nils-herrmann/clean_scirepeval huggingface dataset:
Identification and Resection of Clipped Node Decreases the False negative Rate of Sentinel Lymph Node Surgery in Patients Presenting With Node positive Breast Cancer (T0 T4, N1 N2) Who Receive Neoadjuvant Chemotherapy: Results From ACOSOG Z1071 (Alliance)
Venue: Annals of surgery

The American College of Surgeons Oncology Group Z1071 trial reported a false negative rate (FNR) of 12.6% with sentinel lymph node (SLN) surgery after neoadjuvant chemotherapy in women presenting with node positive breast cancer. One proposed method to decrease the FNR is clip placement in the positive node at initial diagnosis with confirmation of clipped node resection at surgery. Z1071 was a multi institutional trial wherein women with clinical T0 T4,N1 N2,M0 breast cancer underwent SLN surgery and axillary dissection (ALND) after neoadjuvant chemotherapy. In cases with a clip placed in the node, the clip location at surgery (SLN or ALND) was evaluated. A clip was placed at initial node biopsy in 203 patients. In the 170 (83.7% patients with cN1 disease and at least 2 SLNs resected, clip location was confirmed in 141 cases. In 107 (75.9% patients where the clipped node was within the SLN specimen, the FNR was 6.8% (confidence interval [CI] 1.9% 16.5% In 34 (24.1% cases where the clipped node was in the ALND specimen, the FNR was 19.0% (CI: 5.4% 41.9% In cases without a clip placed (n 355) and in those where clipped node location was not confirmed at surgery (n 29) the FNR was 13.4% and 14.3% respectively. Clip placement at diagnosis of node positive disease with removal of the clipped node during SLN surgery reduces the FNR of SLN surgery after neoadjuvant chemotherapy. Clip placement in the biopsy proven node at diagnosis and evaluation of resected specimens for the clipped node should be considered when conducting SLN surgery in this setting.
Expenditure and financial burden for common cancers in China: a hospital based multicentre cross sectional study
Venue: The Lancet

Comprehensive health economic evaluation, a key component of the Cancer Screening Program in Urban China (CanSPUC) was expected to support government policy making on screening initiatives for common cancers (lung, breast, colorectal, oesophageal, liver, and stomach cancer) in urban China. Estimation of expenditure for cancer diagnosis and treatment from a societal perspective was an essential component. The aim of this study was to estimate direct medical and non medical expenditure and to discern the resultant financial burden.  A multicentre cross sectional survey of patients with target cancers or precancerous lesions was conducted in 37 tertiary hospitals in 13 provinces across China, from 2012 to 2014. Each patient was interviewed with a structured questionnaire for sociodemographic, clinical, and expenditure information. Expenditure data was converted to 2014 values and presented as US$ Expenditure and financial burden were quantified as a whole and by subgroups.  Of the included 14 594 patients with cancer (mean age 56*7 years, 58% male) annual household income was $8607. Mean expenditure per patient was $9739 (95% CI 9612 9866) and non medical expenditure accounted for 9*3% Expenditure per patient with colorectal, oesophageal, lung, stomach, liver or breast cancer was $10 978 (10 636 11 321) $10 506 (10 199 10 813) $9970 (9664 10 276) $9891 (9606 10 176) $8668 (8358 8977) and $8532 (8234 8831) respectively. Expenditure increased from stage I to stage IV for colorectal, stomach, and breast cancer (p<0*0001) Out of pocket expenditure of newly diagnosed cancer (2 months before and 10 months after diagnosis) per cancer patient was $4947 (4875 5020) accounting for 57*5% of annual household income, presenting 77*6% of families with an unmanageable financial burden. Apart from cancer site and stage, hospital type, education, occupation, insurance type, and previous years' household income were also significant predictors of expenditure (F=247*9, 56*3, 29*7, 12*8, and 28*7, respectively; all p<0*0001) as well as self reported financial burden (kh2=130*4, 495*1, 1112*2, 1009*4, and 1848*2, respectively; all p<0*0001) In addition, for the included 1532 precancerous patients, mean expenditure was $3221 (3055 3387) a third of expenditure for patients with cancer.  Expenditure for diagnosis and treatment seemed catastrophic for patients with cancer in China, and non medical expenditure was substantial. Expenditure and financial burden varied within subgroups, especially between patients with different degrees of lesions, suggesting that cancer screening might be cost effective in China.
Wireless power transfer to deep tissue mm size implants using wireless repeater node
Venue: 2016 Loughborough Antennas Propagation Conference (LAPC)

This paper proposes a biomedical RFID system meant for wireless interrogation of deep tissue mm size implant sensors. The communication system is based on using a repeater device that amplifies the attenuated downlink power and thus extends sensor read distance. This system enables monitoring of different body organs by placing miniature sensor implants inside them. The repeater device should also be implanted in the wireless power path from external reader to the sensor implant in a safe place not disturbing any body functions.
High efficiency unidirectional wireless power transfer by a triple band deep tissue implantable antenna
Venue: 2016 IEEE MTT S International Microwave Symposium (IMS)

In this study, we introduce a triple band flexible implantable antenna that is tuned by using a ground slot in three specific bands, namely Medical Implanted Communication Service (MICS: 402~405 MHz) for telemetry, the midfield band (lower gigahertz: 1.45~1.6 GHz) for Wireless Power Transfer (WPT) and the Industrial, Scientific and Medical band (ISM: 2.4~2.45 GHz) for power conservation. The telemetry performance of the proposed antenna was simulated and measured by using a porcine heart. To check the feasibility of WPT, a midfield transmitter antenna was introduced. In addition, to reduce the unwanted power leakage due to WPT, a Near Field Plate (NFP) was also used. Finally, power conservation can be realized by triggering the antenna's `sleep mode' in the ISM band.
MicroStrip Balun for TEM Horn Antenna used in Level Measurement

Localized time domain pulses can be used for non contact and non destructive measurement of liquid level in industrial applications. Due to its wider bandwidth and directional radiation pattern, Transverse Electromagnetic (TEM) horn antennas are well suited for target distance measurements. For balanced radiation over a larger bandwidth, a TEM horn antenna is fed using a wideband balun. The design and characterization of a Microstrip wideband balun are presented in this work. Exponentially tapered balun with varying width and spacing were studied using Finite Element Method (FEM) based electromagnetic (EM) solver, Ansys HFSS(r) for operation over 2 10 GHz. Designed balun w as manufactured and characterized using a vector network analyser. Simulation and experimental data indicated better than 10 dB S 11 and VSWR less than 1.5 for the exponentially tapered balun.
Entropy based bare bones particle swarm for dynamic constrained optimization
Venue: Knowl. Based Syst.

This paper proposes an entropy based bare bones particle swarm for solving dynamic constrained optimization problems. The Shannon's entropy is established as a phenotypic diversity index and the proposed algorithm uses the Shannon's index of diversity to aggregate the global best and local best bare bones particle swarm variants. The proposed approach applies the idea of mixture of search directions, using the index of diversity as a factor to balance the influence of the global best and local best search directions. High diversity promotes the search guided by the global best solution, with a normal distribution for exploitation. Low diversity promotes the search guided by the local best solution, with a heavy tailed distribution for exploration. A constraint handling strategy is also proposed, which uses a ranking method with selection based on the technique for order preference by similarity to ideal solution (TOPSIS) to obtain the best solution within a specific population of candidate solutions. Mechanisms to detect changes in the environment and to update particles' memories are also implemented into the proposed algorithm. All these strategies do not act independently. They operate related to each other to tackle problems such as: diversity loss due to convergence and outdated memories due to changes in the environment. The combined effect of these strategies provides an algorithm with ability to maintain a proper balance between exploration and exploitation at any stage of the search process without losing the tracking ability. An empirical study was carried out to evaluate the performance of the proposed approach. Experimental results show the suitability of the algorithm in terms of effectiveness to find good solutions for the benchmark problems investigated. Finally, an application is developed where the proposed algorithm is applied to solve the dynamic economic dispatch problem in power systems.
Improving Wireless Physical Layer Security via Exploiting Co Channel Interference
Venue: IEEE Journal of Selected Topics in Signal Processing

This paper considers a scenario in which a source destination pair needs to establish a confidential connection against an external eavesdropper, aided by the interference generated by another source destination pair that exchanges public messages. The goal is to compute the maximum achievable secrecy degrees of freedom (S.D.o.F) region of a MIMO two user wiretap network. First, a cooperative secrecy transmission scheme is proposed, whose feasible set is shown to achieve all S.D.o.F. pairs on the S.D.o.F. region boundary. In this way, the determination of the S.D.o.F. region is reduced to a problem of maximizing the S.D.o.F. pair over the proposed transmission scheme. The maximum achievable S.D.o.F. region boundary points are obtained in closed form, and the construction of the precoding matrices achieving the maximum S.D.o.F. region boundary is provided. The proposed expressions are functions of the number of antennas at each terminal, and apply to any number of antennas, thus constituting an advancement over prior works that have considered only fixed antenna configurations.
Joint Source Relay Selection for Improving Wireless Physical Layer Security
Venue: 2016 IEEE Global Communications Conference (GLOBECOM)

We explore the physical layer security for a multisource multi relay wireless network in the presence of an eavesdropper, in which one of multiple sources is scheduled to send its message to a destination with the assistance of multiple decode and forward (DF) relays. One eavesdropper is considered at the receiver side, and assumed to be capable of overhearing the transmission from relays to destination. In this paper, the round robin scheduling and the joint source relay selection schemes are presented to improve the physical layer security of the multi source multi relay system, and their closedform intercept probability expressions are derived over Rayleigh fadingchannels.Numericalresultsdemonstratethattheproposed joint source relay selection scheme achieves a better performance than the traditional round robin scheduling in terms of the intercept probability.
UWB at SemEval 2016 Task 5: Aspect Based Sentiment Analysis
Venue: *SEMEVAL

This paper describes our system used in the Aspect Based Sentiment Analysis (ABSA) task of SemEval 2016. Our system uses Maximum Entropy classifier for the aspect category detection and for the sentiment polarity task. Conditional Random Fields (CRF) are used for opinion target extraction. We achieve state of the art results in 9 experiments among the constrained systems and in 2 experiments among the unconstrained systems.
IIT TUDA at SemEval 2016 Task 5: Beyond Sentiment Lexicon: Combining Domain Dependency and Distributional Semantics Features for Aspect Based Sentiment Analysis
Venue: *SEMEVAL

This paper reports the IIT TUDA participation in the SemEval 2016 shared Task 5 of Aspect Based Sentiment Analysis (ABSA) for subtask 1. We describe our system incorporating domain dependency graph features, distributional thesaurus and unsupervised lexical induction using an unlabeled external corpus for aspect based sentiment analysis. Overall, we submitted 29 runs, covering 7 languages and 4 different domains. Our system is placed first in sentiment polarity classification for the English laptop domain, Spanish and Turkish restaurant reviews, and opinion target expression for Dutch and French in restaurant domain, and scores in medium ranks for aspect category identification and opinion target extraction.
XRCE at SemEval 2016 Task 5: Feedbacked Ensemble Modeling on Syntactico Semantic Knowledge for Aspect Based Sentiment Analysis
Venue: *SEMEVAL

This paper presents our contribution to the SemEval 2016 task 5: Aspect Based Sentiment Analysis. We have addressed Subtask 1 for the restaurant domain, in English and French, which implies opinion target expression detection, aspect category and polarity classification. We describe the different components of the system, based on composite models combining sophisticated linguistic features with Machine Learning algorithms, and report the results obtained for both languages.
AKTSKI at SemEval 2016 Task 5: Aspect Based Sentiment Analysis for Consumer Reviews
Venue: *SEMEVAL

This paper describes the polarity classification system designed for participation in SemEval2016 Task 5 ABSA. The aim is to determine the sentiment polarity expressed towards certain aspect within a consumer review. Our system is based on supervised learning using Support Vector Machine (SVM) We use standard features for basic classification model. On top this, we include rules to check precedent polarity sequence. This approach is experimental.
TGB at SemEval 2016 Task 5: Multi Lingual Constraint System for Aspect Based Sentiment Analysis
Venue: *SEMEVAL

This paper gives the description of the TGB system submitted to the Aspect Based Sentiment Analysis Task of SemEval 2016 (Task 5) The system is built on linear binary classifiers for aspect category classification (Slot 1) on lexicon based detection for opinion target expressions extraction (Slot 2) and on linear multi class classifiers for sentiment polarity detection (Slot 3) We conducted several different approaches for feature selection to improve classification performance on both Slot 1 and Slot 3. Our proposed methods are easily adaptable to all languages and domains since they are built as constrained systems which do not use any additional resources other than the provided datasets and which uses standard preprocessing methods.
bunji at SemEval 2016 Task 5: Neural and Syntactic Models of Entity Attribute Relationship for Aspect based Sentiment Analysis
Venue: *SEMEVAL

This paper describes a sentiment analysis system developed by the bunji team in SemEval2016 Task 5. In this task, we estimate the sentimental polarity of a given entity attribute (E#A) pair in a sentence. Our approach is to estimate the relationship between target entities and sentimental expressions. We use two different methods to estimate the relationship. The first one is based on a neural attention model that learns relations between tokens and E#A pairs through backpropagation. The second one is based on a rule based system that examines several verb centric relations related to E#A pairs. We confirmed the effectiveness of the proposed methods in a target estimation task and a polarity estimation task in the restaurant domain, while our overall ranks were modest.
ECNU at SemEval 2016 Task 5: Extracting Effective Features from Relevant Fragments in Sentence for Aspect Based Sentiment Analysis in Reviews
Venue: *SEMEVAL

This paper describes our systems submitted to the Sentence level and Text level AspectBased Sentiment Analysis (ABSA) task (i.e. Task 5) in SemEval 2016. The task involves two phases, namely, Aspect Detection phase and Sentiment Polarity Classification phase. We participated in the second phase of both subtasks in laptop and restaurant domains, which focuses on the sentiment analysis based on the given aspect. In this task, we extracted four types of features (i.e. Sentiment Lexicon Features, Linguistic Features, Topic Model Features and Word2vec Feature) from certain fragments related to aspect rather than the whole sentence. Then the proposed features are fed into supervised classifiers for sentiment analysis. Our submissions rank above average.
AUEB ABSA at SemEval 2016 Task 5 Supervised Machine Learning for Aspect Based Sentiment Analysis

This paper describes our submissions to the Aspect Based Sentiment Analysis task of SemEval 2016. For Aspect Category Detection (Subtask1/Slot1) we used multiple ensembles, based on Support Vector Machine classifiers. For Opinion Target Expression extraction (Subtask1/Slot2) we used a sequence labeling approach with Conditional Random Fields. For Polarity Detection (Subtask1/Slot3) we used an ensemble of two supervised classifiers, one based on hand crafted features and one based on word embeddings. Our systems were ranked in the top 6 positions in all the tasks we participated. The source code of our systems is publicly available.
Decision Mining Revisited Discovering Overlapping Rules
Venue: CAiSE

Decision mining enriches process models with rules underlying decisions in processes using historical process execution data. Choices between multiple activities are specified through rules defined over process data. Existing decision mining methods focus on discovering mutually exclusive rules, which only allow one out of multiple activities to be performed. These methods assume that decision making is fully deterministic, and all factors influencing decisions are recorded. In case the underlying decision rules are overlapping due to non determinism or incomplete information, the rules returned by existing methods do not fit the recorded data well. This paper proposes a new technique to discover overlapping decision rules, which fit the recorded data better at the expense of precision, using decision tree learning techniques. An evaluation of the method on two real life data sets confirms this trade off. Moreover, it shows that the method returns rules with better fitness and precision in under certain conditions.
Multi User Shared Access for Internet of Things
Venue: 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)

Internet of things (IoT) is widely expected to be an important scenario in the fifth generation (5G) wireless network. Major challenges of IoT include the low cost of devices, low energy consumption, low latency and the ability to support a large number of simultaneous connections. In this article, a new type of non orthogonal multiple access scheme called multi user shared access (MUSA) is proposed to support IoT. MUSA adopts a grant free access strategy to simplify the access procedure significantly and utilizes advanced code domain non orthogonal complex spreading to accommodate massive number of users in the same radio resources. A family of complex sequences with short length is chosen as spreading sequence for its ability to enable simple and robust successive interference cancellation at the base station side and cope with high user load. Simulation results show that MUSA can achieve significant gain in user overloading performance compared to orthogonal systems, while incurring much lower control overhead.
Non orthogonal Multi User Superposition and Shared Access

This chapter addresses major technology aspects of non orthogonal multi user superposition transmission and shared access. The chapter describes key techniques: low density spreading (LDS) sparse code multiple access (SCMA) multi user shared access (MUSA) and pattern defined multiple access (PDMA) together with simulation results. For spectral efficiency improvement purposes, a macro coverage scenario is the suitable deployment environment for non orthogonal multi user transmission/access. Deploying non orthogonal multi user schemes in a macro setting can help to get both benefits of both of the technologies that will play an important role in significantly boosting the system capacity. The multiple access mechanism in the uplink of IS 95, code division multiple access (CDMA)2000 and Universal Mobile Terrestrial Services (UMTS) is indeed non orthogonal. One of the key scenarios for downlink non orthogonal multi user transmission is mobile broadband (MBB) in which the target is to maximize the downlink system capacity. Roughly, the schemes can be divided into two groups: direct superposition without Gray mapping restriction and superposition with Gray mapping.
Factors Influencing Online Shopping Behavior: The Mediating Role of Purchase Intention

Internet shopping is a phenomena that is growing rapidly nowadays. A peep into the exponential growth of the main players in this industry indicates there is still a large reservoir of market potential for e commerce. The conveniency of online shopping rendering it an emerging trend among consumers, especially the Gen Y. The prevalence of online shopping has raised the interest of the retailers to focus on this area. Therefore, this study was to determine the relationship between subjective norm, perceived usefulness and online shopping behavior while mediated by purchase intention. University students aged between 18 and 34 that currently pursuing their studies in University Malaysia Perlis were selected as the subject of analysis. 662 out of 800 sets of questionnaires distributed were valid for coding, analyzing and testing the hypothesis. Collected data were then analyzed using SPSS version 18.0 and AMOS version 16.0. Structural Equation Modeling to examine the model fits and hypothesis testing. The conclusion can be depicted that subjective norm and perceived usefulness significant positively influence online purchase intention but subjective norm insignificant influence shopping behavior in a negative way. It is interesting to note that perceived usefulness also insignificantly influence online shopping behavior. Finding also revealed that purchase intention significant positively influence online shopping behavior. For future research, sample from working adults and other variables that related to online shopping were to be included to minimise sampling bias.
Narrating Self Identity in Bisexual Motherhood

Our qualitative study investigated the ways in which bisexual mothers came to identify as such and how their identity interconnected with their personal relationship and parenting histories within the social contexts they experienced. Eight women (ages 28 to 56 years old) who had experienced sexual relationships with both women and men over their life span were interviewed. At the time of their interview the participants were mothers to children of various ages from infancy to adulthood. A Labovian narrative analysis was conducted to highlight key points in their understanding of their sense of self in relation to particular social contexts and their story of how they came to identify as a bisexual mother or not. Our findings pointed to involvement in various self identity projects that were variously integrated and resolved within their life course story, namely, the construction of a positive sexual identity and the development of a romantic relationship and the desire to parent. Our life course development study emphasized sexual self identity as providing a source of agency and organization with respect to personal development in embracing or sidelining opportunities as these occurred or did not occur within changing social contexts over time.