Miracle-dz/UniFAR-FTUs huggingface dataset:
RN / 12 / 03 Evolving Human Competitive Spectra-Based Fault Localisation Techniques 08 / 05 / 2012

Spectra-Based Fault Localisation (SBFL) aims to assist debugging by applying risk evaluation formulæ (sometimes called suspiciousness metrics) to program spectra and ranking statements according to the predicted risk. Designing a risk evaluation formula is often an intuitive process done by human software engineer. This paper presents a Genetic Programming approach for evolving risk assessment formulæ. The empirical evaluation using 92 faults from four Unix utilities produces promising results. GP-evolved equations can consistently outperform many of the human-designed formulæ, such as Tarantula, Ochiai, Jaccard, Ample, and Wong1/2, up to 5.9 times. More importantly, they can perform equally as well as Op2, which was recently proved to be optimal against If-Then-Else-2 (ITE2) structure, or even outperform it against other program structures. 1 The program spectra data used in the paper, as well as the complete empirical results, are available from: http://www.cs. ucl.ac. uk/staff/s.yoo/evolving-sbfl.html. UCL DEPARTMENT OF COMPUTER SCIENCE
Spanish desert ant Large-scale distribution of hybridogenetic lineages in a

References http://rspb.royalsocietypublishing. org/content/281/1774/20132396.full. html#ref-list-1 This article cites 50 articles, 9 of which can be accessed free Subject collections (135 articles) molecular biology  (1477 articles) ecology  (1051 articles) behaviour  Articles on similar topics can be found in the following collections Email alerting service here right-hand corner of the article or click Receive free email alerts when new articles cite this article sign up in the box at the top
THE IMPLEMENTATION OF SCIENTIFIC APPROACH ON SPEAKING SKILL AT SECOND GRADE STUDENTS BASED ON LEARNING STYLE IN SMAN

The objectives of this study were to find out i) the effect of implementation of scientific approach on students‟ speaking achievement and ii) whether students‟ learning style preferences affect the students‟ speaking capability. The research used preexperimental design. The subjects were 28 second year science class students of SMAN 1 Pringsewu. Questionnaires were employed to collect the data of the students‟ learning style preferences and speaking tests were conducted to identify students‟ speaking achievement. The implementation of scientific approach could improve the students‟ speaking skill since the students actively participated in the learning process by speaking through drills and repetitions in meaningful context. This is confirmed by a significant improvement of the students‟ speaking achievement with significant level 0.05. Students‟ learning style preferences also affected their speaking ability. The results suggest that scientific approach facilitates the students to improve their English proficiency. In addition, learning style preferences also contributed to the students‟ success in acquiring language.
GreedyDual* Web Caching Algorithm Exploiting the Two Sources of Temporal Locality in Web Request Streams

The relative importance of long-term popularity and short-term temporal correlation of references for Web cache replacement policies has not been studied thoroughly. This is partially due to the lack of accurate characterization of temporal locality that enables the identi cation of the relative strengths of these two sources of temporal locality in a reference stream. In [21], we have proposed such a metric and have shown that Web reference streams di er signi cantly in the the prevelance of these two sources of temporal locality. These ndings underscore the importance of a Web caching strategy that can adapt in a dynamic fashion to the prevelance of these two sources of temporal locality. In this paper, we propose a novel cache replacement algorithm, GreedyDual*, which is a generalization of GreedyDual-Size. GreedyDual* uses the metrics proposed in [21] to adjust the relative worth of long-term popularity versus short-term temporal correlation of references. Our tracedriven simulation experiments show the superior performance of GreedyDual* when compared to other Web cache replacement policies proposed in the literature.
Kent Academic Repository

Recent advances in Deep Learning (DL) allow for solving complex AI problems that used to be considered very hard. While this progress has advanced many ﬁelds, it is considered to be bad news for CAPTCHAs (Completely Automated Public Turing tests to tell Computers and Humans Apart), the security of which rests on the hardness of some learning problems. In this paper we introduce DeepCAPTCHA, a new and secure CAPTCHA scheme based on adversarial examples , an inherit limitation of the current Deep Learning networks. These adversarial examples are constructed inputs, either synthesized from scratch or computed by adding a small and speciﬁc perturbation called adversarial noise to correctly classiﬁed items, causing the targeted DL network to misclassify them. We show that plain adversarial noise is insufﬁcient to achieve secure CAPTCHA schemes, which leads us to introduce immutable adversarial noise — an adversarial noise that is resistant to removal attempts. In this work we implement a proof of concept system, and its analysis shows that the scheme offers high security and good usability compared to the best previously existing CAPTCHAs
Construction of a high-density integrated genetic linkage map of rubber tree (Hevea brasiliensis) using genotyping-by-sequencing (GBS)

Construction of linkage maps is crucial for genetic studies and marker-assisted breeding programs. Recent advances in next generation sequencing technologies allow for the generation of high-density linkage maps, especially in non-model species lacking extensive genomic resources. Here, we constructed a high-density integrated genetic linkage map of rubber tree (Hevea brasiliensis), the sole commercial producer of high-quality natural rubber. We applied a genotyping-by-sequencing (GBS) technique to simultaneously discover and genotype single nucleotide polymorphism (SNP) markers in two rubber tree populations. A total of 21,353 single nucleotide substitutions were identified, 55% of which represented transition events. GBS-based genetic maps of populations P and C comprised 1704 and 1719 markers and encompassed 2041 cM and 1874 cM, respectively. The average marker densities of these two maps were one SNP in 1.23–1.25 cM. A total of 1114 shared SNP markers were used to merge the two component maps. An integrated linkage map consisted of 2321 markers and spanned the cumulative length of 2052 cM. The composite map showed a substantial improvement in marker density, with one SNP marker in every 0.89 cM. To our knowledge, this is the most saturated genetic map in rubber tree to date. This integrated map allowed us to anchor 28,965 contigs, covering 135 Mb or 12% of the published rubber tree genome. We demonstrated that GBS is a robust and cost-effective approach for generating a common set of genome-wide SNP data suitable for constructing integrated linkage maps from multiple populations in a highly heterozygous agricultural species.
Measurement of top quark polarization in t(t)over-bar lepton+jets final states

We present a measurement of top quark polarization in t (t) over bar pair production in p (p) over bar collisions at root s = 1.96 TeV using data corresponding to 9.7 fb(-1) of integrated luminosity recorded with the D0 detector at the Fermilab Tevatron Collider. We consider final states containing a lepton and at least three jets. The polarization is measured through the distribution of lepton angles along three axes: the beam axis, the helicity axis, and the transverse axis normal to the t (t) over bar production plane. This is the first measurement of top quark polarization at the Tevatron using lepton + jet final states and the first measurement of the transverse polarization in t (t) over bar production. The observed distributions are consistent with standard model predictions of nearly no polarization.
Quantum Hacking in the Age of Measurement-Device-Independent Quantum Cryptography

Cryptography is essential for secure communication in the digital era. Today, publickey cryptography is widely employed, and has provided an efficient method for encrypting content and ensuring both confidentiality and authenticity of electronic communications. However, the security of these systems is based on assumptions of computational hardness within the constraints of current computing capability. Thus, as quantum computing becomes a reality, public-key algorithms will be genuinely vulnerable to attack. By contrast, quantum cryptography, which is based on quantum physics instead of mathematical assumptions, is able to achieve information-theoretic security. Advances in practical quantum cryptographic systems have not kept pace with theory, where an eavesdropper can relatively easily exploit loopholes in practical implementations to compromise theory-proved security. Bridging the gap between perfect theory and imperfect practice has become a priority for the growing field of quantum key distribution (QKD), which has strived to strengthen the practical security of QKD systems. Among all the countermeasures against quantum hacking, the measurement-device-independent (MDI) QKD protocol is promising because it is immune to all side-channel attacks on measurement devices. However, the MDI QKD protocol has some limitations that critically restrict its practical usefulness. Technically, the MDI scheme is not compatible with existing QKD systems, and produces a low key rate. In addition, the theory underlying MDI QKD security is based on the use of trusted source stations. Thus, this protocol is not a universal solution. This thesis further investigates the practical security of quantum cryptography in and beyond MDI quantum cryptography. To overcome the technical limitations of MDI QKD, we first evaluate two other countermeasures against imperfect detections. The first is an industrial patch based on random detection efficiency, recently implemented by ID Quantique in the commercial Clavis2 QKD system. While powerful, experimental testing shows that this countermeasure is not sufficient to defeat the detector blinding attack. The second countermeasure aims to achieve a higher key rate than MDI QKD while maintaining the same security properties. However, our research shows that detector-device-independent (DDI) QKD security is not equivalent to that of MDI QKD and, further, that DDI QKD is insecure against detector side-channel attacks. While this initial work points to the superior performance of MDI QKD systems, core challenges remain. The fundamental security assumption adopted for MDI QKD systems, regarding the exclusive use of trustable source stations, cannot always be satisfied in practice. Our study revealed several side channels of source devices. The first is disclosed
DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models

Deep Learning (DL) models have caused a paradigm shift in our ability to comprehend raw data in various important fields, ranging from intelligence warfare and healthcare to autonomous transportation and automated manufacturing. A practical concern, in the rush to adopt DL models as a service, is protecting the models against Intellectual Property (IP) infringement. The DL models are commonly built by allocating significant computational resources that process vast amounts of proprietary training data. The resulting models are therefore considered to be the IP of the model builder and need to be protected to preserve the owner's competitive advantage. This paper proposes DeepSigns, a novel end-to-end IP protection framework that enables insertion of coherent digital watermarks in contemporary DL models. DeepSigns, for the first time, introduces a generic watermarking methodology that can be used for protecting DL owner's IP rights in both white-box and black-box settings, where the adversary may or may not have the knowledge of the model internals. The suggested methodology is based on embedding the owner's signature (watermark) in the probability density function (pdf) of the data abstraction obtained in different layers of a DL model. DeepSigns can demonstrably withstand various removal and transformation attacks, including model compression, model fine-tuning, and watermark overwriting. Proof-of-concept evaluations on MNIST, and CIFAR10 datasets, as well as a wide variety of neural network architectures including Wide Residual Networks, Convolution Neural Networks, and Multi-Layer Perceptrons corroborate DeepSigns' effectiveness and applicability.
Fine particle mass monitoring with low-cost sensors: Corrections and long-term performance evaluation

Abstract Low-cost sensors for the measurement of fine particulate matter mass (PM2.5) enable dense networks to increase the spatial resolution of air quality monitoring. However, these sensors are affected by environmental factors such as temperature and humidity and their effects on ambient aerosol, which must be accounted for to improve the in-field accuracy of these sensors. We conducted long-term tests of two low-cost PM2.5 sensors: Met-One NPM and PurpleAir PA-II units. We found a high level of self-consistency within each sensor type after testing 25 NPM and 9 PurpleAir units. We developed two types of corrections for the low-cost sensor measurements to better match regulatory-grade data. The first correction accounts for aerosol hygroscopic growth using particle composition and corrects for particle mass below the optical sensor size cut-point by collocation with reference Beta Attenuation Monitors (BAM). A second, fully-empirical correction uses linear or quadratic functions of environmental variables based on the same collocation dataset. The two models yielded comparable improvements over raw measurements. Sensor performance was assessed for two use cases: improving community awareness of air quality with short-term semi-quantitative comparisons of sites and providing long-term reasonably quantitative information for health impact studies. For the short-term case, both sensors provided reasonably accurate concentration information (mean absolute error of ∼4 µg/m3) in near-real time. For the long-term case, tested using year-long collocations at one urban background and one near-source site, error in the annual average was reduced below 1 µg/m3. Hence, these sensors can supplement sparse networks of regulatory-grade instruments, perform high-density neighborhood-scale monitoring, and be used to better understand spatial patterns and temporal air quality trends across urban areas. Copyright © 2019 American Association for Aerosol Research
Context is Everything: An Investigation of Responsibility Beliefs and Interpretations and the Relationship with Obsessive-Compulsive Symptomatology across the Perinatal Period.

BACKGROUND The cognitive-behavioural model of perinatal OCD suggests the role of increased sense of responsibility during the perinatal period in the development and maintenance of obsessive-compulsive symptoms. However, the idiosyncratic nature of responsibility attitudes and interpretations of intrusions is not fully understood. AIMS To investigate how responsibility interpretations regarding intrusions vary across the perinatal period and how this relates to obsessive-compulsive symptomatology. METHOD 94 women (26 antenatal, 35 postpartum and 33 non-childbearing controls) completed measures of responsibility attitudes and interpretations regarding specific intrusions (either general or baby-related), as well as obsessive-compulsive symptomatology, anxiety and depression. RESULTS Postpartum ratings of responsibility interpretations regarding baby-related intrusions were significantly higher than: i) postpartum ratings of responsibility interpretations regarding non-baby intrusions; and ii) control group responsibility interpretations. The groups were not significantly different regarding general responsibility ratings. Ratings of baby-related responsibility interpretations predicted variance in obsessive-compulsive symptomatology. CONCLUSION The postpartum group showed significant differences in responsibility interpretations regarding baby-related intrusions. These responsibility interpretations were shown to predict obsessive-compulsive symptomatology.
CEO Turnover and Relative Performance Evaluation

This paper shows that CEOs are fired after bad firm performance caused by factors beyond their control. Standard economic theory predicts that corporate boards filter out exogenous industry and market shocks from firm performance before deciding on CEO retention. Using a hand-collected sample of 3,365 CEO turnovers from 1993 to 2009, we document that CEOs are significantly more likely to be dismissed from their jobs after bad industry and, to a lesser extent, after bad market performance. A decline in industry performance from the 90th to the 10th percentile doubles the probability of a forced CEO turnover.
International Journal of Innovation in Teaching and Learning (IJITL) Volume I- Issue I (June 2016)

Peace education is a key process for creating peace and devastating conflict and violence. Therefore, peace education promotes the knowledge, skills, attitudes as well as values that pursue to convert individual‟s mindsets, attitudes as well as behaviours. So, peace education is a key instrument for developing a culture of peace and a plan which has been used a large number of nations to stop violent and fatal conflicts. The objectives of the study were: (i) to examine the conceptual awareness of secondary school teachers regarding knowledge component of peace education in Khyber Pakhtunkhwa, Pakistan. (ii) To examine the awareness of secondary school teachers regarding the skills and attitude of peace education in Khyber Pakhtunkhwa, Pakistan. All secondary school teachers of Khyber Pakhtunkhwa were the population of the study. According to the nature of the study the researcher selected 320 secondary teachers from different districts. A self-developed questionnaire was used as a research tool. All statements on the questionnaire were related to conceptual awareness of secondary school teachers regarding peace education. The validity and reliability of the research instrument were accurately confirmed. The data were analyzed through SPSS (version 20). The findings and conclusions of the study showed that most of male secondary school teachers were aware about the three components of peace education. Majority of female secondary school teachers were not aware about the components of peace education.
Original Research by Young Twinkle Students (Orbyts): Ephemeris Refinement of Transiting Exoplanets II

We report follow-up observations of four transiting exoplanets, TRES-2 b, HAT-P-22 b, HAT-P-36 b and XO-2 b, as part of the Original Research By Young Twinkle Students (ORBYTS) program. These observations were taken using the Las Cumbres Observatory Global Telescope Network’s (LCOGT) robotic 0.4 m telescopes and were analyzed using the HOlomon Photometric Software (HOPS). Such observations are key for ensuring accurate transit times for upcoming telescopes, such as the James Webb Space Telescope, Twinkle (Edwards et al. ) and Ariel (Tinetti et al. ), which may seek to characterize the atmospheres of these planets. The data have been uploaded to ExoClock and a significant portion of this work has been completed by secondary school students in London.
On a bilinear Strichartz estimate on irrational tori and some application

We prove a bilinear Strichartz type estimate for irrational tori via a decoupling type argument, \cite{bourgain2014proof}, recovering and generalizing the result of \cite{de2006global}. As a corollary, we derive a global well-posedness result for the cubic defocusing NLS on two dimensional irrational tori with data of infinite energy.
Program for Promoting Social Science Research Aimed at Solutions of Near-Future Problems Design of Interfirm Network to Achieve Sustainable Economic Growth

This paper investigates the effect of banks’ lending capacity on firms’ capital investment. To overcome the difficulties in identifying purely exogenous shocks to firms’ bank financing, we utilize the natural experiment provided by the Great Hanshin-Awaji (Kobe) Earthquake in 1995. Using a unique firm-level dataset that allows us to identify firms and banks in the earthquake-affected area, together with information on bank-firm relationships, we find that the investment ratio of firms located outside of the earthquake-affected area but with their main banks inside the area was lower than that of firms that were both located and had their main banks outside of the area. This result implies that the weakened lending capacity of damaged banks exacerbated the borrowing constraints on the investment of their undamaged client firms. We also find that the negative impact is robust for two alternative measures of bank damage: that to the bank headquarters and that to the branch network. However, the impacts of the two are different in timing; while that of the former emerged immediately after the earthquake, the latter emerged with a one-year lag.
Mention Annotations Alone Enable Efficient Domain Adaptation for Coreference Resolution

Although, recent advances in neural network models for coreference resolution have led to substantial improvements on benchmark datasets, it remains a challenge to successfully transfer those models to new target domains containing many out-of-vocabulary spans and requiring differing annotation schemes. Typical approaches for domain adaptation involve continued training on coreference annotations in the target domain, but obtaining those annotations is costly and time-consuming. In this work, we show that adapting mention detection is the key component to successful domain adaptation of coreference models, rather than antecedent linking. Through timed annotation experiments, we also show annotating mentions alone is nearly twice as fast as annotating full coreference chains. Based on these insights, we propose a method for effectively adapting coreference models that requires only mention annotations in the target domain. We use an auxiliary mention detection objective trained with mention examples in the target domain resulting in higher mention precision. We demonstrate that our approach facilitates sample-and time-efﬁcient transfer to new annotation schemes and lexicons in extensive evaluation across three English coreference datasets: CoNLL-2012 (news/conversation), i2b2/VA (medical case notes), and a dataset of child welfare case notes. We show that annotating mentions results in 7-14% improvement in average F1 over annotating coreference over an equivalent amount of time.