Miracle-dz/UniFAR-FTUs huggingface dataset:
The pragmatic classification of upper extremity motion in 2 neurological patients: a primer 3

11 Recent advances in wearable sensor technology and machine learning (ML) have allowed for the 12 seamless and objective study of human motion in clinical applications, including Parkinson’s 13 disease and stroke. Using ML to identify salient patterns in sensor data has the potential for 14 widespread application in neurological disorders, so understanding how to develop this approach 15 for one’s area of inquiry is vital. We previously proposed an approach that combined wearable 16 inertial measurement units (IMUs) and ML to classify motions made by stroke patients. However, 17 our approach had computational and practical limitations. We address these limitations here in the 18 form of a primer, presenting how to optimize a sensor-ML approach for clinical implementation. 19 First, we demonstrate how to identify the ML algorithm that maximizes classification performance 20 and pragmatic implementation. Second, we demonstrate how to identify the motion capture 21 approach that maximizes classification performance but reduces cost. We used previously 22 collected motion data from chronic stroke patients wearing off-the-shelf IMUs during a 23 rehabilitation-like activity. To identify the optimal ML algorithm, we compared the classification 24 performance, computational complexity, and tuning requirements of four off-the-shelf algorithms. 25 To identify the optimal motion capture approach, we compared the classification performance of 26 various sensor configurations (number and location on the body) and sensor type (IMUs versus 27 accelerometers). Of the algorithms tested, linear discriminant analysis had the highest 28 classification performance, low computational complexity, and modest tuning requirements. Of 29 the sensor configurations tested, seven sensors on the paretic arm and trunk led to the highest 30 classification performance, and IMUs outperformed accelerometers. Overall, we present a refined 31 sensor-ML approach that maximizes both classification performance and pragmatic 32 implementation. In addition, with this primer, we showcase important considerations for 33 appraising off-the-shelf algorithms and sensors for quantitative motion assessment.
Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000

In the last decade, modern data analytics technologies have enabled the creation of software analytics tools offering real-time visualization of various aspects related to software development and usage. These tools seem to be particularly attractive for companies doing agile software development. However, the information provided by the available tools is neither aggregated nor connected to higher quality goals. At the same time, assessing and improving software quality has also been a key target for the software engineering community, yielding several proposals for standards and software quality models. Integrating such quality models into software analytics tools could close the gap by providing the connection to higher quality goals. This study aims at understanding whether the integration of quality models into software analytics tools provides understandable, reliable, useful, and relevant information at the right level of detail about the quality of a process or product, and whether practitioners intend to use it. Over the course of more than one year, the four companies involved in this case study deployed such a tool to assess and improve software quality in several projects. We used standardized measurement instruments to elicit the perception of 22 practitioners regarding their use of the tool. We complemented the findings with debriefing sessions held at the companies. In addition, we discussed challenges and lessons learned with four practitioners leading the use of the tool. Quantitative and qualitative analyses provided positive results; i.e., the practitioners’ perception with regard to the tool’s understandability, reliability, usefulness, and relevance was positive. Individual statements support the statistical findings and constructive feedback can be used for future improvements. We conclude that potential for future adoption of quality models within software analytics tools definitely exists and encourage other practitioners to use the presented seven challenges and seven lessons learned and adopt them in their companies. INDEX TERMS agile software development, case study, quality model, software analytics, software analytics tool, software quality Silverio Martínez-Fernández et al.: Continuously assessing and improving software quality with software analytics tools: a case study n VOLUME XX, 2019
safety of cetirizine ophthalmic solution 0.24% for the treatment of allergic conjunctivitis in adult and pediatric subjects

Purpose: The studies reported here aimed to assess the safety and tolerability of cetirizine ophthalmic solution 0.24%, a new topical ophthalmic medication approved by the US Food and Drug Administration for the treatment of ocular itching associated with allergic conjunctivitis. Patients and methods: Three clinical studies evaluated cetirizine ophthalmic solution 0.24% administration: a Phase I prospective, single-center, open-label, pharmacokinetic (PK) study (N = 11) evaluating single-dose administration and twice-daily (BID) administration for 1 week in healthy adults, and two Phase III, multi-center, randomized, double-masked, vehicle-controlled, parallel-group studies evaluating the safety and tolerability in adult and pediatric populations (2–18 years of age) for up to 6 consecutive weeks. The first safety and tolerability study evaluated cetirizine BID (study 1, N = 512), while the second study examined cetirizine three times daily (TID) (study 2, N = 516). Each study assessed best corrected visual acuity, slit-lamp biomicroscopy, IOP, dilated ophthalmoscopy, treatment-emergent adverse events, vital signs, urine pregnancy test, and physical examination (general health, head, eyes, ears, nose, and throat). The PK study also measured hematology, blood chemistry, and urinalysis, while the two Phase III studies additionally assessed corneal endothelial cell counts (ECC) and ECC density in a subset of subjects (via specular microscopy), and drug administration tolerability. Results: Bilateral administration of cetirizine ophthalmic solution 0.24% resulted in low systemic exposure in the PK study and was associated with a low incidence of mild adverse events. There were no drug-related severe or serious adverse events. The tolerability scores between the active and vehicle groups were comparable, demonstrating high comfort in the administration of cetirizine ophthalmic solution 0.24%. Conclusion: Cetirizine ophthalmic solution 0.24% dosed BID or TID demonstrated an acceptable safety profile and was well-tolerated when administered to subjects aged $ 2 years.
ECG Pulse Body Humidity Body Temperature ... Environment Context : Temperature Humidity Condition Time Context : Daily Time Week Day Location Context : Passed Distance Altitude

Traditional clustering algorithms merely considered static data. Today’s various applications and research issues in big data mining have however to deal with continuous, possibly infinite streams of data, arriving at high velocity. Web traffic data, surveillance data, sensor measurements and stock trading are only some examples of these daily-increasing applications. Since the growth of data volumes is accompanied by a similar raise in their dimensionalities, clusters cannot be expected to completely appear when considering all attributes together. Subspace clustering is a general approach that solved that issue by automatically finding the hidden clusters within different subsets of the attributes rather than considering all attributes together. In this article, novel methods for an efficient subspace clustering of high-dimensional big data streams are presented. Approaches that efficiently combine the anytime clustering concept with the stream subspace clustering paradigm are discussed. Additionally, efficient and adaptive density-based clustering algorithms are presented for high-dimensional data streams. Novel open-source assessment framework and evaluation measures are additionally presented for subspace stream clustering.
Genetic variation in the cellular response of Daphnia magna (Crustacea: Cladocera) to its bacterial parasite

Linking measures of immune function with infection, and ultimately, host and parasite fitness is a major goal in the field of ecological immunology. In this study, we tested for the presence and timing of a cellular immune response in the crustacean Daphnia magna following exposure to its sterilizing endoparasite Pasteuria ramosa. We found that D. magna possesses two cell types circulating in the haemolymph: a spherical one, which we call a granulocyte and an irregular-shaped amoeboid cell first described by Metchnikoff over 125 years ago. Daphnia magna mounts a strong cellular response (of the amoeboid cells) just a few hours after parasite exposure. We further tested for, and found, considerable genetic variation for the magnitude of this cellular response. These data fostered a heuristic model of resistance in this naturally coevolving host–parasite interaction. Specifically, the strongest cellular responses were found in the most susceptible hosts, indicating resistance is not always borne from a response that destroys invading parasites, but rather stems from mechanisms that prevent their initial entry. Thus, D. magna may have a two-stage defence—a genetically determined barrier to parasite establishment and a cellular response once establishment has begun.
Quaternary Faults and Folds (QFF)

Alaska is the most seismically active region of the United States. However, little information exists on the location, style of deformation, and slip rates of Quaternary faults. This interactive map displays locations and relative activity of Alaska's faults and folds. The map offers zoom and scroll options, and multiple base map layers. Click individual fault and fold traces to view basic fault parameters: name, age, slip rate, slip sense, dip direction, mapping certainty, and mapped scale. This resource is intended to provide simple and quick means of visualizing structure locations and characteristics. Users must recognize mapping certainty and data accuracy limitations when zooming in farther than the stated mapped scale for a given feature and treat resulting visual representations with appropriate caveats. The structures displayed are replicated from DGGS publications MP 141 (Quaternary) and MP 150 (pre-Quaternary).
Circulating Tumor Cells as a Biomarker to Assist Molecular Diagnosis for Early Stage Non-Small Cell Lung Cancer

Background and Objective: Compared with tissue biopsy, liquid biopsy is the most preferable non-invasive promising method in personalized medicine, although it has many limitations in isolating circulating tumor cells (CTC). Lung cancer associated mortality is drastically increased due to a shortfall of early-stage detection, which remains a challenge. Herein, we aimed to detect lung cancer at an early-stage using CellCollector device. Methods: 39,627 volunteers underwent low-dose computed tomography; 2508 cases with pulmonary nodules and 7080 with no pulmonary nodules were chosen. After follow-up, 24 patients were diagnosed with early-stage non-small cell lung cancer (NSCLC), and subjected to CTC detection using CellCollector, along with 72 healthy volunteers. Immuno ﬂ uorescence staining for EpCAM/CKs and CD45 were performed for CTC validation. Results: Fifteen out of twenty-four (stage I, n = 18; stage II, n = 6) early-stage lung cancer patients were found to be CTC-positive, whereas no CTC was found in the control group. Genetic mutation of TP53, ERBB2, PDGFRA, CFS1R and FGFR1 in the CTC revealed 71.6% of the mutation sites similar to the tumor tissues of 13 patients. Molecular characterization revealed higher expression of protein PD-LI in CTC (40%) as compared to tumor tissue (26.7%). Moreover, CTC clusters were detected in 40% of patients. Conclusion: CTC detection using the CellCollector in early-stage NSCLC had a relative high capture rate. Moreover, CTC analysis is a prospective setting for molecular diagnostic in cases when tumor tissue biopsy is not desirable.
Tissue-Specific Differentiation of Colonic Macrophages Requires TGF Receptor Mediated Signalling

Intestinal macrophages (m / ) form one of the largest populations of m / in the body and are vital for the maintenance of gut homeostasis. They have several unique properties and are derived from local differentiation of classical Ly6C hi monocytes, but the factors driving this tissue-specific process are not understood. Here we have used global transcriptomic analysis to identify a unique homeostatic signature of mature colonic m / that is acquired as they differentiate in the mucosa. By comparing the analogous monocyte differentiation process found in the dermis, we identify TGF b as an indispensable part of monocyte differentiation in the intestine and show that it enables m / to adapt preciselytotherequirementsoftheirenvironment.Importantly,TGF b Rsignalingon m / hasacrucialroleinregulatingthe accumulation of monocytes in the mucosa, via mechanisms that are distinct from those used by IL10.
The incidence of Melanocytic Naevi (moles) in young children

Background: The number of melanocytic naevi (moles) a person develops is an important phenotypic risk factor/marker for cutaneous melanoma. Studies of migrants to Australia suggest that avoidance of strong sun exposure in childhood decreases adult risk of melanoma. An understanding of the relation of sun exposure in early childhood to the occurrence of naevi may increase our understanding of melanocytic neoplasia. Methods: The development of melanocytic naevi was assessed longitudinally in a cohort of 115 Caucasian neonates who were born in Townsville, Queensland, Australia (latitude 19°16'S) in the Spring of 1994. These children were examined for melanocytic naevi at birth, and at 6, 12, 18, 24, and 36 months of age. An experienced observer used a standard international protocol. Melanocytic naevi of all sizes were recorded by size and body site. Sun exposure was assessed by regular parental questionnaires. Findings: The proportion of children with melanocytic naevi increased rapidly in the first 2 years of life from 2.3% at birth to 10.8% at 6 months, 65.2% at 12 months, 92% at 18 months and 100% at 24 months. The median rate of acquisition of incident melanocytic naevi in these children was 1 [IQR 0, 2] in the first year, 5 [IQR 3, 8] in the second year and 6 [IQR 4, 10] in the third year of life. Children who began acquiring melanocytic naevi before 12 months of age had significantly more naevi at 36 months of age than children who developed their first naevus during their second year of life (median number of additional naevi acquired between 12 and 36 months was 13 versus 8, respectively; WRS p=0.0082). Children who began acquiring melanocytic naevi in the first year of life also played outside in the sun more often than children who began developing naevi later on (χ2 1 df: p = 0.048). Melanocytic naevi were most concentrated on the upper limbs, followed by the head and neck of these children across all ages. In contrast, low relative densities of melanocytic naevi were found on the sun-protected surface of the trunk and the relative excess concentration of melanocytic naevi found on the lower limbs of 12 month-old children diminished with age. Interpretation: These results provide further evidence for the role of sun exposure in the development of melanocytic naevi. It is possible that the age of onset of melanocytic naevus development may influence the risk of melanoma.
Multiple change-points detection in high dimension

Change-point detection is an integral component of statistical modeling and estimation. For high-dimensional data, classical methods based on the Mahalanobis distance are typically inapplicable. We propose a novel testing statistic by combining a modified Euclidean distance and an extreme statistic, and its null distribution is asymptotically normal. The new method naturally strikes a balance between the detection abilities for both dense and sparse changes, which gives itself an edge to potentially outperform existing methods. Furthermore, the number of change-points is determined by a new Schwarz’s information criterion together with a pre-screening procedure, and the locations of the change-points can be estimated via the dynamic programming algorithm in conjunction with the intrinsic order structure of the objective function. Under some mild conditions, we show that the new method provides consistent estimation with an almost optimal rate. Simulation studies show that the proposed method has satisfactory performance of identifying multiple change-points in terms of power and estimation accuracy, and two real data examples are used for illustration.
Chipless and Conventional Radio Frequency Identification : Systems for Ubiquitous Tagging

Object analysis using visual sensors is one of the most important and challenging issues in computer vision research due principally to difficulties in object representation, segmentation, and recognition within a general framework. This has motivated researchers to investigate exploiting the potential identification capability of RFID (radio frequency identification) technology for object analysis. RFID however, has a number of fundamental limitations including a short sensing range, missing tag detection, not working for all objects, and some items being just too small to be tagged. This has meant applying RFID alone has not been entirely effective in computer vision applications. To address these restrictions, object analysis approaches based on a combination of visual sensors and RFID have recently been successfully introduced. This chapter presents a contemporary review on these object analysis techniques for localisation, tracking, and object and activity recognition, together with some future research directions in this burgeoning field. DOI: 10.4018/978-1-4666-1616-5.ch012
Usenix Association 10th Usenix Symposium on Networked Systems Design and Implementation (nsdi '13) 199 Wire Speed Name Lookup: a Gpu-based Approach

This paper studies the name lookup issue with longest prefix matching, which is widely used in URL filtering, content routing/switching, etc. Recently Content-Centric Networking (CCN) has been proposed as a clean slate future Internet architecture to naturally fit the content-centric property of today's Internet usage: instead of addressing end hosts, the Internet should operate based on the identity/name of contents. A core challenge and enabling technique in implementing CCN is exactly to perform name lookup for packet forwarding at wire speed. In CCN, routing tables can be orders of magnitude larger than current IP routing tables, and content names are much longer and more complex than IP addresses. In pursuit of conquering this challenge, we conduct an implementation-based case study on wire speed name lookup, exploiting GPU's massive parallel processing power. Extensive experiments demonstrate that our GPU-based name lookup engine can achieve 63.52M searches per second lookup throughput on large-scale name tables containing millions of name entries with a strict constraint of no more than the telecommunica-tion level 100µs per-packet lookup latency. Our solution can be applied to contexts beyond CCN, such as search engines, content filtering, and intrusion preven-tion/detection. c ⃝ Prof. Qunfeng Dong (qunfeng.dong@gmail.com) and Prof. Bin Liu (lmyujie@gmail.com), placed in alphabetic order, are the correspondence authors of the paper. Yi Wang and Yuan Zu, placed in alphabetic order, are the lead student
Hydrology, river regimes and sediment yield

In comparison to the rest of Europe, Africa, and Asia, most rivers arising and flowing within the Mediterranean watershed typically drain small catchments with mountainous headwaters (Figure 8.1). The hydrology of Mediterranean catchments is strongly influenced by the seasonal distribution of precipitation, catchment geology, vegetation type and extent, and the geomorphology of the slope and channel systems. It is important to appreciate, as the preceding chapters have shown, that the area draining to the Mediterranean Sea is large and enormously variable in terms of the key controls on catchment hydrology outlined above, and it is therefore not possible to define, in hydrological terms, a strict single Mediterranean river type. However, river regimes across the basin do have a marked seasonality that is largely controlled by the climate system (Chapter 3) and, in most basins, the dominant flows occur in winter—but autumn and spring runoff is also important in many areas. These patterns reflect the general water balance of the basin as a whole, but there are key geographical patterns in catchment hydrology and sediment yield and a marked contrast is evident between the more humid north and the semi-arid south and east (Struglia et al. 2004; Chapter 21). Also, because of the long history of vegetation and hillslope modification by human activity and the more recent and widespread implementation of water resource management projects, there are almost no natural river regimes in the Mediterranean region, especially in the middle and lower reaches of river catchments (Cudennec et al. 2007). Runoff generation on hillslopes in the Mediterranean is very closely related to rainfall intensities and land surface properties as discussed in Chapter 6. While this is probably true of most catchments, runoff generation in the Mediterranean is very sensitive to vegetation cover because of the seasonal dynamics of rainfall and the role played by extreme events. The cumulative effect of these characteristics is a specific set of management problems and restoration issues and, although these are rather different in the various socio-political regimes of the region, it can be argued that they are in many ways unique to Mediterranean catchments.
Conference on ‘ Over-and undernutrition : challenges and approaches ’ Symposium 2 : Modern approaches to nutritional research challenges Targeted and non-targeted approaches for metabolite profiling in nutritional research

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