Miracle-dz/UniFAR-FTUs huggingface dataset:
Youth work in a changing society: A case study of Hong Kong youth service providers

Hong Kong has recently witnessed heightened public awareness of the issues of rights, civil society and citizenship. Contested relations with the Beijing government and slower economic growth in mainland China have seen more Hong Kong citizens become involved in civic engagement and identity politics. Youth service providers thus find themselves forced to respond to a rapidly changing society and changing youth needs while being situated in institutions with their own structural constraints and work culture. The result is that occupational stress is increasingly common amongst Hong Kong secondary school teachers and social workers. This paper presents the findings of a qualitative ethnographic study involving 16 in-depth interviews with community leaders, teachers and school-based social workers. How does a changing society affect youth work in general? How does greater discussion of democracy and human rights in the public sphere affect the way that youth service providers perform youth work? What are the changing roles and responsibilities of these providers in offering support to Hong Kong youth? The research themes that emerged include changing demographics and youth scene, a democratising public sphere in relation to Chinese youth and professionalism as a youth service provider.
An efficient page-level FTL to optimize address translation in flash memory

Flash-based solid state disks (SSDs) have been very popular in consumer and enterprise storage markets due to their high performance, low energy, shock resistance, and compact sizes. However, the increasing SSD capacity imposes great pressure on performing efficient logical to physical address translation in a page-level flash translation layer (FTL). Existing schemes usually employ a built-in RAM cache for storing mapping information, called the mapping cache, to speed up the address translation. Since only a fraction of the mapping table can be cached due to limited cache space, a large number of extra operations to flash memory are required for cache management and garbage collection, degrading the performance and lifetime of an SSD. In this paper, we first apply analytical models to investigate the key factors that incur extra operations. Then, we propose an efficient page-level FTL, named TPFTL, which employs two-level LRU lists to organize cached mapping entries to minimize the extra operations. Inspired by the models, we further design a workload-adaptive loading policy combined with an efficient replacement policy to increase the cache hit ratio and reduce the writebacks of replaced dirty entries. Finally, we evaluate TPFTL using extensive trace-driven simulations. Our evaluation results show that compared to the state-of-the-art FTLs, TPFTL reduces random writes caused by address translation by an average of 62% and improves the response time by up to 24%.
On Volume Stabilization by Quantum Corrections

We discuss prospects for stabilizing the volume modulus of N = 1 supersymmetric type IIB orientifold compactiﬁcations using only perturbative corrections to the K¨ahler potential. Concretely, we consider the known string loop corrections and tree-level α ′ corrections. They break the no-scale structure of the potential, which otherwise pro-hibits stabilizing the volume modulus. We argue that when combined, these corrections provide enough ﬂexibility to stabilize the volume of the internal space without non-perturbative eﬀects, although we are not able to present a completely explicit example within the limited set of currently available models. Furthermore, a certain amount of ﬁne-tuning is needed to obtain a minimum at large volume.
Research on the Maximum Flow in Large-scale Network

This article covers a problem that often arises in real life situations-the maximum flow problem. This problem is a classical combinatorial optimization problem, which arises in many engineering and scientific applications. It is also the important content of computer science and operational research. In order to reduce computational complexity, many improvement methods have been proposed. In this paper, applying the thought of granular computing and combining the maximal clique, a new method is proposed to solve the approximately maximum flow problem in complex and large-scale network. By contracting the appropriate maximal clique in the network, we can calculate approximate maximum flow much more efficiently. Experimental results demonstrate that the algorithm we proposed can be used to compute approximate maximum flow in a relatively short period of time and also provide a new approach to the study on the maximum flow problem.
Reindeer grazing increases summer albedo by reducing shrub abundance in Arctic tundra

Previous studies have shown that climate warming is causing shrub cover to increase at high latitudes. Increased shrub cover generally lowers surface albedo, which results in higher energy absorption and further warming. In parts of Fennoscandia, herbivory is known to control vegetation height and abundance, and thus preventing this positive feedback. Here, we combine field measurements of albedo, herbivory and vegetation characteristics in four topographically-defined vegetation types of varying shrub height and abundance with land surface modeling (JULES) to investigate if reindeer grazing can influence the energy balance of an arctic tundra. We find that when reindeer reduces shrub height and abundance, summer albedo increases in both Betula nana-dominated heath vegetation and Salix glauca-dominated willow depressions. Model results reveal associated lower net radiation, and latent and sensible heat fluxes in heavily-grazed sites in all shrub-dominated vegetation types. Our results also suggest that the structural shift from graminoid to shrub tundra drives the difference in summer albedo, rather than shifts from dwarf-shrub to tall-shrub tundra. Reindeer has thus a potential cooling effect on climate by increasing summer albedo and decreasing net radiation, which highlights the importance of mammalian herbivores for the earth system beyond their local grazing impacts. However, the strong effects of reindeer on albedo are probably restricted to areas with high reindeer densities, since a dramatic vegetation change is essential. The importance of these processes across the whole range of reindeer densities found in the arctic tundra needs to be further evaluated.
A Simple and Robust Dissemination protocol for VANETs

Several promising applications for Vehicular Ad-hoc Networks (VANETs) exist. For most of these applications, the communication among vehicles is envisioned to be based on the broadcasting of messages. This is due to the inherent highly mobile environment and importance of these messages to vehicles nearby. To deal with broadcast communication, dissemination protocols must be defined in such a way as to (i) prevent the so-called broadcast storm problem in dense networks and (ii) deal with disconnected networks in sparse topologies. In this paper, we present a Simple and Robust Dissemination (SRD) protocol that deals with these requirements in both sparse and dense networks. Its novelty lies in its simplicity and robustness. Simplicity is achieved by considering only two states (cluster tail and non-tail) for a vehicle. Robustness is achieved by assigning message delivery responsibility to multiple vehicles in sparse networks. Our simulation results show that SRD achieves high delivery ratio and low end-to-end delay under diverse traffic conditions.
Proposed Method for Multimedia Data Security Using Cyclic Elliptic Curve, Chaotic System, and Authentication Using Neural Network

As multimedia applications are used increasingly, security becomes an important issue of security of images. The combination of chaotic theory and cryptography forms an important field of information security. In the past decade, chaos based image encryption is given much attention in the research of information security and a lot of image encryption algorithms based on chaotic maps have been proposed. But, most of them delay the system performance, security, and suffer from the small key space problem. This paper introduces an efficient symmetric encryption scheme based on a cyclic elliptic curve and chaotic system that can overcome these disadvantages. The cipher encrypts 256-bit of plain image to 256-bit of cipher image within eight 32-bit registers. The scheme generates pseudorandom bit sequences for round keys based on a piecewise nonlinear chaotic map. Then, the generated sequences are mixed with the key sequences derived from the cyclic elliptic curve points. The proposed algorithm has good encryption effect, large key space, high sensitivity to small change in secret keys and fast compared to other competitive algorithms.
Towards Self-Protecting Enterprise Applications

Enterprise systems must guarantee high availability and reliability to provide 24/7 services without interruptions and failures. Mechanisms for handling exceptional cases and implementing fault tolerance techniques can reduce failure occurrences, and increase dependability. Most of such mechanisms address major problems that lead to unexpected service termination or crashes, but do not deal with many subtle domain dependent failures that do not necessarily cause service termination or crashes, but result in incorrect results. In this paper, we propose a technique for developing selfprotecting systems. The technique proposed in this paper observes values at relevant program points. When the technique detects a software failure, it uses the collected information to identify the execution contexts that lead to the failure, and automatically enables mechanisms for preventing future occurrences of failures of the same type. Thus, failures do not occur again after the first detection of a failure of the same type.
Excitatory amino acid-induced release of 3H-GABA from cultured mouse cerebral cortex interneurons

A newly developed continuous superfusion model was used for studies of 3H-GABA release from cultured mouse cerebral cortex neurons. It was found that a series of excitatory amino acids (EAAs) representing all receptor subtypes evoked Ca2+- dependent release of 3H-GABA from the neurons. Quisqualate was the most potent agonist tested, with an EC50 value of 75 nM. L-Glutamate, N-methyl-D-aspartate (NMDA), and kainate showed EC50 values of 12, 16 and 29 microM, respectively. The EAA- evoked 3H-GABA release could be blocked by a series of EAA antagonists. The highly selective NMDA antagonist D-2-amino-5-phosphonovaleric acid (D-APV) was found to block NMDA responses, whereas the nonselective antagonists cis-2,3-piperidine dicarboxylic acid (PDA) and gamma-D- glutamyl-aminomethyl sulphonic acid (GAMS) blocked responses to all agonists. NMDA responses were found to be sensitive to Mg+ blockade. EAA- as well as potassium-induced 3H-GABA release from the neurons could be detected as early as day 5 in culture. However, during the culture period up to 12 d, the responses to K+, quisqualate, and NMDA were increased. The ontogenetic development of binding sites for quisqualate, kainate, and NMDA in mouse cortex was studied using the radioligands 3H-alpha-amino-3-hydroxy-5-methyl-4-isoxasole propionate (3H-AMPA), 3H-kainate, and 3H-L-glutamate, respectively. The development of binding sites for the different EAA-receptor subtypes showed a good correlation with the development of neuronal 3H-GABA release evoked by the excitatory amino acids. (ABSTRACT TRUNCATED AT 250 WORDS)
EFEECTIVENES OF PQ4R METACOGNITIVE STRATEGY BASED READING LEARNING MODELS IN JUNIOR HIGH SCHOOL

The objective of research is to find out the efectivenes of metacognitive Preview, Question, Read, Reflect, Recite, Review (PQ4R) strategy based reading learning model to improve SMP students’ reading ability. The method applied in this study is research and development by using both qualitative and quantitative approaches. The research result shows that the ideal learning model needed by the students is metacognitive PQ4R strategy based reading learning model. Structurally, this learning model is viable, relevant, and suitable with the principles of learning model development, both from substantial view and the structural model. Based on the trial result with experimental research design (experimental and control groups), metacognitive PQ4R strategy based reading learning model is effective to be used to improve SMP students’ reading ability. Even the learning outcome is better than the reading class done by the teacher who does not use metacognitive PQ4R strategy. learning metacognitive reading strategies based PQ4R junior high school students are more effective than learning to read that teachers without the use of metacognitive strategies PQ4R with the calculation results of test of 5.975 t test is greater than t table 1.67. So it can be concluded that the learning model based reading metacognitive strategies PQ4R effective and fit for use in secondary schools.
Analyzing Partition Testing Strategies

Partition testing strategies, which divide a program's input domain into subsets with the tester selecting one or more elements from each subdomain, are analyzed. The conditions that affect the efficiency of partition testing are investigated, and comparisons of the fault detection capabilities of partition testing and random testing are made. The effects of subdomain modifications on partition testing's ability to detect faults are studied. >
Accurate 3-D Measurement System Using the Pico Projector-based Phase Shifting Techniques

The 3-D measurement system based on optical method is becoming widely applied. Among those methods, fringe projection techniques provide high resolution, whole-filed 3-D reconstruction of objects in non-contact manner. A custom-made LCD(Liquid Crystal Display) projector for inspection system using fringe projection and phase shifting is expensive and complex. In this paper, the 3-D measurement system using the pico projector is proposed for inexpensive and simple while maintaining high accuracy. Experiments have shown that proposed system is high accuracy. The proposed system applies to measurement of height of LED(Light Emitting Diode) Package.
Invariant Natural Killer T-Cell Control of Type 1 Diabetes: A Dendritic Cell Genetic Decision of a Silver Bullet or Russian Roulette

OBJECTIVE In part, activation of invariant natural killer T (iNKT)-cells with the superagonist α-galactosylceramide (α-GalCer) inhibits the development of T-cell–mediated autoimmune type 1 diabetes in NOD mice by inducing the downstream differentiation of antigen-presenting dendritic cells (DCs) to an immunotolerogenic state. However, in other systems iNKT-cell activation has an adjuvant-like effect that enhances rather than suppresses various immunological responses. Thus, we tested whether in some circumstances genetic variation would enable activated iNKT-cells to support rather than inhibit type 1 diabetes development. RESEARCH DESIGN AND METHODS We tested whether iNKT-conditioned DCs in NOD mice and a major histocompatibility complex–matched C57BL/6 (B6) background congenic stock differed in capacity to inhibit type 1 diabetes induced by the adoptive transfer of pathogenic AI4 CD8 T-cells. RESULTS Unlike those of NOD origin, iNKT-conditioned DCs in the B6 background stock matured to a state that actually supported rather than inhibited AI4 T-cell–induced type 1 diabetes. The induction of a differing activity pattern of T-cell costimulatory molecules varying in capacity to override programmed death-ligand-1 inhibitory effects contributes to the respective ability of iNKT-conditioned DCs in NOD and B6 background mice to inhibit or support type 1 diabetes development. Genetic differences inherent to both iNKT-cells and DCs contribute to their varying interactions in NOD and B6.H2g7 mice. CONCLUSIONS This great variability in the interactions between iNKT-cells and DCs in two inbred mouse strains should raise a cautionary note about considering manipulation of this axis as a potential type 1 diabetes prevention therapy in genetically heterogeneous humans.
On the Parallel Approximability of Some Classes ofQuadratic

In this paper we analyze the parallel approximability of two special classes of Quadratic Programming. First, we consider Convex Quadratic Programming. We show that the problem of Approximating Convex Quadratic Programming is P-complete. We also consider two approximation problems related to it, Solution Approximation and Value Approximation and show both of these cannot be solved in NC, unless P=NC. Secondly, on the positive side, we show that we have an NC Approximation Scheme for those instances of Quadratic Programming that are \smooth" and \positive. " Then we show how to extend the result for positive instances of bounded degree Smooth Integer Programming problems. Finally, we formulate several combinatorial problems as positive QP (or positive Integer Programs) in packing/covering form and show that the presented techniques can be used to obtain NC Approximation Schemes for \dense" instances of such problems.
The Relationship between School Culture and Professional Learning Community in Malaysia

School culture creates a psychosocial environment that profoundly impacts teachers, administrators, students and shapes its organization. Besides, the school considered as learning community and should practice the Professional Learning Community (PLC). This descriptive correlational study examined the relationship between school culture and PLC. This study found that the school culture and PLC have moderate positive relationship (r=0.428). This research also provides ideas for future research by practitioners in this field.
Adults’ Smartphone Addiction

This study was to examine Smartphone addiction level of adults according their age groups. In or-der to identify the factors affecting Smartphone addiction of the subjects, Multiple Regression was used. According to the survey results, 76.4% out of 1,000adult men and women aged 19 or older to 60 or younger in 19 cities and provinces nationwide used Smartphone every day. In all age groups, Smartphone addiction scores of women were significantly higher than those of men (p<.001) and the interaction between age and gender (age*gender) was found to be significant by the analysis (F=2.711, p=.044). In particular, both men and women showed the highest smartphone addiction scores at the age of 19-29 (p<.001). There was a difference in the factors affecting the degree of Smartphone addiction by adult age. Therefore, it is also necessary to develop Smartphone addiction prevention programs and policies targeting adults.
On the relationship between the structural and socioacademic communities of an interdisciplinary coauthorship network

This article presents a study that compares detected structural communities in a coauthorship network to the socioacademic characteristics of the scholars that compose the network. The coauthorship network was created from the bibliographic record of an overt interdisciplinary research group focused on sensor networks and wireless communication. The popular leading eigenvector community detection algorithm was employed to assign a structural community to each scholar in the network. Socioacademic characteristics were gathered from the scholars and include such information as their academic department, academic aﬃliation, country of origin, and academic position. A Pearson’s χ 2 test, with a simulated Monte Carlo, revealed that structural communities best represent groupings of individuals working in the same academic department and at the same institution. A generalization of this result indicates that, contrary to the common conception of a multi-institutional interdisciplinary research group, collaboration is primarily driven by scholar expertise and physical proximity.
Early DoS Attack Detection using Smoothened Time-Series andWavelet Analysis

Denial of Service (DoS) attacks are ubiquitous to computer networks. Flood based attacks are a common class of DoS attacks. DoS detection mechanisms that aim at detecting floods mainly look for sudden changes in the traffic and mark them anomalous. In this paper, we propose a method that considers the traffic in a network as a time-series and smoothens it using exponential moving average and analyzes the smoothened wave using energy distribution based on wavelet analysis. The parameters we used to represent the traffic are number of bytes received per unit time and the proportion between incoming and outgoing bytes. By analyzing the energy distribution in the wavelet form of a smoothened time-series, growth in the traffic, which is the result of a DoS attack can be detected very early. As the parameters we considered represent different properties of the network, the accuracy of the detection will be very high and with less false positives.
ESTIMATION OF THE INTEGRAL TIME SCALE WITH TIME SERIES MODELS

Climateand regional models solve the dynamics of the atmosphere with a resolution ∆ of 10 km or more. They use parameterizations to incorporate the effects of turbulence in the atmospheric boundary layer (ABL). Fluxes, entrainment and dissipation are associated with characteristic time-scales T . They are often constructed from characteristic length scales L for these quantities (temperature, wind velocity, humidity, chemicals) and a characteristic turbulent velocity. The spatial resolution ∆ of the regional model determines where the spectra are truncated and which parts of the dynamics should be parameterized. Ratio ∆ L characterizes the importance of these subgrid-parameterizations. With increasing computational resources, the regional models are refined and the spectral truncation induced by the model resolution shifts towards the turbulent regime. Estimation of L from measurements is therefore of increasing importance for understanding the dynamics of the ABL (Nicholls and LeMone 1980). In many cases L equals the height of the boundary layer, but sometimes it does not: in Large Eddy Simulations of a convective boundary layer Jonker et al. (1999) found that, for certain scalar entrainment ratios, the growth of the L for scalars did not follow the growth of L for velocity and temperature. In this paper we will discuss the estimation of an integral time-scale T from a given signal which via Taylor’s hypothesis gives integral length L. The integral time scale is often defined in terms of an autocovariance function that is given by the time-average of shifted product of observations x nx n m. We will show that application of this definition leads to results that are difficult to interpret. One problem for this definition is the influence of the subtraction of the estimated mean (Sreenivasan et al. 1978) or a trend correction (Kaimal and Finnigan 1994, p.276). Due to these difficulties, this definition is not used in practice in this pure form. Instead, an integral time scale is obtained using the truncated autocovariance function, or, equivalently, the windowed periodogram or smoothed Fast Fourier Transform (FFT). The smoothing is highly arbitrary and therefore estimation of T via FFT is a subjective business.