Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of Pinus radiata D . Don clear wood properties by near-infrared spectroscopy

The use of calibrated near-infrared (NIR) spectroscopy for predicting of a range of solid wood properties is described. The methods developed are applicable to large-scale nondestructive forest resource assessment and to tree breeding and silviculture programs. A series of Pinus radiata D. Don (radiata pine) samples were characterized in terms of density, longitudinal modulus of elasticity (EL), and microfibril angle (MFA). NIR spectra were obtained from the radial/longitudinal face of each sample and used to generate calibrations for the measured physical properties. The relations between laboratory-determined data and N I R fitted data were good in all cases, with coefficients of determination (R 2) ranging from 0.68 for 100/MFA to 0.94 for densitystr~p. A good relation (R 2 = 0.83) was also obtained for EL estimated using data collected by SilviScan2. The finding suggests that an N I R instrument could be calibrated to estimate the E L of increment cores based on SilviScan data. In view of the rapidly expanding range of applications for this technique, it is concluded that appropriately calibrated N I R spectroscopy could form the basis of a testing instrument capable of predicting a range of properties from a single spectrum obtained from the product or from the raw material.
Online intrusion detection design and implementation for SCADA networks

The standardization and interconnection of supervisory control and data acquisition (SCADA) systems has exposed the systems to cyber attacks. To improve the security of the SCADA systems, intrusion detection system (IDS) design is an effective method. However, traditional IDS design in the industrial networks mainly exploits the predefined rules, which needs to be complemented and developed to adapt to the big data scenario. Therefore, this thesis aims to design an anomaly-based novel hierarchical online intrusion detection system (HOIDS) for SCADA networks based on machine learning algorithms theoretically and implement the theoretical idea of the anomaly-based intrusion detection on a testbed. The theoretical design of HOIDS by utilizing the server-client topology while keeping clients distributed for global protection, high detection rate is achieved with minimum network impact. We implement accurate models of normal-abnormal binary detection and multi-attack identification based on logistic regression and quasi-Newton optimization algorithm using the Broyden-Fletcher-Goldfarb-Shanno approach. The detection system is capable of accelerating detection by information gain based feature selection or principle component analysis based dimension reduction. By evaluating our system using the KDD99 dataset and the industrial control system datasets, we demonstrate that our
Reliable and Fast Localization in Ambiguous Environments Using Ambiguity Grid Map

In real-world robotic navigation, some ambiguous environments contain symmetrical or featureless areas that may cause the perceptual aliasing of external sensors. As a result of that, the uncorrected localization errors will accumulate during the localization process, which imposes difficulties to locate a robot in such a situation. Using the ambiguity grid map (AGM), we address this problem by proposing a novel probabilistic localization method, referred to as AGM-based adaptive Monte Carlo localization. AGM has the capacity of evaluating the environmental ambiguity with average ambiguity error and estimating the possible localization error at a given pose. Benefiting from the constructed AGM, our localization method is derived from an improved Dynamic Bayes network to reason about the robot’s pose as well as the accumulated localization error. Moreover, a portal motion model is presented to achieve more reliable pose prediction without time-consuming implementation, and thus the accumulated localization error can be corrected immediately when the robot moving through an ambiguous area. Simulation and real-world experiments demonstrate that the proposed method improves localization reliability while maintains efficiency in ambiguous environments.
Real-Time Detection of Spatial Disorientation in Persons with Mild Cognitive Impairment and Dementia

Background: Detecting manifestations of spatial disorientation in real time is a key requirement for adaptive assistive navigation systems for people with dementia. Objective: To identify predictive patterns of spatial disorientation in cognitively impaired people during unconstrained locomotion behavior in an urban environment. Methods: Accelerometric data and GPS records were gathered during a wayfinding task along a route of about 1 km in 15 people with amnestic mild cognitive impairment or clinically probable Alzheimer’s disease dementia (13 completers). We calculated a set of 48 statistical features for each 10-s segment of the acceleration sensor signal to characterize the physical motion. We used different classifiers with the wrapper method and leave-one-out cross-validation for feature selection and for determining accuracy of disorientation detection. Results: Linear discriminant analysis using three features showed the best classification results, with a cross-validated ROC AUC of 0.75, detecting 65% of all scenes of spatial disorientation in real time. Consideration of an additional feature that informed about a person’s distance to the next traffic junction did not provide an additional information gain. Conclusions: Accelerometric data are able to capture the uniformity and activity of a person’s walking, which are identified as the most informative locomotion features of spatially disoriented behavior. This serves as an important basis for real-time navigation assistance. To improve the required accuracy of real-time disorientation prediction, as a next step we will analyze whether location-based behavior is able to inform about person-centered habitual factors of orientation.
Standardization of Flow Cytometric Immunophenotyping for Hematological Malignancies: The FranceFlow Group Experience

Flow cytometry is broadly used for the identification, characterization, and monitoring of hematological malignancies. However, the use of clinical flow cytometry is restricted by its lack of reproducibility across multiple centers. Since 2006, the EuroFlow consortium has been developing a standardized procedure detailing the whole process from instrument settings to data analysis. The FranceFlow group was created in 2010 with the intention to educate participating centers in France about the standardized instrument setting protocol (SOP) developed by the EuroFlow consortium and to organise several rounds of quality controls (QCs) in order to evaluate the feasibility of its application and its results. Here, we report the 5 year experience of the FranceFlow group and the results of the seven QCs of 23 instruments, involving up to 19 centers, in France and in Belgium. The FranceFlow group demonstrates that both the distribution and applicability of the SOP have been successful. Intercenter reproducibility was evaluated using both normal and pathological blood samples. Coefficients of variation (CVs) across the centers were <7% for the percentages of cell subsets and <30% for the median fluorescence intensities (MFIs) of the markers tested. Intracenter reproducibility provided similar results with CVs of <3% for the percentages of the majority of cell subsets, and CVs of <20% for the MFI values for the majority of markers. Altogether, the FranceFlow group show that the 19 participating labs might be considered as one unique laboratory with 23 identical flow cytometers able to reproduce identical results. Therefore, SOP significantly improves reproducibility of clinical flow in hematology and opens new avenues by providing a robust companion diagnostic tool for clinical trials in hematology. © 2019 International Society for Advancement of Cytometry
Image retrieval based on multi-instance saliency model

Existing methods for visual saliency based image retrieval typically aim at single instance image. However, without any prior knowledge, the content of single instance image is ambiguous and these methods cannot effectively reflect the object of interest. In this paper, we propose a novel image retrieval framework based on multi-instance saliency model. First, the feature saliency is computed based on global contrast, local contrast and sparsity, and the synthesize saliency map is obtained by using Multi-instance Learning (MIL) algorithm to dynamically weight the feature saliency. Then we employ a fuzzy region-growth algorithm on the synthesize saliency map to extract the saliency object. We finally extract color and texture feature as the retrieval feature and measure feature similarity by Euclidean distance. In the experiments, the proposed method can achieve higher multi-instance image retrieval accuracy than the other single instance image retrieval methods based on saliency model.
PathwayMatcher: proteoform-centric network construction enables fine-granularity multiomics pathway mapping

Background Mapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers, e.g. gene sets, in pathway knowledgebases. However, the isoform and post-translational modification states of proteins are lost when converting input and pathways into gene-centric lists. Findings Based on the Reactome knowledgebase, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input, and outputs the possibly affected biochemical reactions, subnetworks, and pathways. Conclusions PathwayMatcher enables refining the network-representation of pathways by including isoform and post-translational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity and it becomes possible to distinguish interactions between different forms of the same protein.
Riding the Roller Coaster

Background Rates of burnout and compassion fatigue among oncology nurses are rising, and the emotional impact of the work increases the risk. This study examined how oncology nurses describe the evolution of emotions from first significant patient loss through cumulative patient death. Objective To explore the emotional evolution of being an oncology nurse. Methods Semistructured interviews with 7 oncology nurses. Thematic analysis was used to analyze the data. Results Participant’s mean age was 41.3 years, with 13.9 years of nursing experience and 10.6 years of oncology experience. One metatheme, “riding the roller coaster,” described the overall emotional experience of the nurses. Three subthemes, “all in and then,” “finding your way,” and “impact on self,” further outlined the process taken to cope with workplace emotions. Conclusions Oncology nurses are frequently exposed to loss and suffering. Findings from this study suggest that new nurses are underprepared for the emotional experience of being an oncology nurse. Further, they define their emotional boundaries in isolation and without guidance on how to develop healthy coping skills. Changing the culture of silence around mental health and well-being among healthcare professionals can provide space for important conversations to occur. Implications for Practice Oncology nurses have few resources to teach them how to cope with the emotions experienced while caring for oncology patients. These findings suggest that alternative approaches to the traditional bereavement programs and innovative interventions offered to new oncology nurses within their first few years are needed.
Assessing longer-term effectiveness of a combined household-level piped water and sanitation intervention on child diarrhoea, acute respiratory infection, soil-transmitted helminth infection and nutritional status: a matched cohort study in rural Odisha, India

Abstract Background Open defecation is widespread in rural India, and few households have piped water connections. While government and other efforts have increased toilet coverage in India, and evaluations found limited immediate impacts on health, longer-term effects have not been rigorously assessed. Methods We conducted a matched cohort study to assess the longer-term effectiveness of a combined household-level piped water and sanitation intervention implemented by Gram Vikas (an Indian NGO) in rural Odisha, India. Forty-five intervention villages were randomly selected from a list of those where implementation was previously completed at least 5 years before, and matched to 45 control villages. We conducted surveys and collected stool samples between June 2015 and October 2016 in households with a child <5 years of age (n = 2398). Health surveillance included diarrhoea (primary outcome), acute respiratory infection (ARI), soil-transmitted helminth infection, and anthropometry. Results Intervention villages had higher improved toilet coverage (85% vs 18%), and increased toilet use by adults (74% vs 13%) and child faeces disposal (35% vs 6%) compared with control villages. There was no intervention association with diarrhoea [adjusted OR (aOR): 0.94, 95% confidence interval (CI): 0.74–1.20] or ARI. Compared with controls, children in intervention villages had lower helminth infection (aOR: 0.44, 95% CI: 0.18, 1.00) and improved height-for-age z scores (HAZ) (+0.17, 95% CI: 0.03–0.31). Conclusions This combined intervention, where household water connections were contingent on community-wide household toilet construction, was associated with improved HAZ, and reduced soil-transmitted helminth (STH) infection, though not reduced diarrhoea or ARI. Further research should explore the mechanism through which these heterogenous effects on health may occur.
Mg2+ restriction downregulates NCC through NEDD4-2 and prevents its activation by hypokalemia.

Hypomagnesemia is associated with reduced kidney function and life-threatening complications, and sustains hypokalemia. The distal convoluted tubule (DCT) determines final urinary Mg2+ excretion, and via activity of the Na+-Cl- cotransporter (NCC) also plays a key role in K+ homeostasis by metering Na+ delivery to distal segments. Little is known about the mechanisms by which plasma [Mg2+] regulates NCC activity, and how low plasma [Mg2+] and [K+] interact to modulate NCC activity. To address this we performed dietary manipulation studies in mice. Compared with normal diet, abundances of total NCC (tNCC) and phosphorylated NCC (pNCC) were lower following short-term (3 days) or long-term (14 days) dietary Mg2+ restriction. Altered NCC activation is unlikely to play a role since we also observed lower tNCC abundance in mice lacking the two NCC-activating kinases SPAK and OSR1 following Mg2+ restriction. The E3 ubiquitin-protein ligase NEDD4-2 regulates NCC abundance during dietary NaCl loading or K+ restriction. Mg2+ restriction did not lower tNCC abundance in inducible nephron-specific NEDD4-2 knockout mice. tNCC and pNCC abundances were similar following short-term Mg2+ or combined Mg2+-K+ restriction, but were dramatically lower compared with low K+ diet. Sustained NCC downregulation may therefore serve a mechanism that enhances distal Na+ delivery during states of hypomagnesemia, maintaining hypokalemia. Similar results were obtained with long-term Mg2+-K+ restriction, but surprisingly, NCC was not activated following long-term K+ restriction despite lower plasma [K+], suggesting significant differences in distal tubule adaptation to acute versus chronic K+ restriction.
STAT6 induces expression of Gas6 in macrophages to clear apoptotic neutrophils and resolve inflammation

Significance Clearance of apoptotic neutrophils by alveolar macrophages (AMФs) is critical for the resolution of acute lung injury (ALI). Here, we demonstrated that induction of the M1 phenotype in MФs activates the transcription factor STAT6 and thereby promotes resolution of lung injury by the increased expression of Gas6, the ligand for efferocytosis. Therefore, targeting the STAT6 activation pathway in AMФs and Gas6 may be a potential therapeutic strategy for resolution of inflammatory lung injury. Efferocytosis of apoptotic neutrophils (PMNs) by alveolar macrophages (AMФs) is vital for resolution of inflammation and tissue injury. Here, we investigated the role of AMФ polarization and expression of the efferocytic ligand Gas6 in restoring homeostasis. In the murine model of lipopolysaccharide (LPS)-induced acute lung injury (ALI), we observed augmented temporal generation of cytokines IL-4 and TSG6 in bronchoalveolar fluid (BALF). Interestingly, we also observed increased expression of antiinflammatory markers consistent with a phenotype shift in AMФs. In particular, AMФs expressed the efferocytic ligand Gas6. In vitro priming of bone marrow–derived macrophages (BMMФs) with IL-4 or TSG6 also induced MФ transition and expression of Gas6. TSG6- or IL-4–primed BMMФs induced efferocytosis of apoptotic PMNs compared with control BMMФs. Adoptive transfer of TSG6- or IL-4–primed BMMФs i.t. into LPS-challenged mice more rapidly and effectively cleared PMNs in lungs compared with control BMMФs. We demonstrated that expression of Gas6 during AMФ transition was due to activation of the transcription factor signal transducer and activator of transcription-6 (STAT6) downstream of IL-4 or TSG6 signaling. Adoptive transfer of Gas6-depleted BMMФs failed to clear PMNs in lungs following LPS challenge and mice showed severely defective resolution of lung injury. Thus, activation of STAT6-mediated Gas6 expression during macrophage phenotype transition resulting in efferocytosis of PMNs plays a crucial role in the resolution of inflammatory lung injury.
Functional Fluorescence Microscopy Imaging (fFMI). Quantitative Scanning-Free Confocal Fluorescence Microscopy for the Characterization of Fast Dynamic Processes in Live Cells.

Functional Fluorescence Microscopy Imaging (fFMI), a time-resolved (21 µs/frame) confocal fluorescence microscopy imaging technique without scanning is developed for quantitative characterization of fast reaction-transport processes in solution and in live cells. The method is based on massively parallel Fluorescence Correlation Spectroscopy (FCS). Simultaneous excitation of fluorescent molecules in multiple spots in the focal plane is achieved using a Diffractive Optical Element (DOE). Fluorescence from the DOE-generated 1024 illuminated spots is detected in a confocal arrangement by a matching matrix detector comprising 32x32 single-photon avalanche photodiodes (SPADs). Software for data acquisition and fast auto- and cross-correlation analysis by parallel signal processing using a Graphic Processing Unit (GPU) allows temporal autocorrelation across all pixels in the image frame in 4 s and cross-correlation between first and second order neighbor pixels in 45 s. We present here this quantitative, time-resolved imaging method with single-molecule sensitivity and demonstrate its usefulness for mapping in live cells location-specific differences in the concentration and translational diffusion of molecules in different subcellular compartments. In particular, we show that molecules without a specific biological function, e.g. the enhanced Green Fluorescent Protein (eGFP), exhibit uniform diffusion. In contrast, molecules that perform specialized biological functions and bind specifically to their molecular targets show location-specific differences in their concentration and diffusion, exemplified here for two transcription factor molecules, the glucocorticoid receptor (GR) before and after nuclear translocation, and the Sex Combs Reduced (Scr) transcription factor in the salivary gland of Drosophila ex vivo.
First Case Report of Human Bacteremia With Malacobacter (Arcobacter) mytili

Abstract Arcobacter spp. are commonly associated with shellfish and have been increasingly implicated in human gastrointestinal disease. We report the first case of human bacteremia with Malacobacter (previously Arcobacter) mytili acquired after exposure to Maryland crab. Arcobacter spp. should be considered in febrile illnesses when the history indicates exposure to seafood.
Evidence of a Link Between Fall-Related Anxiety and High-Risk Patterns of Visual Search in Older Adults During Adaptive Locomotion

Abstract Background Older adults deemed to be at a high risk of falling will often display visual search behaviors likely to impair movement planning when negotiating environmental hazards. It has been proposed that these behaviors may be underpinned by fall-related anxiety. Thus, the aim of this study was to explore the effects of fall-related anxiety on visual search and stepping behaviors during adaptive gait. Methods Forty-four community-dwelling older adults (mean age = 74.61; standard deviation = 6.83) walked along a path and stepped into two raised targets. All participants completed walks at ground level, whereas participants deemed to be at a low risk of falling (n = 24) also completed walks under conditions designed to induce fall-related anxiety (walkway elevated 0.6 m). Participants’ movement kinematics and gaze behavior were measured. Results During ground trials, “high-risk” participants visually prioritized the immediate walkway areas 1–2 steps ahead, at the expense of previewing future stepping constraints. This reduced planning appeared to negatively affect safety, with greater stepping errors observed for future constraints. When completing walks on the elevated walkway, “low-risk” participants similarly prioritized immediate walkway areas, at the expense of planning future stepping actions. These behaviors were associated with greater attention directed toward consciously processing walking movements. Conclusions These findings provide evidence of a link between heightened fall-related anxiety and “high-risk” visual search behaviors associated with greater stepping errors. This information enhances our understanding of why high-risk older adults are less able to safely navigate environmental constraints.
Pay for performance and hip fracture outcomes

Aims Hip fractures are associated with high morbidity, mortality, and costs. One strategy for improving outcomes is to incentivize hospitals to provide better quality of care. We aimed to determine whether a pay-for-performance initiative affected hip fracture outcomes in England by using Scotland, which did not participate in the scheme, as a control. Materials and Methods We undertook an interrupted time series study with data from all patients aged more than 60 years with a hip fracture in England (2000 to 2018) using the Hospital Episode Statistics Admitted Patient Care (HES APC) data set linked to national death registrations. Difference-in-differences (DID) analysis incorporating equivalent data from the Scottish Morbidity Record was used to control for secular trends. The outcomes were 30-day and 365-day mortality, 30-day re-admission, time to operation, and acute length of stay. Results There were 1 037 860 patients with a hip fracture in England and 116 594 in Scotland. Both 30-day (DID -1.7%; 95% confidence interval (CI) -2.0 to -1.2) and 365-day (-1.9%; 95% CI -2.5 to -1.3) mortality fell in England post-intervention when compared with outcomes in Scotland. There were 7600 fewer deaths between 2010 and 2016 that could be attributed to interventions driven by pay-for-performance. A pre-existing annual trend towards increased 30-day re-admissions in England was halted post-intervention. Significant reductions were observed in the time to operation and length of stay. Conclusion This study provides evidence that a pay-for-performance programme improved the outcomes after a hip fracture in England. Cite this article: Bone Joint J 2019;101-B:1015–1023.