Miracle-dz/UniFAR-FTUs huggingface dataset:
Topological weighted fisher vectors for person re-identification

Person re-identification is a fundamental challenging task in Computer Vision that consists on recognizing the same person across multiple potentially non-overlapping cameras. This importance is due to the important challenges that it proposes like pose, background clutter and occlusion, illumination changes and low resolution. Also, most of the existing approaches rely on brute-force matching between pedestrian local descriptors and consequently, suffer from low computational efficiency. So, to address this issues, we present a new perspective for person re-identification based on a histogram encoding scheme that assigns a global signature to each pedestrian image and thus, simplifies the matching process. The main contribution of this paper is the design of an extended weighted version of the traditional Fisher vector (FV) encoding scheme. This is achieved by incorporating the Topological location of the encoded descriptors CN, CHS and 15-d in the encoding process and then combining the obtained Topological weighted histograms in order to form our proposed descriptor. The super Fisher vector representation has improved both the rate and the speedup of the person matching process, while weighting the FV encoding scheme by the Topological weight helped out to remove the noisy and busy background clutters surrounding the pedestrians in the images. Besides, Retinex transform was applied in order to handle the problem of illumination variations. Experimental results made on three challenging datasets, the VIPeR dataset, the CUHK03 dataset and the Market-1501 dataset, prove the effectiveness of the proposed method.
Specialist Nurse Screening for Retinopathy of Prematurity—A Pilot Study

PurposeTo compare the accuracy of retinopathy of prematurity (ROP) screening between nurse specialists and an expert pediatric ophthalmologist. DesignA comparative case series of ROP screening in a level 2 neonatal intensive care unit setting where there is a higher threshold for accepting very premature or unwell neonates. MethodsTrained specialist ROP nurses acquired wide-field digital images, graded ROP, and proposed a follow-up plan. This was compared with the findings by an ROP expert ophthalmologist. Outcomes include sensitivity, specificity, positive predictive value, and negative predictive value of ROP grading by trained ROP nurses. ResultsMean gestational age was 28.6 weeks, and mean birth weight was 1184 g of the 64 consecutive neonates included. A total 316 eye screens was performed. Image acquisition, grading, and a management plan by the ROP nurse were possible in all screens. In right eyes, the presence of any ROP (stage >0) was 15%. Sensitivity, specificity, positive predictive value, and negative predictive value of ROP grading were 91.7% (95% CI, 73%–99%), 80.6% (95% CI, 72.9%–86.9%), 45.8% (95% CI, 31.4%–60.80%), and 98.2% (95% CI, 93.6%–99.8%), respectively. Agreement on the management plan occurred in 84.8% of cases. In virtually all circumstances of disagreement, ROP nurses exaggerated the ROP grading present and/or recommended a repeat screen when discharge from service was more appropriate. ConclusionsOur preliminary findings demonstrated good agreement between ROP nurses and the ROP expert ophthalmologist. Further research in expanding the role of utilizing nonphysician health workers in ROP screening is suggested.
The Efficient Maintenance of Access Roles with Role Hiding

Role-based access control (RBAC) has attracted considerable research interest. However, the computational issues of RBAC models are yet to be thoroughly studied. In this paper, we study the problem of efficient maintenance of large RBAC models in a database-based multi-domain Web service environment. We propose first-order (SQL) algorithms to maintain the reachability of access roles under dynamic changes. The main advantages of our algorithms are: the support of various operations required for managing access roles with fractional information of roles; the maintenance of an update through operating a bounded number of join operations despite of the data size. To the best of our knowledge, our algorithms are the first attempt to maintain RBAC models using a first-order language.
Direct Fourier Reconstruction in Fan-Beam Tomography

We consider the problem of reconstructing tomographic imagery from fan-beam projections using the direct Fourier method (DFM). Previous DFM reconstructions from parallel-beam projections produced images of quality comparable to that of filtered convolution back-projection. Moreover, the number of operations using DFM in the parallel-beam case is proportional to N2 log N versus N3 for back projection [3]. The fan-beam case is more complicated because additional interpolation of the nonuniformly spaced rebinned data is required. We derive bounds on the detector spacing in fan-beam CT that enable direct Fourier reconstruction and describe the full algorithm necessary for processing the fan-beam data. The feasibility of the method is demonstrated with an example. A key result of this paper is that high-quality imagery can be reconstructed from fan-beam data using the DFM in 0 (N2 log N) operations.
Effect of 4‐methoxy 1‐methyl 2‐oxopyridine 3‐carbamide on Staphylococcus aureus by inhibiting UDP‐MurNAc‐pentapeptide, peptidyl deformylase and uridine monophosphate kinase

The present study aimed to investigate the anti‐Staphylococcus aureus and anti‐biofilm properties of 4‐methoxy‐1‐methyl‐2‐oxopyridine‐3‐carbamide (MMOXC) on S. aureus UDP‐MurNAc‐pentapeptide (MurF), peptidyl deformylase (PDF) and uridine monophosphate kinase (UMPK).
A universal hypercomplex color image quality index

In this paper, a color image is represented by a hypercomplex matrix. A universal objective hypercomplex color image quality index is then presented. The proposed index is designed by modeling any color image distortion as a combination of five different factors: loss of correlation, luminance distortion, contrast distortion, color distortion, and intercomponent distortion among the red (R), green (G), and blue (B) components. The analytical results show that the proposed index can measure whether the distortion types are from the structural and/or color information of a color image. The experiments indicate that the proposed index is in agreement with the subjective visual perception of human beings.
Exploring Regulation Genes Involved in the Expression of L-Amino Acid Oxidase in Pseudoalteromonas sp. Rf-1

Bacterial L-amino acid oxidase (LAAO) is believed to play important biological and ecological roles in marine niches, thus attracting increasing attention to understand the regulation mechanisms underlying its production. In this study, we investigated genes involved in LAAO production in marine bacterium Pseudoalteromonas sp. Rf-1 using transposon mutagenesis. Of more than 4,000 mutants screened, 15 mutants showed significant changes in LAAO activity. Desired transposon insertion was confirmed in 12 mutants, in which disrupted genes and corresponding functionswere identified. Analysis of LAAO activity and lao gene expression revealed that GntR family transcriptional regulator, methylase, non-ribosomal peptide synthetase, TonB-dependent heme-receptor family, Na+/H+ antiporter and related arsenite permease, N-acetyltransferase GCN5, Ketol-acid reductoisomerase and SAM-dependent methytransferase, and their coding genes may be involved in either upregulation or downregulation pathway at transcriptional, posttranscriptional, translational and/or posttranslational level. The nhaD and sdmT genes were separately complemented into the corresponding mutants with abolished LAAO-activity. The complementation of either gene can restore LAAO activity and lao gene expression, demonstrating their regulatory role in LAAO biosynthesis. This study provides, for the first time, insights into the molecular mechanisms regulating LAAO production in Pseudoalteromonas sp. Rf-1, which is important to better understand biological and ecological roles of LAAO.
Targeting Tumor Perfusion and Oxygenation to Improve the Outcome of Anticancer Therapy1

Radiotherapy and chemotherapy are widespread clinical modalities for cancer treatment. Among other biological influences, hypoxia is a main factor limiting the efficacy of radiotherapy, primarily because oxygen is involved in the stabilization of the DNA damage caused by ionizing radiations. Radiobiological hypoxia is found in regions of rodent and human tumors with a tissue oxygenation level below 10 mmHg at which tumor cells become increasingly resistant to radiation damage. Since hypoxic tumor cells remain clonogenic, their resistance to the treatment strongly influences the therapeutic outcome of radiotherapy. There is therefore an urgent need to identify adjuvant treatment modalities aimed to increase tumor pO2 at the time of radiotherapy. Since tumor hypoxia fundamentally results from an imbalance between oxygen delivery by poorly efficient blood vessels and oxygen consumption by tumor cells with high metabolic activities, two promising approaches are those targeting vascular reactivity and tumor cell respiration. This review summarizes the current knowledge about the development and use of tumor-selective vasodilators, inhibitors of tumor cell respiration, and drugs and treatments combining both activities in the context of tumor sensitization to X-ray radiotherapy. Tumor-selective vasodilation may also be used to improve the delivery of circulating anticancer agents to tumors. Imaging tumor perfusion and oxygenation is of importance not only for the development and validation of such combination treatments, but also to determine which patients could benefit from the therapy. Numerous techniques have been developed in the preclinical setting. Hence, this review also briefly describes both magnetic resonance and non-magnetic resonance in vivo methods and compares them in terms of sensitivity, quantitative or semi-quantitative properties, temporal, and spatial resolutions, as well as translational aspects.
John Dewey and Education Outdoors: Making Sense of the 'Educational Situation' through more than a Century of Progressive Reforms

In this book we take the reader on a journey through the various curriculum reforms that have emerged in the USA around the idea of conducting education outdoors – through initiatives such as nature-study, camping education, adventure education, environmental education, experiential education and place based education. This is a historical journey with an underlying message for educators, one we are able to illuminate through the educational theories of John Dewey. Central to this message is a deeper understanding of human experience as both aesthetic and reflective, leading to a more coherent comprehension of not just outdoor education, but of education itself.
Linking Neuronal and Behavioral Performance in a Reaction-Time Visual Detection Task

Perceptual decisions are likely to be based on signals that are provided by populations of neurons in early sensory cortical areas. How these neural responses are combined across neurons and over time to mediate behavior is unknown. To study the link between neural responses and perceptual decisions, we recorded the activity of single units (SU) and multiple units (MU) in the primary visual cortex (V1) of monkeys while they performed a reaction-time visual detection task. We then determined how well the target could be detected from these neural signals. We found that, on average, the detection sensitivities supported by SU and MU in V1 are comparable with the detection sensitivity of the monkey even when considering neural responses during brief temporal intervals (median duration, 137 ms) that ended shortly before the monkey's reaction time. However, we observed systematic differences between the overall shape of the neurometric functions and the monkey's psychometric functions. We also examined the quantitative relationship between SU and MU activity and found that MU responses are consistent with the sum of the responses of multiple SU, most of which have low stimulus selectivity. Finally, we found weak but significant trial-to-trial covariations between V1 activity and behavioral choices, demonstrating for the first time that choice probability can be observed at the earliest stages of cortical sensory processing. Together, these results suggest that the activity of a large population of V1 neurons is combined suboptimally by subsequent processing stages to mediate behavioral performance in visual detection tasks.
Minimum Expected Delay-Based Routing Protocol (MEDR) for Delay Tolerant Mobile Sensor Networks

It is a challenging work to develop efficient routing protocols for Delay Tolerant Mobile Sensor Networks (DTMSNs), which have several unique characteristics such as sensor mobility, intermittent connectivity, energy limit, and delay tolerability. In this paper, we propose a new routing protocol called Minimum Expected Delay-based Routing (MEDR) tailored for DTMSNs. MEDR achieves a good routing performance by finding and using the connected paths formed dynamically by mobile sensors. In MEDR, each sensor maintains two important parameters: Minimum Expected Delay (MED) and its expiration time. According to MED, messages will be delivered to the sensor that has at least a connected path with their hosting nodes, and has the shortest expected delay to communication directly with the sink node. Because of the changing network topology, the path is fragile and volatile, so we use the expiration time of MED to indicate the valid time of the path, and avoid wrong transmissions. Simulation results show that the proposed MEDR achieves a higher message delivery ratio with lower transmission overhead and data delivery delay than other DTMSN routing approaches.
Left Atrial Function as Assessed by Speckle-Tracking Echocardiography in Hypertension

AbstractWe investigated left atrial (LA) function in relation to hypertension using 2-dimensional speckle-tracking echocardiography (STE) in subjects with preserved left ventricular (LV) ejection fraction, while accounting for LA enlargement and LV mass and diastolic function.We performed standard 2-dimensional and Doppler echocardiography and LA volumetric measurements and STE strain imaging in hypertensive patients (systolic/diastolic blood pressure ≥140/90 mmHg, or use of antihypertensive drugs, n = 124) and age- and sex-matched normotensive subjects (n = 124). We measured the peak LA velocity, strain, and strain rate during systole and early and late diastole, respectively. We investigated the associations of interests in the presence or absence of LA enlargement (LA volume index ≥28 mL/m2). Hypertensive and normotensive subjects had similar LV ejection fraction and LA diameter (P ≥ 0.22). However, hypertensive compared with normotensive subjects had enlarged LV and impaired diastolic function, and had increased LA volumetric measurements and decreased LA emptying fractions (P < 0.0001). Hypertensive patients also had impaired LA function, as measured by STE velocity, strain, and strain rate in general and in the absence of LA enlargement (P < 0.0001). The differences in LA STE strain rate during LV systole and LA contraction between hypertension and normotension in the absence of LA enlargement remained statistically significant (P < 0.001), after adjustment for age, sex, and LV mass index and E/E’. Hypertension is associated with impaired LA function, as assessed by STE strain imaging technique, even before LA enlargement develops and after LV remodeling is accounted for.
The Reach of the Disposition Effect: Large Sample Evidence Across Investor Classes

We examine detailed daily Australian Stock Exchange share registry data for investors in IPO and index stocks between 1995 and 2000 and find that the 'disposition effect,' investors' reluctance to crystallize losses and relative eagerness to realize gains, is pervasive across investor classes. However, traders instigating larger investments tend to be affected less by the disposition bias. Our novel findings include that (a) the disposition effect ameliorates over time, being undetectable from around 200 trading days after purchase, (b) the 'house money' effect tempers the disposition effect, (c) shareholder loyalty schemes also partially offset investors' relative preference for selling winning stocks, and (d) the reversal of the disposition effect in June (the last month of the Australian tax year) does not occur among investors unable to take advantage of tax shields. In line with earlier research, our results support a tax-related explanation for the June effect rather than window dressing or momentum explanations. Finally, we confirm Odean's finding that the disposition effect is not driven by diversification motives, or by higher transaction costs associated with lower-priced stocks. Copyright (c) International Review of Finance Ltd. 2007.
Hierarchy of mesenchymal stem cells: Comparison of multipotentmesenchymal stromal cells with fibroblast colony forming units

The organization of the compartment of mesenchymal stem cells is still obscure. Two types of human stromal precursor cells are known. Both of them are analyzed in in vitro system: mesenchymal multipotent stromal cells (MMSC) and fibroblast colony forming units (CFU-F). The aim of this study was to compare the main characteristics of MMSC and CFU-F derived from the bone marrow of 24 healthy donors. Growth and differentiation parameters, as well as relative expression levels of different genes were analyzed in MMSC and CFU-F. MMSC were cultivated for 5 passages. CFU-F concentration was determined for each bone marrow sample. The data obtained demonstrated the heterogeneity and hierarchical organization of both studied populations of stromal precursor cells-MMSC and CFU-F. These two types of stromal precursor cells turned to be different in most parameters studied. Altogether MMSC seemed to be more immature cells than CFU-F and took up the higher position in hierarchical tree of mesenchymal stem cells. The rate of differentiation and proliferative potential decreased with the donor’s age in both populations MMSC and CFU-F.
Classification using Iterative Cross-Training Algorithm

The paper presents a generalization of Iterative Cross-Training algorithm (ICT) which was previously applied to Thai Web pages identification [1]. The main concept of ICT is to iteratively train two sub-classifiers by using unlabeled examples in crossing manner. In this paper, we extend the algorithm in order to classify Web pages into course or non-course ones, which is a more challenging problem. We compare ICT against Supervised Naïve Bayes classifier and Co-Training classifier. The experimental results show that ICT still preserves its robustness on this new problem’s characteristic.
Interactive Processing of Morphosyntactic Features in the Bilingual Lexicon

We investigated whether morphosyntactic representations in bilinguals’ native language become activated by form-related representations in their second language. Specifically, we examined whether, relative to English monolinguals, German-English bilinguals would exhibit a bias to initially interpret English nouns ending in –er as referring to a male due to the association of masculine gender with this ending in German. This question was tested by recording bilinguals' and monolinguals' eye movements as they read English sentences containing a stereotypically male, female, or neutral –er noun that was an antecedent of a gender-matching or –mismatching reflexive. The bias to initially interpret the –er nouns' referent as male was assessed by the size of the "mismatch effect" or the difference between the participants' total fixation duration on feminine versus masculine reflexives. The results showed a positive mismatch effect for both the bilinguals and monolinguals in the stereotypical male condition, no mismatch effect for either group in the neutral condition, and a mismatch effect only for the monolinguals in the stereotypical female condition. The results were simulated using a connectionist interactive activation model, and the implications for future study are discussed.
Epoetin alfa in the critically ill: What dose? Which route?

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A Research on Intrusion Detection Based on Support Vector Machines

Mass of the training samples and setting parameters of SVM artificially will affect badly the efficiency to find an optimal decision hyper plane for SVM. In this paper, FCM clustering algorithm and heuristic PSO algorithm are applied to Intrusion Detection. FCM clustering algorithm is designed to help SVM to find the optimal training samples from vast amounts of data; heuristic PSO algorithm is designed to find optimal parameters for SVM intelligently. The result of simulations run on the data of KDDCUP1999 shows that this approach can not only reduce the number of training samples and training time for SVM, but also detect unknown and known intrusions efficiently in the network.