Miracle-dz/UniFAR-FTUs huggingface dataset:
Child-observation system with wide area networks of IoT child observation using information terminal bus stops in Nonoichi city

In Japan, the observation of children using surveillance cameras is on the rise. However, leaking of these surveillance-camera videos to third parties causes problems. Child-observation systems, using equipment such as beacons, are highly popular in Japan. In these systems, the children must carry the equipment. Hence, the equipment cost should be low. Moreover, they work only when the child passes through a particular location, such as an elementary school gate. Therefore, after the child crosses the school gate, parents cannot check the location. In addition, as most systems use simple ID numbers, there are security problems. In this paper, we propose a child-observation system, which enhances data anonymity and security, and has an advanced security function that prevents third parties from exploiting the data. As a result of experimental results of basic test which was carried out the demonstration experiment in Nonoichi city, we confirmed the child-feature information data can be transmitted in each cluster and child-feature information data can be collected to the cluster head correctly.
Current-Voltage Characteristics Across Small Angle Symmetric Tilt Boundaries in Nb-Doped SrTiO3 Bicrystals

Grain boundary structure and current–voltage ( I –V ) characteristics were investigated for Nb-doped SrTiO3 bicrystals having small angle tilt boundaries with misorientation angles of 2 ◦ and 4 ◦ against [001]. The bicrystals were fabricated by using hot-joining technique at 1400 ◦ C for 10 h under a pressure of 0.4 MPa. High resolution transmission electron microscopy study revealed that the joined boundaries are free from any secondary phases such as amorphous phases even on an atomic scale. The structures of the two boundaries are composed of edge type dislocations whose Burgers vector is [010]. But the density of boundary dislocations differs between the two boundaries. They exist at an interval of 10 nm in the 2 ◦ -boundary and 5.2 nm in the 4 ◦ -boundary. On the other hand, it was found that non-linearity in I –V relation across the boundary increases with an increase in the misorientation angle. This result clearly indicates that the potential barrier height is closely related to the density of boundary dislocations in the case of small angle type boundaries.
Shame as a compromise for humiliation and rage in the internal representation of abuse by loved ones: Processes, motivations, and the role of dissociation

ABSTRACT This paper examines one particular way a person abused may come to internally position themselves and the abuser to understand their abuse experience. It is based on a differentiation and exploration of the dynamic relationship between shame and humiliation associated with complex feelings the abused has to the abuser. Humiliation is described as denoting the naked self exposed by another, while shame is described as denoting the naked self exposed to another. From this lens, abusive events are conceived as humiliating experiences that come to be represented as shame experiences. Shame is argued to cover over humiliation in order to separate the abused from their internal representation of the abuser (i.e., conceal the self-other object-relationship). This process is facilitated by dissociation and serves several functions, including cloaking hostile feelings (e.g., humiliation fury) toward the abusive (though loved) object. Shame, with the assistance of dissociation, becomes a compromise formation. It punishes the self for the initial humiliation rage directed at the object, protects the object from further attack and blame for the abuse, and obscures awareness of the rage felt toward the object as well as the reparatory guilt possible from it. Dissociation maintains this position by isolating the interpersonal field, the self and object, from the narrative of abuse events. The potential for freedom comes from eroding dissociation, leaving the shame bubble, entertaining the abusive (though loved) object as etiologically significant, and facing the humiliation and humiliation rage that provides the path to reparatory guilt.
Privacy-Preserving Data Dissemination in Untrusted Cloud

B2B (business-to-business) systems often use service-oriented architecture (SOA) with decomposed business services. These services can interact and share data among each other. Service might use a cloud – hosted database, such as a non - relational encrypted key – value store. However, the cloud platform hosting the database can be untrusted. Data owner needs to be sure that each service can access only those segments of a shared database for which the service is authorized. Furthermore, data requests can come from a service also hosted by untrusted cloud. Hence, there is a need for designing a cloud enterprise framework that can ensure privacy-preserving data dissemination in SOA and accurately detect data leakages. We design and prototype a solution that ensures privacy – preserving dissemination of data. The solution is based on (a) role-based access control, (b) cryptographic capabilities of client's browser, (c) authentication method, (d) subject's trust level. The prototype enables privacy – preserving dissemination of Electronic Health Records (EHRs) hosted in an untrusted cloud.
Mortality salience reduces tactile attention among people with low body esteem

ABSTRACT Death awareness leads to aversion from bodily processes such as breastfeeding and sex, especially among low body esteem individuals. Using a modality bias task, we examined whether primes of death reduced attention to bodily sensations. We subliminally primed 72 undergraduates with either the word death or failed and assessed their attention to tactile and visual stimuli as a function of their body esteem. Results indicated that death primes significantly reduced attention to tactile stimuli relative to visual stimuli in low body esteem individuals. Dissociation from the body, therefore, may be an unconscious terror management strategy utilized by people with low body esteem.
The Graphic Narrative Corpus (GNC): Design, Annotation, and Analysis for the Digital Humanities

Developed for an interdisciplinary DH project, the Graphic Narrative Corpus (GNC) is the first digital corpus of graphic novels, memoirs, and non-fiction written in English. It currently includes 160 book-length titles and will grow to around 250 graphic narratives by 2018. In contrast to collections such as Manga109, the eBDtheque, and the Iyyer corpus, the GNC was conceived to serve both the research needs of humanities and social science scholars and as a data set for computational analysis. The GNC has been constructed as a stratified monitor corpus that balances different historical periods, geographical origin, literary genres, and the gender and ethnic background of authors. Based on an extension of John Walsh's XML-dialect CBML and editor software developed for the corpus, annotation combines a focus on the first ten pages of each title and sample annotation of full-length books. XML-annotation currently includes visual objects, as well as word-image and character relations (panels, characters, balloons, captions, text, interaction types). In addition, we also provide eye-tracking data for annotated titles. Information about the corpus and sample visualizations can be found at: https://groups.uni-paderborn.de/graphic-literature/gncorpus/corpus.php.
Phylogenetic and Functional Diversity of Total (DNA) and Expressed (RNA) Bacterial Communities in Urban Green Infrastructure Bioswale Soils

ABSTRACT New York City (NYC) is pioneering green infrastructure with the use of bioswales and other engineered soil-based habitats to provide stormwater infiltration and other ecosystem functions. In addition to avoiding the environmental and financial costs of expanding traditional built infrastructure, green infrastructure is thought to generate cobenefits in the form of diverse ecological processes performed by its plant and microbial communities. Yet, although plant communities in these habitats are closely managed, we lack basic knowledge about how engineered ecosystems impact the distribution and functioning of soil bacteria. We sequenced amplicons of the 16S ribosomal subunit, as well as seven genes associated with functional pathways, generated from both total (DNA-based) and expressed (RNA) soil communities in the Bronx, NYC, NY, in order to test whether bioswale soils host characteristic bacterial communities with evidence for enriched microbial functioning, compared to nonengineered soils in park lawns and tree pits. Bioswales had distinct, phylogenetically diverse bacterial communities, including taxa associated with nutrient cycling and metabolism of hydrocarbons and other pollutants. Bioswale soils also had a significantly greater diversity of genes involved in several functional pathways, including carbon fixation (cbbL-R [cbbL gene, red-like subunit] and apsA), nitrogen cycling (noxZ and amoA), and contaminant degradation (bphA); conversely, no functional genes were significantly more abundant in nonengineered soils. These results provide preliminary evidence that urban land management can shape the diversity and activity of soil communities, with positive consequences for genetic resources underlying valuable ecological functions, including biogeochemical cycling and degradation of common urban pollutants. IMPORTANCE Management of urban soil biodiversity by favoring taxa associated with decontamination or other microbial metabolic processes is a powerful prospect, but it first requires an understanding of how engineered soil habitats shape patterns of microbial diversity. This research adds to our understanding of urban microbial biogeography by providing data on soil bacteria in bioswales, which had relatively diverse and compositionally distinct communities compared to park and tree pit soils. Bioswales also contained comparatively diverse pools of genes related to carbon sequestration, nitrogen cycling, and contaminant degradation, suggesting that engineered soils may serve as effective reservoirs of functional microbial biodiversity. We also examined both total (DNA-based) and expressed (RNA) communities, revealing that total bacterial communities (the exclusive targets in the vast majority of soil studies) were poor predictors of expressed community diversity, pointing to the value of quantifying RNA, especially when ecological functioning is considered.
Diverging white matter trajectories in children after traumatic brain injury

Objective: To examine longitudinal trajectories of white matter organization in pediatric moderate/severe traumatic brain injury (msTBI) over a 12-month period. Methods: We studied 21 children (16 M/5 F) with msTBI, assessed 2–5 months postinjury and again 13–19 months postinjury, as well as 20 well-matched healthy control children. We assessed corpus callosum function through interhemispheric transfer time (IHTT), measured using event-related potentials, and related this to diffusion-weighted MRI measures of white matter (WM) microstructure. At the first time point, half of the patients with TBI had significantly slower IHTT (TBI-slow-IHTT, n = 11) and half were in the normal range (TBI-normal-IHTT, n = 10). Results: The TBI-normal-IHTT group did not differ significantly from healthy controls, either in WM organization in the chronic phase or in the longitudinal trajectory of WM organization between the 2 evaluations. In contrast, the WM organization of the TBI-slow-IHTT group was significantly lower than in healthy controls across a large portion of the WM. Longitudinal analyses showed that the TBI-slow-IHTT group experienced a progressive decline between the 2 evaluations in WM organization throughout the brain. Conclusions: We present preliminary evidence suggesting a potential biomarker that identifies a subset of patients with impaired callosal organization in the first months postinjury who subsequently experience widespread continuing and progressive degeneration in the first year postinjury.
A Preliminary Analysis on the Effects of Propensity to Trust in Distributed Software Development

Establishing trust between developers working atdistant sites facilitates team collaboration in distributed software development. While previous research has focused on how to build and spread trust in absence of direct, face-to-face communication, it has overlooked the effects of the propensity to trust, i.e., the trait of personality representing the individual disposition to perceive the others as trustworthy. In this study, we present a preliminary, quantitative analysis on how the propensity to trust affects the success of collaborations in a distributed project, where thesuccess is represented by pull requests whose code changes and contributions are successfully merged in the project's repository.
Activity of muscle sympathetic neurons during normotensive pregnancy.

In pathological populations, elevated sympathetic activity is associated with increased activity of individual sympathetic neurons. We used custom action potential detection software to analyze multiunit sympathetic activity in 18 normotensive pregnant women (third trimester; 33 ± 5 wk) and 19 nonpregnant women at rest and a subset (10 and 13, respectively) during a cold pressor challenge. Although the number of action potentials per burst and number of active amplitude-based "clusters" were not different between groups, the total number of sympathetic action potentials per minute was higher in pregnant women at rest. Individual clusters were active predominately once per burst, suggesting they represent single neurons. Action potentials occurred in closer succession in normotensive pregnant (interspike interval 36 ± 10 ms) versus nonpregnant women (50 ± 27 ms; P < 0.001) at rest. Pregnant women had a lower total peripheral resistance (11.7 ± 3.0 mmHg·l-1·min) than nonpregnant women (15.1 ± 2.7 mmHg·l-1·min; P < 0.001), indicating a blunted neurovascular transduction. The cold pressor reduced the number of action potentials per burst in both groups due to shortening of the R-R interval in conjunction with increased burst frequency; total neural firing per minute was unchanged. Thus elevated sympathetic activity during normotensive pregnancy is specific to increased incidence of multiunit bursts. This is likely due to decreased central gating of burst output as opposed to generalized increases in central drive. These data also reinforce the concept that pregnancy appears to be the only healthy state of chronic sympathetic hyperactivity of which we are aware.
Handwriting Style Mixture Adaptation

In handwriting recognition, the test data usually come from multiple writers which are not shown in the training data. Therefore, adapting the base classifier towards the new style of each writer can significantly improve the generalization performance. Traditional writer adaptation methods usually assume that there is only one writer (one style) in the test data, and we call this situation as style-clear adaptation. However, a more common situation is that multiple handwriting styles exist in the test data, which is widely appeared in multi-font documents and handwriting data produced by the cooperation of multiple writers. We call the adaptation in this situation as style-mixture adaptation. To deal with this problem, in this paper, we propose a novel method called K-style mixture adaptation (K-SMA) with the assumption that there are totally K styles in the test data. Specifically, we first partition the test data into K groups (style clustering) according to their style consistency, which is measured by a newly designed style feature that can eliminate class (category) information and keep handwriting style information. After that, in each group, a style transfer mapping (STM) is used for writer adaptation. Since the initial style clustering may be not reliable, we repeat this process iteratively to improve the adaptation performance. The K-SMA model is fully unsupervised which do not require either the class label or the style index. Moreover, the K-SMA model can be effectively combined with the benchmark convolutional neural network (CNN) models. Experiments on the online Chinese handwriting database CASIA-OLHWDB demonstrate that K-SMA is an efficient and effective solution for style-mixture adaptation.
Floor Plan Generation and Auto Completion Based on Recurrent Neural Networks

During early design phases, the architect's task is to develop a floor plan layout from a high level description. This process is usually conducted manually nowadays in an iterative manner. In order to assist the architect with repetitive tasks during the individual design steps, we trained a recurrent neural network to mimic the architect's behavior. Our approach is based on sequences that recreate the user's behavior and that we generated from simple floor plans. By utilizing a dedicated inferencing mechanism, we are able to implement the generation of different design steps and tasks using a single LSTM model. We compare two different types of sequencing approaches by calculating their errors on a test set for a selected design step and evaluating the results qualitatively. While the current performance still needs to be improved for productive use, our dedicated inference mechanism shows a functional behavior.
[POSTER] Usability Analysis of an Off-the-Shelf Hand Posture Estimation Sensor for Freehand Physical Interaction in Egocentric Mixed Reality

This paper explores freehand physical interaction in egocentric Mixed Reality by performing a usability study on the use of hand posture estimation sensors. We report on precision, interactivity and usability metrics in a task-based user study, exploring the importance of additional visual cues when interacting. A total of 750 interactions were recorded from 30 participants performing 5 different interaction tasks (Move, Rotate: Pitch (Y axis) and Yaw (Z axis), Uniform scale: enlarge and shrink). Additional visual cues resulted in an average shorter time to interact, however, no consistent statistical differences were found in between groups for performance and precision results. The group with additional visual cues gave the system and average System Usability Scale (SUS) score of 72.33 (SD 16.24) while the other scored a 68.0 (SD 18.68). Overall, additional visual cues made the system being perceived as more usable, despite the fact that the use of these two different conditions had limited effect on precision and interactivity metrics.
Technical Debt and the Software Project Characteristics. A Repository-Based Exploratory Analysis

Technical debt is a deviation of any software project's aspect related to a quality standard previously established. In general, this deviation is created to accomplish a short-term objective, but may cause some difficulties to perform further software developments and evolutions. Even though this happens in many software projects today, there is no common understanding of which factors and conditions can contribute to the accumulation of software technical debts. To account for the aspects of software projects (like size, time, the number of commit to correct defects and the number of collaborators) that may contribute to software technical debts, we collected data from fifty projects in a public software repository to make a statistical analysis on the relation of some aspects with the software technical debts. This paper presents the results of this study from which we realized that the project's size, the number of collaborators and speed of development are the most related aspects with the number of software technical debts. On the other hand, the number of commits created to correct the defects did not show to be connected to the amount of technical debt found in the analyzed projects.
Distances and Isomorphism between Networks and the Stability of Network Invariants

We develop the theoretical foundations of a network distance that has recently been applied to various subfields of topological data analysis, namely persistent homology and hierarchical clustering. While this network distance has previously appeared in the context of finite networks, we extend the setting to that of compact networks. The main challenge in this new setting is the lack of an easy notion of sampling from compact networks; we solve this problem in the process of obtaining our results. The generality of our setting means that we automatically establish results for exotic objects such as directed metric spaces and Finsler manifolds. We identify readily computable network invariants and establish their quantitative stability under this network distance. We also discuss the computational complexity involved in precisely computing this distance, and develop easily-computable lower bounds by using the identified invariants. By constructing a wide range of explicit examples, we show that these lower bounds are effective in distinguishing between networks. Finally, we provide a simple algorithm that computes a lower bound on the distance between two networks in polynomial time and illustrate our metric and invariant constructions on a database of random networks and a database of simulated hippocampal networks.
IHB: A scalable and efficient scheme to identify homologous binaries in IoT firmwares

Due to the extensive code reuse and the widespread use of third-party SDKs, homologous binaries are widely found in IoT firmwares. Once a vulnerability is found in one firmware, other firmwares sharing the similar piece of codes are at high risk. Thus, homologous binary search is of great significance to IoT firmware security analysis. However, there are still no scalable and efficient homologous binary search methods for IoT firmwares. The time complexity of the state-of-the-art method is O(N), and it is not scalable for large-scale IoT firmwares. In this paper, we design, implement, and evaluate a scalable and efficient homologous binary search scheme (termed as IHB) for IoT firmwares with time complexity O(1). The main idea of our methodology is to leverage readable strings in binaries to calculate the similarities between different IoT firmwares. Furthermore, we employ a string filter and the string-based MinHash to achieve both accuracy and efficiency. We test both our scheme and the state-of-the-art methods on a real dataset containing 1024 binary files. The results show that our method is three orders of magnitude more efficient than the existing methods. Meanwhile, our method has a higher true positive rate (92.88%) and a lower false positive rate (2.83%). In the interest of open science, we also make our tools and datasets publicly available to seed future improvements.
A Convenient Framework for Health and Medical Decision Making Processes

Several approaches may be proposed for decision making. People usually base their judgments on common sense and the vast amount of knowledge they have accumulated through experience. One might also proceed by analogy or look for a more general problem with a known solution and then apply this general solution to the particular case to be solved, or one might use the language of a formal decision-making method and then use the algorithms proposed by the model to solve the problem. The early Seventies was a period of intense research to develop decision support models to help clinicians making decisions in view of the uncertainty with which they are frequently confronted. Many authors turned towards decision analysis methods proposing an explicit framework and logic to create a model ll'bese decision-making situations [ 1]. 'tiany outstanding articles began appearing on the subject at that time. These articles opened the way to research and thinking on how to fonnatize diagnostic and therapeutic l'easoning. The article by Pauker and kassirer [2], published in 1975 in the ~ew England Journal of Medicine, Is one of these. Rereading it now, 25 years later, along with some of the other important Commentary