Miracle-dz/UniFAR-FTUs huggingface dataset:
Monitoring Drought Effects on Vegetation Productivity Using Satellite Solar-Induced Chlorophyll Fluorescence

Around the world, the increasing drought, which is exacerbated by climate change, has significant impacts on vegetation carbon assimilation. Identifying how short-term climate anomalies influence vegetation productivity in a timely and accurate manner at the satellite scale is crucial to monitoring drought. Satellite solar-induced chlorophyll fluorescence (SIF) has recently been reported as a direct proxy of actual vegetation photosynthesis and has more advantages than traditional vegetation indices (e.g., the Normalized Difference Vegetation Index, NDVI and the Enhanced Vegetation Index, EVI) in monitoring vegetation vitality. This study aims to evaluate the feasibility of SIF in interpreting drought effects on vegetation productivity in Victoria, Australia, where heat stress and drought are often reported. Drought-induced variations in SIF and absorbed photosynthetically active radiation (APAR) estimations based on NDVI and EVI were investigated and validated against results indicated by gross primary production (GPP). We first compared drought responses of GPP and vegetation proxies (SIF and APAR) during the 2009 drought event, considering potential biome-dependency. Results showed that SIF exhibited more consistent declines with GPP losses induced by drought than did APAR estimations during the 2009 drought period in space and time, where APAR had obvious lagged responses compared with SIF, especially in evergreen broadleaf forest land. We then estimated the sensitivities of the aforementioned variables to meteorology anomalies using the ARx model, where memory effects were considered, and compared the correlations of GPP anomaly with the anomalies of vegetation proxies during a relatively long period (2007–2013). Compared with APAR, GPP and SIF are more sensitive to temperature anomalies for the general Victoria region. For crop land, GPP and vegetation proxies showed similar sensitivities to temperature and water availability. For evergreen broadleaf forest land, SIF anomaly was explained better by meteorology anomalies than APAR anomalies. GPP anomaly showed a stronger linear relationship with SIF anomaly than with APAR anomalies, especially for evergreen broadleaf forest land. We showed that SIF might be a promising tool for effectively evaluating short-term drought impacts on vegetation productivity, especially in drought-vulnerable areas, such as Victoria.
A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks

Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques for digital pattern classification. Very recently, deep learning (DL) models have emerged as a powerful solution to approach many machine learning (ML) problems. In particular, convolutional neural networks (CNNs) are currently the state of the art for many image classification tasks. While there exist several promising proposals on the application of CNNs to LULC classification, the validation framework proposed for the comparison of different methods could be improved with the use of a standard validation procedure for ML based on cross-validation and its subsequent statistical analysis. In this paper, we propose a general CNN, with a fixed architecture and parametrization, to achieve high accuracy on LULC classification over RS data from different sources such as radar and hyperspectral. We also present a methodology to perform a rigorous experimental comparison between our proposed DL method and other ML algorithms such as support vector machines, random forests, and k-nearest-neighbors. The analysis carried out demonstrates that the CNN outperforms the rest of techniques, achieving a high level of performance for all the datasets studied, regardless of their different characteristics.
Ixazomib: an investigational drug for the treatment of lymphoproliferative disorders

ABSTRACT Introduction: Ixazomib is a new, orally administered, reversible proteasome inhibitor which is under investigation for the treatment of refractory/relapsed multiple myeloma (MM), systemic light chain amyloidosis (AL) and Waldenström macroglobulinemia (WM). Areas covered: This article covers the mechanism of action, pharmacology and clinical trial results of ixazomib while under investigation for the treatment of various lymphoproliferative disorders. We examine the findings from several phase 3 clinical trials (i) the pivotal TOURMALINE-MM1 study investigating ixazomib versus placebo in combination with lenalidomide and dexamethasone; (ii) the TOURMALINE-MM3 study investigating ixazomib versus placebo as a maintenance therapy in newly diagnosed MM following induction therapy and autologous stem cell transplantation; (iii) the TOURMALINE-MM2 study investigating ixazomib versus placebo in combination with lenalidomide and dexamethasone in patients with newly diagnosed MM; and (iv) TOURMALINE-AL1 investigating ixazomib plus dexamethasone in patients with relapsed/refractory AL amyloidosis. Finally, we explore early phase clinical studies of this agent in Waldenström macroglobulinemia. Expert opinion: A key advantage of ixazomib is that it could allow an efficacious treatment approach to MM and other lymphoproliferative disorders through a convenient oral administration route. Ixazomib could soon be used in combination treatment regimens, but more work is necessary to define the place of this agent going forward. Trial registration: ClinicalTrials.gov identifier: NCT02420847. Trial registration: ClinicalTrials.gov identifier: NCT00932698. Trial registration: ClinicalTrials.gov identifier: NCT00963820. Trial registration: ClinicalTrials.gov identifier: NCT00963820. Trial registration: ClinicalTrials.gov identifier: NCT01383928. Trial registration: ClinicalTrials.gov identifier: NCT01939899. Trial registration: ClinicalTrials.gov identifier: NCT02898259. Trial registration: ClinicalTrials.gov identifier: NCT03323151. Trial registration: ClinicalTrials.gov identifier: NCT02632396. Trial registration: ClinicalTrials.gov identifier: NCT03547700. Trial registration: ClinicalTrials.gov identifier: NCT00893464. Trial registration: ClinicalTrials.gov identifier: NCT02158975. Trial registration: ClinicalTrials.gov identifier: NCT02481310. Trial registration: ClinicalTrials.gov identifier: NCT02339922. Trial registration: ClinicalTrials.gov identifier: NCT01318902. Trial registration: ClinicalTrials.gov identifier: NCT01659658. Trial registration: ClinicalTrials.gov identifier: NCT02400437.
Fecal immunochemical test in cancer screening – colonoscopy outcome in FIT positives and negatives

Abstract Objectives: Fecal immunochemical test (FIT) is used in colorectal cancer (CRC) screening, but evaluations of multiple sample strategies in colonoscopy screening cohorts are rare. The aim of this study was to assess accuracy of FIT for advanced neoplasia (AN) with two fecal samples in a colonoscopy screening cohort. Materials and methods: The study comprised 1155 participants of the colonoscopy arm in SCREESCO (Screening of Swedish Colons, NCT02078804), a randomized controlled study on CRC screening of 60-year-olds from the Swedish average-risk population. Participants provided two FIT samples prior to colonoscopy. First sample, mean of two, and any of the two samples above cut off level were assessed. Colonoscopy findings (CRC, advanced adenoma (AA), AN (CRC + AA) and adenoma characteristics) were evaluated in uni- and multivariable analysis in relation to FIT positivity (at ≥10 µg hemoglobin (Hb)/g). Results: Of 1155 invited, 806 (416 women, 390 men) participated. CRC, AA and non-AA were found in one (0.1%), 80 (9.9%) and 145 (18%), respectively. Sensitivity and specificity for AN were 20%/93%, 25%/92% and 26%/89% for first, mean of two and any of the two samples respectively at cut off level 10 µg/g, corresponding to 60 (74%)–65 (80%) participants with missed AN. The difference in sensitivity between screening strategies was non-significant. The specificity for first sample was significantly higher than for any of the two samples at cut off 10 µg/g (p = .02) and 20 µg/g (p = .04). FIT positivity in participants with adenoma was associated with pedunculated shape (p = .007) and high-risk dysplasia (p = .009). Conclusions: In an average-risk colonoscopy screening cohort of 60-year-olds, sensitivity for AN was modest and did not increase when using two samples instead of one. FIT predominantly detected adenomas with pedunculated shape and high-risk dysplasia, and participants with flat or broad based adenomas may thus be missed in screening.
Optimal Real-Time Operation Strategy for Microgrid: An ADP-Based Stochastic Nonlinear Optimization Approach

This paper proposes an approximate dynamic programming (ADP) based algorithm for the real-time operation of the microgrid under uncertainties. First, the optimal operation of the microgrid is formulated as a stochastic mixed-integer nonlinear programming (MINLP) problem, combining the ac power flow and the detailed operational character of the battery. For this NP-hard problem, the proposed ADP based energy management algorithm decomposes the original multitime periods MINLP problem into single-time period nonlinear programming problems. Thus, the sequential decisions can be made by solving Bellman's equation. Historical data is utilized offline to improve the optimality of the real-time decision, and the dependency on the forecast information is reduced. Comparative numerical simulations with several existing methods demonstrate the effectiveness and efficiency of the proposed algorithm.
$M$-Channel Critically Sampled Spectral Graph Filter Banks With Symmetric Structure

This letter proposes a class of $M$-channel spectral graph filter banks with a symmetric structure, that is, the transform has sampling operations and spectral graph filters on both the analysis and synthesis sides. The filter banks achieve maximum decimation, perfect recovery, and orthogonality. The proposed transform uses sampling in the graph frequency domain. This enables us to use any variation operators and apply the transforms to arbitrary graphs even when the filter banks have symmetric structures. We clarify the perfect reconstruction conditions and show design examples. An experiment on graph signal denoising conducted to examine the performance of the proposed filter bank is described.
Statistical significance and scientific misconduct: improving the style of the published research paper

Abstract A science, business, or law that is basing its validity on the level of p-values, t statistics and other tests of statistical significance is looking less and less relevant and more and more unethical. Today’s economist uses a lot of wit putting a clever index of opportunity cost into his models; but then, like the amnesiac, he fails to see opportunity cost in statistical estimates he makes of those same models. Medicine, psychology, pharmacology and other fields are similarly damaged by this fundamental error of science, keeping bad treatments on the market and good ones out. A few small changes to the style of the published research paper using statistical methods can bring large beneficial effects to more than academic research papers. It is suggested that misuse of statistical significance be added to the definition of scientific misconduct currently enforced by the NIH, NSF, Office of Research Integrity and others.
Socioemotional selectivity and psychological health in amyotrophic lateral sclerosis patients and caregivers: a longitudinal, dyadic analysis

Abstract Objective: Socioemotional selectivity theory predicts that as the end of life approaches, goals and resources that provide immediate, hedonic reward become more important than those that provide delayed rewards. This study tested whether these goal domains differentially affected psychological health in the context of marital dyads in which one partner had been diagnosed with amyotrophic lateral sclerosis (ALS), a life-limiting disease. Design: ALS patients (N = 102) being treated in three multidisciplinary clinics and their spouses (N = 100) reported their loneliness, financial worry and psychological health every 3 months for up to 18 months. Main Outcome Measure: Psychological health composite. Results: In multilevel dyadic models, patients and spouses had similar levels of financial worry and loneliness. Both patients and spouses had worse psychological health with higher loneliness, but only spouses had worse psychological health with higher financial worry. Significant interactions with age and disease severity indicated that older spouses were more affected by loneliness than were younger spouses, and patients with less severe disease were more affected by financial worry than patients with more severe disease. Conclusion: The results provide good support for socioemotional selectivity theory’s implications for psychological health in a strong test of the theory.
Utility-Oriented Online Load Restoration Considering Wind Power Penetration

An efficient load recovery of a bulk system with wind power penetration requires careful consideration of uncertainties related to it, as well as online data gathered from measurement devices. From the perspective of uncertainties, a novel utility-based decision-making method is proposed in this paper. The method combines both risk and return of the load restoration strategy to assist decision making in uncertain states, and it also provides a utility function to present the preference of the load restoration strategy. Furthermore, a utility-oriented optimization model is created to select the strategy with the largest utility value with a certain confidence level. To achieve efficient utilization of online data, as well as to ensure high computation efficiency, the utility-oriented optimization is transformed into a scenario-based linear programming model. The proposed method fills the gap between online data and the optimal load restoration strategy in an uncertain condition. Besides, the optimal strategy is provided with adjustable robustness according to security requirements and data exactness. Therefore, it is particularly applicable for online load restoration with wind power penetration. The effectiveness of the proposed method is validated using the IEEE-30 bus test system and an actual power system from the North-East of Shandong province, China.
HERBS I: Metallicity and alpha enhancement along the Galactic bulge minor axis

To better understand the origin and evolution of the Milky Way bulge, we have conducted a survey of bulge red giant branch and clump stars using the High Efficiency and Resolution Multi-Element Spectrograph on the Anglo–Australian Telescope. We targeted ARGOS survey stars with predetermined bulge memberships, covering the full metallicity distribution function. The spectra have signal-to-noise ratios comparable to, and were analysed using the same methods as the GALAH survey. In this work, we present the survey design, stellar parameters, distribution of metallicity, and alpha-element abundances along the minor bulge axis at latitudes b = −10°, − 7.5°, and −5°. Our analysis of ARGOS stars indicates that the centroids of ARGOS metallicity components should be located ≈0.09 dex closer together. The vertical distribution of α-element abundances is consistent with the varying contributions of the different metallicity components. Closer to the plane, alpha abundance ratios are lower as the metal-rich population dominates. At higher latitudes, the alpha abundance ratios increase as the number of metal-poor stars increases. However, we find that the trend of alpha-enrichment with respect to metallicity is independent of latitude. Comparison of our results with those of GALAH DR2 revealed that for [Fe/H] ≈ −0.8, the bulge shares the same abundance trend as the high-α disc population. However, the metal-poor bulge population ([Fe/H] ≲ −0.8) show enhanced alpha abundance ratios compared to the disc/halo. These observations point to fairly rapid chemical evolution in the bulge, and that the metal-poor bulge population does not share the same similarity with the disc as the more metal-rich populations.
Re‐reading of OraQuick HIV‐1/2 rapid antibody test results: quality assurance implications for HIV self‐testing programmes

Scale‐up of HIV self‐testing (HIVST) will play a key role in meeting the United Nation's 90‐90‐90 targets. Delayed re‐reading of used HIVST devices has been used by early implementation studies to validate the performance of self‐test kits and to estimate HIV positivity among self‐testers. We investigated the stability of results on used devices under controlled conditions to assess its potential as a quality assurance approach for HIVST scale‐up.
Approximate Query Processing using Deep Generative Models

Data is generated at an unprecedented rate surpassing our ability to analyze them. The database community has pioneered many novel techniques for Approximate Query Processing (AQP) that could give approximate results in a fraction of time needed for computing exact results. In this work, we explore the usage of deep learning (DL) for answering aggregate queries specifically for interactive applications such as data exploration and visualization. We use deep generative models, an unsupervised learning based approach, to learn the data distribution faithfully such that aggregate queries could be answered approximately by generating samples from the learned model. The model is often compact - few hundred KBs - so that arbitrary AQP queries could be answered on the client side without contacting the database server. Our other contributions include identifying model bias and minimizing it through a rejection sampling based approach and an algorithm to build model ensembles for AQP for improved accuracy. Our extensive experiments show that our proposed approach can provide answers with high accuracy and low latency.
Optimizing Network Slice Dimensioning via Resource Pricing

Network slicing has been viewed as a key enabler for the next-generation software-defined and cloud-based network (e.g., 5G and beyond) to accommodate diverse services in a flexible and cost-efficient fashion. Network slicing allows a network slice provider (NSP) to operate on a common network infrastructure to create customized isolated logical networks (i.e., network slices) for network slice customers (NSCs), (i.e., service providers). NSP and NSCs are independent operators who pursue profit maximization, while in the literature, only network cost optimization is intensively investigated in terms of service function chain embedding, i.e., virtual network function (VNF) placement and flow routing. Therefore, slices should be dimensioned (i.e., resources allocated to slices) according to the resource availability and the economic mechanism in the network, so as to optimize the resource utilization and improve the profit of NSP/NSCs. In this paper, we study elastic slice dimensioning with resource pricing as a Stackelberg pricing game, in which the NSP sells slices by pricing resources and NSCs adjust their slice’s resource demand on VNF capacity and bandwidth, while both are trying to maximize their profit. Then, we formulate optimization problems for the pricing game and find that a closed form solution of the optimal price cannot be obtained for a non-trivial network. Hence, we propose a resource pricing algorithm that aims to maximize the NSP’s profit and the network’s social welfare. Compared with existing usage-based pricing method and two heuristic methods, our proposed pricing algorithm for slice dimensioning strikes a trade-off between maximizing NSP’s profit and other metrics, including the resource utilization. Hence, it will helpfully exploiting the benefits of network slicing.
Community HIV Screening among MSM in Three Indonesian Cities.

BACKGROUND Indonesia lags its peers with regard to ART coverage of PLHIV. Insufficient HIV testing among MSM and other key affected populations remains a barrier to increasing ART coverage. OBJECTIVE This report presents the results of the first government-endorsed implementation research study of a community screening approach to increasing the rate of HIV testing among MSM in three cities. METHODS All new MSM outreach contacts meeting eligibility criteria during March-June 2017 were included in the study. HIV testing at a government health facility, which is required to qualify for government-supported ART, was advised for all new contacts. Men refusing formal testing were offered a HIV screening test in a community setting using a saliva-based rapid test and advised to get a confirmatory test at a health facility. All outreach contacts and testing activities were recorded on individual client records. RESULTS Of 1,149 eligible MSM, 27% were willing to be referred to receive HIV testing at a health facility, among which 83% were confirmed to have tested. Of the 838 study subjects refusing health facility testing, 38% accepted community screening. The screening positivity rate was 14.8%. Only 38% of men with reactive screening tests received a confirmatory test at a health facility, along with 8% of those with non-reactive tests. CONCLUSION While community screening resulted in more MSM knowing their HIV status, reluctance avail of government health facility-based services, or indeed to be tested at all, must be addressed if community screening is to accelerate progress in getting HIV-positive MSM onto treatment.
A Gramian Description of the Degree 4 Generalized Elliptope

One of the most widely studied convex relaxations in combinatorial optimization is the relaxation of the cut polytope $\mathscr C^N$ to the elliptope $\mathscr E^N$, which corresponds to the degree 2 sum-of-squares (SOS) relaxation of optimizing a quadratic form over the hypercube $\{\pm 1\}^N$. We study the extension of this classical idea to degree 4 SOS, which gives an intermediate relaxation we call the degree 4 generalized elliptope $\mathscr E_4^N$. Our main result is a necessary and sufficient condition for the Gram matrix of a collection of vectors to belong to $\mathscr E_4^N$. Consequences include a tight rank inequality between degree 2 and degree 4 pseudomoment matrices, and a guarantee that the only extreme points of $\mathscr E^N$ also in $\mathscr E_4^N$ are the cut matrices; that is, $\mathscr E^N$ and $\mathscr E_4^N$ share no "spurious" extreme point. For Gram matrices of equiangular tight frames, we give a simple criterion for membership in $\mathscr{E}_4^N$. This yields new inequalities satisfied in $\mathscr{E}_4^N$ but not $\mathscr{E}^N$ whose structure is related to the Schlafli graph and which cannot be obtained as linear combinations of triangle inequalities. We also give a new proof of the restriction to degree 4 of a result of Laurent showing that $\mathscr{E}_4^N$ does not satisfy certain cut polytope inequalities capturing parity constraints. Though limited to this special case, our proof of the positive semidefiniteness of Laurent's pseudomoment matrix is short and elementary. Our techniques also suggest that membership in $\mathscr{E}_4^N$ is closely related to the partial transpose operation on block matrices, which has previously played an important role in the study of quantum entanglement. To illustrate, we present a correspondence between certain entangled bipartite quantum states and the matrices of $\mathscr{E}_4^N\setminus\mathscr{C}^N$.