Miracle-dz/UniFAR-FTUs huggingface dataset:
Gamma knife radiosurgery on the trigeminal ganglion for idiopathic trigeminal neuralgia: Results and review of the literature

Background: In the present study, we evaluate the results of gamma knife surgery (GKS) for the treatment of trigeminal neuralgia (TN) using the trigeminal ganglion (TG’) and the adjacent fibers of trigeminal nerve as a target. Methods: From February 2013 to July 2017, we treated 30 cases of TN with GKS. In this group, all patients had an idiopathic typical TN. The radiosurgical target was conformed through two isocenters, 8 and 4 mm at the cavum de Meckel. The maximum dose was 86 Gy using the isodose line of 50%. The median age of the patients was 58.5 (range 28–94) years old, and the median time from diagnosis to GKS was 94 months (range 13–480 months). The median follow-up was 28.5 (range 12–49) months. Clinical outcomes were analyzed. Univariate and multivariate analyses were performed to evaluate factors that correlated with a favorable, pain-free outcome. Results: The mean time to relief of pain was 7 (range 1–40) days. The percentage of patients with significant pain relief was 93.3%. Relapse in pain was noted in four patients at 3, 16, 19, and 36 months. Nine patients were treated in acute status. Fourteen patients had intense pain between 1 and 7 days before the procedure. Among those with the recurrence of their symptoms, one patient had a microvascular decompression. Multivariate regression adjusted for age and sex suggests that, by 40 months, 70% of the patients treated with radiosurgery will remain pain free. At the last follow-up, GKS resulted in pain relief in 86.6% of patients. Our analysis suggests that, using this technique, we can expect that approximately 70% of patients with TN will have some degree of pain improvement at 3 years’ post radiosurgery. Conclusions: GKS on TG appears to be a reasonable treatment option with short latency period, minor collateral effects, and high percentage of pain control. The mechanism of action of radiosurgery could be related to the inactivation of the satellite glial cells in the TG.
Frame based object detection - an application for traffic monitoring

In this paper, we describe a system that is capable of detecting and segmenting objects from video frames which helps in traffic surveillance. Shadow is one of the problems faced by most of the object detection systems. It will affect the result of object detection and segmentation. Hence a shadow removal method is applied in the preprocessing phase of the system to amplify the accuracy of detection. MATLAB is the major platform for developing this system. By differentiating the background and foreground of the video scenes using MATLAB embedded functions, the foreground regions are segmented as the objects. The segmented objects are saved for further development of computer vision applications such as object recognition and classification. The proposed system is tested with four traffic video scenes and the experimental results show that the system works well with an accuracy of approximately 90% achieved.
Variable forgetting factor PASTd algorithm for time-varying subspace estimation

A new subspace tracking algorithm based on the PASTd algorithm is proposed. The algorithm is obtained by introducing the variable forgetting factor, which adapts itself to the time-varying subspace environments. The tracking capability of the proposed algorithm is demonstrated by computer simulations in an abruptly changing DOA scenario. The estimation results of the variable forgetting factor PASTd (VFF-PASTd) algorithm outperform those of the PASTd algorithm in the nonstationary case as well as in the stationary case.
NLMPC for Real Time Path Following and Collision Avoidance

Path following has been widely studied in the literature. A standard formulation is to use a moving coordinate system attached to the path: a Fernet reference frame [1] [2]. The in [1] is preferable, because the moving frame is uniquely determined by the vehicle position and it is not necessary to introduce an additional degree of freedom. Although a singularity problem arises when the lateral vehicle displacement coincides with the curvature radius of the path. This situation is not relevant in our application: a highway curvature radius is at least an order of magnitude larger than the admissible lateral displacement.
Deepening Understanding of Pharmacy Practice through Experiencing Virtual Reality and Mobile Patient-Health Application

Technologies such as notebook computers, virtual reality devices and mobile applications can be useful tools to prepare pharmacy students in the 21st century [1]. Pharmacy educators start getting their students to use mobile applications and technology to enrich the learning experience, and students can find useful and reliable medical references and drug information with medical mobile applications [2]. More importantly, students need to build a comprehensive understanding that pharmacy is not only about drug dispensing or prescription checking; they should have an opportunity to experience how they connect with patients and perform medication reviews with changes in patients’ health conditions over time, modelling the practice of professional pharmacists [3]. Generation Z pharmacy students in Hong Kong have a lot of exposure to the use of mobile applications for communication with peers. This case study reports how a pharmacy educator redesigned the curriculum so that students could gain a balance between cognitive knowledge and the human side of pharmacy practice by experiencing ways of communication with doctors and patients using virtual reality devices connected to mobile phones or notebook computers in preparation for clinical internships. In addition, a mobile application for e-health support for patients is under development; it will gather health records of individual patients, information on drugs being prescribed and the pharmacist, and medical appointment data. A pilot has been conducted to fine-tune the user interface of the application before it is launched in the autumn, 2019. The pharmacy educator may then be able to demonstrate to students how the application will allow pharmacists to build a sustainable approach to providing services to patients who have had acute or chronic diseases in the community from admission to a hospital to follow-up medication requirements and review of medication prescriptions in the growing aging population in Hong Kong.
An Analysis on Effective Classification Method for Massive Data in Cloud Computing Environment

The network information in cloud computing environment is in the format of massive data with high dimension features. In order to increase the accuracy of massive data automatic classification, this paper proposes a relevant massive data classification algorithm. This algorithm first transfers the features of the massive data in the cloud computing environment into one multi-objective optimization problem. In the specific mining area, the algorithm associatively classifies the massive data information and the selective standard is the high accuracy. The simulation and experiment test the performance of the algorithm which shows the algorithm can effectively classify the features of the massive data in the cloud computing. The algorithm can increase the accuracy and efficiency of the automatic classification which is an effective method for massive data.
A Web-based retrieval system for 3D polygonal models

This paper describes a Web-based retrieval system for 3D polygonal models. Feature descriptors of 3D polygonal model are reduced by feature descriptor grouping techniques. This enables fast queries of 3D polygonal models from the databases. Also, the system can retrieve colors from material color databases for 3D polygonal models reflecting users' preferences. The system can display 3D models queried to standard Web browsers interactively. Our preliminary experimental result showed good recall and precision for the retrieval test.
Phonetic and / or phonological errors and phonetic flexibility abilities : A case study of two non-fluent aphasic patients

In aphasia, an important question is the level of language processing at which speech errors occur. This study focused on errors than can arise at phonological or phonetic encoding. Phonetic paraphasias are generally considered as occurring in patients with non-fluent aphasia and consist in incorrect articulatory realization of phonemes due to motor planification impairment in the phonetic system. On the other hand, phonological paraphasias generally occur in patients with fluent aphasia and are defined as substitution, transposition, deletion or inversion of phonemes due to incorrect phoneme selection within the phonological system (Laine & Martin, 2006; but see Blumstein et al., 1980; Nespoulous et al., 2013). However, the distinction between phonological and phonetic paraphasias is generally based on perceptual analyses that could be influenced by the experimenter’s perceptual system.
A single-chip GaAs RF transceiver for 1.9-GHz digital mobile communication systems

A 1.9-GHz single-chip GaAs RF transceiver has been successfully developed using a planar self-aligned gate FET suitable for low-cost and high-volume production. This IC includes a negative voltage generator for 3-V single voltage operation and a control logic circuit to control transmit and receive functions, together with RF front-end analog circuits-a power amplifier, an SPDT switch, two attenuators for transmit and receive modes, and a low-noise amplifier. The IC can deliver 22-dBm output power at 30% efficiency with 3-V single power supply, The new negative voltage generator operates with charge time of less than 200 ns, producing a low level of spurious outputs below -70 dBc through the power amplifier. The generator also suppresses gate-bias voltage deviations to within 0.05 V even when gate current of -144 /spl mu/A flows. The IC incorporates a new interface circuit between the logic circuit and the switch which enables it to handle power outputs over 24 dBm with only an operating voltage of 3 V. This transceiver will be expected to enable size reductions in telephones for 1.9-GHz digital mobile communication systems.
A Rare Pathology of the Parotid Gland: Epitheloid Hemangioendothelioma

Epitheloid hemangioendothelioma is a tumor of vascular origin with the proliferation of endothelial cells in Epitheloid morphology which is reported very rarely in parotid gland. Clinically it has a borderline acting pattern between hemangioma and angio sarcoma with its local aggressive and metastatic features. World Health Organization put the Epitheloid subtype of hemangioendothelioma to the malign category in soft tissue tumors classification in 2013. Herein we report a case of Epitheloid hemangioendothelioma who had experienced total parathyriodectomy due to a parotid mass in our clinic. In 2 years of follow up of this case any recurrences is not determined.
DFC: Dynamic UL–DL Frame Configuration Mechanism for Improving Channel Access in eLAA

Enhanced licensed-assisted-access (eLAA) and MulteFire are the latest mechanisms that utilize unlicensed bands while keeping the benefits of LTE. Though eLAA/MulteFire helps to solve the Wi-Fi coexistence issue to a significant extent, its performance suffers due to competition from neighboring transmitting nodes in the unlicensed band to access the channel. We take advantage of new frame structure type-3, proposed for eLAA/MulteFire and formulate a dynamic uplink–downlink (UL–DL) frame configuration (DFC) mechanism to improve the channel access probability which uses an optimization game based on potential game theory. The DFC delivers a minimum of 40% improvement over arbitrary UL–DL frame configuration mechanism.
Telerobotic management system: coordinating multiple human operators with multiple robots

This paper describes an application called the Tele-robotic management system (TMS) for coordinating multiple operators with multiple robots for applications such as underground mining. TMS utilizes several graphical interfaces to allow the user to define a partially ordered plan for multiple robots. This plan is then converted to a Petri net for execution and monitoring. TMS uses a distributed framework to allow robots and operators to easily integrate with the applications. This framework allows robots and operators to join the network and advertise their capabilities through services. TMS then decides whether tasks should be dispatched to a robot or a remote operator based on the services offered by the robots and operators.
ULTRA-LOW COMPLEXITY CONTROL MECHANISMS FOR SENSOR NETWORKS AND ROBOTIC SWARMS

Biologically inspired swarms of autonomous robots have been used successfully in a variety of robotic applications ranging from various kinds of ground-based robots, to unmanned aerial vehicles. Typically, all of these systems use digital communications among swarm agents to implement their behavioral rules (e.g., because they need to exchange information about the location of agents). In this paper, we propose a general control architecture for ultra-low complexity robotic swarms that can be fully implemented in analog hardware and does not require digital communication for any part of the swarm coordination. We demonstrate the versatility and effectiveness of the proposed mechanisms both in simulations and on a robotic swarm platform for a variety of applications, ranging from area coverage, to target tracking, target interception or target enclosure, to active exploration and target finding, among others. The proposed system is extremely simple, robust, and scales well. It allows for homogeneous and heterogeneous swarms and has been successfully applied in several physical instantiations.
Small-target detection in multispectral imagery with cyclic overlay processing

The detection of small, hostile targets in multispectral imagery is generally complicated by sensor noise, atmospheric obscurants, and spatial distortions induced by the point-spread function (PSF). Traditional methods for multispectral detection of small targets, such as signature- based discrimination predicated upon deterministic physical models, have not proven robust in the presence of camera noise at low light levels. The additional problem of target variability also confounds a signature-based approach. Due to time-dependent variations in illuminant spectra response, targets can appear to have different spectral properties at different times of day and under various weather conditions. In this paper, we discuss computationally efficient methods for locating targets that differ spectrally from their spatially adjacent backgrounds but are similar to features located elsewhere in the source image. In particular, we note that flicker effects can be produced in which target intensity appears to vary differently with background intensity. Such effects are produced computationally by cyclic overlay processing (COP), which sequentially displays monospectral band images to achieve different perceived flicker rates of target and background. When combined with knowledge about the human visual system (HVS), COP can be successfully used in conjunction with neighborhood operations to segment target regions in highly cluttered imagery. We emphasize the role of target-background contrast in potentiating flicker effects, and discuss algorithms for computing COP. Analyses emphasize computational cost and effectiveness of various COP filter configurations for detecting targets that are similar to, or partially obscured by, surrounding cover or earth. We also discuss the implementation of our algorithms on parallel processors, in particular, the parallel algebraic logic (PAC) architecture currently being implemented in cooperation with Lockheed- Martin and USAF Wright Laboratory. Our algorithms are written in image algebra, a rigorous, concise, inherently parallel notation that unifies linear and nonlinear mathematics in the image domain and has been implemented on a variety of parallel processors. Thus, our algorithms are both feasible and portable.
On Image Decompression with Embedded Characteristic Information

Since the internet has become a main method of image's transmission and storage, how to prevent illegal diffusion for some images deserves wide attention and discussion. This paper introduces an effective method of registering the decode program with the personal characteristic information. To guarantee the ownership and the integrity of the image data, with processed chaotic sequence or random sequences, the installation procedure produces distinctive registering numbers which indicate the users’ information.
Error concealment techniques for an all-digital high-definition television system

Broadcasting High Definition Television (HDTV) requires the transmission of an enormous amount of information within a highly restricted bandwidth. Adhering to the transmission constraints, channel errors are inevitable. This paper proposes error concealment techniques to remove subjective effects of transmission errors. Error concealment techniques for several data parameters transmitted for the compressed representation of HDTV are considered. Specifically, we address errors in motion vectors and DCT coefficients. The concealment techniques estimate the true value of the corrupted parameters by exploiting the spatial and temporal correlation within the image sequence. In general, the error concealment techniques are found to be extremely successful in removing degradations from the decoded image.
Designing A Model of Vocational Training Programs for Disables through ODL

This study was conducted to designing a model of vocational training programs for disables. For this purpose desk review was carried out and the vocational training models/programs of Israel, U.K., Vietnam, Japan and Thailand were analyzed to form a conceptual frame work of the model. Keeping in view the local conditions/requirements a model of vocational training program was proposed. The proposed model involved the vocational training plan for the job of cashier for mild group, receptionist for moderate and computer operator for severe group. It specified the type of disability as well involved in the training plan. The model recommended the vocational training of three levels of disability; mild, moderate and severe irrespective to the type. The model consisted of details of structure, objectives, professional support involved, vocational training plan and syllabus/activities, evaluation and on job training etc. International practices regarding VT mixed with the national existing situations were critically analyzed during desk review and finally a plan of VT for disables was proposed. A survey was conducted via a questionnaire to get opinion of the heads and senior vocational instructors of Federal Government vocational training and rehabilitation centers for PWDs. The collected data was statistically analyzed to quantify the suggestions on proposed model. The major findings included that all stakeholders considered VT helpful in rehabilitation of PWDs. All heads and vocational instructors are willing to adopt this model, minimum or no extra funds are needed in its implementation, the vocational teacher employed in the centers can easily manage to adopt this model at their centers because no extra training is required for the staff and they all endorse the VT plan proposed in this model. A vocational training model is required to reduce socio-economic gap and to set professional standards by developing human resources trained in trades. The syllabus, activities and methodology proposed for the vocational training of the students at special education centers for the disables was agreed upon by the experts. It was recommended that vocational training model on various jobs for specific disabilities may be developed. Vocational training model for after school youth may also be developed on similar pattern. It was recommended that vocational training must be implemented through ODL for the training of PWDs in acquiring vocational skills if there is no vocational skill training teacher or resources available at the centers. In this way a large number of individuals who are taking education at special education centers and institutions can take benefits from VET programs at a time with minimal cost provided at their door steps or at institutions.
Do serum estrogen levels affect the antibody response to flu vaccines in post-menopausal women?

Public health and the improvement of human health has been a topic of interest for centuries – even more so in current society. Preventative healthcare, specifically, has become a focus in recent years. Vaccines are one of the primary methods in which health officials attempt to improve both individual and collective human health before any issues even arise. That is why it is imperative to take into account any factors that may impede the ability of vaccines to perform to their full capacity. This includes the presence – or lack thereof – of certain hormones, like estrogen. Obesity has also been shown to have a negative effect on antibody response to the flu vaccine (Sheridan et al.). Post-menopausal women have been shown to be especially susceptible to numerous health related consequences like obesity (Colombel et al.) and decline in immune responses, which can possibly be attributed to estrogen deprivation (Gameiro et al.). This association is further supported by a mouse model study by Nguyen et al. which showed hormone replacement therapy to have a positive effect on antibody response to the influenza vaccine in post-menopausal mice. Because a decline in estrogen is thought to possibly be the cause of a declined antibody response to the flu vaccine in the mouse model, we hypothesized that post-menopausal women with less estrogen will have a decreased antibody response to the 2014-2015 H1N1 flu vaccine. Furthermore, though obese post-menopausal women have been shown to have higher levels of estrogen than non-obese post-menopausal women – opposite trend of pre-menopausal women (Freeman et al.) – we additionally hypothesized that obese postmenopausal women will also have a decreased immune response to the 2014-2015 H1N1 flu vaccine. To test these hypotheses, we collected pre and 30 days post influenza vaccine serum samples from twenty-four post-menopausal. Enzyme-linked immunosorbent assays (ELISA) were conducted on the preand post-vaccination serum samples and their antibody responses and estrogen levels were assessed and compared. As expected, mean estrogen concentrations increased with increasing BMI categorization. Additionally, overweight post-menopausal women had a greater mean antibody response as opposed to healthy weight or obese post-menopausal women. However, this data was not significant. Though this data was not significant, it should be repeated with a larger sample size and with second blood draws done more than 30 days postvaccination. Another potential expansion of this study is to include data from pre-menopausal women, as well, since there may be more variations in estrogen in their serum.