Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between Hyperspectral Measurements and Mangrove Leaf Nitrogen Concentrations

The use of spectral response curves for estimating nitrogen (N) leaf concentrations generally has been found to be a challenging task for a variety of plant species. In this investigation, leaf N concentration and corresponding laboratory hyperspectral data were examined for two species of mangrove (Avicennia germinans, Rhizophora mangle) representing a variety of conditions (healthy, poor condition, dwarf) of a degraded mangrove forest located in the Mexican Pacific. This is the first time leaf nitrogen content has been examined using close range hyperspectral remote sensing of a degraded mangrove forest. Simple comparisons between individual wavebands and N concentrations were examined, as well as two models employed to predict N concentrations based on multiple wavebands. For one model, an Artificial Neural Network (ANN) was developed based on known N absorption bands. For comparative purposes, a second model, based on the well-known Stepwise Multiple Linear Regression (SMLR) approach, was employed using the entire dataset. For both models, the input data included continuum removed reflectance, band depth at the centre of the absorption feature (BNC), and log (1/BNC). Weak to moderate correlations were found between N concentration and single band spectral responses. The results also indicate that ANNs were more predictive for N concentration than was SMLR, and had consistently higher r2 values. The highest r2 value (0.91) was observed in the prediction of black mangrove (A. germinans) leaf N concentration using the BNC transformation. It is thus suggested that artificial neural networks could be used in a complementary manner with other techniques to assess mangrove health, thereby improving environmental monitoring in coastal wetlands, which is of prime importance to local communities. In addition, it is recommended that the BNC transformation be used on the input for such N concentration prediction models.
A Retrospective Study of Clinical Response Predictors in Subcutaneous Allergen Immunotherapy With House Dust Mites for Allergic Rhinitis

Purpose House dust mites (HDM) are major allergens that cause allergic rhinitis (AR). Allergen-specific subcutaneous immunotherapy (SCIT) has been shown to be clinically beneficial in many clinical trials. Such trials, however, are not reflective of all patient populations. The aim of this study was to describe the efficacy and safety of SCIT in routine clinical practice in Korean adults with AR sensitized to HDM. Methods We reviewed medical records of 304 patients with AR treated at an allergy clinic of a tertiary hospital using SCIT with aluminum hydroxide-adsorbed allergen extract targeting HDM alone or with pollens for at least 1 year from 2000 to 2012. Patients with asthma were excluded. Rates of remission, defined as no further requirement of maintenance medication, over time were determined by means of life tables and extension of survival analysis. Specific immunoglobulin E (IgE) levels to HDM were categorized into 6 classes. Results The mean time until achieving remission was 4.9±0.1 years, and the cumulative incidence of remission from AR was 76.6%. Severe AR (odds ratio [OR], 0.40; 95% confidence interval [CI], 0.23-0.69; P=0.001), specific IgE levels to HDM ≥17.5 kU/L (OR, 1.85; 95% CI, 1.01-3.37; P=0.045), and duration of immunotherapy ≥3 years (OR, 7.37; 95% CI, 3.50-15.51; P<0.001) were identified as significant predictors of clinical remission during SCIT for patients with AR sensitized to HDM. Overall, 73 patients (24.0%) experienced adverse reactions to SCIT, and only 1 case of anaphylaxis (0.3%) developed. Conclusions SCIT with HDM was found to be effective and safe for patients with AR. Specific IgE levels to HDM and a duration of SCIT ≥3 years may be predictors of clinical responses to SCIT in AR patients.
Biofibres, biodegradable polymers and biocomposites: An overview

Recently the critical discussion about the preservation of natural resources and recycling has led to the renewed interest concerning biomaterials with the focus on renewable raw materials. Because of increasing environmental consciousness and demands of legislative authorities, use and removal of traditional composite structures, usually made of glass, carbon or aramid fibers being reinforced with epoxy, unsaturated polyester, or phenolics, are considered critically. Recent advances in natural fiber development, genetic engineering and composite science offer significant opportunities for improved materials from renewable resources with enhanced support for global sustainability. The important feature of composite materials is that they can be designed and tailored to meet different requirements. Since natural fibers are cheap and biodegradable, the biodegradable composites from biofibers and biodegradable polymers will render a contribution in the 21st century due to serious environmental problem. Biodegradable polymers have offered scientists a possible solution to waste-disposal problems associated with traditional petroleum-derived plastics. For scientists the real challenge lies in finding applications which would consume sufficiently large quantities of these materials to lead price reduction, allowing biodegradable polymers to compete economically in the market. Today's much better performance of traditional plastics are the outcome of continued RD however the existing biodegradable polymers came to public only few years back. Prices of biodegradable polymers can be reduced on mass scale production; and such mass scale production will be feasible through constant R&D efforts of scientists to improve the performance of biodegradable plastics. Manufacture of biodegradable composites from such biodegradable plastics will enhance the demand of such materials. The structural aspects and properties of several biofibers and biodegradable polymers, recent developments of different biodegradable polymers and biocomposites are discussed in this review article. Collaborative R&D efforts among material scientists and engineers as well as intensive co-operation and co-ordination among industries, research institutions and government are essential to find various commercial applications of biocomposites even beyond to our imagination.
Secondary Prevention of Chronic PTSD by Early and Short-Term Administration of Escitalopram: A Prospective Randomized, Placebo-Controlled, Double-Blind Trial.

OBJECTIVE Prospective studies have not identified a viable pharmacologic strategy for secondary prevention of posttraumatic stress disorder (PTSD). The authors examined whether preventive intervention via early and short-term administration of a selective serotonin reuptake inhibitor (SSRI), within 1 month of exposure to a traumatic event (before diagnosis of PTSD could be made), may reduce the severity of PTSD symptoms according to DSM-IV at 13 months' follow-up. METHODS Over 25,000 screening calls to patients referred to an emergency department for a traumatic event performed between June 2006 and December 2008 yielded 353 participants who were recruited within the month following a traumatic event . Participants were randomly assigned in a double-blind design to escitalopram (n = 176) or placebo (n = 177). The per-protocol analysis comprised 198 participants (escitalopram, n = 102; placebo, n = 96) who received treatment for 12 to 24 weeks and were available for follow-up at week 56. RESULTS The primary outcome measure, the Clinician Administered PTSD Scale (CAPS), revealed no prevention effect. However, a secondary outcome, the Pittsburgh Sleep Quality Inventory (PSQI), showed better results for the SSRI group than for the placebo group. For a subset of participants who experienced intentional trauma (missile attacks, rape, or physical assault; n = 50), the prevention effect was found on both primary and secondary measures (CAPS, PSQI and measures of depression and global illness severity). CONCLUSIONS Early and short-term administration of escitalopram was not shown to prevent PTSD, although it did improve sleep quality. In a subgroup of participants who experienced intentional trauma, however, this early-treatment approach may be effective as secondary prevention. This large study is the first to investigate the preventive effect of early administration of escitalopram on PTSD. It highlights the relevance of the type of trauma (intentional vs unintentional) to the outcome. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT00300313​​.
A rapid method to verify single‐cell deposition setup for cell sorters

Studying single cells reveals biology that cannot be explored using bulk techniques. Cell sorters provide the opportunity of separating single cells either for cell culture or for downstream molecular applications such as qPCR to study specific gene expression and single cell mRNA sequencing. Some of these molecular studies can be expensive so the investigator will often want reassurance that the cell sorter can reliably deposit a single droplet into each well of a 96‐well or 384‐well plate. Such plates may contain very small volumes of fluid as reducing the volume of fluid used can reduce the cost of the assay. To miss some of the wells could leave the data set incomplete requiring costly repetition. To verify this by microscopy is at best very time consuming and at worst impossible. Here, an inexpensive colorimetric method is described for verifying whether a well, in either a 96‐ or 384‐well plate, did receive a single sorted droplet from a cell sorter into the fluid at the bottom of the well. The droplet consists of particles suspended in an enzymatic solution, horseradish peroxidase, which is deposited into microtiter plate wells containing a substrate, 3,3′,5,5′‐tetramethylbenzidine. This method requires no special equipment or expertise and is rapid enough to be performed directly prior to the single‐cell sorting experiment. © 2016 International Society for Advancement of Cytometry
An Adaptive Process-Variation-Aware Technique for Power-Gating-Induced Power/Ground Noise Mitigation in MPSoC

Power gating (PG) is one of the most effective techniques to reduce the leakage power in multiprocessor system-on-chips (MPSoCs). However, the power-mode transition during the PG period of an individual processing unit (PU) will introduce serious power/ground (P/G) noise to the neighboring PUs. As technology scales, the P/G noise problem becomes a severe reliability threat to MPSoCs. At the same time, the increasing manufacturing process variations (PVs) also bring uncertainties to the P/G noise problem and make it difficult to predict and mitigate. To tackle this problem, in this paper, we analyze the PG-induced P/G noise in the presence of PVs and propose a hardware-software collaborated runtime technique to adaptively protect PUs from P/G noise. Sensor network-on-chip is used to gather noise information and coordinate different system components. An online PV-aware algorithm is developed to effectively decide the noise impact range and arrange protections for affected PUs based on the collected noise information. We evaluate the proposed technique through cycle-level Monte Carlo simulations of NoC-based MPSoCs in different scales. The experimental results on various realistic applications show that our technique could achieve comparable reliability to the most reliable static technique while improve on average 3.78%-29.5% the system energy efficiency and reduce 15.7%-70.4% the performance penalty on different MPSoC scales.
A decreased Ca2+-wave propagation is found among cultured RPE cells from dystrophic RCS rats.

PURPOSE The authors investigated intercellular communication among cultured rat retinal pigment epithelial (RPE) cells isolated from dystrophic Royal College of Surgeons (RCS) rats by studying the conduction of the [Ca2+]i wave elicited by mechanical stimulation. The effect of protein phosphorylation was measured by modulating the protein kinase C (PKC), protein kinase A (PKA), and tyrosine kinase activity. METHODS Cultured RPE cells isolated from neonatal control Long-Evans (LE) and dystrophic RCS rats were analyzed using the fluorescent dye fluo-3 to measure the Ca2+-wave propagation on mechanical stimulation to investigate the intercellular communication. RESULTS Mechanical stimulation in LE-RPE cells resulted in a centrifugally spreading Ca2+ wave through the neighboring cells. When a mechanical stimulus was applied on RCS-RPE cells, a significantly reduced Ca2+-response was found in the neighboring cells compared with that of control RPE cells. Activation of PKC almost completed blocked the mechanically induced Ca2+ rise in the neighboring RCS-RPE cells. In contrast to LE-RPE cells, an activation of PKA also significantly decreased the Ca2+-wave propagation in RCS-RPE cells. Inhibition of PKA had no effect on the intercellular communication in LE- or RCS-RPE cells. In addition, when protein phosphatase activity or tyrosine kinase activity was inhibited, an increased Ca2+ rise in the neighboring cells on mechanical stimulation was measured, reaching levels currently found for LE-RPE cells. CONCLUSIONS In dystrophic RCS-RPE cells, a decreased intercellular Ca2+-wave propagation is found. This intercellular communication can be mediated by protein phosphorylation.
Computing Bottleneck Distance for 2-D Interval Decomposable Modules

Computation of the interleaving distance between persistence modules is a central task in topological data analysis. For $1$-D persistence modules, thanks to the isometry theorem, this can be done by computing the bottleneck distance with known efficient algorithms. The question is open for most $n$-D persistence modules, $n>1$, because of the well recognized complications of the indecomposables. Here, we consider a reasonably complicated class called {\em $2$-D interval decomposable} modules whose indecomposables may have a description of non-constant complexity. We present a polynomial time algorithm to compute the bottleneck distance for these modules from indecomposables, which bounds the interleaving distance from above, and give another algorithm to compute a new distance called {\em dimension distance} that bounds it from below.
Phylogenetic Resolution and Quantifying the Phylogenetic Diversity and Dispersion of Communities

Conservation biologists and community ecologists have increasingly begun to quantify the phylogenetic diversity and phylogenetic dispersion in species assemblages. In some instances, the phylogenetic trees used for such analyses are fully bifurcating, but in many cases the phylogenies being used contain unresolved nodes (i.e. polytomies). The lack of phylogenetic resolution in such studies, while certainly not preferred, is likely to continue particularly for those analyzing diverse communities and datasets with hundreds to thousands of taxa. Thus it is imperative that we quantify potential biases and losses of statistical power in studies that use phylogenetic trees that are not completely resolved. The present study is designed to meet both of these goals by quantifying the phylogenetic diversity and dispersion of simulated communities using resolved and gradually ‘unresolved’ phylogenies. The results show that: (i) measures of community phylogenetic diversity and dispersion are generally more sensitive to loss of resolution basally in the phylogeny and less sensitive to loss of resolution terminally; and (ii) the loss of phylogenetic resolution generally causes false negative results rather than false positives.
The effectiveness of the COPE healthy lifestyles TEEN program: a school‐based intervention in middle school adolescents with 12‐month follow‐up

AIM The goal of this study is to assess the applicability and long-term effectiveness of the T-COPE Healthy TEEN program on adolescent health. BACKGROUND Obesity and mental health disorders are major public health problems in adolescents. In this context, including long-term and multiple behavioural obesity prevention programs are becoming increasingly important. DESIGN A quasi-experimental design with pre-test/post-test control group and repeated measurements. METHODS Eighty-seven (45 in intervention group, 42 in control group) adolescents were included from two different middle schools in the intervention program. The data were analysed by using descriptive statistics, Pearson chi-square, Fisher's exact test, Student-t test, repeated measures of variance analysis and Cohen's d effect size. RESULTS No significant difference was found between the intervention and control groups in terms of descriptive characteristics, behavioural and cognitive variables of the adolescents. Following the intervention, the adolescents in intervention groups showed improvements in nutritional behaviour, physical activity and stress management. These improvements concerned increased physical walking measured in the number of physical steps per week daily fruit and vegetable consumption and the daily quantity of water ingested. While their nutrition/physical activity knowledge significantly increased, their weight and anxiety symptoms significantly decreased. The effect of the program on body mass index, depression and health beliefs of the adolescents were not significant compared with the control group. CONCLUSION The applicability of the T-COPE Healthy TEEN program on Turkish adolescents and its effectiveness on their health behaviours, nutrition and physical activity knowledge and stress management were revealed in this study.
Fluctuations of the Longest Common Subsequence for Sequences of Independent Blocks

The problem of the order of the uctuation of the Longest Common Subsequence (LCS) of two independent sequences has been open for decades. There exist contradicting conjectures [8], [4] on the topic. Lember and Matzinger [17] showed that with i.i. d. binary strings, the standard deviation is asymptotically linear in the length of the strings provided that 0 and 1 have very dierent probabilities. Nonetheless, with two i.i. d. sequences and a nite number of equiprobable colors the typical size of the uctuation remains unknown. A contiguous substring consisting only of one type of symbol is called block. For i.i. d. sequences with equiprobable symbols the blocks are independent of each other. In the present article, we determine the order of the uctuation of the LCS, for a special model of i.i. d. blocks. For achieving this goal, we developed a method which allows to reformulate the uctuation problem as (relatively) low dimensional optimization problem. The model we consider here is with three equiproble block lengths. The method can be applied to any other case including i.i. d. sequences, only that the optimization problem might be more complicated. The LCS problem can be formulated as a last passage percolation problem with correlated weights. The problem of the
Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps

Visual robot navigation within large-scale, semistructured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many state-of-the-art navigation approaches only operate locally instead of gaining a more conceptual understanding of the planning objective. This limits the complexity of tasks a robot can accomplish and makes it harder to deal with uncertainties that are present in the context of real-time robotics applications. In this work, we present Topomap, a framework which simplifies the navigation task by providing a map to the robot which is tailored for path planning use. This novel approach transforms a sparse feature-based map from a visual Simultaneous Localization And Mapping (SLAM) system into a three-dimensional topological map. This is done in two steps. First, we extract occupancy information directly from the noisy sparse point cloud. Then, we create a set of convex free-space clusters, which are the vertices of the topological map. We show that this representation improves the efficiency of global planning, and we provide a complete derivation of our algorithm. Planning experiments on real world datasets demonstrate that we achieve similar performance as RRT* with significantly lower computation times and storage requirements. Finally, we test our algorithm on a mobile robotic platform to prove its advantages.
Altered filamin A enables amyloid beta-induced tau hyperphosphorylation and neuroinflammation in Alzheimer’s disease

Alzheimer’s disease (AD) is a neurodegenerative disease with proteopathy characterized by abnormalities in amyloid beta (Aβ) and tau proteins. Defective amyloid and tau propagate and aggregate, leading to eventual amyloid plaques and neurofibrillary tangles. New data show that a third proteopathy, an altered conformation of the scaffolding protein filamin A (FLNA), is critically linked to the amyloid and tau pathologies in AD. Altered FLNA is pervasive in AD brain and without apparent aggregation. In a striking interdependence, altered FLNA is both induced by Aβ and required for two prominent pathogenic signaling pathways of Aβ. Aβ monomers or small oligomers signal via the α7 nicotinic acetylcholine receptor (α7nAChR) to activate kinases that hyperphosphorylate tau to cause neurofibrillary lesions and formation of neurofibrillary tangles. Altered FLNA also enables a persistent activation of toll-like-receptor 4 (TLR4) by Aβ, leading to excessive inflammatory cytokine release and neuroinflammation. The novel AD therapeutic candidate PTI-125 binds and reverses the altered FLNA conformation to prevent Aβ’s signaling via α7nAChR and aberrant activation of TLR4, thus reducing multiple AD-related neuropathologies. As a regulator of Aβ’s signaling via α7nAChR and TLR4, altered FLNA represents a novel AD therapeutic target.
Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus

Objective: We assessed the sensitivity and specificity of 8 electronic health record (EHR)-based phenotypes for diabetes mellitus against gold-standard American Diabetes Association (ADA) diagnostic criteria via chart review by clinical experts. Materials and Methods: We identified EHR-based diabetes phenotype definitions that were developed for various purposes by a variety of users, including academic medical centers, Medicare, the New York City Health Department, and pharmacy benefit managers. We applied these definitions to a sample of 173 503 patients with records in the Duke Health System Enterprise Data Warehouse and at least 1 visit over a 5-year period (2007–2011). Of these patients, 22 679 (13%) met the criteria of 1 or more of the selected diabetes phenotype definitions. A statistically balanced sample of these patients was selected for chart review by clinical experts to determine the presence or absence of type 2 diabetes in the sample. Results: The sensitivity (62–94%) and specificity (95–99%) of EHR-based type 2 diabetes phenotypes (compared with the gold standard ADA criteria via chart review) varied depending on the component criteria and timing of observations and measurements. Discussion and Conclusions: Researchers using EHR-based phenotype definitions should clearly specify the characteristics that comprise the definition, variations of ADA criteria, and how different phenotype definitions and components impact the patient populations retrieved and the intended application. Careful attention to phenotype definitions is critical if the promise of leveraging EHR data to improve individual and population health is to be fulfilled.