Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring Instability of Mobility Management in Cellular Networks

Communication in cellular networks is based on serving cells that provide the basic network service. In the real world, serving cells overlap which means the number of serving cells covering one position is usually more than one. Recently, the instability of mobility management in cellular networks has been studied to monitor and analyze the handoff process in mobile devices. However, the handoff process is actually produced by base stations instead of mobile devices. Hence, it is of great importance to measure the handoff process of mobility management from the base station side. In this article, we present a series of experiments performed using the data obtained by mobile network operators. The contributions of this study are three-fold. We reproduce a handoff process and handoff loop from both the mobile device level and the base station level, and confirm the existence of a handoff loop by measurements from the base station side. Through large-range measurements, we discover that only a small part of serving cells is involved in the handoff process, and in most cases, the number of candidate serving cells is much smaller than the number of cells that cover some position; namely, when a handoff loop occurs, the number of candidate serving cells is quite small, which is in contrast to our assumption. We confirm that the handoff loop often occurs in indoor conditions or when the mobile device has frequent communication with the base station. Finally, we present several comprehensive facts about the handoff process and handoff loop and provide suggestions that can be used to increase the quality of service of cellular networks.
Efficient Classification of Digital Images based on Pattern-features

Selecting a suitable set of features, which is able to represent the data to be processed while retaining the relevant distinctive information, is one of the most important issues in classification problems. While different features can be extracted from the raw data, only few of them are actually relevant and effective for the classification process. Since relevant features are often unknown a priori, many candidate features are usually introduced. This degrades both the speed and the predictive accuracy of the classifier due to the presence of redundancy in the feature candidate set. We propose a class of features for image classification based on the notion of irredundant bidimensional pair-patterns, and we present an algorithm for image classification based on their extraction. The devised technique scales well on parallel multi-core architectures, as witnessed by the experimental results that have been obtained exploiting a benchmark image dataset.
Collective Efficacy: Development and Validation of a Measurement Scale for Use in Public Health and Development Programmes

Impact evaluations of water, sanitation, and hygiene interventions have demonstrated lower than expected health gains, in some cases due to low uptake and sustained adoption of interventions at a community level. These findings represent common challenges for public health and development programmes relying on collective action. One possible explanation may be low collective efficacy (CE)—perceptions regarding a group’s ability to execute actions related to a common goal. The purpose of this study was to develop and validate a metric to assess factors related to CE. We conducted this research within a cluster-randomised sanitation and hygiene trial in Amhara, Ethiopia. Exploratory and confirmatory factor analyses were carried out to examine underlying structures of CE for men and women in rural Ethiopia. We produced three CE scales: one each for men and women that allow for examinations of gender-specific mechanisms through which CE operates, and one 26-item CE scale that can be used across genders. All scales demonstrated high construct validity. CE factor scores were significantly higher for men than women, even among household-level male-female dyads. These CE scales will allow implementers to better design and target community-level interventions, and examine the role of CE in the effectiveness of community-based programming.
Visual Exploration in Autism Spectrum Disorder: Exploring Age Differences and Dynamic Features Using Recurrence Quantification Analysis

Eye‐tracking studies have demonstrated that individuals with autism spectrum disorder sometimes show differences in attention and gaze patterns. This includes preference for certain nonsocial objects, heightened attention to detail, and more difficulty with attention shifting and disengagement, which may be associated with restricted and repetitive behaviors. This study utilized a visual exploration task and replicates findings of reduced number of objects explored and increased fixation duration on high autism interest objects in a large sample of individuals with autism spectrum disorder (n = 129, age 6–54 years) in comparison with a typically developing group. These findings correlated with parent‐reported repetitive behaviors. Additionally, we applied recurrent quantification analysis to enable identification of new eye‐tracking features, which accounted for temporal and spatial differences in viewing patterns. These new features were found to discriminate between autism spectrum disorder and typically developing groups and were correlated with parent‐reported repetitive behaviors. Original and novel eye‐tracking features identified by recurrent quantification analysis differed in their relationships to reported behaviors and were dependent on age. Trial Registration: NCT02299700. Autism Research 2018, 11: 1554–1566. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.
A Distinct Subset of Fibroblastic Stromal Cells Constitutes the Cortex-Medulla Boundary Subcompartment of the Lymph Node

The spatiotemporal regulation of immune responses in the lymph node (LN) depends on its sophisticated tissue architecture, consisting of several subcompartments supported by distinct fibroblastic stromal cells (FSCs). However, the intricate details of stromal structures and associated FSC subsets are not fully understood. Using several gene reporter mice, we sought to discover unrecognized stromal structures and FSCs in the LN. The four previously identified FSC subsets in the cortex are clearly distinguished by the expression pattern of reporters including PDGFRβ, CCL21-ser, and CXCL12. Herein, we identified a unique FSC subset expressing both CCL21-ser and CXCL12 in the deep cortex periphery (DCP) that is characterized by preferential B cell localization. This subset was clearly different from CXCL12highLepRhigh FSCs in the medullary cord, which harbors plasma cells. B cell localization in the DCP was controlled chiefly by CCL21-ser and, to a lesser extent, CXCL12. Moreover, the optimal development of the DCP as well as medulla requires B cells. Together, our findings suggest the presence of a unique microenvironment in the cortex-medulla boundary and offer an advanced view of the multi-layered stromal framework constructed by distinct FSC subsets in the LN.
TZC: Efficient Inter-Process Communication for Robotics Middleware with Partial Serialization

Inter-process communication (IPC) is one of the core functions of modern robotics middleware. We propose an efficient IPC technique called TZC (Towards Zero-Copy). As a core component of TZC, we design a novel algorithm called partial serialization. Our formulation can generate messages that can be divided into two parts. During message transmission, one part is transmitted through a socket and the other part uses shared memory. The part within shared memory is never copied or serialized during its lifetime. We have integrated TZC with ROS and ROS2 and find that TZC can be easily combined with current open-source platforms. By using TZC, the overhead of IPC remains constant when the message size grows. In particular, when the message size is 4MB (less than the size of a full HD image), TZC can reduce the overhead of ROS IPC from tens of milliseconds to hundreds of microseconds and can reduce the overhead of ROS2 IPC from hundreds of milliseconds to less than 1 millisecond. We also demonstrate the benefits of TZC by integrating it with TurtleBot2 to be used in autonomous driving scenarios. We show that by using TZC, the braking distance can be 16% shorter than with ROS.
Total Variation and Rank-1 Constraint RPCA for Background Subtraction

Background subtraction (BS) in video sequences is a main research field, and the aim is to separate moving objects in the foreground from stationary background. Using the framework of schemes-based robust principal component analysis (RPCA), we propose a novel BS method employing the more refined prior representations for the static and dynamic components of the video sequences. Specifically, the rank-1 constraint is exploited to describe the strong low-rank property of background layer (temporal correlation of static component), and 3-D total variation measure and $L_{1}$ norm are used to model the spatial-temporal smoothness of foreground layer and sparseness of noise (dynamic component). This method introduces rank-1, smooth, and sparse properties into the RPCA framework for BS task, and it is dubbed TR1-RPCA. In addition, an efficient algorithm based on the alternating direction method of multipliers is designed to solve the proposed BS model. Extensive experiments on simulated and real videos demonstrate the superiority of the proposed method.
Elderly acute lymphoblastic leukemia: a Mayo Clinic study of 124 patients

Abstract Poor outcomes in elderly acute lymphoblastic leukemia (ALL) are well recognized, but the contributors are ill-defined. We characterized 124 patients ≥60 years old at our institution. The majority (n = 102, 82%) were treated with intensive chemotherapy. Of these, 8/102 (8%) died within the first 100 days; 92/102 (90%) achieved complete remission (CR/CRi). Only 31/124 (25%) patients underwent allogeneic hematopoietic stem cell transplantation. The median overall survival (OS) for the entire cohort was 19.8 months. In a multivariate analysis, ECOG performance status ≥2, high white blood cell count, and high lactate dehydrogenase (at time of diagnosis) negatively influenced OS (p<.01). In a subgroup analysis of the intensive treatment group, BCR-ABL1+ patients had markedly better OS (hazard ratio 0.3, 95% CI 0.1–0.7; p<.01). In summary, despite few early deaths and a high CR/CRi rate, elderly ALL continues to have a poor prognosis, underscoring the need for more effective therapies.
REPICA: Rewriting Position Independent Code of ARM

Binary rewriting techniques are widely used in program vulnerability fixing, obfuscation, security-oriented transforming, and otherpurposes, such as binary profiling and optimization. Over the past decade, most binary instrumentation techniques have been studied on <inline-formula> <tex-math notation="LaTeX">$\times 86$ </tex-math></inline-formula> architecture, specifically focusing onthe challenges of instrumenting non-PIC. In contrast, ARM architecture has received little attention, and statically instrumenting PIC has not been studied in depth. In ARM, owing to its fixed-length instructions, addresses are frequently computed via multiple stages, making it difficult to handle all relative addresses, especially the relative address of <italic>base-plus-offset</italic> and <italic>base-plus-index addressing</italic>. In this paper, we present <monospace>REPICA</monospace>, a static binary instrumentation technique which can rewrite ARM binaries compiled in a position-independent fashion. <monospace>REPICA</monospace> can instrument at anywhere without symbolic information. With the aim of identifying andprocessing relative-addresses accurately, we designed a value-set analysis specialized for PIC of which the domain is in symbolic format. We also identified a new challenge for situations all relative addresses cannot be corrected in an optimized way and solvedthis problem efficiently by the stepwise correction of each relative address. We implemented a prototype of <monospace>REPICA</monospace> and experimented with approximately 1200 COTS binaries and SPECint2006 benchmarks. The experiment showed that all binaries rewritten by <monospace>REPICA</monospace> maintain relative addresses correctly with negligible execution and space overhead. Finally, we exhibit the effectiveness of <monospace>REPICA</monospace> by using it to implement a shadow stack.
Simultaneous Face Detection and Pose Estimation Using Convolutional Neural Network Cascade

Recent studies show that convolutional neural networks (CNNs) has made a series of breakthroughs in the two tasks of face detection and pose estimation, respectively. There are two CNN frameworks for solving these two integrated tasks simultaneously. One is to use face detection network to detect faces firstly, and then use pose estimation network to estimate each face’s pose; the other is to use region proposal algorithm to generate many candidate regions that may contain faces, and then use a single deep multi-task CNN to process these regions for simultaneous face detection and pose estimation. The former’s problem is pose estimation’s performance is affected by face detection network because two networks are separate. The latter generates lots of candidate regions, which will bring huge computation cost to CNN and can’t achieve real-time. To solve the above existing problems, we propose a multi-task CNN cascade framework that integrates these two tasks. We show that multi-task learning of face detection and head pose estimation helps to extract more representative features. We exploit CNN feature fusion strategy to further improve head pose estimation’s performance. We evaluate face detection on FDDB benchmark, and evaluate pose estimation on AFW benchmark. Our method achieves comparative result compared with state-of-the-art in these two tasks and can achieve real-time performance.
Short Telomere Length as a Biomarker Risk of Lung Cancer Development Induced by High Radon Levels: A Pilot Study

Long-term exposure to radon has been determined to be the second leading cause of lung cancer after tobacco smoking. However, an in-depth study of this topic has not been explicitly carried out in Chiang Mai (Thailand). This paper presents the results of an indoor radon level measurement campaign in dwellings of Chiang Mai using total of 110 detectors (CR-39) during one year. The results show that the average radon levels varied from 35 to 219 Bq/m3, with an overall average of 57 Bq/m3. The finding also shows that the average value is higher than the global average value of 39 Bq/m3. In addition, to examine the cause of lung cancer development among people with risk of chronic exposure to radon during their lifetime, 35 non-smoker lung cancer patients and 33 healthy nonsmokers were analyzed for telomere length. As expected, telomere length was significantly shorter in lung cancer patients than in healthy nonsmokers. Among healthy nonsmokers, the telomere length was significantly shorter in a high radon group than in an unaffected low radon group. To the best of our knowledge, our research provides the first attempt in describing the shortened telomeres in areas with high levels of environmental radon that might be related to lung cancer development.
Rif1 inhibits replication fork progression and controls DNA copy number in Drosophila

Control of DNA copy number is essential to maintain genome stability and ensure proper cell and tissue function. In Drosophila polyploid cells, the SNF2-domain-containing SUUR protein inhibits replication fork progression within specific regions of the genome to promote DNA underreplication. While dissecting the function of SUUR’s SNF2 domain, we identified a physical interaction between SUUR and Rif1. Rif1 has many roles in DNA metabolism and regulates the replication timing program. We demonstrate that repression of DNA replication is dependent on Rif1. Rif1 localizes to active replication forks in an SUUR-dependent manner and directly regulates replication fork progression. Importantly, SUUR associates with replication forks in the absence of Rif1, indicating that Rif1 acts downstream of SUUR to inhibit fork progression. Our findings uncover an unrecognized function of the Rif1 protein as a regulator of replication fork progression.
Bidirectional intraflagellar transport is restricted to two sets of microtubule doublets in the trypanosome flagellum

Intraflagellar transport (IFT) is the rapid bidirectional movement of large protein complexes driven by kinesin and dynein motors along microtubule doublets of cilia and flagella. Here we used a combination of high-resolution electron and light microscopy to investigate how and where these IFT trains move within the flagellum of the protist Trypanosoma brucei. Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) analysis of trypanosomes showed that trains are found almost exclusively along two sets of doublets (3-4 and 7-8) and distribute in two categories according to their length. High-resolution live imaging of cells expressing mNeonGreen::IFT81 or GFP::IFT52 revealed for the first time IFT trafficking on two parallel lines within the flagellum. Anterograde and retrograde IFT occur on each of these lines. At the distal end, a large individual anterograde IFT train is converted in several smaller retrograde trains in the space of 3-4 seconds while remaining on the same side of the axoneme.
Translation of morphological and functional musculoskeletal imaging

In an effort to develop quantitative biomarkers for degenerative joint disease and fill the void that exists for diagnosing, monitoring, and assessing the extent of whole joint degeneration, the past decade has been marked by a greatly increased role of noninvasive imaging. This coupled with recent advances in image processing and deep learning opens new possibilities for promising quantitative techniques. The clinical translation of quantitative imaging was previously hampered by tedious non‐scalable and subjective image analysis. Osteoarthritis (OA) diagnosis using X‐rays can be automated by the use of deep learning models and pilot studies showed feasibility of using similar techniques to reliably segment multiple musculoskeletal tissues and detect and stage the severity of morphological abnormalities in magnetic resonance imaging (MRI). Automation and more advanced feature extraction techniques have applications on larger more heterogeneous samples. Analyses based on voxel based relaxometry have shown local patterns in relaxation time elevations and local correlations with outcome variables. Bone cartilage interactions are also enhanced by the analysis of three‐dimensional bone morphology and the potential for the assessment of metabolic activity with simultaneous Positron Emission Tomography (PET)/MR systems. Novel techniques in image processing and deep learning are augmenting imaging to be a source of quantitative and reliable data and new multidimensional analytics allow us to exploit the interactions of data from various sources. In this review, we aim to summarize recent advances in quantitative imaging, the application of image processing and deep learning techniques to study knee and hip OA. ©2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res XX:XX–XX, 2018.
Linked Data in Education: A Survey and a Synthesis of Actual Research and Future Challenges

Linked Data principles and technologies are being investigated in various areas. In the Educational context, many studies are using Linked Data trying to solve problems of interoperability of educational data and resources, enriching educational content, and personalizing and recommending educational content and practices. This article presents a systematic mapping of proposals which have been adopting Linked Data to support education, and, based on analysis of these proposals, we discuss the tools, vocabularies, and datasets being used, providing a research landscape of the area. We also present challenges and trends which can foster future research in this area.
Cold Physical Plasma Selectively Elicits Apoptosis in Murine Pancreatic Cancer Cells In Vitro and In Ovo

Background/Aim: Poor prognosis of pancreatic cancer has remained almost unchanged in recent years. Cold physical plasma was suggested as an innovative anticancer strategy, but its selective killing activity of malignant over non-malignant cells has only partially been explored. The present study aimed at exploring the effect of cold physical plasma on cellular viability. Materials and Methods: Induction of cell death and apoptosis by cold physical plasma was investigated in murine PDA6606 pancreatic cancer cells and primary murine fibroblasts in vitro (2D and 3D cultures) and in ovo. Results: Plasma increased apoptosis in PDA6606 to a significantly higher extent compared to fibroblasts. Antioxidants abrogated these effects, suggesting a prime role of reactive oxygen species in plasma-induced apoptosis. Plasma increased apoptosis of 3D PDA6606 multicellular spheres grown in vitro and in ovo, to significantly higher rates compared to that of fibroblasts, with minimum in ovo inflammation or necrosis observed by hematoxylin and eosin staining (H&E). Conclusion: These data support the future intra-operative application of cold physical plasma for the treatment of microscopic residual tumor tissue after surgical resection.
Excess Mortality and Causes Associated with Chikungunya, Puerto Rico, 2014–2015

During 2014–2015, a total of 31 deaths were associated with the first chikungunya epidemic in Puerto Rico. We analyzed excess mortality from various causes for the same months during the previous 4 years and detected 1,310 deaths possibly attributable to chikungunya. Our findings raise important questions about increased mortality rates associated with chikungunya.
Consistency and validity of interdisciplinarity measures

Abstract Measuring interdisciplinarity is a pertinent but challenging issue in quantitative studies of science. There seems to be a consensus in the literature that the concept of interdisciplinarity is multifaceted and ambiguous. Unsurprisingly, various different measures of interdisciplinarity have been proposed. However, few studies have thoroughly examined the validity and relations between these measures. In this study, we present a systematic review of these interdisciplinarity measures and explore their inherent relations. We examine these measures in relation to the Web of Science journal subject categories. Our results corroborate recent claims that the current measurements of interdisciplinarity in science studies are both confusing and unsatisfying. We find surprisingly deviant results when comparing measures that supposedly should capture similar features or dimensions of the concept of interdisciplinarity. We therefore argue that the current measurements of interdisciplinarity should be interpreted with much caution in science and evaluation studies, or in relation to science policies. We also question the validity of current measures and argue that we do not need more of the same, but rather something different in order to be able to measure the multidimensional and complex construct of interdisciplinarity.