nils-herrmann/clean_scirepeval huggingface dataset:
A Survey on Search Systems for Extracting And Searching in Scholarly Big Data

Search systems that is designed to search for information. CiteSeer was a public search engine and digital library for scientific and academic papers, primarily in the fields of computer and information science, that has been replaced by CiteSeer .CiteSeer provides free access to over 4 million full text academic documents and rarely seen functionalities. There is no platform available for scholars to automatically search, extract, analyse and discover algorithms, tables, figures, images, collaborators, acknowledgments, metadata, pseudo codes, semantic hierarchical sections and mathematical expressions in scholarly big data. Hence Special purpose search systems are used to extract and search from articles. The limitations of existing search engines make the search problem more challenging. In this paper a survey of search systems has been presented.
Speech Is 3x Faster than Typing for English and Mandarin Text Entry on Mobile Devices
Venue: ArXiv

With laptops and desktops, the dominant method of text entry is the full size keyboard; now with the ubiquity of mobile devices like smartphones, two new widely used methods have emerged: miniature touch screen keyboards and speech based dictation. It is currently unknown how these two modern methods compare. We therefore evaluated the text entry performance of both methods in English and in Mandarin Chinese on a mobile smartphone. In the speech input case, our speech recognition system gave an initial transcription, and then recognition errors could be corrected using either speech again or the smartphone keyboard. We found that with speech recognition, the English input rate was 3.0x faster, and the Mandarin Chinese input rate 2.8x faster, than a state of the art miniature smartphone keyboard. Further, with speech, the English error rate was 20.4% lower, and Mandarin error rate 63.4% lower, than the keyboard. Our experiment was carried out using Deep Speech 2, a deep learning based speech recognition system, and the built in Qwerty or Pinyin (Mandarin) Apple iOS keyboards. These results show that a significant shift from typing to speech might be imminent and impactful. Further research to develop effective speech interfaces is warranted.
Diet derived 25 hydroxyvitamin D3 activates vitamin D receptor target gene expression and suppresses EGFR mutant non small cell lung cancer growth in vitro and in vivo
Venue: Oncotarget

Epidemiologic studies implicate vitamin D status as a factor that influences growth of EGFR mutant lung cancers. However, laboratory based evidence of the biological effect of vitamin D in this disease is lacking. To fill this knowledge gap, we determined vitamin D receptor (VDR) expression in human lung tumors using a tissue microarray constructed of lung cancer cases from never smokers (where EGFR gene mutations are prevalent) Nuclear VDR was detected in 19/19 EGFR mutant tumors. Expression tended to be higher in tumors with EGFR exon 19 deletions than those with EGFR L858R mutations. To study anti proliferative activity and signaling, EGFR mutant lung cancer cells were treated with the circulating metabolite of vitamin D, 25 hydroxyvitamin D3 (25D3) 25D3 inhibited clonogenic growth in a dose dependent manner. CYP27B1 encodes the 1a hydroxylase (1aOHase) that converts 25D3 to the active metabolite, 1,25 dihydroxyvitamin D3 (1,25D3) Studies employing VDR siRNA, CYP27B1 zinc finger nucleases, and pharmacologic inhibitors of the vitamin D pathway indicate that 25D3 regulates gene expression in a VDR dependent manner but does not strictly require 1aOHase mediated conversion of 25D3 to 1,25D3. To determine the effects of modulating serum 25D3 levels on growth of EGFR mutant lung tumor xenografts, mice were fed diets containing 100 or 10,000 IU vitamin D3/kg. High dietary vitamin D3 intake resulted in elevated serum 25D3 and significant inhibition of tumor growth. No toxic effects of supplementation were observed. These results identify EGFR mutant lung cancer as a vitamin D responsive disease and diet derived 25D3 as a direct VDR agonist and therapeutic agent.
Physical activity, nutritional status, and dietary habits of students of a medical university
Venue: Sport Sciences for Health

Nutritional habits and physical activity influence the health status of young adults. In this study, we engaged a group of 151 students from a medical university (90 female and 61 male subjects) Anthropometric parameters, dietary habits (a 7 day dietary recall) and level of physical activity were measured. It was found that the daily food rations of female (F) and male (M) students were improperly balanced and characterized by high amount of total and animal protein, phosphorus, vitamin A, cholesterol, and insufficient intake of carbohydrates, dietary fiber, and vitamin C. Female subjects consumed low amounts of total fat and calcium. The intake of protein (total and animal) fat, phosphorus, and cholesterol correlated with higher body mass. The physical activity of the students was found to be higher than the average physical activity of the European Union populations, and a general tendency of lowering level of physical activity with age was observed. Students with the highest level of physical activity (MET 1500) consumed lower amounts of simple carbohydrates (galactose and saccharose) when compared to students with lower physical activity (MET 600, p 0.05) Therefore, this study concluded that the dietary habits should be modified to prevent the development of diet dependent diseases. Various forms of physical activity should be proposed to students and they should be encouraged to participate in high level of physical activity so as to promote good health status.
Dietary Habits of Saudi Medical Students at University of Dammam.
Venue: International journal of health sciences

To evaluate the dietary habits and life style of medical students.  This is a cross sectional study as self reported questionnaire for the male and female medical students at College of Medicine University of Dammam, eastern province, Kingdom of Saudi Arabia, comparing their habits and life style according to their gender and to their academic levels; 1(st) 3(rd) and 6(th) year.  562 students participated in the study with response rate of 91% average age: 20.2776+ 2.06175) males students were 333 (59.25% and female students were 229 (40.75% corresponding to the actual male to female ratio in this medical school. The majority of the students (91.3% were consuming fast foods, majority are males (85% do it 3 times or more per week, only 8.7% denied eating fast food with no significant difference between the three academic levels. Majority of students are aware of the benefits of the vegetables and fruits and the disadvantage of the soft drinks yet most of them consume a lot of soft drinks and less of vegetables and fruits. Physical exercise was not done regularly in 65% of the male medical students and 80% of the female with almost similar percentage in all the three levels.  Contrary to the expectations and regardless of studying in medical college, our medical students; both male and females at different academic levels are having major bad dietary habits and life style that is comparable to the general population in the kingdom.
Designing a Permanent Magnetic Actuator for Vacuum Circuit Breakers Using the Taguchi Method and Dynamic Characteristic Analysis
Venue: IEEE Transactions on Industrial Electronics

Permanent magnetic actuators (PMAs) are usually used for vacuum circuit breakers (VCBs) due to their fast linear motion and large holding force. As the holding force becomes larger, so does the current capacity of the circuit breaker. Producing a large holding force with the same PMA size is therefore important in PMA design. This paper presents a design method of a PMA for VCBs. To attain the desired holding force under the restriction of the PMA size, most of the influential PMA yoke design parameters were obtained by the Taguchi method. PMA dynamic characteristics were simulated considering the electromagnetic characteristics, the PMA driving circuit, and the mechanical components connected to the PMA output shaft. Experiments were performed to validate the proposed design method, and the experimental results were compared with the simulation results.
EXPLORATORY INNOVATION, EXPLOITATIVE INNOVATION AND INNOVATION PERFORMANCE: THE MODERATING ROLE OF ALLIANCE PARTNER DIVERSITY

Addressing the mixed findings in the literature, we distinguish between two distinct types of innovations, exploitative and exploratory innovations, and study their relationships with innovation performance. Organizational ambidexterity, the ability of a firm to simultaneously pursue both explorative and exploitative innovations, has been highlighted as increasingly important for the sustained competitive advantage of firms. By using the Community Innovation Survey 2006 micro data for innovation from twelve countries, we showed that simultaneously pursuing exploratory and exploitative innovation hinders firms' innovation performance. Furthermore, we proposed that firms' collaborations with different types of partners (suppliers, customers, competitors, research institutions and universities) would moderate the impact of exploitative and exploratory innovations on firm innovation performance differently. Our study also reveals that that the use of diverse collaborators is beneficial to the contradictory pressures for explorative and exploitative innovations.
An improved crescent electrode in electrowetting based microfludic
Venue: 2016 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M NANO)

Electrode is a vital component in the digital microfludic based on electrowetting on dielectric(EWOD) in order to improve the driving performance, this paper proposed a novel improved crescent electrode shape, establish the EWOD device model through the finite element method(FEM) to compute the driving force of the droplet. The result shows that droplet's electrostatic force on the proposed electrode shape is more stable, the standard deviation is decreased by 41.18% compared with the crescent electrode, and during droplet crossing two adjacent electrodes, the minimum actuation force of droplet on the proposed electrode is 5.9mN which is improved by 23.43% compared with the crescent electrode. And in addition, the proposed electrode is composed of two symmetrical sub electrodes, hence the droplet bidirectional movement has the same driving performance, it is more consistent with the manipulation of droplet in practical application.
Using Fourier transform infrared spectroscopy to evaluate biological effects induced by photodynamic therapy
Venue: Lasers in surgery and medicine

Vibrational spectroscopic methods associated with multivariate statistical techniques have been succeeded in discriminating skin lesions from normal tissues. However, there is no study exploring the potential of these techniques to assess the alterations promoted by photodynamic effect in tissue. The present study aims to demonstrate the ability of Fourier Transform Infrared (FTIR) spectroscopy on Attenuated total reflection (ATR) sampling mode associated with principal component linear discriminant analysis (PC LDA) to evaluate the biochemical changes caused by photodynamic therapy (PDT) in skin neoplastic tissue.
A Feature Scaling Based $k$ Nearest Neighbor Algorithm for Indoor Positioning Systems
Venue: IEEE Internet of Things Journal

With the increasing popularity of WLAN infrastructure, WiFi fingerprint based indoor positioning systems have received considerable attention recently. Much existing work in this aspect adopts classification techniques that match a vector of radio signal strengths (RSSs) reported by a mobile station (MS) to pretrained reference fingerprints sampled from different access points (APs) at different reference points (RPs) with known positions. However, in the calculation of signal distances between different RSS vectors, existing techniques fail to consider the fact that equal RSS differences at different RSS levels may not mean equal differences in geometrical distances in complex indoor environment. To address this issue, in this paper, we propose a feature scaling based k nearest neighbor (FS kNN) algorithm for achieving improved localization accuracy. In FS kNN, we build a novel RSS level based FS model, which introduces RSS level based scaling weights in the computation of effective signal distances between signal vector reported by a MS and reference fingerprints in a radio map. Experimental results show that FS kNN can achieve an average location error as low as 1.70 m, which is superior to existing work.
A Feature Scaling Based k Nearest Neighbor Algorithm for Indoor Positioning Systems
Venue: IEEE Internet Things J.

With the increasing popularity of WLAN infrastructure, WiFi fingerprint based indoor positioning systems have received considerable attention recently. Much existing work in this aspect adopts classification techniques that match a vector of radio signal strengths (RSSs) reported by a mobile station (MS) to pretrained reference fingerprints sampled from different access points (APs) at different reference points (RPs) with known positions. However, in the calculation of signal distances between different RSS vectors, existing techniques fail to consider the fact that equal RSS differences at different RSS levels may not mean equal differences in geometrical distances in complex indoor environment. To address this issue, in this paper, we propose a feature scaling based $k$ nearest neighbor (FS $k$ NN) algorithm for achieving improved localization accuracy. In FS $k$ NN, we build a novel RSS level based FS model, which introduces RSS level based scaling weights in the computation of effective signal distances between signal vector reported by a MS and reference fingerprints in a radio map. Experimental results show that FS $k$ NN can achieve an average location error as low as 1.70 m, which is superior to existing work.
A comparative study on portfolio optimization problem
Venue: 2016 International Conference on Engineering MIS (ICEMIS)

This paper is a comparative study of metaheuristics in the portfolio optimization problem. The objective is to present the results obtained with the meta heuristics Cat Swarm Optimization CSO, bat algorithm BA and particle swarm optimization PSO applied to the cardinality constrained efficient frontier model CCEF, the results obtained has compared with those done using the unconstrained efficient frontier model UEF.
Solving portfolio optimization problem through differential evolution
Venue: 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

Portfolio theories best describes the asset management. Several investment offers are available to a customer and the task is to select the most appropriate option to gain the maximum financial benefit. The investor requires a thorough comparative study to decide the best possible option where the return is maximum and the risk is minimum. Portfolio optimization can help in the process of decision making by bringing out the selected options beneficial for the investor. In this paper we have considered the Markovitz's Mean Variance portfolio optimization model and the data is considered from National Stock Exchange (NSE) Mumbai. Differential Evolution, a population based metaheuristics is applied for obtaining the optimal portfolio.
Policy based signature scheme from lattices
Venue: Des. Codes Cryptogr.

Policy based signature, introduced by Bellare and Fuchsbauer at PKC 2014, is a new type of digital signature in which a signer is only allowed to sign messages satisfying certain policy specified by the authority, but the signatures should not reveal the underlying policy. Having these features, policy based signatures are attractive from both theoretical and practical aspects. In their pioneering paper, Bellare and Fuchsbauer have provided generic constructions of policy based signatures, and a concrete instantiation based on pairings. In this work, we develop the recent techniques in lattice based cryptography to construct a (delegatable) policy based signature scheme from lattice assumptions. Specifically, we adapt Langlois et al.'s zero knowledge argument system (PKC 2014) for the Bonsai tree signature scheme (Eurocrypt 2010) to enable the prover to convince the verifier that its secret witness satisfies an additional condition. Making the protocol non interactive via the Fiat Shamir transformation, we obtain a policy based signature scheme supporting polynomially many policies, which satisfies the two security requirements (simulatability and extractability) in the random oracle model. Furthermore, our construction can be efficiently extended to a delegatable policy based signature, thanks to the hierarchical structure of the Bonsai tree. Our contribution is twofold. On the one hand, we enrich the scope of policy based signatures by providing the first quantum resistant instantiation. On the other hand, our technical approach can potentially be applied to design a wide variety of privacy enhanced lattice based cryptographic constructions.
Signature Schemes with Efficient Protocols and Dynamic Group Signatures from Lattice Assumptions
Venue: ASIACRYPT

A recent line of works initiated by Gordon, Katz and Vaikuntanathan Asiacrypt 2010 gave lattice based constructions allowing users to authenticate while remaining hidden in a crowd. Despite five years of efforts, known constructions are still limited to static sets of users, which cannot be dynamically updated. This work provides new tools enabling the design of anonymous authentication systems whereby new users can join the system at any time. Our first contribution is a signature scheme with efficient protocols, which allows users to obtain a signature on a committed value and subsequently prove knowledge of a signature on a committed message. This construction is well suited to the design of anonymous credentials and group signatures. It indeed provides the first lattice based group signature supporting dynamically growing populations of users. As a critical component of our group signature, we provide a simple joining mechanism of introducing new group members using our signature scheme. This technique is combined with zero knowledge arguments allowing registered group members to prove knowledge of a secret short vector of which the corresponding public syndrome was certified by the group manager. These tools provide similar advantages to those of structure preserving signatures in the realm of bilinear groups. Namely, they allow group members to generate their own public key without having to prove knowledge of the underlying secret key. This results in a two message joining protocol supporting concurrent enrollments, which can be used in other settings such as group encryption. Our zero knowledge arguments are presented in a unified framework where: i The involved statements reduce to arguing possession of a 1,0,1\ vector \mathbf {x} with a particular structure and satisfying \mathbf {P}\cdot \mathbf {x} \mathbf {v} \bmod q$ for some public matrix \mathbf {P} and vector \mathbf {v} ii The reduced statements can be handled using permuting techniques for Stern like protocols. Our framework can serve as a blueprint for proving many other relations in lattice based cryptography.
Application of teaching learning based optimization procedure for the development of SVM learned EDM process and its pseudo Pareto optimization
Venue: Appl. Soft Comput.

Two stage soft computing (SVM TLBO) (PLM TLBO pseudo PARETO) based virtual system of manufacturing process EDM is developed.Virtual data generator of EDM process learned by support vector machine (SVM) with internal parameters (C, and tuned by teaching learning based optimization (TLBO) is reported.Modifications namely population based termination criteria, initialize population with high dispersion and way of choosing teacher in case of multiple best learners performing same score, over standard TLBO are suggested. Further, a comparison between performances of TLBO and PSO in model development is studied.A simple procedure for pseudo Pareto front development by modified TLBO is proposed.Inverse solution procedure for selection of optimum available machine parameter setting corresponding to specific output combination is elaborated. Manufacturing processes could be well characterized by both the quantitative and the qualitative measurements of their performances. In case of conflicting type performance measures, it is necessary to get possible optimum values of all performances simultaneously, like higher material removal rate (MRR) with lower average surface roughness (ASR) in electric discharge machining (EDM) process. EDM itself is a stochastic process and predictions of responses MRR and ASR are still difficult. Advanced structural risk minimization based learning system support vector machine (SVM) is, therefore, applied to capture the random variations in EDM responses in a robust way. Internal parameters of SVM C, and are tuned by modified teaching learning based optimization (TLBO) procedure. Subsequently, using the developed SVM model as a virtual data generator of EDM process, responses are generated at the different points in the experimental space and power law models are fitted to the estimated data. Varying the weight factors, different weighted combinations of the inverse of MRR and the ASR are minimized by modified TLBO. Pseudo Pareto front passing through the optimum results, thus obtained, gives a guideline for selection of optimum achievable value of ASR for a specific demand of MRR. Further, inverse solution procedure is elaborated to find the near optimum setting of process parameters in EDM machine to obtain the specific need based MRR ASR combination.
Fin whales and microplastics: The Mediterranean Sea and the Sea of Cortez scenarios.
Venue: Environmental pollution

The impact that microplastics have on baleen whales is a question that remains largely unexplored. This study examined the interaction between free ranging fin whales (Balaenoptera physalus) and microplastics by comparing populations living in two semi enclosed basins, the Mediterranean Sea and the Sea of Cortez (Gulf of California, Mexico) The results indicate that a considerable abundance of microplastics and plastic additives exists in the neustonic samples from Pelagos Sanctuary of the Mediterranean Sea, and that pelagic areas containing high densities of microplastics overlap with whale feeding grounds, suggesting that whales are exposed to microplastics during foraging; this was confirmed by the observation of a temporal increase in toxicological stress in whales. Given the abundance of microplastics in the Mediterranean environment, along with the high concentrations of Persistent Bioaccumulative and Toxic (PBT) chemicals, plastic additives and biomarker responses detected in the biopsies of Mediterranean whales as compared to those in whales inhabiting the Sea of Cortez, we believe that exposure to microplastics because of direct ingestion and consumption of contaminated prey poses a major threat to the health of fin whales in the Mediterranean Sea.
Automatic segmentation of HEp 2 cell Fluorescence microscope images using level set method via geometric active contours
Venue: 2016 23rd International Conference on Pattern Recognition (ICPR)

A method for segmenting HEp 2 cells in Indirect Immuno Fluorescence microscope (IIF) images is implemented and evaluated. Challenges to accurate segmentation include the complexity of the data acquired at multiple wavelengths, overlapping cells, and variations in staining. Level set methods via geometric active contours are used to solve this problem. Level set methods use morphological operations to estimate an initial cell boundary and are fully automated. Geometric active contours are able to adapt to the curve topology of the cell boundary. Segmentation performance is evaluated using six indices: boundary displacement error, global consistency error, variation of information, Jaccard distance error, rand index and F index.