nils-herrmann/clean_scirepeval huggingface dataset:
Plasticity of Cancer Cell Invasion-Mechanisms and Implications for Therapy.

Cancer cell migration is a plastic and adaptive process integrating cytoskeletal dynamics, cell-extracellular matrix and cell-cell adhesion, as well as tissue remodeling. In response to molecular and physical microenvironmental cues during metastatic dissemination, cancer cells exploit a versatile repertoire of invasion and dissemination strategies, including collective and single-cell migration programs. This diversity generates molecular and physical heterogeneity of migration mechanisms and metastatic routes, and provides a basis for adaptation in response to microenvironmental and therapeutic challenge. We here summarize how cytoskeletal dynamics, protease systems, cell-matrix and cell-cell adhesion pathways control cancer cell invasion programs, and how reciprocal interaction of tumor cells with the microenvironment contributes to plasticity of invasion and dissemination strategies. We discuss the potential and future implications of predicted "antimigration" therapies that target cytoskeletal dynamics, adhesion, and protease systems to interfere with metastatic dissemination, and the options for integrating antimigration therapy into the spectrum of targeted molecular therapies.
A fast algorithm for integrating connected-component labeling and euler number computation

This paper proposes a fast algorithm for integrating connected-component labeling and Euler number computation. Based on graph theory, the Euler number of a binary image in the proposed algorithm is calculated by counting the occurrences of four patterns of the mask for processing foreground pixels in the first scan of a connected-component labeling process, where these four patterns can be found directly without any additional calculation; thus, connected-component labeling and Euler number computation can be integrated more efficiently. Moreover, when computing the Euler number, unlike other conventional algorithms, the proposed algorithm does not need to process background pixels. Experimental results demonstrate that the proposed algorithm is much more efficient than conventional algorithms either for calculating the Euler number alone or simultaneously calculating the Euler number and labeling connected components.
[Guidelines of the European Respiratory Society and the European Society of Thoracic Surgeons for the management of malignant pleural mesothelioma].

Disclaimer: "This Chinese translation has not been reviewed by European Respiratory Society prior to publication, therefore the European Respiratory Society may not be responsible for any errors, omissions or inaccuracies, or for any consequences arising there from, in the Chinese content." Correspondence to: A. Scherpereel. Dept of Pulmonary and Thoracic Oncology, Hospital Calmette CHRU of Lille 59037 Lille Cedex, France E-mail: a-scherpereel@chru-lille.fr  35: 479-495. 欧洲呼吸学会和欧洲胸外科医师学会恶性 胸膜间皮瘤诊疗指南
Suitability of LTE for drone-to-infrastructure communications in very low level airspace

The increasing availability of cheap and powerful drones for various applications is likely to cause a heavy usage of the very low level airspace in metropolitan areas with hundreds of simultaneously airborne drones per square kilometer in the near future. Certainly, the predicted large number of drones presents a major challenge to future UTM and especially to supporting communications systems. However, a robust and reliable communications system for drone-to-infrastructure communications is inevitably needed to grant all drones access to various services provided by UTM. In previous works, it has already been shown that commercial LTE networks are capable of providing connectivity to drones flying at low altitudes in principle. However, airborne drones which transmit data to the UTM infrastructure produce severe inter-cell interference since they have a strong line-of-sight connection to multiple LTE base stations at a time. Hence, we investigate further the suitability of the LTE uplink for drone-to-infrastructure communications in very low level airspace by LTE system-level simulations in this work. In particular, we identify the maximum drone density that can be thoroughly monitored and safely coordinated by a UTM system with LTE communication links. Our simulations show that an LTE system with 5 Mhz uplink bandwidth can support a message delivery ratio of more than 95% for drone densities of up to 200 drones per square kilometer assuming that all drones have to periodically transmit messages of 300 bytes at a rate of 10 Hz. It is concluded that future research has to focus on the mitigation of inter-cell interference so even a larger number of drones can get reliable access to all UTM services.
Sensor data fusion using a probability density grid

A novel technique has been developed at DRDC Ottawa for fusing electronic warfare (EW) sensor data by numerically combining the probability density function representing the measured value and error estimate provided by each sensor. Multiple measurements are sampled at common discrete intervals to form a probability density grid and combined to produce the fused estimate of the measured parameter. This technique, called the discrete probability density (DPD) method, is used to combine sensor measurements taken from different locations for the EW function of emitter geolocation. Results are presented using simulated line of bearing measurements and are shown to approach the theoretical location accuracy limit predicted by the Cramer-Rao lower bound. The DPD method is proposed for fusing other geolocation sensor data including time of arrival, time difference of arrival, and a priori information.
Designing Hardware for Machine Learning: The Important Role Played by Circuit Designers

Machine learning is becoming increasingly important in this era of big data. It enables us to extract meaningful information from the overwhelming amount of data being generated and collected every day. This information can be used to analyze and understand the data to identify trends (e.g., surveillance and portable/wearable electronics) or to take immediate action (e.g., robotics/drones, self-driving cars, and smart Internet of Things). In many applications, embedded processing near the sensor is preferred over the cloud due to privacy or latency concerns or limitations in the communication bandwidth. However, sensor devices often have stringent constraints on energy consumption and cost in addition to throughput and accuracy requirements. Circuit designers can play an important role in addressing these challenges by developing energy-efficient platforms to perform the necessary processing for machine learning. In this article, we will give a short overview of the key concepts in machine learning, discuss its challenges particularly in the embedded space, and highlight various opportunities where circuit designers can help to address these challenges.
Democracy , News Media , and Famine Prevention : Amartya Sen and The Bihar Famine

In much of his writings on poverty, famines, and malnutrition, Amartya Sen argues that Democracy is the best way to avoid famines partly because of its ability to use a free press, and that the Indian experience since independence confirms this. His argument is partly empirical, but also relies on some a priori assumptions about human motivation. In his “Democracy as a Universal Value” he claims: Famines are easy to prevent if there is a serious effort to do so, and a democratic government, facing elections and criticisms from opposition parties and independent newspapers, cannot help but make such an effort. Not surprisingly, while India continued to have famines under British rule right up to independence ...they disappeared suddenly with the establishment of a multiparty democracy and a free press.
12 Intelligent Flight Control of an Autonomous Quadrotor

This chapter describes the different steps of designing, building, simulating, and testing an intelligent flight control module for an increasingly popular unmanned aerial vehicle (UAV), known as a quadrotor. It presents an in-depth view of the modeling of the kinematics, dynamics, and control of such an interesting UAV. A quadrotor offers a challenging control problem due to its highly unstable nature. An effective control methodology is therefore needed for such a unique airborne vehicle. The chapter starts with a brief overview on the quadrotor's background and its applications, in light of its advantages. Comparisons with other UAVs are made to emphasize the versatile capabilities of this special design. For a better understanding of the vehicle's behavior, the quadrotor's kinematics and dynamics are then detailed. This yields the equations of motion, which are used later as a guideline for developing the proposed intelligent flight control scheme. In this chapter, fuzzy logic is adopted for building the flight controller of the quadrotor. It has been witnessed that fuzzy logic control offers several advantages over certain types of conventional control methods, specifically in dealing with highly nonlinear systems and modeling uncertainties. Two types of fuzzy inference engines are employed in the design of the flight controller, each of which is explained and evaluated. For testing the designed intelligent flight controller, a simulation environment was first developed. The simulations were made as realistic as possible by incorporating environmental disturbances such as wind gust and the ever-present sensor noise. The proposed controller was then tested on a real test-bed built specifically for this project. Both the simulator and the real quadrotor were later used for conducting different attitude stabilization experiments to evaluate the performance of the proposed control strategy. The controller's performance was also benchmarked against conventional control techniques such as input-output linearization, backstepping and sliding mode control strategies. Conclusions were then drawn based on the conducted experiments and their results.
Parking Assistance System for Leaving Perpendicular Parking Lots: Experiments in Daytime\/Nighttime Conditions

Backing-out and heading-out maneuvers in perpendicular or angle parking lots are one of the most dangerous maneuvers, especially in cases where side parked cars block the driver view of the potential traffic flow. In this paper, a new vision-based Advanced Driver Assistance System (ADAS) is proposed to automatically warn the driver in such scenarios. A monocular grayscale camera was installed at the back-right side of a vehicle. A Finite State Machine (FSM) defined according to three CAN Bus variables and a manual signal provided by the user is used to handle the activation/deactivation of the detection module. The proposed oncoming traffic detection module computes spatio-temporal images from a set of predefined scan-lines which are related to the position of the road. A novel spatio-temporal motion descriptor is proposed (STHOL) accounting for the number of lines, their orientation and length of the spatio-temporal images. Some parameters of the proposed descriptor are adapted for nighttime conditions. A Bayesian framework is then used to trigger the warning signal using multivariate normal density functions. Experiments are conducted on image data captured from a vehicle parked at different location of an urban environment, including both daytime and nighttime lighting conditions. We demonstrate that the proposed approach provides robust results maintaining processing rates close to real time.
Inferring User Interests From Microblogs Ceren Budak Anitha

We address the problem of inferring users’ interests from microblogging sites such as Twitter, based on their utterances and interactions in the social network. Inferring user interests is important for systems such as search and recommendation engines to provide information that is more attuned to the likes of its users. In this paper, we propose a probabilistic generative model of user utterances that encapsulates both user and network information. This model captures the complex interactions between varied interests of the users, his level of activeness in the network, and the information propagation from the neighbors. As exact probabilistic inference in this model is intractable, we propose an online variational inference algorithm that also takes into account evolving social graph, user and his neighbors? interests. We prove the optimality of the online inference with respect to an equivalent batch update. We present experimental results performed on the actual Twitter users, validating our approach. We also present extensive results showing inadequacy of using Mechanical Turk platform for large scale validation.
Millimeter-wave beamforming as an enabling technology for 5G cellular communications: theoretical feasibility and prototype results

The ever growing traffic explosion in mobile communications has recently drawn increased attention to the large amount of underutilized spectrum in the millimeter-wave frequency bands as a potentially viable solution for achieving tens to hundreds of times more capacity compared to current 4G cellular networks. Historically, mmWave bands were ruled out for cellular usage mainly due to concerns regarding short-range and non-line-of-sight coverage issues. In this article, we present recent results from channel measurement campaigns and the development of advanced algorithms and a prototype, which clearly demonstrate that the mmWave band may indeed be a worthy candidate for next generation (5G) cellular systems. The results of channel measurements carried out in both the United States and Korea are summarized along with the actual free space propagation measurements in an anechoic chamber. Then a novel hybrid beamforming scheme and its link- and system-level simulation results are presented. Finally, recent results from our mmWave prototyping efforts along with indoor and outdoor test results are described to assert the feasibility of mmWave bands for cellular usage.
A new surgical correction of cryptotia: a new flap design and switched double banner flap.

Cryptotia is a congenital auricular anomaly that frequently occurs in Asians. In cryptotia, the upper third of the auricle is collapsed and buried under the temporal skin. We have treated patients who could not be treated by splinting with bent paper clips, using various surgical methods.1–4 Several problems remain, however, such as conspicuous scars, a shallow auriculotemporal sulcus, and incomplete correction of auricular cartilage. Therefore, we devised a new surgical method using a new skin flap design based on Fukuda’s method2 and a new concept of Tanzer’s double banner flap.5 Using this method, we produced good auricular contour with a deep auriculotemporal sulcus and no conspicuous scars.
An Evaluation of the Proposed Framework for Access Control in the Cloud and BYOD Environment

As the bring your own device (BYOD) to work trend grows, so do the network security risks. This fast-growing trend has huge benefits for both employees and employers. With malware, spyware and other malicious downloads, tricking their way onto personal devices, organizations need to consider their information security policies. Malicious programs can download onto a personal device without a user even knowing. This can have disastrous results for both an organization and the personal device. When this happens, it risks BYODs making unauthorized changes to policies and leaking sensitive information into the public domain. A privacy breach can cause a domino effect with huge financial and legal implications, and loss of productivity for organizations. This is a difficult challenge. Organizations need to consider user privacy and rights together with protecting networks from attacks. This paper evaluates a new architectural framework to control the risks that challenge organizations and the use of BYODs. After analysis of large volumes of research, the previous studies addressed single issues. We integrated parts of these single solutions into a new framework to develop a complete solution for access control. With too many organizations failing to implement and enforce adequate security policies, the process needs to be simpler. This framework reduces system restrictions while enforcing access control policies for BYOD and cloud environments using an independent platform. Primary results of the study are positive with the framework reducing access control issues. Bring your own device; access control; policy; security
Context encoders as a simple but powerful extension of word2vec

With a strikingly simple architecture and the ability to learn meaningful word embeddings efficiently from texts containing billions of words, word2vec remains one of the most popular neural language models used today. However, as only a single embedding is learned for every word in the vocabulary, the model fails to optimally represent words with multiple meanings and, additionally, it is not possible to create embeddings for new (out-of-vocabulary) words on the spot. Based on an intuitive interpretation of the continuous bag-of-words (CBOW) word2vec model’s negative sampling training objective in terms of predicting context based similarities, we motivate an extension of the model we call context encoders (ConEc). By multiplying the matrix of trained word2vec embeddings with a word’s average context vector, out-ofvocabulary (OOV) embeddings and representations for words with multiple meanings can be created based on the words’ local contexts. The benefits of this approach are illustrated by using these word embeddings as features in the CoNLL 2003 named entity recognition (NER) task.
A Comprehensive Survey on various Feature Selection Methods to Categorize Text Documents

Feature selection is one of the well known solution to high dimensionality problem of text categorization. In text categorization, selection of good features (terms) plays a very important role. Feature selection is a strategy that can be used to improve categorization accuracy, effectiveness and computational efficiency. This paper presents an empirical study of most widely used feature selection methods viz. Term Frequency-Inverse Document Frequency (tf·idf ), Information Gain (IG), Mutual Information(MI), CHI-Square (χ), Ambiguity Measure (AM), Term Strength (TS), Term Frequency-Relevance Frequency (tf·rf ) and Symbolic Feature Selection (SFS) with five different classifiers (Nave Bayes, KNearest Neighbor, Centroid Based Classifier, Support Vector Machine and Symbolic Classifier). Experimentations are carried out on standard bench mark datasets like Reuters-21578, 20-Newsgroups and 4 University dataset.
Chatbot Design - Towards a Social Analysis Using i* and process architecture

Software systems are often designed without considering their social intentionality and the software process changes required to accommodate them. With the rise of artificial intelligence and cognitive services-based systems, software can no longer be considered a passive participant in a domain. Structured and methodological approaches are required to study the intentions and motives of such software systems and their corresponding effect on the design of business and software processes that interact with these software systems. This paper considers chatbots as domain example for illustrating the complexities of designing such intentional and intelligent systems, and the resultant changes and reconfigurations in processes. A mechanism of associating process architecture models and actor models is presented. The modeling and analysis of two types of chatbots retrieval-based and generative are shown using both process architecture and actor models.
Design & Development of a GSM Based Vehicle Theft Control System

This paper deals with the design & development of a theft control system for an automobile, which is being used to prevent/control the theft of a vehicle. The developed system makes use of an embedded system based on GSM technology. The designed & developed system is installed in the vehicle. An interfacing mobile is also connected to the microcontroller, which is in turn, connected to the engine. Once, the vehicle is being stolen, the information is being used by the vehicle owner for further processing. The information is passed onto the central processing insurance system, where by sitting at a remote place, a particular number is dialed by them to the interfacing mobile that is with the hardware kit which is installed in the vehicle. By reading the signals received by the mobile, one can control the ignition of the engine; say to lock it or to stop the engine immediately. Again it will come to the normal condition only after entering a secured password. The owner of the vehicle & the central processing system will know this secured password. The main concept in this design is introducing the mobile communications into the embedded system. The designed unit is very simple & low cost. The entire designed unit is on a single chip. When the vehicle is stolen, owner of vehicle may inform to the central processing system, then they will stop the vehicle by just giving a ring to that secret number and with the help of SIM tracking knows the location of vehicle and informs to the local police or stops it from further movement.
Forensic entomology

Necrophagous insects are important in the decomposition of cadavers. The close association between insects and corpses and the use of insects in medicocriminal investigations is the subject of forensic entomology. The present paper reviews the historical background of this discipline, important postmortem processes, and discusses the scientific basis underlying attempts to determine the time interval since death. Using medical techniques, such as the measurement of body temperature or analysing livor and rigor mortis, time since death can only be accurately measured for the first two or three days after death. In contrast, by calculating the age of immature insect stages feeding on a corpse and analysing the necrophagous species present, postmortem intervals from the first day to several weeks can be estimated. These entomological methods may be hampered by difficulties associated with species identification, but modern DNA techniques are contributing to the rapid and authoritative identification of necrophagous insects. Other uses of entomological data include the toxicological examination of necrophagous larvae from a corpse to identify and estimate drugs and toxicants ingested by the person when alive and the proof of possible postmortem manipulations. Forensic entomology may even help in investigations dealing with people who are alive but in need of care, by revealing information about cases of neglect.
3 D vs . 2 D Surface Shape Analysis of the Corpus Callosum in Premature Neonates

Regional morphometic analyses of the corpus callosum (CC) are typically done using the 2D medial section of the structure, but the shape information is lost through this method. Here we perform 3D regional group comparisons of the surface anatomy of the CC between 12 preterm and 11 term-born neonates. We reconstruct CC surfaces from manually segmented brain MRI and build parametric meshes on the surfaces by computing surface conformal parameterizations with holomorphic 1-forms. Surfaces are registered by constrained harmonic maps on the parametric domains and statistical comparisons between the two groups are performed via multivariate tensor-based morphometry (mTBM). We detect statistically significant morphological changes in the genu and the splenium. Our mTBM analysis is compared to the medial axis distance [13], and to a usual 2D analysis.