Miracle-dz/UniFAR-FTUs huggingface dataset:
The casualties of transition: the health impact of NEET status and some approaches to managing it

ABSTRACT Youth unemployment can be understood as a public health risk. This paper explores the multi-disciplinary literature in this field, and its relevance to support for NEET (not in education, employment or training) young people. Unemployment may have a scarring effect on health, with lifelong consequences for individuals and for society. To the extent that illness has social causation, it may potentially have social remedies. Evidence for the effectiveness of mental health prevention with young people is limited, but recent research suggests that moving people on from unemployment leads to health improvements. Schools, colleges, training providers, and the welfare benefits system all have a role to play in reducing the impact of unemployment. Career guidance services are particularly well placed to reach potentially vulnerable young people.
The dual of nothing

We consider ``bubbles of nothing'' constructed by analytically continuing black hole solutions in anti--de Sitter space. These provide interesting examples of smooth time-dependent backgrounds which can be studied through the AdS/CFT correspondence. Our examples include bubbles constructed from Schwarzschild-AdS, Kerr-AdS and Reissner-Nordstr\"om AdS. The Schwarzschild bubble is dual to Yang-Mills theory on three-dimensional de Sitter space times a circle. We construct the boundary stress tensor of the bubble spacetime and relate it to the properties of field theory on de Sitter space.
Content-Adaptive Steganography by Minimizing Statistical Detectability

Most current steganographic schemes embed the secret payload by minimizing a heuristically defined distortion. Similarly, their security is evaluated empirically using classifiers equipped with rich image models. In this paper, we pursue an alternative approach based on a locally estimated multivariate Gaussian cover image model that is sufficiently simple to derive a closed-form expression for the power of the most powerful detector of content-adaptive least significant bit matching but, at the same time, complex enough to capture the non-stationary character of natural images. We show that when the cover model estimator is properly chosen, the state-of-the-art performance can be obtained. The closed-form expression for detectability within the chosen model is used to obtain new fundamental insight regarding the performance limits of empirical steganalysis detectors built as classifiers. In particular, we consider a novel detectability limited sender and estimate the secure payload of individual images.
A Novel Approach on Color Image Refocusing and Defocusing

In this study we present a novel approach on a color image refocusing and defocusing. In detail, the proposed method can accomplish the tasks of color image refocusing and defocusing. Our proposed method is thus a process of recovering the original color image from the degraded color image observations. This approach has the advantage of canny edge detection process for preserving the sharp Edges and lines of color images for restoring the blurred color image. Blind deconvolution algorithm is used to blurred images where image recovery process has been performed with little or no prior knowledge of the degrading point spread function.
Database Architecture Optimized for the New Bottleneck: Memory Access

In the past decade, advances in speed of commodity CPUs have far out-paced advances in memory latency. Main-memory access is therefore increasingly a performance bottleneck for many computer applications, including database systems. In this article, we use a simple scan test to show the severe impact of this bottleneck. The insights gained are translated into guidelines for database architecture; in terms of both data structures and algorithms. We discuss how vertically fragmented data structures optimize cache performance on sequential data access. We then focus on equi-join, typically a random-access operation, and introduce radix algorithms for partitioned hash-join. The performance of these algorithms is quantied using a detailed analytical model that incorporates memory access cost. Experiments that validate this model were performed on the Monet database system. We obtained exact statistics on events like TLB misses, L1 and L2 cache misses, by using hardware performance counters found in modern CPUs. Using our cost model, we show how the carefully tuned memory access pattern of our radix algorithms make them perform well, which is conrmed by experimental results.
Simulation of Mutually Coupled Oscillators Using Nonlinear Phase Macromodels

Design of integrated RF circuits requires detailed insight in the behavior of the used components. Unintended coupling and perturbation effects need to be accounted for before production, but full simulation of these effects can be expensive or infeasible. In this paper, we present a method to build nonlinear phase macromodels of voltage-controlled oscillators. These models can be used to accurately predict the behavior of individual and mutually coupled oscillators under perturbation at a lower cost than full circuit simulations. The approach is illustrated by numerical experiments with realistic designs.
Scalable signaling underlay for overlay networks

This paper presents the design of a scalable decentralized signaling underlay infrastructure, which features a DHT based management information storage and query-based state lookup mechanism. The signaling underlay is aimed to apply a decentralized "peer-to-peer" style searching and discovering engine into the management and control plane of the overlay network, including grid networks and p2p applications, to facilitate deployment of QoS service.
THE ROLE OF PERFORMANCE FEEDBACK QUALITY TO REDUCE THE PROPENSITY TO CREATE BUDGETARY SLACK AT PRIVATE UNIVERSITY

This study aims to test hypotheses developed by Lavengin and Mendoza (2013). This study aims to investigate the positive effect of performance feedback quality on perceived procedural justice and perceived interactional justice. Furthermore, this study investigated the negative effect of perceived procedural justice and perceived interactional justice on a propensity to create budgetary slack with trust in the supervisor as a mediating variable. This study uses a survey method via questionnaire, with middle and lower manager who participate in preparing a budget at Private University as respondent. The results show that performance feedback quality can increase perceived procedural justice and perceived interactional justice. Furthermore, this study can not prove that perceived procedural justice and perceived interactional justice can reduce the propensity to create budgetary slack through trust in supervisor. Nevertheless, the results can prove that perceived interactional justice can reduce the propensity to create budgetary slack, that means the relationship between perceived interactional justice and propensity to create budgetary slack is a direct relationship. The results also show that interactional justice can increase trust in the supervisor. Overall, this study can prove the hypotheses developed by Langevin and Mendoza (2013), that management control systems can reduce a manager’s unethical behavior.
The schema evolution and data migration framework of the environmental mass database IMIS

This paper describes a framework that supports the simultaneous evolution of object-oriented data models and relational schemas with respect to a tool-supported object-relational mapping. The proposed framework accounts for non-trivial data migration induced by type evolution from the outset. The support for data migration is offered on the level of transparent data access. The framework consists of the following integrated parts: an automatic model change detection mechanism, a generator for schema evolution code and a generator for data migration APIs. The framework has been concepted in the IMIS project. IMIS is an information system for environmental radioactivity measurements. Though the indicated domain especially demands a solution like the one discussed in this paper, the achievements are of general purpose for multi-tier system architectures with object-relational mapping.
Bacteriocins, spite and virulence

There has been much interest in using social evolution theory to predict the damage to a host from parasite infection, termed parasite virulence. Most of this work has focused on how high kinship between the parasites infecting a host can select for more prudent exploitation of the host, leading to a negative relationship between virulence and parasite kinship. However, it has also been shown that if parasites can cooperate to overcome the host, then high parasite kinship within hosts can select for greater cooperation and higher growth rates, hence leading to a positive relationship between virulence and parasite kinship. We examine the impact of a spiteful behaviour, chemical (bacteriocin) warfare between microbes, on the evolution of virulence, and find a new relationship: virulence is maximized when the frequency of kin among parasite's; social partners is low or high, and is minimized at intermediate values. This emphasizes how biological details can fundamentally alter the qualitative nature of theoretical predictions made by models of parasite virulence.
Finding an Unknown Acyclic Orientation of a Given Graph

Let c(G) be the smallest number of edges we have to test in order to determine an unknown acyclic orientation of the given graph G in the worst case. For example, if G is the complete graph on n vertices, then c(G) is the smallest number of comparisons needed to sort n numbers. We prove that c(G) ≤ (1/4 + o(1))n2 for any graph G on n vertices, answering in the affirmative a question of Aigner, Triesch and Tuza [Discrete Mathematics144 (1995) 3–10]. Also, we show that, for every ϵ > 0, it is NP-hard to approximate the parameter c(G) within a multiplicative factor 74/73 − ϵ.
The Design of dynamical S-boxes based on discrete chaos map system

This paper presents a method for obtaining dynamically cryptographically strong substitution boxes (S-boxes) based on discrete chaos map system (DCMS). The cryptographical properties such as bijection, nonlinearity, strict avalanche, output bits independence and equiprobable input/output XOR distribution of these S-boxes are analyzed in detail. The results of numerical analysis show that all the criteria for designing good S-box can be satisfied approximately. As a result, our approach is suitable for practical application in designing block cryptosystem.
A set-membership approach to improved PNLMS algorithm

To improve convergence speed across different sparseness levels, an approach adapting dynamically to the level of sparseness using a new proportionate-type NLMS algorithm is researched. It can keep the fast initial convergence speed during the whole adaptation process until the adaptive filter reaches its steady state, but it may come at the expense of a slight increase in the computational complexity per update. For this reason, the idea of improving proportionate adaptation combined with the framework of set-membership filtering in an attempt to reduce computational complexity of algorithm is presented. Because of fewer coefficients updated in the new algorithm, the computational effort decreases significantly. Simulation results show the proposed algorithm obtains a faster convergence rates than IPNLMS algorithm in sparse circumstances, and has the same performance with their conventional counterparts for situation of dispersive channel.
Breakdown of a Benchmark Score Without Internal Analysis of Benchmarking Program

A breakdown of a benchmark score is how much each aspect of the system performance affects the score. Existing methods require internal analysis on the benchmarking program and then involve the following problems: (1) require a certain amount of labor for code analysis, profiling, simulation, and so on and (2) require the benchmarking program itself. In this paper, we present a method for breaking down a benchmark score without internal analysis of the benchmarking program. The method utilizes regression analysis of benchmark scores on a number of systems. Experimental results with 3 benchmarks on 15 Android smartphones showed that our method could break down those benchmark scores even though there is room for improvement in accuracy.
TLR and TNF-R1 activation of the MKK3/MKK6–p38α axis in macrophages is mediated by TPL-2 kinase

Previous studies suggested that Toll-like receptor (TLR) stimulation of the p38α MAP kinase (MAPK) is mediated by transforming growth factor-β-activated kinase 1 (TAK1) activation of MAPK kinases, MKK3, MKK4 and MKK6. We used quantitative mass spectrometry to monitor tumour progression locus 2 (TPL-2)-dependent protein phosphorylation following TLR4 stimulation with lipopolysaccharide, comparing macrophages from wild-type mice and Map3k8D270A/D270A mice expressing catalytically inactive TPL-2 (MAP3K8). In addition to the established TPL-2 substrates MKK1/2, TPL-2 kinase activity was required to phosphorylate the activation loops of MKK3/6, but not of MKK4. MKK3/6 activation required IκB kinase (IKK) phosphorylation of the TPL-2 binding partner nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB1) p105, similar to MKK1/2 activation. Tumour necrosis factor (TNF) stimulation of MKK3/6 phosphorylation was similarly dependent on TPL-2 catalytic activity and IKK phosphorylation of NF-κB1 p105. Owing to redundancy of MKK3/6 with MKK4, Map3k8D270A mutation only fractionally decreased lipopolysaccharide activation of p38α. TNF activation of p38α, which is mediated predominantly via MKK3/6, was substantially reduced. TPL-2 catalytic activity was also required for MKK3/6 and p38α activation following macrophage stimulation with Mycobacterium tuberculosis and Listeria monocytogenes. Our experiments demonstrate that the IKK/NF-κB1 p105/TPL-2 signalling pathway, downstream of TAK1, regulates MKK3/6 and p38α activation in macrophages in inflammation.
A Need Analysis On Ict-based English Material For Teaching And Learning Of Reading For High School Students In South Bengkulu

This research was aimed to find out ICT media are preferred by high school students in South Bengkulu in learning reading and to describe the reading materials should be used with ICT media. The research design was mixed method quantitative and qualitative with the subjects of this research were 302 high school students and 11 English teachers in South Bengkulu. The instruments of this research were questionairre and open-ended interview. The findings of the research revealed that (1) online ICT media was prefered by high school students in South Bengkulu in learning reading and (2) kinds of text became the reading material that should be used with ICT media. To suggest, a broader field test still needed to be done to achieve a better result and other researchers who are interested in the incorporation of ICT in learning teaching are suggested to conduct further investigation which possibly deals with other language skills.
The Need for (Long) Chains in Kidney Exchange

It has been previously shown that for sufficiently large pools of patient-donor pairs, (almost) efficient kidney exchange can be achieved by using at most 3-way cycles, i.e. by using cycles among no more than 3 patient-donor pairs. However, as kidney exchange has grown in practice, cycles among n>3 pairs have proved useful, and long chains initiated by non-directed, altruistic donors have proven to be very effective. We explore why this is the case, both empirically and theoretically. We provide an analytical model of exchange when there are many highly sensitized patients, and show that large cycles of exchange or long chains can significantly increase efficiency when the opportunities for exchange are sparse. As very large cycles of exchange cannot be used in practice, long non-simultaneous chains initiated by non-directed donors significantly increase efficiency in patient pools of the size and composition that presently exist. Most importantly, long chains benefit highly sensitized patients without harming low-sensitized patients.
A LANDCOVER CLASSIFICATION SCHEME FOR HIGH RESOLUTION IMAGERY AND IT ’ S APPLICATION TO BUSHFIRE PROTECTION IN RESIDENTIAL AREAS

With the increasing degree of global climate change, bushfires are becoming a major threat to human life and property. A risk assessment of bushfires is dependent on the availability of suitable information on the environment and human activities. Most of the spatial information for fire behaviour prediction is time-dependent, so it is both quite difficult and potentially very expensive to maintain and ensure the reliability of such data. A suitable source of wide coverage is high resolution (≤1m) satellite imagery for risk assessment in bushfire areas. Our objective is to exploit high-resolution stereo data such as IKONOS and extract all possible information such as the vertical dimensions of a forest, the crown size and shape of some individual trees, the location of tree and grass areas, the topography of bare land and the location of housing areas. This was achieved by extracting a DSM, DTM and landcover from IKONOS stereo multispectral imagery. Then we employed FARSITE (Fire Area Simulator http://www.farsite.org) to simulate fire behaviour with several different ignition points in order to assess the risk to housing within residential areas which can be detected by our classification scheme. This case study shows how high resolution stereo images can be exploited to cope with a natural disaster by extracting detailed information on both the natural and man-made environment.
Analysis of a jet stream induced gravity wave associated with an observed stratospheric ice cloud over Greenland

A polar stratospheric ice cloud (PSC type II) was observed by airborne lidar above Greenland on 14 January 2000. It was the unique observation of an ice cloud over Greenland during the SOLVE/THESEO 2000 campaign. Mesoscale simulations with the hydrostatic HRM model are presented which, in contrast to global analyses, are capable to produce a vertically propagating gravity wave that induces the low temperatures at the level of the PSC afforded for the ice formation. The simulated minimum temperature is ∼8 K below the driving analyses and ∼4.5 K below the frost point, exactly coinciding with the location of the observed ice cloud. Despite the high elevations of the Greenland orography the simulated gravity wave is not a mountain wave. Analyses of the horizontal wind divergence, of the background wind profiles, of backward gravity wave ray-tracing trajectories, of HRM experiments with reduced Greenland topography and of several diagnostics near the tropopause level provide evidence that the wave is emitted from an intense, rapidly evolving, anticyclonically curved jet stream. The precise physical process responsible for the wave emission could not be identified definitely, but geostrophic adjustment and shear instability are likely candidates. In order to evaluate the potential frequency of such nonorographic polar stratospheric cloud events, the non-linear balance equation diagnostic is performed for the winter 1999/2000. It indicates that ice-PSCs are only occasionally generated by gravity waves emanating from spontaneous adjustment. Correspondence to: S. Buss (sbuss@largeur.com)
Triangulation of the neurocomputational architecture underpinning reading aloud

Significance Reading is a critical linguistic skill, but understanding of its cognitive and neural bases is incomplete. Using functional MRI, we found reading-related activation in two areas of anterior temporal cortex, an area not previously associated with reading. Activation profiles of these sites were consistent with the predictions of computational reading models that ascribe a key role to semantic knowledge in reading words with irregular spellings. We also found individual differences in the reading neural network that were predicted by an independent measure of semantic reliance in reading. Such individual differences have been hypothesized on theoretical grounds to explain variation in reading abilities among neurodegenerative patients. Here we provide the first direct evidence, to our knowledge, for their existence in the healthy brain. The goal of cognitive neuroscience is to integrate cognitive models with knowledge about underlying neural machinery. This significant challenge was explored in relation to word reading, where sophisticated computational-cognitive models exist but have made limited contact with neural data. Using distortion-corrected functional MRI and dynamic causal modeling, we investigated the interactions between brain regions dedicated to orthographic, semantic, and phonological processing while participants read words aloud. We found that the lateral anterior temporal lobe exhibited increased activation when participants read words with irregular spellings. This area is implicated in semantic processing but has not previously been considered part of the reading network. We also found meaningful individual differences in the activation of this region: Activity was predicted by an independent measure of the degree to which participants use semantic knowledge to read. These characteristics are predicted by the connectionist Triangle Model of reading and indicate a key role for semantic knowledge in reading aloud. Premotor regions associated with phonological processing displayed the reverse characteristics. Changes in the functional connectivity of the reading network during irregular word reading also were consistent with semantic recruitment. These data support the view that reading aloud is underpinned by the joint operation of two neural pathways. They reveal that (i) the ATL is an important element of the ventral semantic pathway and (ii) the division of labor between the two routes varies according to both the properties of the words being read and individual differences in the degree to which participants rely on each route.
Feature Extraction of Iris Images using ICA for Person Authentication

This paper describes the Iris based authentication system using the Independent Component Analysis (ICA). In this paper, a customized iris extraction algorithm has been applied directly on the unfiltered grayscale image. The polar coordinate system has been used by the researchers for iris processing. Instead, an algorithm based on intrinsic coordinate system has been proposed to save on computation with satisfactory results. ICA has been used very successfully in face recognition. The proposed algorithm of ICA has been tested on "UBIRIS Iris Database of noisy and noise free images" of average iris visibility and the results showed the accuracy of identification more than 83% with excellent processing speed.
Concise Total Synthesis of (+)-Zeylenone with Antitumor Activity and Structure-Activity Relationship of Its Derivatives

(-)-Zeylenone is a promising cytotoxic agent，which is a natural product isolated from Uvaria grandiflora Roxb. Though substantial antitumor mechanism has been researched , little has focused on its enantiomer (+)-Zeylenone.This article will try to find a gram scale synthesis method of (+)-Zeylenone and explain the structure-activity relationship of this kind of compound. Total synthesis of (+)-zeylenone was completed in 13 steps with quinic acid as starting material in 8.8% overall yield. The highlight of the route was the control of the three carbon’s chirality by clever use of single step dihydroxylation under the direction of the key C-3 chirality. In addition, zeylenone derivatives were designed and synthesized and their antitumor activity were evaluated against three human cancer cell lines using the CCK8 assay. Structure-activity relationship suggested compounds with both two absolute configurations exhibited good activity. Besides, hydroxyls at C-1/2 position were crucial for the activity and esterification of C-1 hydroxyl with large groups made the activity disappeared. Hydroxyl at C-3 position was also important as proper ester substituent could increase the potency.