Miracle-dz/UniFAR-FTUs huggingface dataset:
CinPatent: Datasets for Patent Classification

Patent classification is the task that assigns each input patent into several codes (classes). Due to its high demand, several datasets and methods have been introduced. However, the lack of both systematic performance comparison of baselines and access to some datasets creates a gap for the task. To fill the gap, we introduce two new datasets in English and Japanese collected by using CPC codes. The English dataset includes 45,131 patent documents with 425 labels and the Japanese dataset contains 54,657 documents with 523 labels. To facilitate the next studies, we compare the performance of strong multi-label text classification methods on the two datasets. Experimental results show that AttentionXML is consistently better than other strong baselines. The ablation study is also conducted in two aspects: the contribution of different parts (title, abstract, description, and claims) of a patent and the behavior of baselines in terms of performance with different training data segmentation. We release the two new datasets with the code of the baselines.
Blind separation of mixed images using higher order statistics

The separation of mixed images is a very exciting area of research, especially when no a priori information is available about the mixed images. In such a case, blind signal separation (BSS) technique is needed to recover independent sources given only sensor observations, which are assumed to be unknown independent images. Classical eigen and singular value decomposition techniques, which are based on second order statistics, fail to blindly separate mixed signals in many circumstances. On the other hand, many techniques based on higher order statistics were suggested to blindly separate mixed independent signals and images. These techniques are generally known as independent component analysis (ICA) as they are oriented towards searching for the statistically independent components in the signal mixture (instead pf the uncorrelated components in the techniques based on second order statistics). In this paper, we investigate the performance of a technique based on higher order statistics, namely higher order eigen-value decomposition (HOEVD) in the blind separation of mixed images. Illustrative examples using different types of images and different mixing matrices are utilized to demonstrate the ability of the considered technique.
Warnings: Violation Symptoms Indicating Architecture Erosion

As a software system evolves, its architecture tends to degrade, and gradually impedes software maintenance and evolution activities and negatively impacts the quality attributes of the system. The main root cause behind architecture erosion phenomenon derives from violation symptoms (such as violations of architecture pattern). Previous studies focus on detecting violations in software systems using architecture conformance checking approaches. However, code review comments are also rich sources that may contain extensive discussions regarding architecture violations. In this work, we investigated the characteristics of architecture violation symptoms in code review comments from the developers' perspective. We employed a set of keywords related to violation symptoms to collect 606 (out of 21,583) code review comments from four popular OSS projects in the OpenStack and Qt communities. We manually analyzed the collected 606 review comments to provide the categories and linguistic patterns of violation symptoms, as well as the reactions how developers addressed them. Our findings show that: (1) 10 categories of violation symptoms are discussed by developers during the code review process; (2) The frequently-used terms of expressing violation symptoms are"inconsistent"and"violate", and the most frequently-used linguistic pattern is Problem Discovery; (3) Refactoring and removing code are the major measures (90%) to tackle violation symptoms, while a few violation symptoms were ignored by developers. Our findings suggest that the investigation of violation symptoms can help researchers better understand the characteristics of architecture erosion and facilitate the development and maintenance activities, and developers should explicitly manage violation symptoms, not only for addressing the existing architecture violations but also preventing future violations.
On the Privacy-Utility Trade-Off With and Without Direct Access to the Private Data

We study an information theoretic privacy mechanism design problem for two scenarios where the private data is either observable or hidden. In the hidden private data scenario, an agent observes useful data <inline-formula> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula> that is correlated with private data <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>, and generate disclosed data <inline-formula> <tex-math notation="LaTeX">$U$ </tex-math></inline-formula> which maximizes the revealed information about <inline-formula> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula> while satisfying a bounded privacy leakage constraint. Considering the other scenario, the agent has additional access to <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>. To design the privacy mechanism, we first extend the Functional Representation Lemma and Strong Functional Representation Lemma by relaxing the independence condition and thereby allowing a certain leakage. We then find lower and upper bounds on the privacy-utility trade-offs in both scenarios. In particular, for the case where no leakage is allowed and <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula> is observable, our upper and lower bounds improve previous bounds. Considering bounded mutual information as privacy constraint and the observable private data scenario we show that if the common information and mutual information between <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula> are equal, then the attained upper bound is tight. Finally, the privacy-utility trade-off with prioritized private data is studied where part of <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula> is more private than the remaining part.
Content Rating Classification for Fan Fiction

Content ratings can enable audiences to determine the suitability of various media products. With the recent advent of fan fiction, the critical issue of fan fiction content ratings has emerged. Whether fan fiction content ratings are done voluntarily or required by regulation, there is the need to automate the content rating classification. The problem is to take fan fiction text and determine the appropriate content rating. Methods for other domains, such as online books, have been attempted though none have been applied to fan fiction. We propose natural language processing techniques, including traditional and deep learning methods, to automatically determine the content rating. We show that these methods produce poor accuracy results for multi-classification. We then demonstrate that treating the problem as a binary classification problem produces better accuracy. Finally, we believe and provide some evidence that the current approach of self-annotating has led to incorrect labels limiting classification results.
A scanning photon microscope for non-destructive observations of crystal defect and interface trap distributions in silicon wafers

A sophisticated flying spot scanner in which 2 kHz AC surface photovoltages induced in a Si wafer due to the chopped irradiation of a photon beam 0.4 mm in diameter are non-destructively measured through a 25 mu m air gap between the wafer surface and a transparent electrode is developed. Photovoltage distributions on a wafer 50 to 150 mm in diameter are measured in 5 min, and displayed as a 512*480 pixel black and white image. With the use of near infrared (peaking at 896 and 1076 nm) and blue (peaking at 448 nm) photon sources (cathode ray tubes), it is possible to measure crystal defect distribution in the bulk and interface trap distribution at the wafer surface separately. The apparatus is successfully applied to observations of swirl patterns and radiation damage induced by an electron beam in thermally oxidised p-type Si wafers.
A Cut-and-solve Algorithm for Virtual Machine Consolidation Problem

The virtual machine consolidation problem (VMCP) attempts to determine which servers to be activated, how to allocate virtual machines (VMs) to the activated servers, and how to migrate VMs among servers such that the summation of activated, allocation, and migration costs is minimized subject to the resource constraints of the servers and other practical constraints. In this paper, we first propose a new mixed integer linear programming (MILP) formulation for the VMCP. We show that compared with existing formulations, the proposed formulation is much more compact in terms of smaller numbers of variables or constraints, which makes it suitable for solving large-scale problems. We then develop a cut-and-solve (C&S) algorithm, a tree search algorithm to efficiently solve the VMCP to optimality. The proposed C&S algorithm is based on a novel relaxation of the VMCP that provides a stronger lower bound than the natural continuous relaxation of the VMCP, making a smaller search tree. By extensive computational experiments, we show that (i) the proposed formulation significantly outperforms existing formulations in terms of solution efficiency; and (ii) compared with standard MILP solvers, the proposed C&S algorithm is much more efficient.
Dubbing in Practice: A Large Scale Study of Human Localization With Insights for Automatic Dubbing

We investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319.57 hours of video from 54 professionally produced titles. This is the first such large-scale study we are aware of. The results challenge a number of assumptions commonly made in both qualitative literature on human dubbing and machine-learning literature on automatic dubbing, arguing for the importance of vocal naturalness and translation quality over commonly emphasized isometric (character length) and lip-sync constraints, and for a more qualified view of the importance of isochronic (timing) constraints. We also find substantial influence of the source-side audio on human dubs through channels other than the words of the translation, pointing to the need for research on ways to preserve speech characteristics, as well as transfer of semantic properties such as emphasis and emotion, in automatic dubbing systems.
The Consistency of Probabilistic Databases with Independent Cells

A probabilistic database with attribute-level uncertainty consists of relations where cells of some attributes may hold probability distributions rather than deterministic content. Such databases arise, implicitly or explicitly, in the context of noisy operations such as missing data imputation, where we automatically fill in missing values, column prediction, where we predict unknown attributes, and database cleaning (and repairing), where we replace the original values due to detected errors or violation of integrity constraints. We study the computational complexity of problems that regard the selection of cell values in the presence of integrity constraints. More precisely, we focus on functional dependencies and study three problems: (1) deciding whether the constraints can be satisfied by any choice of values, (2) finding a most probable such choice, and (3) calculating the probability of satisfying the constraints. The data complexity of these problems is determined by the combination of the set of functional dependencies and the collection of uncertain attributes. We give full classifications into tractable and intractable complexities for several classes of constraints, including a single dependency, matching constraints, and unary functional dependencies.
Minimum Eigenvalue Detection for Spectrum Sensing in Cognitive Radio

Spectrum sensing is a key task for cognitive radio. Our motivation is to increase the probability of detection for spectrum sensing in cognitive radio. In this paper, we proposed a new semi blind method which is based on minimum Eigenvalue of a covariance matrix. The ratio of the minimum eigenvalue to noise power is used as the test statistic. The method does not need channel and signal information as prior knowledge. Eigenvalue based algorithm perform better than energy detection for correlated signal. Our proposed method is better than the maximum eigenvalue and energy detection for correlated signal. We perform Simulation which is based on digital TV signal. In all tests, our method performs better than maximum eigenvalue detection and energy detection. DOI: http://dx.doi. org/10.11591/ijece.v4i4. 6226
Evaluation of Static Analysis on Web Applications

Web services are becoming business-critical components, often deployed with critical software bugs that can be maliciously explored. Web vulnerability scanners allow the detection of security vulnerabilities in web services by stressing the service from the point of view of an attacker. However, research and practice show that different scanners perform differently in vulnerability detection. This paper presents a qualitative evaluation of security vulnerabilities found in web applications. Some well-known vulnerability scanners have been used to identify security flaws in web service implementations. Many vulnerabilities have been observed, which confirms that many services are deployed without proper security testing. Additionally, having reviewed and considered several articles, the differences in the vulnerabilities detected and the high number of false positives observed highlight the limitations of web vulnerability scanners in detecting security vulnerabilities in web services. Furthermore, this work will discuss the static analysis approach for discovering security vulnerabilities in web applications and complimenting it with proven research findings or solutions. These vulnerabilities include broken access control, cross-site scripting, SQL injections, buffer overflow, unrestricted file upload, broken authentications, etc. Web applications are becoming mission-essential components for businesses, potentially risking having several software vulnerabilities that hackers can exploit maliciously. A few Vulnerability scanners have been used to detect security weaknesses in web service applications, and many vulnerabilities have been discovered, thus confirming that many online apps are launched without sufficient security testing.
Acquiring religious words: dialogical and individual construction of a word's meaning

By the age of eight, there is a significant increase in abstract words in the child's lexicon. A crucial contribution can be seen in the linguistic input, i.e. the way how abstract words are presented by caregivers by means of linguistic perspectivation and emotionalization. Following an interactionist way, we were interested in how the semantics of abstract words is constructed by child and caregiver in duet. We focused on a subset of abstract words and studied the acquisition of meaning of the religious concept mercy. We expected religious words to be emotionally anchored and presented with perspectivation, both contributing to learning. Exploring the dialogic constructions, we investigated eight 7- to 8-year olds and their parents during dialogic reading and studied their strategies focusing on the linguistic means of emotionalization and perspectivation in contextualizing the word. In a subsequent test, we analysed these means used by the children and assessed their individual understanding of mercy. Our analyses indicate that during reading, the enrichment of semantics by emotionalization was related between child and caregiver, whereas cross-situationally, a simultaneous enrichment of emotionalization and perspectivation was present. Moreover, the children demonstrated a conceptual understanding of mercy in religious contexts, but not in secular contexts. This article is part of the theme issue ‘Concepts in interaction: social engagement and inner experiences’.
Diagnosis with Confidence: Deep Learning for Reliable Classification of Squamous Lesions of the Upper Aerodigestive Tract

Background Diagnosis of head and neck (HN) squamous dysplasias and carcinomas is critical for patient care cure and follow-up. It can be challenging, especially for grading intraepithelial lesions. Despite recent simplification in the last WHO grading system, the inter- and intra-observer variability remains substantial, particularly for non-specialized pathologists, exhibiting the need for new tools to support pathologists. Methods In this study we investigated the potential of deep learning to assist the pathologist with automatic and reliable classification of HN lesions following the 2022 WHO classification system. We created, for the first time, a large-scale database of histological samples (>2000 slides) intended for developing an automatic diagnostic tool. We developed and trained a weakly supervised model performing classification from whole slide images (WSI). We evaluated our model on both internal and external test sets and we defined and validated a new confidence score to assess the predictions which can be used to identify difficult cases. Results Our model demonstrated high classification accuracy across all lesion types on both internal and external test sets (respectively average AUC: 0.878 (95% CI:[0.834-0.918]) and 0.886 (95% CI: [0.813-0.947])) and the confidence score allowed for accurate differentiation between reliable and uncertain predictions. Conclusions Our results demonstrate that the model, associated with confidence measurements, can help in the difficult task of classifying head and neck squamous lesions by limiting variability and detecting ambiguous cases, taking us one step closer to a wider adoption of AI-based assistive tools.
Intraspecific chemodiversity provides plant individual- and neighbourhood-mediated associational resistance towards aphids

Some plant species express an extraordinarily high intraspecific diversity in phytochemicals (= chemodiversity). As discussed for biodiversity, higher chemodiversity may provide better protection against environmental stress, including herbivory. However, little is known about whether the resistance of a plant individual towards herbivores is mostly governed by its own chemodiversity or by associational resistance provided by conspecific neighbours. To investigate the role of chemodiversity in plant-aphid interactions, we used the Asteraceae Tanacetum vulgare, whose individuals differ pronouncedly in the composition of leaf terpenoids, forming distinct chemotypes. Plants were set-up in a field consisting of 60 plots, each containing five individuals of either the same or different chemotypes. Presence of winged aphids, indicating aphid attraction, and abundance of winged and unwinged aphids, indicating fitness, were scored weekly on each plant, focusing on three commonly occurring aphid species specialised on T. vulgare. During the peak abundance of aphids, leaf samples were taken from all plants for re-analyses of the terpenoid composition and quantification of terpenoid chemodiversity, calculated on an individual plant (Shannon index, Hsind) and plot level (Hsplot). Aphid attraction was neither influenced by chemotype nor plot-type. The real-time odour environment may be very complex in this setting, impeding clear preferences. In contrast, the abundance was affected by both chemotype and plot-type. On average, more Uroleucon tanaceti aphids were found on plants of two of the chemotypes growing in homogenous compared to heterogenous plots, supporting the associational resistance hypothesis. For Macrosiphoniella tanacetaria the probability of presence on a plant differed between plot-types on one chemotype. Terpenoid chemodiversity expressed as a gradient revealed negative Hsplot effects on U. tanaceti, but a positive correlation of Hsind with the abundance of M. tanacetaria. Aphids of M. fuscoviride were not affected by any level of chemodiversity. Synthesis. This study shows that not only the chemotype and chemodiversity of individual plants but also that of conspecific neighbours influence plant-herbivore interactions. These effects are highly specific with regard to the plant chemotype, the aphid species as well as its morphs (winged vs. unwinged). Furthermore, our results highlight the importance of analysing chemodiversity at different levels.
RecView: an interactive R application for viewing and locating recombination positions using pedigree data

Recombination generates new haplotypes and disconnects linked genes thereby increasing the efficiency of selection and the adaptive potential. Quantifying the recombination landscape, i.e., the recombination rate variation along chromosomes, is important for understanding how evolutionary processes such as selection and drift are acting on genes and chromosomes. Here, we present RecView, an interactive R application, designed to view and locate recombination positions along chromosomes using whole-genome genotype data of a three-generation pedigree. RecView visualises the grandparent-of-origin of all informative alleles along each chromosome of the offspring in the pedigree. It also infers putative recombination positions with two algorithms, one based on change in the proportion of the alleles with specific grandparent-of-origin, and one on the degree of continuity of alleles with the same grandparent-of-origin, along the chromosome. Putative recombination positions are given in base pairs together with an estimated error based on the local density of informative alleles. We demonstrate the applicability of RecView using sequencing data of one 120 Mb-large chromosome of one offspring (and its four grandparents and two parents) of a passerine bird, the great reed warbler (Acrocephalus arundinaceus). On this chromosome, we detected five recombination events, three on the paternal chromosome and two on the maternal chromosome with both algorithms. To evaluate how sensitive the analysis is for SNP density, we downsampled our data to 10% of the original dataset. In conclusion, we provide an easy-to-use and highly effective application for viewing and locating recombination positions along chromosomes in small pedigrees. RecView and test data are available on GitHub (https://github.com/HKyleZhang/RecView.git).
The Evolutionary History of Drosophila simulans Y Chromosomes Reveals Molecular Signatures of Resistance to Sex Ratio Meiotic Drive

The recent evolutionary history of the Y chromosome in Drosophila simulans, a worldwide species of Afrotropical origin, is closely linked to that of X-linked meiotic drivers (Paris system). The spread of the Paris drivers in natural populations has elicited the selection of drive resistant Y chromosomes. To infer the evolutionary history of the Y chromosome in relation to the Paris drive, we sequenced 21 iso-Y lines, each carrying a Y chromosome from a different location. Among them, 13 lines carry a Y chromosome that is able to counteract the effect of the drivers. Despite their very different geographical origins, all sensitive Y’s are highly similar, suggesting that they share a recent common ancestor. The resistant Y chromosomes are more divergent and segregate in four distinct clusters. The phylogeny of the Y chromosome confirms that the resistant lineage predates the emergence of Paris drive. The ancestry of the resistant lineage is further supported by the examination of Y-linked sequences in the sister species of D. simulans, D. sechellia, and D. mauritiana. We also characterized the variation in repeat content among Y chromosomes and identified multiple simple satellites associated with resistance. Altogether, the molecular polymorphism allows us to infer the demographic and evolutionary history of the Y chromosome and provides new insights on the genetic basis of resistance.