nils-herrmann/clean_scirepeval huggingface dataset:
Design and implementation of a tdd-based 128-antenna massive MIMO prototype system

Owing to the dramatic mobile IP growth, the emerging Internet of Things, and cloud-based applications, wireless networking is witnessing a paradigm shift. By fully exploiting spatial degrees of freedom, massive multiple-input-multiple-output (MIMO) systems promise significant gains in data rates and link reliability. Although the research community has recognized the theoretical benefits of these systems, building the hardware of such complex systems is a challenge in practice. This paper presents a time division duplex (TDD)-based 128-antenna massive MIMO prototype system from theory to reality. First, an analytical signal model is provided to facilitate the setup of a feasible massive MIMO prototype system. Second, a link-level simulation consistent with practical TDDbased massive MIMO systems is conducted to guide and validate the massive MIMO system design. We design and implement the TDDbased 128-antenna massive MIMO prototype system with the guidelines obtained from the link-level simulation. Uplink real-time video transmission and downlink data transmission under the configuration of multiple single-antenna users are achieved. Comparisons with state-of-the-art prototypes demonstrate the advantages of the proposed system in terms of antenna number, bandwidth, latency, and throughput. The proposed system is also equipped with scalability, which makes the system applicable to a wide range of massive scenarios.
Artificial Intelligence in Music Education: A Critical Review

This paper reviews the principal approaches to using Artificial Intelligence in Music Education. Music is a challenging domain for Artificial Intelligence in Education (AI-ED) because music is, in general, an open-ended domain demanding creativity and problem-seeking on the part of learners and teachers. In addition, Artificial Intelligence theories of music are far from complete, and music education typically emphasises factors other than the communication of ‘knowledge’ to students. This paper reviews critically some of the principal problems and possibilities in a variety of AI-ED approaches to music education. Approaches considered include: Intelligent Tutoring Systems for Music; Music Logo Systems; Cognitive Support Frameworks that employ models of creativity; highly interactive interfaces that employ AI theories; AI-based music tools; and systems to support negotiation and reflection. A wide variety of existing music AI-ED systems are used to illustrate the key issues, techniques and methods associated with these approaches to AI-ED in Music.
Real-time bidirectional path tracing via rasterization

Global illumination drastically improves visual realism of interactive applications. Although many interactive techniques are available, they have some limitations or employ coarse approximations. For example, general instant radiosity often has numerical error, because the sampling strategy fails in some cases. This problem can be reduced by a bidirectional sampling strategy that is often used in off-line rendering. However, it has been complicated to implement in real-time applications. This paper presents a simple real-time global illumination system based on bidirectional path tracing. The proposed system approximates bidirectional path tracing by using rasterization on a commodity DirectX® 11 capable GPU. Moreover, for glossy surfaces, a simple and efficient artifact suppression technique is also introduced.
Robust Biomechanical Model-Based 3-D Indoor Localization and Tracking Method Using UWB and IMU

This paper proposes a robust sensor fusion algorithm to accurately track the spatial location and motion of a human under various dynamic activities, such as walking, running, and jumping. The position accuracy of the indoor wireless positioning systems frequently suffers from non-line-of-sight and multipath effects, resulting in heavy-tailed outliers and signal outages. We address this problem by integrating the estimates from an ultra-wideband (UWB) system and inertial measurement units, but also taking advantage of the estimated velocity and height obtained from an aiding lower body biomechanical model. The proposed method is a cascaded Kalman filter-based algorithm where the orientation filter is cascaded with the robust position/velocity filter. The outliers are detected for individual measurements using the normalized innovation squared, where the measurement noise covariance is softly scaled to reduce its weight. The positioning accuracy is further improved with the Rauch–Tung–Striebel smoother. The proposed algorithm was validated against an optical motion tracking system for both slow (walking) and dynamic (running and jumping) activities performed in laboratory experiments. The results show that the proposed algorithm can maintain high accuracy for tracking the location of a subject in the presence of the outliers and UWB signal outages with a combined 3-D positioning error of less than 13 cm.
Key roles of adjuvants in modern vaccines

Vaccines containing novel adjuvant formulations are increasingly reaching advanced development and licensing stages, providing new tools to fill previously unmet clinical needs. However, many adjuvants fail during product development owing to factors such as manufacturability, stability, lack of effectiveness, unacceptable levels of tolerability or safety concerns. This Review outlines the potential benefits of adjuvants in current and future vaccines and describes the importance of formulation and mechanisms of action of adjuvants. Moreover, we emphasize safety considerations and other crucial aspects in the clinical development of effective adjuvants that will help facilitate effective next-generation vaccines against devastating infectious diseases.
Design of Cooperative Non-Orthogonal Multicast Cognitive Multiple Access for 5G Systems: User Scheduling and Performance Analysis

Non-orthogonal multiple access (NOMA) is emerging as a promising, yet challenging, multiple access technology to improve spectrum utilization for the fifth generation (5G) wireless networks. In this paper, the application of NOMA to multicast cognitive radio networks (termed as MCR-NOMA) is investigated. A dynamic cooperative MCR-NOMA scheme is proposed, where the multicast secondary users serve as relays to improve the performance of both primary and secondary networks. Based on the available channel state information (CSI), three different secondary user scheduling strategies for the cooperative MCR-NOMA scheme are presented. To evaluate the system performance, we derive the closed-form expressions of the outage probability and diversity order for both networks. Furthermore, we introduce a new metric, referred to as mutual outage probability to characterize the cooperation benefit compared to non-cooperative MCR-NOMA scheme. Simulation results demonstrate significant performance gains are obtained for both networks, thanks to the use of our proposed cooperative MCR-NOMA scheme. It is also demonstrated that higher spatial diversity order can be achieved by opportunistically utilizing the CSI available for the secondary user scheduling.
Bi-directional FlipFET TM MOSFETs for Cell Phone Battery Protection Circuits

A bi-directional chip scale power MOSFET device is introduced for use in cell phone battery protection circuits. This device utilises the monolithic integration of two common drain power MOSFETs and solder bump technology to produce an ultra low footprint solution. Battery protection MOSFET packaging technology is reviewed along with cell phone current requirements. Comparisons are drawn between the in circuit performance of the bi-directional device and an industry standard TSSOP8. Device related losses in relation to IC drive strategy and conclusions on the effects of Rdson and package volume on cell phone talk and standby times are presented.
Detection and sequencing of Zika virus from amniotic fluid of fetuses with microcephaly in Brazil: a case study.

The incidence of microcephaly in Brazil in 2015 was 20 times higher than in previous years. Congenital microcephaly is associated with genetic factors and several causative agents. Epidemiological data suggest that microcephaly cases in Brazil might be associated with the introduction of Zika virus. We aimed to detect and sequence the Zika virus genome in amniotic fluid samples of two pregnant women in Brazil whose fetuses were diagnosed with microcephaly.



In this case study, amniotic fluid samples from two pregnant women from the state of Paraíba in Brazil whose fetuses had been diagnosed with microcephaly were obtained, on the recommendation of the Brazilian health authorities, by ultrasound-guided transabdominal amniocentesis at 28 weeks' gestation. The women had presented at 18 weeks' and 10 weeks' gestation, respectively, with clinical manifestations that could have been symptoms of Zika virus infection, including fever, myalgia, and rash. After the amniotic fluid samples were centrifuged, DNA and RNA were extracted from the purified virus particles before the viral genome was identified by quantitative reverse transcription PCR and viral metagenomic next-generation sequencing. Phylogenetic reconstruction and investigation of recombination events were done by comparing the Brazilian Zika virus genome with sequences from other Zika strains and from flaviviruses that occur in similar regions in Brazil.



We detected the Zika virus genome in the amniotic fluid of both pregnant women. The virus was not detected in their urine or serum. Tests for dengue virus, chikungunya virus, Toxoplasma gondii, rubella virus, cytomegalovirus, herpes simplex virus, HIV, Treponema pallidum, and parvovirus B19 were all negative. After sequencing of the complete genome of the Brazilian Zika virus isolated from patient 1, phylogenetic analyses showed that the virus shares 97-100% of its genomic identity with lineages isolated during an outbreak in French Polynesia in 2013, and that in both envelope and NS5 genomic regions, it clustered with sequences from North and South America, southeast Asia, and the Pacific. After assessing the possibility of recombination events between the Zika virus and other flaviviruses, we ruled out the hypothesis that the Brazilian Zika virus genome is a recombinant strain with other mosquito-borne flaviviruses.



These findings strengthen the putative association between Zika virus and cases of microcephaly in neonates in Brazil. Moreover, our results suggest that the virus can cross the placental barrier. As a result, Zika virus should be considered as a potential infectious agent for human fetuses. Pathogenesis studies that confirm the tropism of Zika virus for neuronal cells are warranted.
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

We introduce Similarity Group Proposal Network (SGPN), a simple and intuitive deep learning framework for 3D object instance segmentation on point clouds. SGPN uses a single network to predict point grouping proposals and a corresponding semantic class for each proposal, from which we can directly extract instance segmentation results. Important to the effectiveness of SGPN is its novel representation of 3D instance segmentation results in the form of a similarity matrix that indicates the similarity between each pair of points in embedded feature space, thus producing an accurate grouping proposal for each point. Experimental results on various 3D scenes show the effectiveness of our method on 3D instance segmentation, and we also evaluate the capability of SGPN to improve 3D object detection and semantic segmentation results. We also demonstrate its flexibility by seamlessly incorporating 2D CNN features into the framework to boost performance.
THE LEARNING ORGANIZATION FROM THE PERSPECTIVE OF THE EVOLUTIONARY EPISTEMOLOGY

Many authors have laid down a concept about organizational learning and the learning organization. Amongst them They contributed an explanation on how organizations learn and provided tools to transfer the theoretical concepts of organizational learning into practice. Regarding the present situation it seems, that organizational learning becomes even more important. This paper provides a complementary view on the learning organization from the perspective of the evolutionary epistemology. The evolutionary epistemology gives an answer, where the subjective structures of cognition come from and why they are similar in all human beings. Applying this evolutionary concept to organizations it could be possible to provide a deeper insight of the cognition processes of organizations and explain the principles that lay behind a learning organization. It also could give an idea, which impediments in learning, caused by natural dispositions, deduced from genetic barriers of cognition in biology are existing and managers must be aware of when trying to facilitate organizational learning within their organizations.
Detecting Malicious Web Links and Identifying Their Attack Types

Malicious URLs have been widely used to mount various cyber attacks including spamming, phishing and malware. Detection of malicious URLs and identification of threat types are critical to thwart these attacks. Knowing the type of a threat enables estimation of severity of the attack and helps adopt an effective countermeasure. Existing methods typically detect malicious URLs of a single attack type. In this paper, we propose method using machine learning to detect malicious URLs of all the popular attack types and identify the nature of attack a malicious URL attempts to launch. Our method uses a variety of discriminative features including textual properties, link structures, webpage contents, DNS information, and network traffic. Many of these features are novel and highly effective. Our experimental studies with 40,000 benign URLs and 32,000 malicious URLs obtained from real-life Internet sources show that our method delivers a superior performance: the accuracy was over 98% in detecting malicious URLs and over 93% in identifying attack types. We also report our studies on the effectiveness of each group of discriminative features, and discuss their evadability.
The Nest Architecture of the Ant Odontomachus brunneus


The architecture of the subterranean nests of the ant Odontomachus brunneus (Patton) (Hymenoptera: Formicidae) was studied by means of casts with dental plaster or molten metal. The entombed ants were later recovered by dissolution of plaster casts in hot running water. O. brunneus excavates simple nests, each consisting of a single, vertical shaft connecting more or less horizontal, simple chambers. Nests contained between 11 and 177 workers, from 2 to 17 chambers, and 28 to 340 cm(2) of chamber floor space and reached a maximum depth of 18 to 184 cm. All components of nest size increased simultaneously during nest enlargement, number of chambers, mean chamber size, and nest depth, making the nest shape (proportions) relatively size-independent. Regardless of nest size, all nests had approximately 2 cm(2) of chamber floor space per worker. Chambers were closer together near the top and the bottom of the nest than in the middle, and total chamber area was greater near the bottom. Colonies occasionally incorporated cavities made by other animals into their nests.
Traumatic Penile Injury: From Circumcision Injury to Penile Amputation

The treatment of external genitalia trauma is diverse according to the nature of trauma and injured anatomic site. The classification of trauma is important to establish a strategy of treatment; however, to date there has been less effort to make a classification for trauma of external genitalia. The classification of external trauma in male could be established by the nature of injury mechanism or anatomic site: accidental versus self-mutilation injury and penis versus penis plus scrotum or perineum. Accidental injury covers large portion of external genitalia trauma because of high prevalence and severity of this disease. The aim of this study is to summarize the mechanism and treatment of the traumatic injury of penis. This study is the first review describing the issue.
Tracking EEG changes in response to alpha and beta binaural beats.

A binaural beat can be produced by presenting two tones of a differing frequency, one to each ear. Such auditory stimulation has been suggested to influence behaviour and cognition via the process of cortical entrainment. However, research so far has only shown the frequency following responses in the traditional EEG frequency ranges of delta, theta and gamma. Hence a primary aim of this research was to ascertain whether it would be possible to produce clear changes in the EEG in either the alpha or beta frequency ranges. Such changes, if possible, would have a number of important implications as well as potential applications. A secondary goal was to track any observable changes in the EEG throughout the entrainment epoch to gain some insight into the nature of the entrainment effects on any changes in an effort to identify more effective entrainment regimes. Twenty two healthy participants were recruited and randomly allocated to one of two groups, each of which was exposed to a distinct binaural beat frequency for ten 1-minute epochs. The first group listened to an alpha binaural beat of 10 Hz and the second to a beta binaural beat of 20 Hz. EEG was recorded from the left and right temporal regions during pre-exposure baselines, stimulus exposure epochs and post-exposure baselines. Analysis of changes in broad-band and narrow-band amplitudes, and frequency showed no effect of binaural beat frequency eliciting a frequency following effect in the EEG. Possible mediating factors are discussed and a number of recommendations are made regarding future studies, exploring entrainment effects from a binaural beat presentation.
Unusual suicide with a chainsaw.

Described here is a case of suicide with the use of a chainsaw. A female suffering from schizophrenia committed suicide by an ingenious use of a chainsaw that resulted in the transection of her cervical spine and spinal cord. The findings of the resulting investigation are described and the mechanism of suicides with the use of a chainsaw is reviewed. A dry bone study was realized to determine the bone sections, the correlation between anatomic lesions and characteristics of chainsaw. The damage of organs and soft tissues is compared according to the kinds of chainsaw used.
Scaling up physical activity interventions worldwide: stepping up to larger and smarter approaches to get people moving

The global pandemic of physical inactivity requires a multisectoral, multidisciplinary public-health response. Scaling up interventions that are capable of increasing levels of physical activity in populations across the varying cultural, geographic, social, and economic contexts worldwide is challenging, but feasible. In this paper, we review the factors that could help to achieve this. We use a mixed-methods approach to comprehensively examine these factors, drawing on the best available evidence from both evidence-to-practice and practice-to-evidence methods. Policies to support active living across society are needed, particularly outside the health-care sector, as demonstrated by some of the successful examples of scale up identified in this paper. Researchers, research funders, and practitioners and policymakers in culture, education, health, leisure, planning, and transport, and civil society as a whole, all have a role. We should embrace the challenge of taking action to a higher level, aligning physical activity and health objectives with broader social, environmental, and sustainable development goals.
Virtual Reality Simulation Modeling for a Haptic Glove

The recent addition of force and touch feedback to Virtual Reality simulations has enhanced their realism. Research on haptics interfaces is now extended to physical modeling of contact surfaces, object hardness, surface deformation, etc.. This is especially needed when dextrous manipulation of virtual objects is concerned. This paper describes a VR system using a haptic glove (Rutgers Master II) connected to a PC workstation, and a new method for modeling virtual hand haptic interactions. An application example presented here is an orthopedic rehabilitation library. The exercises in this library involve interactions with dynamic objects and physical modeling of plasticity.
Automatic Anomaly Detection in the Cloud Via Statistical Learning

Performance and high availability have become increasingly important drivers, amongst other drivers, for user retention in the context of web services such as social networks, and web search. Exogenic and/or endogenic factors often give rise to anomalies, making it very challenging to maintain high availability, while also delivering high performance. Given that service-oriented architectures (SOA) typically have a large number of services, with each service having a large set of metrics, automatic detection of anomalies is nontrivial. Although there exists a large body of prior research in anomaly detection, existing techniques are not applicable in the context of social network data, owing to the inherent seasonal and trend components in the time series data. To this end, we developed two novel statistical techniques for automatically detecting anomalies in cloud infrastructure data. Specifically, the techniques employ statistical learning to detect anomalies in both application, and system metrics. Seasonal decomposition is employed to filter the trend and seasonal components of the time series, followed by the use of robust statistical metrics – median and median absolute deviation (MAD) – to accurately detect anomalies, even in the presence of seasonal spikes. We demonstrate the efficacy of the proposed techniques from three different perspectives, viz., capacity planning, user behavior, and supervised learning. In particular, we used production data for evaluation, and we report Precision, Recall, and F-measure in each case.
Pressure ulcer knowledge of registered nurses, assistant nurses and student nurses: a descriptive, comparative multicentre study in Sweden.

The aim of this study was to describe and compare the knowledge of registered nurses (RNs), assistant nurses (ANs) and student nurses (SNs) about preventing pressure ulcers (PUs). PU prevention behaviours in the clinical practice of RNs and ANs were also explored. A descriptive, comparative multicentre study was performed. Hospital wards and universities from four Swedish county councils participated. In total, 415 participants (RN, AN and SN) completed the Pressure Ulcer Knowledge Assessment Tool. The mean knowledge score for the sample was 58·9%. The highest scores were found in the themes 'nutrition' (83·1%) and 'risk assessment' (75·7%). The lowest scores were found in the themes 'reduction in the amount of pressure and shear' (47·5%) and 'classification and observation' (55·5%). RNs and SNs had higher scores than ANs on 'aetiology and causes'. SNs had higher scores than RNs and ANs on 'nutrition'. It has been concluded that there is a knowledge deficit in PU prevention among nursing staff in Sweden. A major educational campaign needs to be undertaken both in hospital settings and in nursing education.
Numerical password via graphical input — An authentication system on embedded platform

Graphical systems have been in use in the embedded world for user authentication. Image based systems use image, area or pattern selection process. This paper presents a novel method that employ image recognition at its first level and a modified PassPoint logic with randomization using LFSR at its next level to provide a well secured password authentication system. The proposed real-time authentication scheme for embedded system aims at reducing the password storage space against a similar implementation on embedded platform.