nils-herrmann/clean_scirepeval huggingface dataset:
Clinical translation of a PSMA inhibitor for 99mTc-based SPECT.

Prostate-specific membrane antigen (PSMA) is highly over-expressed in advanced prostate cancers. 68Ga-labeled PSMA inhibitors (iPSMA) are currently used for prostate cancer detection by PET imaging. The availability of simple, efficient and reproducible radiolabeling procedures is essential for developing new SPECT radiopharmaceuticals for clinical translation. The aim of this research was to prepare 99mTc-EDDA/HYNIC-Lys(Nal)-Urea-Glu (99mTc-EDDA/HYNIC-iPSMA) obtained from lyophilized kit formulations and evaluate the in vitro and in vivo radiopharmaceutical binding to prostate cancer cells over-expressing PSMA, as well as the 99mTc-EDDA/HYNIC-iPSMA normal biodistribution in humans and the preliminary uptake in patients with prostate cancer.



99mTc labeling was performed by adding sodium pertechnetate solution and a 0.2M phosphate buffer (pH 7.0) to a lyophilized formulation containing HYNIC-iPSMA, EDDA, tricine, mannitol and stannous chloride. The radiochemical purity was evaluated by reversed-phase HPLC and ITLC-SG analyses. Stability studies in human serum were performed by size-exclusion HPLC. In vitro cell uptake was tested using prostate cancer cells (LNCaP) with blocked and non-blocked receptors. Biodistribution and tumor uptake were determined in LNCaP tumor-bearing nude mice with blocked and non-blocked receptors, and images were obtained using a micro-SPECT/CT. Whole-body images from three healthy men and two patients with histologically-confirmed prostate cancer (one of them with a previous 68Ga-PSMA-617scan) were acquired at 1h and 3h after 99mTc-EDDA/HYNIC-iPSMA administration with radiochemical purities of >98%.



In vitro and in vivo studies showed high radiopharmaceutical stability in human serum, specific recognition for PSMA, high tumor uptake (10.22±2.96% ID/g at 1h) with rapid blood clearance and mainly kidney elimination. Preliminary images in patients demonstrated the ability of 99mTc-EDDA/HYNIC-iPSMA to detect tumors and metastases of prostate cancer as well as 68Ga-PSMA-617 does.



The results obtained in this study warrant further dosimetry and clinical studies to determine the specificity and sensitivity of 99mTc-EDDA/HYNIC-iPSMA.
Power subsystem of GÖKTÜRK 2 flight model

The purpose of a power subsystem is to ensure reliable delivery of electrical power compatible with all loads under all foreseeable operational states and environments, during all mission phases, and over the intended design life of the loads and of the space vehicle and the power subsystem is unarguably the most critical subsystem on a satellite. Therefore, reliability, efficiency, autonomy, redundancy and size features become critical issues in design and implementation of a satellite power system. Moreover, these parameters associated with the power subsystem usually determine the lifetime of a satellite. This paper describes the design details with redundancy concept, autonomous operation, and sizing of GÖKTÜRK-2 power system flight model. The technical description of the subsystem and each module including the qualification level tests is also presented. For the battery charge regulators, the parallel operation, synchronization, electro-magnetic radiation reduction techniques, an effective MPPT algorithm will be presented in detail. Newly developed Electronic Separation Switch Module for the safe electrical separation from launch vehicle is also introduced here. Moreover, the power production-consumption analysis for different scenarios and early orbit data will also be presented roughly.
The Visual Object Tracking VOT2016 Challenge Results

The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply prelearned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending The Visual Object Tracking VOT2016 challenge results 3 the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website .
Development Kits for 3 D Optical Metrology Systems

Structured light is the process of projecting known patterns of pixels onto an object. When combined with a synchronized camera, a structured light pattern generator can enable highly accurate 3D optical measurements. This application note presents the operating theory of structured light systems, as well as the key components and design considerations. Special attention is given to hardware selection (pattern generator and camera), and choice of structured light patterns. A sample implementation using the LightCommanderTM development kit is detailed to provide the reader a starting point to developing their own system.
3D - Playfair cipher with additional bitwise operation

3D-Playfair cipher is multiple letter encryption cipher. In this, trigraphs of plaintext are treated as single units and converted into corresponding cipher text trigraphs. 3D-Playfair Ciphers originates due to the limitations in classical Playfair as it supports only alphabets and may not support two alphabets at the same time. It also eliminates the fact that a diagram and its reverse will encrypt in a similar fashion. 3D-Playfair cipher supports all 26 alphabets, 10 digits and 28 special characters. The theme of research is to furnish security to data which contains alphabets numerals and special characters during transmission that's why additional bitwise operations are introduced and applied on the cipher text of 3D-Playfair cipher with a random key. Linear Feedback Shift Register is a good candidate for generation of random sequences and is selected for generating random keys for bitwise operations to offer better security to cipher text before transmission over the internet. Here X-OR or X-NOR operations are taken into consideration for the bitwise operations based on the key.
Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome.

Methods for assessment, e.g., anthropometric indicators and imaging techniques, of several phenotypes of human obesity, with special reference to abdominal fat content, have been evaluated. The correlation of fat distribution with age, gender, total body fat, energy balance, adipose tissue lipoprotein lipase and lipolytic activity, adipose tissue receptors, and genetic characteristics are discussed. Several secreted or expressed factors in the adipocyte are evaluated in the context of fat tissue localization. The body fat distribution and the metabolic profile in nonobese and obese individuals is discussed relative to lipolysis, antilypolysis and lipogenesis, insulin sensitivity, and glucose, lipid, and protein metabolism. Finally, the endocrine regulation of abdominal visceral fat in comparison with the adipose tissue localized in other areas is presented.
Making Open Data Transparent: Data Discovery on Open Data

Open Data plays a major role in open government initiatives. Governments around the world are adopting Open Data Principles promising to make their Open Data complete, primary, and timely. These properties make this data tremendously valuable. Open Data poses interesting new challenges for data integration research and we take a look at one of those challenges, data discovery. How can we find new data sets within this ever expanding sea of Open Data. How do we make this sea transparent?
Investigating the functions of subregions within anterior hippocampus

Previous functional MRI (fMRI) studies have associated anterior hippocampus with imagining and recalling scenes, imagining the future, recalling autobiographical memories and visual scene perception. We have observed that this typically involves the medial rather than the lateral portion of the anterior hippocampus. Here, we investigated which specific structures of the hippocampus underpin this observation. We had participants imagine novel scenes during fMRI scanning, as well as recall previously learned scenes from two different time periods (one week and 30 min prior to scanning), with analogous single object conditions as baselines. Using an extended segmentation protocol focussing on anterior hippocampus, we first investigated which substructures of the hippocampus respond to scenes, and found both imagination and recall of scenes to be associated with activity in presubiculum/parasubiculum, a region associated with spatial representation in rodents. Next, we compared imagining novel scenes to recall from one week or 30 min before scanning. We expected a strong response to imagining novel scenes and 1-week recall, as both involve constructing scene representations from elements stored across cortex. By contrast, we expected a weaker response to 30-min recall, as representations of these scenes had already been constructed but not yet consolidated. Both imagination and 1-week recall of scenes engaged anterior hippocampal structures (anterior subiculum and uncus respectively), indicating possible roles in scene construction. By contrast, 30-min recall of scenes elicited significantly less activation of anterior hippocampus but did engage posterior CA3. Together, these results elucidate the functions of different parts of the anterior hippocampus, a key brain area about which little is definitely known.
SHiP: Signature-based Hit Predictor for high performance caching

The shared last-level caches in CMPs play an important role in improving application performance and reducing off-chip memory bandwidth requirements. In order to use LLCs more efficiently, recent research has shown that changing the re-reference prediction on cache insertions and cache hits can significantly improve cache performance. A fundamental challenge, however, is how to best predict the re-reference pattern of an incoming cache line.
 This paper shows that cache performance can be improved by correlating the re-reference behavior of a cache line with a unique signature. We investigate the use of memory region, program counter, and instruction sequence history based signatures. We also propose a novel Signature-based Hit Predictor (SHiP) to learn the re-reference behavior of cache lines belonging to each signature. Overall, we find that SHiP offers substantial improvements over the baseline LRU replacement and state-of-the-art replacement policy proposals. On average, SHiP improves sequential and multiprogrammed application performance by roughly 10% and 12% over LRU replacement, respectively. Compared to recent replacement policy proposals such as Seg-LRU and SDBP, SHiP nearly doubles the performance gains while requiring less hardware overhead.
The 128 Point New Mixed Radix-2 and Radix-4 Pipeline Combined SDF-MDC FFT / IFFT Processor For MIMO-OFDM Transceiver

Multi-in Multi-out Orthogonal Frequency Division Multiplexing (MIMO-OFDM) transceiver is an advanced digital communication which aims at higher throughput. It is the main part in the software defined radio which is the trending communication platform. FFT and IFFT are the key blocks in OFDM and by optimizing those, MIMO-OFDM transceiver performance improvises. To improve the performances of MIMO-OFDM transceiver architecture, a new algorithm was developed for exhibiting frequency transformation process, called “Mixed Radix-2 and Radix-4 Pipeline combined Single path Delay Feedback (”. Along with this a new algorithm is developed for multiplication of twiddle factor structure called “Modified Bit Parallel Multiplication (MBPM)” which is shifters based parallel multiplier architecture. It had provided a high throughput (2.4 Gsample/s) with 30.605ns latency lower power consumption and less area utilization (30k logic gates).
Security Issues in the Internet of Things ( IoT ) : A Comprehensive Study

Wireless communication networks are highly prone to security threats. The major applications of wireless communication networks are in military, business, healthcare, retail, and transportations. These systems use wired, cellular, or adhoc networks. Wireless sensor networks, actuator networks, and vehicular networks have received a great attention in society and industry. In recent years, the Internet of Things (IoT) has received considerable research attention. The IoT is considered as future of the internet. In future, IoT will play a vital role and will change our living styles, standards, as well as business models. The usage of IoT in different applications is expected to rise rapidly in the coming years. The IoT allows billions of devices, peoples, and services to connect with others and exchange information. Due to the increased usage of IoT devices, the IoT networks are prone to various security attacks. The deployment of efficient security and privacy protocols in IoT networks is extremely needed to ensure confidentiality, authentication, access control, and integrity, among others. In this paper, an extensive comprehensive study on security and privacy issues in IoT networks is provided. Internet of Things (IoT); security issues in IoT; security; privacy
Probabilistic Perspectives on Collecting Human Uncertainty in Predictive Data Mining

In many areas of data mining, data is collected from human beings. In this contribution, we ask the question of how people actually respond to ordinal scales. The main problem observed is that users tend to be volatile in their choices, i.e. complex cognitions do not always lead to the same decisions, but to distributions of possible decision outputs. This human uncertainty may sometimes have quite an impact on common data mining approaches and thus, the question of effective modelling this so called human uncertainty emerges naturally.
 Our contribution introduces two different approaches for modelling the human uncertainty of user responses. In doing so, we develop techniques in order to measure this uncertainty at the level of user inputs as well as the level of user cognition. With support of comprehensive user experiments and large-scale simulations, we systematically compare both methodologies along with their implications for personalisation approaches. Our findings demonstrate that significant amounts of users do submit something completely different (action) than they really have in mind (cognition). Moreover, we demonstrate that statistically sound evidence with respect to algorithm assessment becomes quite hard to realise, especially when explicit rankings shall be built.
Athena: A Framework for Scalable Anomaly Detection in Software-Defined Networks

Network-based anomaly detection is a well-mined area of research, with many projects that have produced algorithms to detect suspicious and anomalous activities at strategic points in a network. In this paper, we examine how to integrate an anomaly detection development framework into existing software-defined network (SDN) infrastructures to support sophisticated anomaly detection services across the entire network data plane, not just at network egress boundaries. We present Athena as a new SDN-based software solution that exports a well-structured development interface and provides general purpose functions for rapidly synthesizing a wide range of anomaly detection services and network monitoring functions with minimal programming effort. Athena is a fully distributed application hosting architecture, enabling a unique degree of scalability from prior SDN security monitoring and analysis projects. We discuss example use-case scenarios with Athena's development libraries, and evaluate system performance with respect to usability, scalability, and overhead in real world environments.
Recognizing tactic patterns in broadcast basketball video using player trajectory

The explosive growth of the sports fandom inspires much research on manifold sports video analyses and applications. The audience, sports fans, and even professionals require more than traditional highlight extraction or semantic summarization. Computer-assisted sports tactic analysis is inevitably in urging demand. Recognizing tactic patterns in broadcast basketball video is a challenging task due to its complicated scenes, varied camera motion, frequently occlusions between players, etc. In basketball games, the action screen means that an offensive player perform a blocking move via standing beside or behind a defender for freeing a teammate to shoot, to receive a pass, or to drive in for scoring. In this paper, we propose a screen-strategy recognition system capable of detecting and classifying screen patterns in basketball video. The proposed system automatically detects the court lines for camera calibration, tracks players, and discriminates the offensive/defensive team. Player trajectories are calibrated to the realworld court model for screen pattern recognition. Our experiments on broadcast basketball videos show promising results. Furthermore, the extracted player trajectories and the recognized screen patterns visualized on a court model indeed assist the coach/players or the fans in comprehending the tactics executed in basketball games informatively and efficiently.
Event Processing across Edge and the Cloud for Internet of Things Applications

The rapid growth of sensing devices has opened up complex event processing (CEP) for real-time analytics in Internet of Things (IoT) Applications. While CEP has traditionally been centralized, the increasing capabilities of edge devices like smart phones, and the operational needs of low latency and privacy makes it desirable to use both edge and the Cloud for distributed CEP, the former often serving as event sources. This paper motivates the need for real-time analytics across edge and the Cloud, formalizes an optimization problem for bi-partitioning a CEP query pipeline based on IoT application needs, and proposes an initial solution.
Curved document image rectification

Digitization of documents has gained prominence in the recent past for data preserving. Paper documents can be converted to digital form by using various modes of acquisition techniques. In this paper processing of data captured using normal digital camera has been considered. The camera captured document images may contain warped document due to perspective and geometric distortions. Curvature of text lines is a prominent characteristic of such distortions, which can affect the recognition accuracy of Optical Characters for OCR (Optical Character Recognition). To improve the accuracy, rectification of perspective distortions plays an important role. Here, a rectification technique that detects and straightens text lines with curvature in document images captured using normal digital camera is proposed.
Enhanced Handover Decision Algorithm in Heterogeneous Wireless Network

Transferring a huge amount of data between different network locations over the network links depends on the network's traffic capacity and data rate. Traditionally, a mobile device may be moved to achieve the operations of vertical handover, considering only one criterion, that is the Received Signal Strength (RSS). The use of a single criterion may cause service interruption, an unbalanced network load and an inefficient vertical handover. In this paper, we propose an enhanced vertical handover decision algorithm based on multiple criteria in the heterogeneous wireless network. The algorithm consists of three technology interfaces: Long-Term Evolution (LTE), Worldwide interoperability for Microwave Access (WiMAX) and Wireless Local Area Network (WLAN). It also employs three types of vertical handover decision algorithms: equal priority, mobile priority and network priority. The simulation results illustrate that the three types of decision algorithms outperform the traditional network decision algorithm in terms of handover number probability and the handover failure probability. In addition, it is noticed that the network priority handover decision algorithm produces better results compared to the equal priority and the mobile priority handover decision algorithm. Finally, the simulation results are validated by the analytical model.
Robust Large-Scale Localization in 3D Point Clouds Revisited

We tackle the problem of getting a full 6-DOF pose estimation of a query image inside a given point cloud. This technical report re-evaluates the algorithms proposed by Y. Li et al. “Worldwide Pose Estimation using 3D Point Cloud” . Our code computes poses from 3 or 4 points, with both known and unknown focal length. The results can easily be displayed and analyzed with Meshlab. We found both advantages and shortcomings of the methods proposed. Furthermore, additional priors and parameters for point selection, RANSAC and pose quality estimate (inlier test) are proposed and applied.
Design and Development of GPS-GSM Based Tracking System with Google Map Based Monitoring

GPS is one of the technologies that are used in a huge number of applications today. One of the applications is tracking your vehicle and keeps regular monitoring on them. This tracking system can inform you the location and route travelled by vehicle, and that information can be observed from any other remote location. It also includes the web application that provides you exact location of target. This system enables us to track target in any weather conditions. This system uses GPS and GSM technologies. The paper includes the hardware part which comprises of GPS, GSM, Atmega microcontroller MAX 232, 16x2 LCD and software part is used for interfacing all the required modules and a web application is also developed at the client side. Main objective is to design a system that can be easily installed and to provide platform for further enhancement.
Magnetization switching by spin-orbit torque in an antiferromagnet-ferromagnet bilayer system.

Spin-orbit torque (SOT)-induced magnetization switching shows promise for realizing ultrafast and reliable spintronics devices. Bipolar switching of the perpendicular magnetization by the SOT is achieved under an in-plane magnetic field collinear with an applied current. Typical structures studied so far comprise a nonmagnet/ferromagnet (NM/FM) bilayer, where the spin Hall effect in the NM is responsible for the switching. Here we show that an antiferromagnet/ferromagnet (AFM/FM) bilayer system also exhibits a SOT large enough to switch the magnetization of the FM. In this material system, thanks to the exchange bias of the AFM, we observe the switching in the absence of an applied field by using an antiferromagnetic PtMn and ferromagnetic Co/Ni multilayer with a perpendicular easy axis. Furthermore, tailoring the stack achieves a memristor-like behaviour where a portion of the reversed magnetization can be controlled in an analogue manner. The AFM/FM system is thus a promising building block for SOT devices as well as providing an attractive pathway towards neuromorphic computing.
Machine Learning Approach for Intrusion Detection on Cloud Virtual Machines

Development of the cloud computing in recent years is increasing rapidly and gained great success, its security issues have got more and more attention. Many challenges in cloud computation increase the threat of data and service availability. There is need of many security services in order to improve cloud security for users as well as providers. In this paper, we propose a Anomaly Intrusion Detection System using machine learning approach for virtual machines on cloud computing. Our proposal is feature selection over events from Virtual Machine Monitor to detect anomaly in parallel to training the system so it will learn new threats and update the model. The experiment has been carried out on NSL-KDD'99 datasets using Naïve Bayes Tree (NB Tree) Classifier and hybrid approach of NB Tree and Random Forest.