Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Fast Algorithm for Linearly Unmixing Hyperspectral Images

Linear spectral unmixing is nowadays an essential tool to analyze remotely sensed hyperspectral images. Although many different contributions have been uncovered during the last two decades, the majority of them are based on dividing the whole process of linearly unmixing a given hyperspectral image into three sequential steps: 1) estimation of the number of endmembers that are present in the hyperspectral image under consideration; 2) extraction of these endmembers from the hyperspectral data set; and 3) calculation of the abundances associated with the endmembers induced in the previous step per each mixed pixel of the image. Although this de facto processing chain has proven to be accurate enough for unmixing most of the images collected by hyperspectral remote sensors, it is also true that it is not exempt of drawbacks, such as the fact that all the possible combinations of algorithms in order to fully unmix a hyperspectral image according to the aforementioned processing chain demand a formidable computational effort, which tends to be higher the better the performance of the designed unmixing chain is. This troublesome issue unfortunately prevents the use of hyperspectral imaging technology in applications under real-time constraints, in which hyperspectral images have to be analyzed in a short period of time. Hence, there is a clear need to face the challenge of fully exploiting the unquestionable benefits of the hyperspectral imaging technology for these applications, but concurrently overcoming the limitations imposed by the computationally complex nature of the processes involved. For this purpose, this paper introduces a novel algorithm named fast algorithm for linearly unmixing hyperspectral images (FUN), which is capable of fully unmixing a hyperspectral image with at least the same accuracy than state-of-the-art approaches while demanding a much lower computational effort, independent of the characteristics of the image under analysis. The FUN algorithm is based on the concept of orthogonal projections and allows performing the estimation of the number of endmembers and their extraction simultaneously, using the modified Gram-Schmidt method. The operations performed by the FUN algorithm are simple and can be easily parallelized. Moreover, this algorithm is able to calculate the abundances using very similar operations, also based on orthogonal projections, which makes it easier to achieve a hardware implementation to perform the entire unmixing process. The benefits of our proposal are demonstrated with a diverse set of artificially generated hyperspectral images and with the well-known AVIRIS Cuprite image, for which the proposed FUN algorithm is able to reduce in a factor of more than 31 times the time required for processing it, while providing a better unmixing performance than traditional methods.
Sequential Randomized Matrix Factorization for Gaussian Processes: Efficient Predictions and Hyper-parameter Optimization

This paper presents a sequential randomized lowrank matrix factorization approach for incrementally predicting values of an unknown function at test points using the Gaussian Processes framework. It is well-known that in the Gaussian processes framework, the computational bottlenecks are the inversion of the (regularized) kernel matrix and the computation of the hyper-parameters defining the kernel. The main contributions of this paper are two-fold. First, we formalize an approach to compute the inverse of the kernel matrix using randomized matrix factorization algorithms in a streaming scenario, i.e., data is generated incrementally over time. The metrics of accuracy and computational efficiency of the proposed method are compared against a batch approach based on use of randomized matrix factorization and an existing streaming approach based on approximating the Gaussian process by a finite set of basis vectors. Second, we extend the sequential factorization approach to a class of kernel functions for which the hyperparameters can be efficiently optimized. All results are demonstrated on two publicly available datasets.
Differentiation of eleven Fusarium spp. isolated from sugar beet, using restriction fragment analysis of a polymerase chain reaction-amplified translation elongation factor 1alpha gene fragment.

Sugar beet in Europe is commonly grown in wheat and maize crop rotations and subsequently pile-stored for several weeks. Beet is threatened by the colonization of saprophytic as well as pathogenic Fusarium spp. A tool for reliable identification based on sequence information of the translation elongation factor 1alpha (TEF-1alpha) gene was developed for the numerous Fusarium spp. being isolated from sugar beets. In all, 65 isolates from different species (Fusarium avenaceum, F. cerealis, F. culmorum, F. equiseti, F. graminearum, F. oxysporum, F. proliferatum, F. redolens, F. solani, F. tricinctum, and F. venenatum) were obtained from sugar beet at different developmental stages from locations worldwide. Database sequences for additional species (F. sporotrichioides, F. poae, F. torulosum, F. hostae, F. sambucinum, F. subglutinans, and F. verticillioides), isolated from sugar beets in previous studies, were included in the analysis. Molecular sequence analysis of the partial TEF-1alpha gene fragment revealed sufficient variability to differentiate between the Fusarium spp. , resulting in species-dependent separation of the isolates analyzed. This interspecific divergence could be translated into a polymerase chain reaction restriction fragment length polymorphism assay using only two subsequent restriction digests for the differentiation of 17 of 18 species.
Tension Force-Induced ATP Promotes Osteogenesis Through P2X7 Receptor in Osteoblasts

Orthodontic tooth movement induces alveolar bone resorption and formation by mechanical stimuli. Force exerted on the traction side promotes bone formation. Adenosine triphosphate (ATP) is one of the key mediators that respond to bone cells by mechanical stimuli. However, the effect of tension force (TF)‐induced ATP on osteogenesis is inadequately understood. Accordingly, we investigated the effect of TF on ATP production and osteogenesis in MC3T3‐E1 cells. Cells were incubated in the presence or absence of P2X7 receptor antagonist A438079, and then stimulated with or without cyclic TF (6% or 18%) for a maximum of 24 h using Flexercell Strain Unit 3000. TF significantly increased extracellular ATP release compared to control. Six percent TF had maximum effect on ATP release compared to 18% TF and control. Six percent TF induced the expression of Runx2 and Osterix. Six percent TF also increased the expression of extracellular matrix proteins (ECMPs), ALP activity, and the calcium content in ECM. A438079 blocked the stimulatory effect of 6% TF on the expression of Runx2, Osterix and ECMPs, ALP activity, and calcium content in ECM. This study indicated that TF‐induced extracellular ATP is released in osteoblasts, suggesting that TF‐induced ATP promotes osteogenesis by autocrine action through P2X7 receptor in osteoblasts. J. Cell. Biochem. 116: 12–21, 2015. © 2014 The Authors. Journal of Cellular Biochemistry published by Wiley Periodicals, Inc.
Pastoral aspects of educational leadership: a phenomenological approach

This phenomenological study has sought to discover the types of behaviors school principals engage in that could be considered pastoral in nature. Four practicing principals were interviewed with this in mind. The participants were selected for their experiences, according to their superintendents, of having dealt effectively with crises. Their actions and responses to the needs of staff, students, evidenced pastoral aspects of educational leadership. It is the conclusion of this study that their work in this regard is an ongoing and intentional practice worthy of future study.
A Constant Factor Localized Algorithm for Computing Connected Dominating Sets in Wireless Sensor Networks

Connected dominating sets (CDSs) are probably the most common way of constructing virtual backbones for broadcasting operation in wireless sensor networks. This is because such backbones guarantee to reduce unnecessary message transmissions or flooding in the network. In this paper we propose a simple localized algorithm to construct a small-sized CDS. Considering the sensors deployed in the plane, our main idea is based on the computation of convex hulls of sensor nodes (nodes are considered points in the plane) in a localized manner and a simple coloring scheme, which produces a CDS in unit disk graphs whose size is at most 38*|MCDS| where |MCDS| is the size of a minimum CDS. To the best of our knowledge, this is a significant improvement over the best published results in the same context [5]. We also analyze grids and trees to compute the exact approximation ratios for the problem. We show that our algorithm produces an optimal CDS if the graph is a tree and in the case of grids the approximation factor is 2.
The efficacy and safety of nivolumab in previously treated advanced non-small-cell lung cancer: a meta-analysis of prospective clinical trials

Background Nivolumab (BMS-936558/ONO-4538) was the first monoclonal antibody targeting programmed death (PD)-1. So far, a number of clinical trials on nivolumab have showed satisfactory efficacy in treating non-small-cell lung cancer (NSCLC). Herein, we present a meta-analysis evaluating the efficacy and safety of nivolumab for previously treated advanced NSCLC patients. Methods Electronic databases were searched for eligible literature. Data of objective response rate (ORR), disease control rate, overall survival, progression-free survival, and adverse effects (AEs) were extracted and pooled. Outcomes analyzed and presented in this study were according to the original data from nivolumab 3 mg/kg. Results In general, nine trials with 817 patients were included in this meta-analysis. The pooled ORR, disease control rate, 1-year overall survival rate, and 1-year progression-free survival rate were 20% (95% confidence interval [CI]: 17%–23%), 36% (95% CI: 22%–51%), 47% (95% CI: 40%–53%), 21% (95% CI: 18%–24%), respectively. In addition, the rate of grade 3–4 AEs was only 8% (95% CI: 6%–12%). Subgroup analysis showed no significant difference in terms of ORR between squamous and non-squamous NSCLC (odds ratio 1.23, 95% CI: 0.63–2.39, P=0.51). However, significantly greater ORR was presented in programmed cell death ligand 1 (PD-L1) positive cohort (ORR 31%, 95% CI: 24%–38%), compared to PD-L1 negative cohort (ORR 12%, 95% CI: 9%–17%). The odds ratio for objective response to nivolumab in PD-L1 positive cases relative to negative cases was 3.08 (95% CI: 1.87–5.08, P<0.0001). Conclusion In conclusion, nivolumab is a promising second-line agent for previously treated advanced NSCLC with manageable AEs. Both squamous and non-squamous NSCLC patients showed similar efficacy. In addition, patients with positive PD-L1 expression had better response from nivolumab. Microabstract We present a meta-analysis evaluating the efficacy and safety of nivolumab for previously treated advanced NSCLC patients. In our study, nivolumab is a promising second-line agent for previously treated advanced NSCLC with manageable AEs. Both squamous and non-squamous NSCLC patients showed similar efficacy. In addition, patients with positive PD-L1 expression had better response from nivolumab.
Conventional QT Variability Measurement vs. Template Matching Techniques: Comparison of Performance Using Simulated and Real ECG

Increased beat-to-beat variability in the QT interval (QTV) of ECG has been associated with increased risk for sudden cardiac death, but its measurement is technically challenging and currently not standardized. The aim of this study was to investigate the performance of commonly used beat-to-beat QT interval measurement algorithms. Three different methods (conventional, template stretching and template time shifting) were subjected to simulated data featuring typical ECG recording issues (broadband noise, baseline wander, amplitude modulation) and real short-term ECG of patients before and after infusion of sotalol, a QT interval prolonging drug. Among the three algorithms, the conventional algorithm was most susceptible to noise whereas the template time shifting algorithm showed superior overall performance on simulated and real ECG. None of the algorithms was able to detect increased beat-to-beat QT interval variability after sotalol infusion despite marked prolongation of the average QT interval. The QTV estimates of all three algorithms were inversely correlated with the amplitude of the T wave. In conclusion, template matching algorithms, in particular the time shifting algorithm, are recommended for beat-to-beat variability measurement of QT interval in body surface ECG. Recording noise, T wave amplitude and the beat-rejection strategy are important factors of QTV measurement and require further investigation.
CODI: Combinatorial Optimization for Data Integration: results for OAEI 2011

In this paper, we describe our probabilistic-logical alignment system CODI (Combinatorial Optimization for Data Integration). The system provides a declarative framework for the alignment of individuals, concepts, and properties of two heterogeneous ontologies. CODI leverages both logical schema information and lexical similarity measures with a well-defined semantics for A-Box and T-Box matching. The alignments are computed by solving corresponding combinatorial optimization problems.
A Comparative Study of Resource Allocation Schemes in Heterogeneous Cellular Networks on the Downlink

Network densification through heterogeneous networks (HetNets) is considered as a promising paradigm to address the ever increasing mobile users’ data demands in 5G networks. A HetNet consists of macro cells (each with a macro base station) overlaid with a number of small cells (each with a low-power base station) and has been shown to significantly improve the network capacity when supported by carefully designed radio resource management (RRM) techniques. RRM is typically studied via a joint optimisation problem over three network processes, namely, resource allocation (RA), user association (UA) and user scheduling (US), and is the focus of this thesis. Our first objective is to characterise the optimal HetNet performance by jointly optimising these three processes through a unified framework under different channel deployment scenarios. Towards this, we focus on two RA schemes, namely, partially shared deployment (PSD) and co-channel deployment with almost blank subframes (ABS), proposed by 3GPP for future HetNets. In the first part of the thesis, we revisit a unified optimisation framework under PSD that allows us to configure the network parameters (e.g., number of channels per-cell and power per-channel) and allocate optimal throughputs to users in a fair manner. The framework under consideration is based on a snapshot model where, in each snapshot, the number of users and channel gains are assumed to be fixed and known. Although the previous study on this framework provides many interesting engineering insights, it is primarily based on two wrong assumptions in terms of channel modelling and US which we correct in our work. We also revisit a similar framework but under ABS and conduct a thorough comparative study between ABS and PSD. We first show that the α−fair scheduling problem under ABS is generally much more involved than that under PSD for α 6= 1. To verify whether the US complexities involved from deploying ABS are justifiable, we compare the throughput performance of the two schemes under a static setting, where the number of users in each snapshot is assumed to be fixed. Our results indicate that PSD outperforms ABS for different choices of α and under different HetNet configurations. In the second part of the thesis, we further study our frameworks under a dynamic
Faster autotrophic growth of anaerobic ammonium-oxidizing microorganisms in presence of nitrite, using inocula from Colombia Crecimiento rápido autotrófico de microorganismos anaerobios oxidadores de amonio en presencia de nitrito, usando inóculos de Colombia

Summary Anammox is a nitrite dependent process, catalyzed by bacteria of the order Brocadiales. Anammox bacteria oxidize ammonia under anoxic conditions, with nitrite as electron acceptor producing dinitrogen gas. Here, we demonstrated the presence of anammox bacteria by enriched them in a SBR reactor, with anaerobic samples taken from de bottom of a pond used in primary wastewater treatment. The enrichment reached nitrogen (N) removal rates of nearly 1.92kg N/m3/day. (The stoichiometry of the reaction matched previous anammox studies). The enriched bacterial communities were analyzed by Fluorescence In situ Hybridization (FISH), and showed a nearly 90% enrichment at the end of the experiment (day 90). As far as we know this is the first time that the anammox bacteria were enriched using Colombian inocula. The enrichment was achieved in relatively short time with high yields and have an excellent potential for application in wastewater treatment opening the opportunity to treat nitrogen-rich effluents by partial nitritation and anammox, thereby decreasing operational costs with respect to aeration (nitrification) and addition of organic electron donor (heterotrophic denitrification). This more sustainable treatment is a good alternative to control nutrient pollution in water bodies in tropical countries.
Low-Level Laser Therapy Attenuates LPS-Induced Rats Mastitis by Inhibiting Polymorphonuclear Neutrophil Adhesion

ABSTRACT The aim of this study was to investigate the effects of low-level laser therapy (LLLT) on a rat model of lipopolysaccharide (LPS)-induced mastitis and its underlying molecular mechanisms. The rat model of mastitis was induced by inoculation of LPS through the canals of the mammary gland. The results showed that LPS-induced secretion of IL-1β and IL-8 significantly decreased after LLLT (650 nm, 2.5 mW, 30 mW/cm2). LLLT also inhibited intercellular adhesion molecule-1 (ICAM-1) expression and attenuated the LPS-induced decrease of the expression of CD62L and increase of the expression of CD11b. Moreover, LLLT also suppressed LPS-induced polymorphonuclear neutrophils (PMNs) entering the alveoli of the mammary gland. The number of PMNs in the mammary alveolus and the myeloperoxidase (MPO) activity were decreased after LLLT. These results suggested that LLLT therapy is beneficial in decreasing the somatic cell count and improving milk nutritional quality in cows with an intramammary infection.
Effect of a single and repeated stress exposure on gene expression of catecholamine biosynthetic enzymes in brainstem catecholaminergic cell groups in rats

Brainstem catecholaminergic neurons significantly participate in the regulation of neuroendocrine system activity, particularly during stressful conditions. However, so far the precise quantitative characterisation of basal and stress‐induced changes in gene expression and protein levels of catecholaminergic biosynthetic enzymes in these neurons has been missing. Using a quantitative reverse transcription‐polymerase chain reaction method, we investigated gene expression of catecholamine biosynthetic enzymes in brainstem noradrenergic and adrenergic cell groups in rats under resting conditions as well as in acutely and repeatedly stressed animals. For the first time, we described quantitative differences in basal levels of catecholamine biosynthetic enzyme mRNA in brainstem catecholaminergic ascending and descending projecting cell groups. Moreover, we found and defined some differences among catecholaminergic cell groups in the time‐course of mRNA levels of catecholaminergic enzymes following a single and especially repeated immobilisation stress. The data obtained support the assumption that brainstem catecholaminergic cell groups represent a functionally differentiated system, which is highly (but specifically) activated in rats exposed to stress. Therefore, potential interventions for the treatment of stress‐related diseases need to affect the activity of brainstem catecholaminergic neurons not uniformly but with some degree of selectivity.
A state action frequency approach to throughput maximization over uncertain wireless channels

We consider scheduling over a wireless system, where the channel state information is not available a priori to the scheduler, but can be inferred from the past. Specifically, the wireless system is modeled as a network of parallel queues. We assume that the channel state of each queue evolves stochastically as an ON/OFF Markov chain. The scheduler, which is aware of the queue lengths but is oblivious of the channel states, has to choose one queue at a time for transmission. The scheduler has no information regarding the current channel states, but can estimate them by using the acknowledgment history. We first characterize the capacity region of the system using tools from Markov Decision Processes (MDP) theory. Specifically, we prove that the capacity region boundary is the uniform limit of a sequence of Linear Programming (LP) solutions. Next, we combine the LP solution with a queue length based scheduling mechanism that operates over long ‘frames,’ to obtain a throughput optimal policy for the system. By incorporating results from MDP theory within the Lyapunov-stability framework, we show that our frame-based policy stabilizes the system for all arrival rates that lie in the interior of the capacity region.
Exploiting facial expressions for affective video summarisation

This paper presents an approach to affective video summarisation based on the facial expressions (FX) of viewers. A facial expression recognition system was deployed to capture a viewer's face and his/her expressions. The user's facial expressions were analysed to infer personalised affective scenes from videos. We proposed two models, pronounced level and expression's change rate, to generate affective summaries using the FX data. Our result suggested that FX can be a promising source to exploit for affective video summaries that can be tailored to individual preferences.
Nursing Staff Reductions in Pennsylvania Hospitals: Exploring the Discrepancy between Perceptions and Data

Previous research has not confirmed public and practitioner perceptions of a decline in hospital nurse staffing. One reason for this discrepancy is that aggregate or mean values may not be an accurate description of the situation in a sizable percentage of hospitals. This article calculates the mean percentage change in various measures of nursing staff in Pennsylvania hospitals, 1991-1997, and the percentage of hospitals that experienced various degrees of this change. Major findings are that the means of changes in nursing staff understate the declines. When adjusted for patient severity and outpatient care, 50 percent of the hospitals experienced large decreases in RNs per patient days of care, 70 percent had large decreases in LPNs per patient days of care, and 56 percent had large declines in licensed nurses per patient days of care. Overall, the findings support perceptions of a decline in licensed nurse staffing. Policy implications are discussed.