nils-herrmann/clean_scirepeval huggingface dataset:
Multilayer integration and packaging on substrate integrated waveguide for next generation wireless applications

This paper presents the design techniques and realization examples of innovative multilayer substrate integrated waveguide (SIW) structures for integrated wireless system applications. Such multilayered SIW implementation presents numerous advantages such as low profile, light weight, wideband characteristics, and easy integration with other devices and components. In this paper, the state-of-the-art of multilayer SIW passive components for low-cost high-density integrated transceiver design are presented. Filters, couplers, phase shifters, power dividers, and antenna arrays designed for specific applications are discussed and the advantages gained from multilayer schemes are described. Despite their easy fabrications and outstanding performances, these technologies are still struggling to compete with others for potential mainstream solutions. In this paper, we also discuss challenging issues in the development of multilayer SIW integrated modules that should enable a near-future successful widespread deployment.
Serratia marcescens Rhabdomyolysis

Serratia marcescens has been recognized as an important cause of nosocomial and community-acquired infections. To our knowledge, we describe the first case of S. marcescens rhabdomyolysis, most probably related to acute cholecystitis and secondary bacteremia. The condition was successfully managed with levofloxacin. Keeping in mind the relevant morbidity and mortality associated with bacterial rhabdomyolysis, physicians should consider this possibility in patients with suspected or proven bacterial disease. We suggest S. marcescens should be regarded as a new causative agent of infectious rhabdomyolysis.
Adaptive diversification of recommendation results via latent factor portfolio

This paper studies result diversification in collaborative filtering. We argue that the diversification level in a recommendation list should be adapted to the target users' individual situations and needs. Different users may have different ranges of interests -- the preference of a highly focused user might include only few topics, whereas that of the user with broad interests may encompass a wide range of topics. Thus, the recommended items should be diversified according to the interest range of the target user. Such an adaptation is also required due to the fact that the uncertainty of the estimated user preference model may vary significantly between users. To reduce the risk of the recommendation, we should take the difference of the uncertainty into account as well.
 In this paper, we study the adaptive diversification problem theoretically. We start with commonly used latent factor models and reformulate them using the mean-variance analysis from the portfolio theory in text retrieval. The resulting Latent Factor Portfolio (LFP) model captures the user's interest range and the uncertainty of the user preference by employing the variance of the learned user latent factors. It is shown that the correlations between items (and thus the item diversity) can be obtained by using the correlations between latent factors (topical diversity), which in return significantly reduce the computation load. Our mathematical derivation also reveals that diversification is necessary, not only for risk-averse system behavior (non-adpative), but also for the target users' individual situations (adaptive), which are represented by the distribution and the variance of the latent user factors. Our experiments confirm the theoretical insights and show that LFP succeeds in improving latent factor models by adaptively introducing recommendation diversity to fit the individual user's needs.
Design of PRN based Octa-rate clock and data recovery circuit using FPGA

Clock and data recovery (CDR) circuit plays a vital role for wired serial link communication in multi mode based system on chip (SOC). In wire linked communication systems, when data flows without any accompanying clock over a single wire, the receiver of the system is required to recover this data synchronously without losing the information. Therefore there exists a need for CDR circuits in the receiver of the system for recovering the clock or timing information from these data. The existing Octa-rate CDR circuit is not compatible to real time data, such a data is unpredictable, non periodic and has different arrival times and phase widths. Thus the proposed PRN based Octa-rate Clock and Data Recovery circuit is made compatible to real time data by introducing a Random Sequence Generator. The proposed PRN based Octa-rate Clock and Data Recovery circuit consists of PRN Sequence Generator, 16-Phase Generator, Early Late Phase Detector and Delay Line Controller. The FSM based Delay Line Controller controls the delay length and introduces the required delay in the input data. The PRN based Octa-rate CDR circuit has been realized using Xilinx ISE 13.2 and implemented on Vertex-5 FPGA target device for real time verification. The delay between the input and the generation of output is measured and analyzed using Logic Analyzer AGILENT 1962 A.
Mitek Suspension of the Lateral Nasal Wall.

The nasal valve has long been described as the anatomical boundary most likely to inhibit nasal airflow and lead to subsequent nasal obstruction. Although many procedures can address this area to improve the nasal airway, for over 20 years, suture lateralization of the external nasal valve has been described as a minimally invasive technique that can improve nasal breathing. We report our modification of the standard technique in which we lateralize the placement of the bone-anchored suture and incorporate Gore-Tex within the nasal vestibular incision to prevent tissue migration.
Internet of Things Based Intelligent Street Lighting System for Smart City

This project aims for designing and executing the advanced development in embedded systems for energy saving of street lights. Currently we have a manual system where the street lights will be switched ON in the evening before the sunsets and they are switched OFF in the next day morning after there is sufficient light on the outside[1]. But the actual timing for these lights to be switched ON is when there is absolute darkness. With this, the power will be wasted up to some extent. This project gives solution for electrical power wastage . Also the manual operation of the lighting system is completely eliminated. The proposed system provide a solution for energy saving. This is achieved by sensing and approaching a vehicle using an IR transmitter and IR Receiver couple. Upon sensing the movement the sensor transmit the data to the microcontroller which furthermore the Light to switch ON . Similarly as soon as the vehicle or an obstacle goes away the Light gets switched OFF as the sensor sense any object at the same time the status(ON/OFF) of the street light can be accessed from anywhere and anytime through internet. This project is implemented with smart embedded system which controls the street lights based on detection of vehicles or any other obstacles on the street .Whenever the obstacle is detected on the street within the specified time the light will get automatically ON/OFF according to the obstacle detection and the same information can be accessed through internet. The real time information of the street light(ON/OFF Status) can be accessed from anytime, anywhere through internet.
A new algorithm for computing Boolean operations on polygons

This paper presents a new algorithm for computing Boolean operations on polygons. This kind of operations are frequently used in Geosciences in order to get spatial information from spatial data modeled as polygons. The presented algorithm is simple and easy to understand and implement. Let n be the total number of edges of all the polygons involved in a Boolean operation and k be the number of intersections of all the polygon edges. Our algorithm computes the Boolean operation in time O((n + k) log n). Finally, the proposed algorithm works with concave polygons with holes, and with regions composed of polygon sets. Furthermore, it can be easily adapted to work with self-intersecting polygons.
An efficient and cost effective FPGA based implementation of the Viola-Jones face detection algorithm

We present an field programmable gate arrays (FPGA) based implementation of the popular Viola-Jones face detection algorithm, which is an essential building block in many applications such as video surveillance and tracking. Our implementation is a complete system level hardware design described in a hardware description language and validated on the affordable DE2-115 evaluation board. Our primary objective is to study the achievable performance with a low-end FPGA chip based implementation. In addition, we release to the public domain the entire project. We hope that this will enable other researchers to easily replicate and compare their results to ours and that it will encourage and facilitate further research and educational ideas in the areas of image processing, computer vision, and advanced digital design and FPGA prototyping.
Stereo-based 6D object localization for grasping with humanoid robot systems

Robust vision-based grasping is still a hard problem for humanoid robot systems. When being restricted to using the camera system built-in into the robot's head for object localization, the scenarios get often very simplified in order to allow the robot to grasp autonomously. Within the computer vision community, many object recognition and localization systems exist, but in general, they are not tailored to the application on a humanoid robot. In particular, accurate 6D object localization in the camera coordinate system with respect to a 3D rigid model is crucial for a general framework for grasping. While many approaches try to avoid the use of stereo calibration, we will present a system that makes explicit use of the stereo camera system in order to achieve maximum depth accuracy. Our system can deal with textured objects as well as objects that can be segmented globally and are defined by their shape. Thus, it covers the cases of objects with complex texture and complex shape. Our work is directly linked to a grasping framework being implemented on the humanoid robot ARM AR and serves as its perception module for various grasping and manipulation experiments in a kitchen scenario.
Using social networks to harvest email addresses

Social networking is one of the most popular Internet activities with millions of members from around the world. However, users are unaware of the privacy risks involved. Even if they protect their private information, their name is enough to be used for malicious purposes. In this paper we demonstrate and evaluate how names extracted from social networks can be used to harvest email addresses as a first step for personalized phishing campaigns. Our blind harvesting technique uses names collected from the Facebook and Twitter networks as query terms for the Google search engine, and was able to harvest almost 9 million unique email addresses. We compare our technique with other harvesting methodologies, such as crawling the World Wide Web and dictionary attacks, and show that our approach is more scalable and efficient than the other techniques. We also present three targeted harvesting, techniques that aim to collect email addresses coupled with personal information for the creation of personalized phishing emails. By using information available in Twitter to narrow down the search space and, by utilizing the Facebook email search functionality, we are able to successfully map 43.4% of the user profiles to their actual email address. Furthermore, we harvest profiles from Google Buzz, 40% of whom provide a direct mapping to valid Gmail addresses.
Morphological classification of blood leucocytes by microscope images

The classification and the count of white blood cells in microscopy images allows the in vivo assessment of a wide range of important hematic pathologies (i.e., from presence of infections to leukemia). Nowadays, the morphological cell classification is typically made by experienced operators. Such a procedure presents undesirable drawbacks: slowness and it presents a not standardized accuracy since it depends on the operator's capabilities and tiredness. Only few attempts of partial/full automated systems based on image-processing systems are present in literature and they are still at prototype stage. This paper presents a methodology to achieve an automated detection and classification of leucocytes by microscope color images. The proposed system firstly individuates in the blood image the leucocytes from the others blood cells, then it extracts morphological indexes and finally it classifies the leucocytes by a neural classifier in Basophil, Eosinophil, Lymphocyte, Monocyte and Neutrophil.
Demo: OpenAirInterface: an open LTE network in a PC

LTE 4G cellular networks are gradually being adopted by all major operators in the world and are expected to rule the cellular landscape at least for the current decade. They will also form the starting point for further progress beyond the current generation of mobile cellular networks to chalk a path towards fifth generation mobile networks. The lack of open cellular ecosystem has limited applied research in this field within the boundaries of vendor and operator R&D groups. Furthermore, several new approaches and technologies are being considered as potential elements making up such a future mobile network, including cloudification of radio network, radio network programability and APIs following SDN principles, native support of machine-type communication, and massive MIMO. Research on these technologies requires realistic and flexible experimentation platforms that offer a wide range of experimentation modes from real-world experimentation to controlled and scalable evaluations while at the same time retaining backward compatibility with current generation systems.
 In this work, we present OpenAirInterface (OAI) as a suitably flexible platform towards open LTE ecosystem and playground . We will demonstrate an example of the use of OAI to deploy a low-cost open LTE network using commodity hardware with standard LTE-compatible devices. We also show the reconfigurability features of the platform.
A universal state-of-charge algorithm for batteries

State-of-charge (SOC) measures energy left in a battery, and it is critical for modeling and managing batteries. Developing efficient yet accurate SOC algorithms remains a challenging task. Most existing work uses regression based on a time-variant circuit model, which may be hard to converge and often does not apply to different types of batteries. Knowing open-circuit voltage (OCV) leads to SOC due to the well known mapping between OCV and SOC. In this paper, we propose an efficient yet accurate OCV algorithm that applies to all types of batteries. Using linear system analysis but without a circuit model, we calculate OCV based on the sampled terminal voltage and discharge current of the battery. Experiments show that our algorithm is numerically stable, robust to history dependent error, and obtains SOC with less than 4% error compared to a detailed battery simulation for a variety of batteries. Our OCV algorithm is also efficient, and can be used as a real-time electro-analytical tool revealing what is going on inside the battery.
Advanced strategies for quality control of Chinese medicines.

Quality control is always the critical issue for Chinese medicines (CMs) with their worldwide increasing use. Different from western medicine, CMs are usually considered that multiple constituents are responsible for the therapeutic effects. Therefore, quality control of CMs is a challenge. In 2011, the strategies for quantification, related to the markers, reference compounds and approaches, in quality control of CMs were reviewed (Li, et al.,  2011, 55, 802-809). Since then, some new strategies have been proposed in these fields. Therefore, the review on the strategies for quality control of CMs should be updated to improve the safety and efficacy of CMs. Herein, novel strategies related to quality marker discovery, reference compound development and advanced approaches (focused on glyco-analysis) for quality control, during 2011-2016, were summarized and discussed.
Personal names and the attentional blink: a visual "cocktail party" effect.

Four experiments were carried out to investigate an early- versus late-selection explanation for the attentional blink (AB). In both Experiments 1 and 2, 3 groups of participants were required to identify a noun (Experiment 1) or a name (Experiment 2) target (experimental conditions) and then to identify the presence or absence of a 2nd target (probe), which was their own name, another name, or a specified noun from among a noun distractor stream (Experiment 1) or a name distractor stream (Experiment 2). The conclusions drawn are that individuals do not experience an AB for their own names but do for either other names or nouns. In Experiments 3 and 4, either the participant's own name or another name was presented, as the target and as the item that immediately followed the target, respectively. An AB effect was revealed in both experimental conditions. The results of these experiments are interpreted as support for a late-selection interference account of the AB.
Is emotional contagion special? An fMRI study on neural systems for affective and cognitive empathy

Empathy allows us to simulate others' affective and cognitive mental states internally, and it has been proposed that the mirroring or motor representation systems play a key role in such simulation. As emotions are related to important adaptive events linked with benefit or danger, simulating others' emotional states might constitute of a special case of empathy. In this functional magnetic resonance imaging (fMRI) study we tested if emotional versus cognitive empathy would facilitate the recruitment of brain networks involved in motor representation and imitation in healthy volunteers. Participants were presented with photographs depicting people in neutral everyday situations (cognitive empathy blocks), or suffering serious threat or harm (emotional empathy blocks). Participants were instructed to empathize with specified persons depicted in the scenes. Emotional versus cognitive empathy resulted in increased activity in limbic areas involved in emotion processing (thalamus), and also in cortical areas involved in face (fusiform gyrus) and body perception, as well as in networks associated with mirroring of others' actions (inferior parietal lobule). When brain activation resulting from viewing the scenes was controlled, emotional empathy still engaged the mirror neuron system (premotor cortex) more than cognitive empathy. Further, thalamus and primary somatosensory and motor cortices showed increased functional coupling during emotional versus cognitive empathy. The results suggest that emotional empathy is special. Emotional empathy facilitates somatic, sensory, and motor representation of other peoples' mental states, and results in more vigorous mirroring of the observed mental and bodily states than cognitive empathy.
Multiscale Geometric Methods for Data Sets II: Geometric Multi-Resolution Analysis

Data sets are often modeled as point clouds in R, for D large. It is often assumed that the data has some interesting low-dimensional structure, for example that of a d-dimensional manifold M, with d much smaller than D. When M is simply a linear subspace, one may exploit this assumption for encoding efficiently the data by projecting onto a dictionary of d vectors in R (for example found by SVD), at a cost (n + D)d for n data points. When M is nonlinear, there are no “explicit” constructions of dictionaries that achieve a similar efficiency: typically one uses either random dictionaries, or dictionaries obtained by black-box optimization. In this paper we construct data-dependent multi-scale dictionaries that aim at efficient encoding and manipulating of the data. Their construction is fast, and so are the algorithms that map data points to dictionary coefficients and vice versa. In addition, data points are guaranteed to have a sparse representation in terms of the dictionary. We think of dictionaries as the analogue of wavelets, but for approximating point clouds rather than functions.
Scale structure: Processing minimum standard and maximum standard scalar adjectives

Gradable adjectives denote a function that takes an object and returns a measure of the degree to which the object possesses some gradable property [Kennedy, C. (1999). Projecting the adjective: The syntax and semantics of gradability and comparison. . Scales, ordered sets of degrees, have begun to be studied systematically in semantics [Kennedy, C. (to appear). Vagueness and grammar: the semantics of relative and absolute gradable predicates. Linguistics and Philosophy; Kennedy, C. and McNally, L. (2005). Scale structure, degree modification, and the semantics of gradable predicates. Language, 81, 345-381; Rotstein, C., and Winter, Y. (2004). Total adjectives vs. partial adjectives: scale structure and higher order modifiers. Natural Language Semantics, 12, 259-288.]. We report four experiments designed to investigate the processing of absolute adjectives with a maximum standard (e.g., clean) and their minimum standard antonyms (dirty). The central hypothesis is that the denotation of an absolute adjective introduces a 'standard value' on a scale as part of the normal comprehension of a sentence containing the adjective (the "Obligatory Scale" hypothesis). In line with the predictions of Kennedy and McNally (2005) and Rotstein and Winter (2004), maximum standard adjectives and minimum standard adjectives systematically differ from each other when they are combined with minimizing modifiers like slightly, as indicated by speeded acceptability judgments. An eye movement recording study shows that, as predicted by the Obligatory Scale hypothesis, the penalty due to combining slightly with a maximum standard adjective can be observed during the processing of the sentence; the penalty is not the result of some after-the-fact inferencing mechanism. Further, a type of 'quantificational variability effect' may be observed when a quantificational adverb (mostly) is combined with a minimum standard adjective in sentences like "The dishes are mostly dirty", which may receive either a degree interpretation (e.g., 80% dirty) or a quantity interpretation (e.g., 80% of the dishes are dirty). The quantificational variability results provide suggestive support for the Obligatory Scale hypothesis by showing that the standard of a scalar adjective influences the preferred interpretation of other constituents in the sentence.