frequent updates, and is more suitable for massive data streams.
Feasibility of Applying the Extended ICF Core Set for Stroke to Clinical Settings in Rehabilitation: A Preliminary Study

Objective To evaluate the potential feasibility of application of the extended International Classification of Functioning, Disability and Health (ICF) Core Set for stroke. Methods We retrospectively reviewed the medical records of 40 stroke outpatients (>6 months after onset) admitted to the Department of Rehabilitation Medicine for comprehensive rehabilitation. Clinical information of the patients were respectively evaluated to link to the 166 second-level categories of the extended ICF Core Set for stroke. Results Clinical information could be linked to 111 different ICF categories, 58 categories of the body functions component, eight categories of the body structures component, 38 categories of the activities and participation component, and seven categories of the environmental factors component. Conclusion The body functions component might be feasible for application of the extended ICF Core Set for stroke to clinical settings. The activities and participation component and environmental factors component may not be directly applied to clinical settings without additional evaluation tools including interview and questionnaire.
Research for human action recognition based on depth information

Action recognition is always a very active and challenging research topic in the field of computer vision. Kinect, as a motion sensing input device which can capture both color and depth images, open up new possibilities of dealing with this task. In this paper, we build a system to track and classify the human action based on the Microsoft Kinect technology. During the feature extraction step, we use the depth camera to capture depth information of human and propose a method to generate a skeleton model as our main features. Then, a multi-class Support Vector Machine (SVM) is adopted to recognize actions. Our method simplifies and systematizes the task of human action recognition meanwhile the experimental results show promising performance.
Membership classification using Integer Bloom Filter

Due to the large quantity of digital information now available, information search engines provide a popular and important Internet service. Issues involved in the improvement of digital content search efficiency include: keyword filtering, inefficient search filtering, and existence search queries. Internet services are currently focusing on improving efficiency and accuracy. Through a pre-processing filter of inefficient search contents, a waste of Internet resources can be avoided and search efficiency can be improved. This study proposes an Integer Bloom Filter (IBF) that combines the concepts of a Bloom Filter (BF) and an artificial neutral network. It is based on the basic structure of the Bloom Filter so that multiple attribute existence algorithms can be developed. The algorithm's characteristics include: error-detected ratio, parallel computing, multiple attribute identification, non-fixed length string sample applications, as well as dynamic sample addition. With the non-fixed length string sample, the research results show that under proper conditions, the error-detected ratio has a very satisfactory performance and an on-line/off-line application field demonstrates its stable and highly efficient performance.
Coordinated control of multiple autonomous underwater vehicle system

This paper explores the problem of coordinated control of multiple autonomous underwater vehicle system (MAUVS) in the real-world tasks such as environmental exploration and oceanographic sampling. These tasks involve solving a distributed multi-agent planning problem in which the actions of underwater vehicles are tightly coupled. A distributed control architecture MOOS-IvP is applied to the MAUVS. In this approach, fully distributed control of underwater vehicles is realized and behavior-based control strategy is used to ensure a timely reaction of the vehicles in complex and dynamic environment. The architecture is further extended with market-based coordination strategy to tackle the problem of task level cooperation of MAUVS in task execution. It is shown in this paper that the integration of market based coordination strategy and MOOS-IvP architecture can enable the MAUVS to work efficiently in tasks require both loosely-coupled and tightly coupled cooperation.
Distributed Collision-Free Message Broadcasting in Multichannel Wireless Networks

Broadcasting is essential in many wireless network applications. The main problem of broadcasting in a wireless network is the broadcast messages may collide with other transmissions. Normally, no acknowledgement (ACK) message is sent back on receipt of broadcast packet, thus, the source node cannot determine if the broadcast is successful. In this paper, a mechanism that ensures collision-free message broadcasting in a multichannel wireless network is provided.