Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis of 6O-Stearoyl-1 , 2O-isopropylidene-α-D-glucofuranose Derivatives for Antimicrobial Evaluation

This work mainly describes the selective synthesis of 6-O-stearoylation of 1,2O-isopropylidene-α-D-gluco-furanose and subsequent testing of this compound and its derivatives for antimicrobial activity. Bisacetone D-glucose (3) was prepared from Dglucose, which upon selective deprotection of the 5,6-O-isopropylidene group gave 3,5,6triol (4) in good yield. Unimolecular direct stearoylation of this triol at low temperature provided the desired selective 6-O-stearoate (5) in 64% yield. To further elucidate the structure and to create novel glucofuranose derivatives of biological importance, 3,5-diO-acetate (6), 3,5-di-O-mesylate (7) and 3,5-di-O-benzoate (8) were also prepared from the stearoate (5). All of the glucofuranoses (3–8) were tested via in-vitro antibacterial and antifungal functionality tests against 10 human pathogenic bacteria and 7 fungi. These experiments revealed that some of the tested glucofuranose derivatives (5, 6 and 8) showed excellent antimicrobial functionality compared to standard antibiotics.
Multi-Focus Image Fusion Using Cross Bilateral Filter in NSCT Domain

Given that the edge details of the image are not well extracted into the fused image, the cross bilateral filter (CBF) which considers both gray level similarities and geometric closeness of the neighboring pixels without smoothing edges is combined with non-subsampled contourlet transform (NSCT) in this paper for multi-focus image fusion. Firstly, the source images are decomposed into low frequency coefficients map and high frequency coefficients map through NSCT. Then the low frequency coefficients will be fused by Sum-Modified-Laplacian (SML) and the fused high frequency coefficient are obtained using CBF, and the high frequency fusion rule is a weighted average method using the weights computed from the detail images that are extracted from the two high frequency coefficient maps. Finally, the inverse NSCT is utilized to get the fused image in which all the objects are clear. At the end of this paper, in order to compare with some traditional fusion methods, some experimental results are displayed to show the superiority of this method.
Blood Pressure Variability: Prognostic Value and Therapeutic Implications

Blood pressure variability (BPV) is considered nowadays a novel risk factor for cardiovascular disease. Early findings in sinoaortic denervated rats have clearly shown that enhanced fluctuation of blood pressure induced left ventricular hypertrophy, vascular stiffness, and renal lesion. A large number of clinical trials confirm that short-term and long-term blood pressure variability independently contributes to target organ damage, cardiovascular events, and mortality not only in hypertensive patients but also in subjects with diabetes mellitus and chronic kidney disease. Therefore, amelioration of BPV has been suggested as an additional target of the treatment of cardiovascular diseases. Preliminary evidence obtained from meta-analysis and controlled clinical trials has shown that antihypertensive classes differ in their ability to control excessive BP fluctuations with an impact in the prevention of cardiovascular events. Calcium channel blockers seem to be more effective than other blood pressure lowering drugs for the reduction of short-term and long-term BPV. In order to increase actual knowledge regarding the prognostic value and therapeutic significance of BPV in cardiovascular disease, there is a need for additional clinical studies specifically designed for the study of the relevance of short-term and long-term BPV control by antihypertensive drugs.
A near real time SMS grey traffic detection

Lately, mobile operators experience threats from SMS grey routes which are used by fraudsters to evade SMS fees and to deny them millions in revenues. But more serious are the threats to the user's security and privacy and consequently the operator's reputation. Therefore, it is crucial for operators to have adequate solutions to protect both their network and their customers against this kind of fraud. Unfortunately, so far there is no sufficiently efficient countermeasure against grey routes. This paper proposes a near real time SMS grey traffic detection which makes use of Counting Bloom Filters combined with blacklist and whitelist to detect SMS grey traffic on the fly and to block them. The proposed detection has been implemented and proved to be quite efficient. The paper provides also comprehensive explanation of SMS grey routes and the challenges in their detection. The implementation and verification are also described thoroughly.
Improved Adaptive Cleaning Method for RFID Data Stream

Significant missed readings and tag transitions pose a challenge for real-time RFID middleware in data reliability. Fixed cleaning method proposed can only address the data completeness while neglect to capture the motion of tags. Shawn R. Jeffery introduced an adaptive cleaning method which can compensate missed readings and the dynamic tags, but we find its accuracy falls sometimes when tag moves out the detected region. In this paper, we present an improved method, which can provide a better accuracy in both smoothing missed readings and detecting tag transitions, and experiment result had shown that our method can improve data reliability clearly by about 15% to gain a better quality of data.
Preconditioning and Iterative Solution of All-at-Once Systems for Evolutionary Partial Differential Equations

Standard Krylov subspace solvers for self-adjoint problems have rigorous convergence bounds based solely on eigenvalues. However, for non-self-adjoint problems, eigenvalues do not determine behavior even for widely used iterative methods. In this paper, we discuss time-dependent PDE problems, which are always non-self-adjoint. We propose a block circulant preconditioner for the all-at-once evolutionary PDE system which has block Toeplitz structure. Through reordering of variables to obtain a symmetric system, we are able to rigorously establish convergence bounds for MINRES which guarantee a number of iterations independent of the number of time-steps for the all-at-once system. If the spatial differential operators are simultaneously diagonalizable, we are able to quickly apply the preconditioner through use of a sine transform; and for those that are not, we are able to use an algebraic multigrid process to provide a good approximation. Results are presented for solution to both the heat and convection .
A Vulnerability Exploits Detection Method Based on Binary Program Behavior Analysis

Nowadays, Vulnerability exploiting has become a major means of malicious code communication. In order to solve the problem that polymorphic and metamorphic vulnerability exploit variants is difficult to detect, it presents a method of detecting vulnerability exploits based on binary behavior analysis in this paper. The method track and monitor the memory and register changes the binary file's behavior results, and have a formal verification on application's behavior through intermediate‐level language. In this paper, we examine the performance of binary analysis by taking two sets of experiments for separate targets, one is 13 local file vulnerabilities, the other is web browser vulnerabilities. The results show that the exploits detection method based on binary behavior analysis can be effectively used for analysis and detection of the vulnerabilities, also with significantly reduced time and space complexity.
How Ethical Leadership Encourages Employee Voice Behavior in China: The Mediating Role of Organizational Harmony

This paper examines that ethical leadership encourages employees to engage in voice behavior via increasing organizational harmony in China. Using quantitative methods, the results suggest that ethical leadership is positively related to employee-perceived harmony and employee voice. Moreover, ethical leadership is proved to significantly enhance voice behavior through promoting organizational harmony in the Chinese workplace. This research therefore contributes to the leadership literature, seeing that it develops a context-specific framework linking the unique Chinese cultural idiosyncrasy “harmony” to the relationship between ethical leadership and employee voice. In terms of practical implications, the findings enable foreign entrepreneurs to gain a better understanding of the role and the conduct of ethical leadership in the Chinese context.
Functional effects of TrkA inhibition on system xC−-mediated glutamate release and cancer-induced bone pain

Breast cancer cells release the signalling molecule glutamate via the system xC− antiporter, which is upregulated to exchange extracellular cystine for intracellular glutamate to protect against oxidative stress. Here, we demonstrate that this antiporter is functionally influenced by the actions of the neurotrophin nerve growth factor on its cognate receptor tyrosine kinase, TrkA, and that inhibiting this complex may reduce cancer-induced bone pain via its downstream actions on xCT, the functional subunit of system xC−. We have characterized the effects of the selective TrkA inhibitor AG879 on system xC− activity in murine 4T1 and human MDA-MB-231 mammary carcinoma cells, as well as its effects on nociception in our validated immunocompetent mouse model of cancer-induced bone pain, in which BALB/c mice are intrafemorally inoculated with 4T1 murine carcinoma cells. AG879 decreased functional system xC− activity, as measured by cystine uptake and glutamate release, and inhibited nociceptive and physiologically relevant responses in tumour-bearing animals. Cumulatively, these data suggest that the activation of TrkA by nerve growth factor may have functional implications on system xC−-mediated cancer pain. System xC−-mediated TrkA activation therefore presents a promising target for therapeutic intervention in cancer pain treatment.
Transgender Theory and Embodiment: The risk of racial marginalisation

Queer theories have received criticism for their ethnocentrism and their lack of careful attention to the lived realities of transsexual and transgendered people. A forum is being established through the publication of transgender theorists' work, where transgender theorists may rework 'queer', but how well does this reworking address concerns about ethnocentrism? For some 'transpeople' it is important to maintain traditional cultural values by resisting identification with (contemporary western) medical discourses on transsexuality. How might queer and transgender theorising inform and be informed by the discursive pathways being carved out by people for whom medicalised understandings of gender may be deemed culturally inappropriate? I illustrate the points made in this paper by drawing from interviews with gender liminal people who live in New Zealand and who belong to cultures indigenous to the South Pacific. Whilst wholeheartedly supporting the efforts of transgenderists to challenge medical constructions of transsexuality, one of the purposes of this paper is to critique the way perspectives of whiteness echo, largely unacknowledged, through transgender theorising and to thus inspire more critical thinking about the racialised aspects of transsexual bodies and transgendered ways of being.
Frontotemporal Lobe Degeneration as Origin of Scans Without Evidence of Dopaminergic Deficit

The term scans without evidence of dopaminergic deficit (SWEDD) can be associated with any patient diagnosed at first with Parkinson’s disease but with a negative dopamine transporter-single photon emission computed tomography (DaTSPECT), which does not confirm the presynaptic dopaminergic deficiency. Therefore, an alternative diagnosis should be sought to support parkinsonism as a clinical diagnosis. Parkinsonism is a well-known manifestation of frontotemporal lobar degeneration (FTLD), particularly frequent in those with positive DaTSPECT. Here, we reinforce previous observations that parkinsonism can be present in FTLD patients with negative DaTSPECT and therefore, FTLD may account for a percentage of patients with SWEDD. We gather the clinical observations supporting this hypothesis and describe a case report illustrating this idea. Studies suggest the result of DaTSPECT in FTLD may depend on the neuropathology and clinical subtype. However, most studies do not provide a clinical description of the clinical subtype or pathological features making the association between subtypes of FTLD and DaTSPECT results impossible at the moment. Further studies correlating clinical, neuropsychological, neuroimaging, genetic, and pathology findings are needed to better understand parkinsonism in FTLD.
Epistemology of the Oppressed: The Dialectics of Paulo Freire's Theory of Knowledge.

As part of a critical analysis of his work, this paper argues that, at its core, Freire's critical, liberatory pedagogy as conceived in Education as the Practice of Freedom (P. Freire, 1982a), coherently systematized in Extension or Communication (P. Freire, 1982b) and carried out through Pedagogy of the Oppressed (P. Freire, 1974) into his later works (P. Freire, 1992, 1998a; Shor & Freire, 1987), is grounded in a thoroughly Marxist, or dialectical materialist, theory of knowledge (Roberts, 2003). It is my contention in this paper that an explication of Freire's dialectical materialist epistemology provides for an increased understanding Freire's liberatory pedagogy as a whole because it is difficult to grasp Freire's pedagogy without understanding its Marxism (Allman, 1999). [i]
Review: Prevention of anxiety among at‐risk children and adolescents – a systematic review and meta‐analysis

BACKGROUND Anxiety disorders are common, often start in childhood and run a chronic course. As such there is a need for effective prevention. METHODS We conducted a systematic review and meta-analyses of randomized, controlled trials to prevent the onset of anxiety disorders in 'at risk' young people. Diagnostic and symptom outcomes were examined. Putative moderators were tested as was publication bias. RESULTS We included 16 trials (2545 young people). Two trials reported diagnostic outcomes, and significant effects were found for these at end-of-programme (RR = .09, 95%CI = .02 to .16), 6- (RR = .17, 95%CI = .06 to .27) and 12-month (RR = .31, 95%CI .17 to .45) follow-ups. Based on 16 trials, improved anxiety symptoms were significant compared to nonattention controls only, with small effect sizes reported by young people at the end-of-programmes, 6- and 12-month follow-ups; and by parents at the end of the programmes and 12-, but not 6-, month follow-ups. There was no evidence of significant moderation or publication bias. CONCLUSIONS Fourteen studies included children and young people who presented with elevated anxiety symptoms, but anxiety disorder was not ruled out in the participants in these studies. Hence, these studies might be reporting results of mixed prevention/early intervention programmes. Prevention programmes that target developmental risk factors, not only disorder maintaining factors, appear most promising. The clinically meaningful impact of anxiety disorder prevention programmes remains unknown.
An ontology of scientific uncertainty : methodological lessons from analyzing expressions of uncertainty in food risk assessment

The relationship between scientific knowledge and uncertainty in science has been a central question in risk analysis. There have been several conceptualizations of uncertainty but most have been normative efforts to construct an ontology on the basis of theoretical considerations and there have been few empirical attempts to build such an ontology through textual analysis. Studies investigating how such ontologies work are equally scarce. We developed an ontology to investigate uncertainty in risk assessment in food safety comparing the EU and the US, and the two main domains of food safety: biohazards and contaminants. The ontology gauges expressions of uncertainty in two ways: one looks for stylistic clues of judgment, the other registers the content of the uncertainty expressed in the documents. We have built a large data base where English language risk assessment documents by the European Food Safety Agency and the three US agencies primarily responsible for food safety in the US are coded according to our ontology. We are also in the process of creating software that uses machine-learning algorithm to code risk assessment documents in our database. In our paper, we lay out our approach to scientific uncertainty, then describe the ontologies we developed to assess expressions of scientific uncertainty in risk assessment documents in food safety. We then discuss the results from supervised Machine Learning and the implications for both the method of machine coding and the insights we gained for human coding. Finally, we discuss some findings using the ontology testing three sets of hypotheses. The first one looks at differences in national styles in applied scientific research, the second differences in epistemic cultures between scientific subfields in food safety and the third about the effect of research and new knowledge on uncertainty.
Multimedia Representation Using Graph-Based Models and Applications

5 ΠΕΡΙΛΗΨΗ . 6 ΛΕΞΕΙΣ ΚΛΕΙΔΙΑ . 6 ΣΥΝΟΨΗ . 9 ACKNOWLEDGEMENTS . 19 PROLOGUE . 21 CHAPTER 1. GRAPH CENTRALITIES AND COMMUNITY DETECTION . 23 1.1 CENTRALITY MEASURES. 23 Degree centrality . 24 Betweenness centrality . 24 Closeness centrality . 25 Eigenvector centrality . 26 Page Rank . 27 Mapping entropy . 27 Mapping entropy Betweenness . 28 Mapping entropy extensions . 28 1.2 OTHER GRAPH-BASED MEASURES. 29 Coreness . 29 Eccentricity . 30 Clustering coefficient (local transitivity) . 31 1.3 COMMUNITY DETECTION. 32 Girvan–Newman algorithm . 32 Modularity Maximization – Fast Greedy algorithm . 33 Louvain method . 34 Infomap method . 34 Other Methods . 35 CHAPTER 2. BAG OF WORDS AND GRAPH OF WORDS. 37 2.1 BAG OF WORDS . 37 Tf-idf scores and text retrieval . 37 N-gram model . 40 Stopwords . 41 2.2 GRAPH OF WORDS . 43 CHAPTER 3. APPLICATION TO KEYWORD EXTRACTION . 45 3.1 METHODS . 45 3.2 EVALUATION MEASURES . 46 Average precision . 47 mean Average Precision . 47 Jaccard similarity . 48 3.3 DATASET DESCRIPTION . 49 3.4 SETTINGS . 49 3.5 RESULTS . 50 CHAPTER 4. TEXT CLUSTERING . 53 4.1 METHODS . 53
The Impact of Uncle Rewards on Selfish Mining in Ethereum

Many of today's crypto currencies use blockchains as decentralized ledgers and secure them with proof of work. In case of a fork of the chain, Bitcoin's rule for achieving consensus is selecting the longest chain and discarding the other chain as stale. It has been demonstrated that this consensus rule has a weakness against selfish mining in which the selfish miner exploits the variance in block generation by partially withholding blocks. In Ethereum, however, under certain conditions stale blocks don't have to be discarded but can be referenced from the main chain as uncle blocks yielding a partial reward. This concept limits the impact of network delays on the expected revenue for miners. But the concept also reduces the risk for a selfish miner to gain no rewards from withholding a freshly minted block. This paper uses a Monte Carlo simulation to quantify the effect of uncle blocks both to the profitability of selfish mining and the blockchain's security in Ethereum (ETH). A brief outlook about a recent Ethereum Classic (ETC) improvement proposal that weighs uncle blocks during the selection of the main chain will be given.
Semantic regions segmentation using a spatio-temporal model from an UAV image sequence with an optimal configuration for data acquisition*

ABSTRACT Unmanned aerial vehicles (UAV) are used to conduct a variety of recognition as well as specific missions such as target tracking and safe landing. The transmitted image sequences to be interpreted at ground station usually face limited requirements of the data transmission. In this paper, on the one hand, we handle a surveillance mission with segmenting an UAV video's content into semantic regions. A multi-class image segmentation approach is proposed considering UAV video-specific characteristics. After post-processing steps on the segmentation results, a support vector-machine classifier is used to recognize regions. A Markov model is introduced to combine the results from the previous frames in order to improve the accuracy. On the other hand, this study also assesses the influences of data reduction techniques on the proposed techniques. The comparisons between the untreated configuration and control conditions under manipulations of the frame rate, spatial resolution, and compression ratio, demonstrate how these data reduction techniques adversely influence the algorithm's performance. The experiments also point out the optimal configuration in order to obtain a trade-off between the target performance and requirements of the data transmission.
Coupling of Discontinuous Galerkin Schemes for Viscous Flow in Porous Media with Adsorption

Polymer flooding is an important stage of enhanced oil recovery in petroleum reservoir engineering. A model of this process is based on the study of multicomponent viscous flow in porous media with adsorption. This model can be expressed as a Brinkman-based model of flow in porous media coupled to a nonstrictly hyperbolic system of conservation laws for multiple components (water and polymers) that form the aqueous phase. The discretization proposed for this coupled flow-transport problem combines an ${H}({div})$-conforming discontinuous Galerkin (DG) method for the Brinkman flow problem with a classical DG method for the transport equations. The DG formulation of the transport problem is based on discontinuous numerical fluxes. An invariant region property is proved under the (mild) assumption that the underlying mesh is a B-triangulation [B. Cockburn, S. Hou, and C. -W. Shu, Math. Comp., 54 (1990), pp. 545--581]. This property states that only physically relevant (bounded and nonnegative) saturation and .
Validation of voxel-based morphometry (VBM) based on MRI

Voxel-based morphometry (VBM) is an automated and objective image analysis technique for detecting differences in regional concentration or volume of brain tissue composition based on structural magnetic resonance (MR) images. VBM has been used widely to evaluate brain morphometric differences between different populations, but there isn't an evaluation system for its validation until now. In this study, a quantitative and objective evaluation system was established in order to assess VBM performance. We recruited twenty normal volunteers (10 males and 10 females, age range 20-26 years, mean age 22.6 years). Firstly, several focal lesions (hippocampus, frontal lobe, anterior cingulate, back of hippocampus, back of anterior cingulate) were simulated in selected brain regions using real MRI data. Secondly, optimized VBM was performed to detect structural differences between groups. Thirdly, one-way ANOVA and post-hoc test were used to assess the accuracy and sensitivity of VBM analysis. The results revealed that VBM was a good detective tool in majority of brain regions, even in controversial brain region such as hippocampus in VBM study. Generally speaking, much more severity of focal lesion was, better VBM performance was. However size of focal lesion had little effects on VBM analysis.