Miracle-dz/UniFAR-FTUs huggingface dataset:
Preoperative Stereotactic Radiosurgery for Brain Metastases

Stereotactic radiosurgery (SRS) is increasingly utilized to treat the resection cavity following resection of brain metastases and recent randomized trials have confirmed postoperative SRS as a standard of care. Postoperative SRS for resected brain metastases improves local control compared to observation, while also preserving neurocognitive function in comparison to whole brain radiation therapy (WBRT). However, even with surgery and SRS, rates of local recurrence at 1 year may be as high as 40%, especially for larger cavities, and there is also a known risk of leptomeningeal disease after surgery. Additional treatment strategies are needed to improve control while maintaining or decreasing the toxicity profile associated with treatment. Preoperative SRS is discussed here as one such approach. Preoperative SRS allows for contouring of an intact metastasis, as opposed to an irregularly shaped surgical cavity in the post-op setting. Delivering SRS prior to surgery may also allow for a “sterilizing” effect, with the potential to increase tumor control by decreasing intra-operative seeding of viable tumor cells beyond the treated cavity, and decreasing risk of leptomeningeal disease. Because there is no need to treat brain surrounding tumor in the preoperative setting, and since the majority of the high dose volume can then be resected at surgery, the rate of symptomatic radiation necrosis may also be reduced with preoperative SRS. In this mini review, we explore the potential benefits and risks of preoperative vs. postoperative SRS for brain metastases as well as the existing literature to date, including published outcomes with preoperative SRS.
ProducTron: Towards Flexible Distributed and Networked Production

With the evolution of cloud computing, internet of things and the application of new approaches from communication and information technologies in industrial production, possibilities for a networked production of different production technologies arise. Established approaches use manufacturing execution systems as local production coordination systems at workshop level without considering cross-site production or the integration of different stakeholders along the value chain of production. This paper presents an architectural concept, referred to as the ProducTron, for the digital integration of different manufacturing and common engineering modules for flexible distributed networked production as a possible basis for an Internet of Production.
An Investigation on Service Quality Attributes of Indian Hotels by Text Mining

The Global tourism competitiveness report 2017 has placed India in 40th position in the global. In many significant domains or pillars, India falls far behind compared to other nations. Many studies related to tourist satisfaction has apparently revealed the role of quality of accommodation, Service quality of hotel personnel, Affordability, Variety in tourist accommodations etc acts as important pull factor in deciding tourist behavior. In this backdrop, an attempt to revisit service quality perception of foreign travelers about hotels is of paramount importance. To create a favorable perception in the minds of foreign travelers and to encourage positive word of mouth of such attribute is essential. To know and improve those attributes this study is done, and from the study, we found that the attributes such as rooms, housekeeping, and food have more negative reviews from the customers. Thus the hotels should improve on these attributes.
A Hybrid BLSTM-C Neural Network Proposed for Chinese Text Classification

Text classification has always been a concern in area of natural language processing, especially nowadays the data are getting massive due to the development of Internet. Recurrent neural network (RNN) is one of the most popular method for natural language processing due to its recurrent architecture which give it ability to process serialized information. In the meanwhile, Convolutional neural network (CNN) has shown its ability to extract features from visual imagery. This paper combine the advantages of RNN and CNN and proposed a model called BLSTM-C for Chinese text classification. BLSTM-C begins with a Bi-directional long short-term memory (BLSTM) layer, which is an special kind of RNN, to get a sequence output based on the past context and the future context. Then it feed this sequence to CNN layer which is utilized to extract features from the previous sequence. We evaluate BLSTM-C model on several experiments such as sentiment classification and category classification and the result shows our model's satisfying performance on these text tasks.
RepoVis: Visual Overviews and Full-Text Search in Software Repositories

Project managers and software developers often have difficulty maintaining an overview of the structure, evolution, and status of collaborative software projects. Some tools are available for typical source code management systems, which provide summary statistics or simple visual representations of merge-branch graphs. However, comprehensive visual overview and search facilities for such repositories are lacking. RepoVis is a new tool which provides comprehensive visual overviews and full-text search for projects maintained in Git repositories. The overview shows folders, files, and lines of code colour-coded according to last modification, developer, file type, or associated issues. Full-text searches can be performed for terms of interest within source code files, commit messages, or any associated metadata or usability findings, with matches displayed visually in the overview. The utility of the RepoVis approach is illustrated with three use cases of real-world software inspection. Insights are presented into the utility of full-text search and visual presentation of matches for program comprehension.
Regulation of Placental Extravillous Trophoblasts by the Maternal Uterine Environment

During placentation invasive extravillous trophoblasts (EVTs) migrate into the maternal uterus and modify its vessels. In particular, remodeling of the spiral arteries by EVTs is critical for adapting blood flow and nutrient transport to the developing fetus. Failures in this process have been noticed in different pregnancy complications such as preeclampsia, intrauterine growth restriction, stillbirth, or recurrent abortion. Upon invasion into the decidua, the endometrium of pregnancy, EVTs encounter different maternal cell types such as decidual macrophages, uterine NK (uNK) cells and stromal cells expressing a plethora of growth factors and cytokines. Here, we will summarize development of the EVT lineage, a process occurring independently of the uterine environment, and formation of its different subtypes. Further, we will discuss interactions of EVTs with arteries, veins and lymphatics and illustrate how the decidua and its different immune cells regulate EVT differentiation, invasion and survival. The present literature suggests that the decidual environment and its soluble factors critically modulate EVT function and reproductive success.
Lord of Secure: the Virtual Reality Game for Educating Network Security

At the present, the security on the Internet is very sensitive and important. Most of the computer science curricula in universities and institutes of higher education provides this knowledge in term of computer and network security. Therefore, students studying in the information technology area need to have some basic knowledge about the security in order to prevent the potential attacks and protect themselves from hackers or intruders. Unfortunately, the network security concept is moderately abstract when students learn in the traditional lecture-based class. In this paper, to motivate and help students to perceive better than in the traditional classroom, we propose a security game called “Lord of Secure”, which is a virtual reality (VR) game on Android for education. It is an alternative learning materials for learners to gain the knowledge about the network security effectively. The game composes of main topics of the network security such as Firewall, IDS, IPS, and Honey pot. Moreover, the game will give the players knowledge about network security through the virtual world. The game also contains several quizzes including pretest and posttest, so players will know how much they gain more knowledge about network security by comparing scores before and after playing the game.
Exploring and Visualising Spaces of Tree Reconciliations

— Tree reconciliation is the mathematical tool that is used to investigate the coevolution of organisms, such as hosts and parasites. A common approach to tree reconciliation involves specifying a model that assigns costs to certain events, such as cospeciation, and then tries to ﬁnd a mapping between two speciﬁed phylogenetic trees which minimises the total cost of the implied events. For such models, it has been shown that there may be a huge number of optimal solutions, or at least solutions that are close to optimal. It is therefore of interest to be able to systematically compare and visualise whole collections of reconciliations between a speciﬁed pair of trees. In this paper, we consider various metrics on the set of all possible reconciliations between a pair of trees, some that have been deﬁned before but also new metrics that we shall propose. We show
Fiber Bragg Grating Sensor for the Determination of Static and Dynamic Strain

An optical Fiber Bragg Grating (FBG) is developed by creating a periodic variation in the refractive index along the core of a single mode optical fiber. It is observed that Fiber Bragg Grating Strain Sensors (FBGSS) offers some unique advantages over the conventional strain gauges. FBGSS are found to be well suited for the hybrid composite materials that are often used in highly stressed surfaces like in airplanes. In structural health monitoring these sensors can be used in hazardous and highly corrosive atmosphere. The present work describes the design, development and characterization of a FBG sensor for the accurate measurement of static and dynamic strain. The FBG is mounted on a cantilever structure made up of stainless steel. A standard metal foil strain gauge is also pasted for the comparison of measurement. The reflected spectrum is monitored using an interrogator interfaced with a personal computer. The developed method can be extended for the measurement of temperature, vibration, impact analysis etc.
Cooperative NOMA With Incremental Relaying: Performance Analysis and Optimization

In conventional cooperative non-orthogonal multiple access (NOMA) networks, spectral efficiency loss occurs due to a half-duplex constraint. To address this issue, we propose an incremental cooperative NOMA (ICN) protocol for a two-user downlink network. In particular, this protocol allows the source to adaptively switch between a direct NOMA transmission mode and a cooperative NOMA transmission mode according to a 1-bit feedback from the far user. We analytically prove that the proposed ICN protocol outperforms the conventional cooperative NOMA protocol. In addition, an optimal power allocation strategy at the source is studied to minimize the asymptotic system outage probability. Finally, numerical results validate our theoretical analysis, present insights, and quantify the enhancement achieved over the benchmark scheme.
Fabrication of Schottky Diodes on Zn-polar BeMgZnO/ZnO Heterostructure Grown by Plasma-assisted Molecular Beam Epitaxy

Heterostructure field effect transistors (HFETs) utilizing a two dimensional electron gas (2DEG) channel have a great potential for high speed device applications. Zinc oxide (ZnO), a semiconductor with a wide bandgap (3.4 eV) and high electron saturation velocity has gained a great deal of attention as an attractive material for high speed devices. Efficient gate modulation, however, requires high-quality Schottky contacts on the barrier layer. In this article, we present our Schottky diode fabrication procedure on Zn-polar BeMgZnO/ZnO heterostructure with high density 2DEG which is achieved through strain modulation and incorporation of a few percent Be into the MgZnO-based barrier during growth by molecular beam epitaxy (MBE). To achieve high crystalline quality, nearly lattice-matched high-resistivity GaN templates grown by metal-organic chemical vapor deposition (MOCVD) are used as the substrate for the subsequent MBE growth of the oxide layers. To obtain the requisite Zn-polarity, careful surface treatment of GaN templates and control over the VI/II ratio during the growth of low temperature ZnO nucleation layer are utilized. Ti/Au electrodes serve as Ohmic contacts, and Ag electrodes deposited on the O2 plasma pretreated BeMgZnO surface are used for Schottky contacts.
On-line Detection of Pantograph Offset Based on Deep Learning

A safe train operation relies on the well-contact of pantograph and the power grid above, therefore identifying the state of pantograph plays an vital role. Among all of the malfunctions, pantograph offset is a strong reflection of the state. We have proposed a new approach to reconstructing the three-dimensional (3D) information of the bow by substituting the offset with connection of left and right horns. To locate the region of pantograph horn, we refer to an efficient deep learning method, named Single Shot MultiBox Detector (SSD). In the located area, region growing or wiener filtering is applied to extract connected components and enhance the prospects. For processed images, grayscale morphological gradients is adopted to obtain image edges, on which Harris corner detection can provide dozens of potential corner-points. These points containing one correct horn point needs selection by assuming the lowest one is the best, only when the background noise is as low as possible. After attaining the two-dimensional (2D) image coordinates of the horns, binocular stereo vision method makes contribution to reconstructing 3D coordinates. Using the 3D coordinate line of the left and right horns to represent the pantograph offset can easily reflect the degree of deviation by comparing it with the initial location of pantograph. Our approach is of great significance to prevent malfunction, which are about to arise later, such as horn loss or deflection, spark of pantograph and catenary system contact-point. The detection of the pantograph offset provides a strong guarantee for maintaining railway traffic safety.
A Low Cost X-Band UWB Antenna for Medical Application: Optimal Design and Analysis

In this research paper, a low cost X-band UWB antenna for medical application is reported. The proposed ultra wide-band (UWB) antenna exhibit at the resonant frequency of 10.3 GHz with bandwidth of 1800 MHz and the regular monopole shape rectangular patch antenna is considered to achieve the wider bandwidth also regular line feeding techniques is utilized. The overall radiation size is 24mm × 14mm with thickness of 1mm and commercially available substrate material FR4 epoxy is presents in this research work. This proposed UWB antenna display at the return loss of −27.5 dB and $\text{VSWR} < 2$. By using high frequency structure simulator (HFSS) tools the return loss, voltage standing wave ratio, radiation pattern, radiation efficiency and current distribution has been analyzed. The above projected UWB antenna has unidirectional radiation pattern and produce moderate gain. This compact size X-band UWB antenna is highly recommended for medical field particularly intera operative radio therapy application also suitable for wireless body area network (WBAN) applications.
Measurement System for Classification of Hand’s Gesture

The goal was to create precise hardware that would be able to measure signal of myopotentials from defined area of forearm for the computer analysis without external noise and with right amplification. The second goal was to program an algorithm which could classify specific gestures of hand based on an analysis of myopotencial signals. The computer software was programmed in C# programming language. Signal processing and drawing to user interface was in real time. The one of five possible gestures that user made was analysed by using fuzzy logic and designed system of scaling. It was developed fuzzy classification which is able to recognize gestures with high accuracy.
Effects of Acute Cold Stress After Long-Term Cold Stimulation on Antioxidant Status, Heat Shock Proteins, Inflammation and Immune Cytokines in Broiler Heart

To investigate the effects of acute cold stress (ACS) on chicken heart after cold stimulation, female broilers were raised in either normal (C) or gradually decreasing temperatures (CS I and CS II) for 34 days followed by a 24 h ACS at 7°C. Cardiac tissues were collected from the pre-ACS and ACS time points to analyze the histopathological changes, antioxidant status and the expression of heat shock proteins, inflammatory factors and immune-related cytokines. The CS II heart tissues showed shrunken cell membranes and nuclei, disordered or ruptured myocardial fibers, higher MDA content and upregulation in HSP27, HSP40, HSP70, NF-κB, COX-2, PTGEs, iNOS, TNF-α and IL-4 mRNAs, and in protein levels of HSP40, NF-κB and iNOS and reduction in CAT, GSH-px and SOD activity, as well as HSP90 and IFN-γ levels compared to the control tissues before ACS. In contrast, the HSPs were significantly increased, and the inflammatory and immune related factors were unaltered prior to the ACS in the CS I compared to the C group. Following ACS, MDA content was significantly increased and antioxidant activity was significantly decreased in the CS I and CS II groups compared to the C group. The levels of HSP27, HSP70, HSP90, inflammatory factors and IL-4 were significantly reduced and that of IFN-γ was significantly increased in CS I broiler hearts; the reverse trends were seen in CS II relative to CS I. Compared to the pre-ACS levels, that of HSP27, HSP40, HSP60, inflammatory factors and IL-4 were increased and IFN-γ was decreased in the C and CS II groups after ACS. Therefore, cold stimulation at drastically lower temperatures induced cardiac damage, which was further aggravated by ACS. In contrast, cold stimulation at only 3°C lower than normal temperature improved the adaptability of the broilers to ACS.
Continuous Speech Recognition System for Malayalam Language Using Kaldi

An automatic speech recognition system aims to enable communication between human and computer. Here a continuous Malayalam speech recognition system is developed and realized using Kaldi toolkit. For building the proposed system, MFCC features and its transformations such as LDA and MLLT are extracted from Malayalam speech sentences. Then, the system has been trained to estimate the HMM parameters for speech sound units. Performance of both monophone and triphone models using bi-gram language model is compared in terms of word error rate(WER). A substantial drop in WER is obtained for triphone models.
[Research Paper] Obfuscating Java Programs by Translating Selected Portions of Bytecode to Native Libraries

Code obfuscation is a popular approach to turn program comprehension and analysis harder, with the aim of mitigating threats related to malicious reverse engineering and code tampering. However, programming languages that compile to high level bytecode (e.g., Java) can be obfuscated only to a limited extent. In fact, high level bytecode still contains high level relevant information that an attacker might exploit. In order to enable more resilient obfuscations, part of these programs might be implemented with programming languages (e.g., C) that compile to low level machine-dependent code. In fact, machine code contains and leaks less high level information and it enables more resilient obfuscations. In this paper, we present an approach to automatically translate critical sections of high level Java bytecode to C code, so that more effective obfuscations can be resorted to. Moreover, a developer can still work with a single programming language, i.e., Java.
Development and implementation of a geolocation system to determine the approximate time of arrival of a public transport bus to a user in the city of Trujillo-Perú

In this paper presents the development of a geolocation system to determine the approximate time of arrival of a public transport bus to a user of it. First, the module that obtains information on latitude, longitude, speed and time of the transport bus is designed and implemented. Second, a web server is developed that processes the data received from the transport bus, as well as from the user. Third, a mobile application is created that shows on an interactive map the information processed by the web server (location and approximate time of bus-user arrival). Finally, the results of different applications made in field are shown and discussed.
Dynamic Resource Allocation Using Fuzzy Prediction System

Virtualization is the main technology in the large scale data centers with which resources are shared among different application running on different VMs. Virtualization through virtual machine monitor (VMM) like Xen only provides resource isolation among co-located VMs. However, it has been shown that resource isolation does not imply performance isolation between VMs. Hence it necessitates on-demand allocation of the physical shared resources to individual VM as per their dynamic requirements to satisfy the SLA between customer and cloud provider. To do this efficiently future resource utilization is predicted using fuzzy logic based prediction. To avoid underestimation prediction errors due to spikes in the workload, the predicted values are padded with proper value and immediately resource caps are raised. The resource conflict is resolved locally if resources are available otherwise migration is triggered. This scheme allocates resources efficiently and reduces the response time as compared to static allocation. The resource saving with proposed method is around 30-40% and around 10-20% performance improvement in terms of response time of an application.
Design and Analysis of Upper Arm Exoskeleton with Virtual Reality based Motion Tracking Capabilities

Robotic rehabilitation is the new therapy for patients that suffering from leg or limb injuries. Patient”s second option is to use robotic rehabilitation instead of traditional rehabilitation because robotic rehabilitation consumes less money and shorter period of time. Robotics rehabilitation can be improved by constructing an exoskeleton. An exoskeleton is an external structure that contains links and joints attached to the patient“s body. The challenging development in human-machine interface is to design product that serves the patient need to rehabilitate the injuries and to develop smart connection between the device and the human body. This exoskeleton design is required to perform one degree of freedom extension/flexion movement. The device consists of frame, motor, force sensor and casing. In this design the motor needs to develop the required amount of torque so the patient can perform the movement easily.
Broadband Three-Way LC-Ladder Divider on a Double-Sided PCB

This paper describes wideband three-way Wilkinson power dividers using LC-ladder circuits. The proposed dividers consist of multi-section LC-ladder circuits between input and output ports, and their output ports are connected each other through external circuits composed of series RL circuits. By connecting the appropriate external circuits in accordance with the number of LC-ladder circuits, the proposed dividers can be realized extremely wideband operation. In order to verify the design procedure, wideband three-way Wilkinson power dividers are simulated and fabricated at VHF-band. As results of simulation and experiment, we can obtain broadband characteristics with a relative bandwidth of over 60%, which are near agreement with the theoretical results.