Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of SMES and ScES based power conditioning systems

The selection of the less expensive power conditioning system (PCS) is the aim of the work where two types of PCS are taken into consideration. The first type of PCS is based on superconducting magnetic energy storage (SMES) while the second one is based on supercapacitor energy storage (ScES). The comparison is based on installed power as the criterion. An illustrative example is given in the work
The Design and Application of the Threshold Birthmark Algorithm based on Mutual Information Gain Rate

In order to resist the damage of digital text works in high BER networks or illegal copy in publication, we propose a robust feature-extracting algorithm based on threshold technology and then construct a new threshold birthmark algorithm. The information gain rate has been used to veraciously measure the importance of the feature in feature-extracting, and threshold(t,n) technology has also been used in constructing birthmark to reduce the cost and achieve good tolerance for different conditions. So the application based on this algorithm can overcome the text defect comes from bad channel or manual malicious modification. The method has been proven IND-CCA2 secure and robust. At the end of this paper we introduce a scheme of copyright protection based on this method.
Parallel iterative reengineering model of legacy systems

Great improvements have been made in methodologies on reengineering of legacy systems to enhance the migration process. Unfortunately, taking into account the large scale of these systems, the duration of reengineering process can still be quite long which will make an impact on the business the systems supported. In this paper we propose a parallel iterative reengineering model to reduce the reengineering process duration. The model uses the method of Formal Concept Analysis to process the complex access relationship between legacy components and shared data. An algorithm named “Bottom-Up”, which consists of two parts, is introduced to build the parallel schedule for the reengineering process. This model shortens the reengineering duration and has been proven to be successful in improving the transition system's performance in a comparative experiment.
Circularly-Polarized DRA-Slot Hybrid Antenna for Dualband Applications

A dielectric resonator antenna (DRA) is placed on top of an L-probe-fed slotted cavity to form a circularly polarized (CP) hybrid antenna. The zonal slot is perturbed to excite CP fields in the lower band, whereas the DRA located on top of the cavity is fed by an inclined slot to excite CP fields in the upper band. Ansoft HFSS was used to simulate the proposed configuration. The return loss, axial ratio and radiation pattern are presented.
Operating system enhancements to prevent the misuse of system calls

We propose a cost-e ective mechanism, to control the invocation of critical, from the security viewpoint, system calls. The integration into existing UNIX operating systems is carried out by instrumenting the code of the system calls so that the system call itself once invoked checks to see whether the invoking process and the argument values passed comply with the rules held in an access control database. This method provides simple interception of both system calls and their argument values and do not require changes in the kernel data structures and algorithms. All kernel modi cations are transparent to the application processes that can continue to work correctly without needing changes of the source code or re-compilation. A working prototype has been implemented inside the kernel of the Linux operating system, the prototype is able to detect and block also bu er over ow based attacks.
A Neural Network Congestion Control Algorithm for the Internet

A new approach of controlling congestion in the Internet is proposed in this paper via regulating the round trip towards satisfying a user imposed desired sending time. For this purpose linear in the weights neural networks are employed to construct an on-line model for the estimated round trip depending on source rate (control input) and congestion level which is directly measured from the network via monitoring the state of the marking bit for each packet acknowledgement. When the network has enough resources (throughout the transmission period) to support the user requirement the neural network based rate control algorithm guarantees the uniform ultimate boundedness of the achieved round trip with respect to an arbitrarily small neighborhood of the desired round trip. In the unfortunate case of high congestion, the controller reduces the rate to the point of logical congestion levels. Simulation studies illustrate the approach, highlighting various performance measures (i.e. fairness, buffer level, source allocation) and verifying theoretical analysis
The Judicialization of Politics in Asia

1. The Judicialization of Politics in Asia: Towards a Framework of Analysis Bjorn Dressel Part 1: Established Democracies 2. The Judicialization of Japanese Politics? Tom Ginsburg and Tokujin Matsudaira 3. Causes and Conditions for Sustainable Judicialization of Politics in Korea Jongcheol Kim and Jonghyun Park 4. The Judiciary, Policy, and Politics in India Shylashri Shankar Part 2: Fragile and Young Democracies 5. Thailand: Judicialization of Politics or Politicization of the Judiciary? Bjorn Dressel 6. Indonesia's Constitutional Court: Conservative Activist or Strategic Operator? Simon Butt 7. From Judicialization to Politicization of the Judiciary: The Philippine Case Alejandro N. Cienca 8. The Judicialization of Politics in Pakistan Charles Kennedy Part 3: Authoritarian and Semi-Authoritarian Settings 9. China's Supreme People's Court within the "Political-Legal System" Shumei Hou and Ron Keith 10. Cambodia's Judiciary: Heading for Political Judicialization? Kheang Un and Sokbunthoeun So 11. Malaysia: Limited and Intermittent Judicialization of Politics Chandra Kanagasabai 12. Leadership, Law, and Legitimacy: Reflections on the Changing Nature of Judicial Politics in Asia Haig Patapan
RNAa Is Conserved in Mammalian Cells

Background RNA activation (RNAa) is a newly discovered mechanism of gene activation triggered by small double-stranded RNAs termed ‘small activating RNAs’ (saRNAs). Thus far, RNAa has only been demonstrated in human cells and is unclear whether it is conserved in other mammals. Methodology/Principal Findings In the present study, we evaluated RNAa in cells derived from four mammalian species including nonhuman primates (African green monkey and chimpanzee), mouse, and rat. Previously, we identified saRNAs leading to the activation of E-cadherin, p21, and VEGF in human cells. As the targeted sequences are highly conserved in primates, transfection of each human saRNA into African green monkey (COS1) and chimpanzee (WES) cells also resulted in induction of the intended gene. Additional saRNAs targeting clinically relevant genes including p53, PAR4, WT1, RB1, p27, NKX3-1, VDR, IL2, and pS2 were also designed and transfected into COS1 and WES cells. Of the nine genes, p53, PAR4, WT1, and NKX3-1 were induced by their corresponding saRNAs. We further extended our analysis of RNAa into rodent cell types. We identified two saRNAs that induced the expression of mouse Cyclin B1 in NIH/3T3 and TRAMP C1 cells, which led to increased phosphorylation of histone H3, a downstream marker for chromosome condensation and entry into mitosis. We also identified two saRNAs that activated the expression of CXCR4 in primary rat adipose–derived stem cells. Conclusions/Significance This study demonstrates that RNAa exists in mammalian species other than human. Our findings also suggest that nonhuman primate disease models may have clinical applicability for validating RNAa-based drugs.
Effective bioremediation strategy for rapid in situ cleanup of anoxic marine sediments in mesocosm oil spill simulation

The purpose of present study was the simulation of an oil spill accompanied by burial of significant amount of petroleum hydrocarbons (PHs) in coastal sediments. Approximately 1000 kg of sediments collected in Messina harbor were spiked with Bunker C furnace fuel oil (6500 ppm). The rapid consumption of oxygen by aerobic heterotrophs created highly reduced conditions in the sediments with subsequent recession of biodegradation rates. As follows, after 3 months of ageing, the anaerobic sediments did not exhibit any significant levels of biodegradation and more than 80% of added Bunker C fuel oil remained buried. Anaerobic microbial community exhibited a strong enrichment in sulfate-reducing PHs-degrading and PHs-associated Deltaproteobacteria. As an effective bioremediation strategy to clean up these contaminated sediments, we applied a Modular Slurry System (MSS) allowing the containment of sediments and their physical–chemical treatment, e.g., aeration. Aeration for 3 months has increased the removal of main PHs contaminants up to 98%. As revealed by CARD-FISH, qPCR, and 16S rRNA gene clone library analyses, addition of Bunker C fuel oil initially affected the activity of autochthonous aerobic obligate marine hydrocarbonoclastic bacteria (OMHCB), and after 1 month more than the third of microbial population was represented by Alcanivorax-, Cycloclasticus-, and Marinobacter-related organisms. In the end of the experiment, the microbial community composition has returned to a status typically observed in pristine marine ecosystems with no detectable OMHCB present. Eco-toxicological bioassay revealed that the toxicity of sediments after treatment was substantially decreased. Thus, our studies demonstrated that petroleum-contaminated anaerobic marine sediments could efficiently be cleaned through an in situ oxygenation which stimulates their self-cleaning potential due to reawakening of allochtonous aerobic OMHCB.
Rule Induction With Probabilistic Rough Classifiers

We present an algorithm ProbRough for inducing decision rules from data. The algorithm combines all the positive aspects of rule induction systems with the exibility of the probabilistic representation of data and learned knowledge. It accepts imprecise and incomplete data of any mixed qualitative and quantitative type. The probabilistic structure of data is estimated from the learning set using the frequency-based estimators. The results of learning are described in the form of a certain partition of the feature space. The partition elements are of a special geometrical shape, which enables the presentation of the decision rules in a simple form meaningful to humans. Nevertheless, the prediction accuracy is comparable or superior to more sophisticated classiiers. The ProbRough algorithm searches through the set of various partitions using the criterion based on minimizing the misclassiica-tion costs. We illustrate the algorithm behavior on several real-life datasets, acknowledged in the machine learning community.
ASSESSING THE IMPACT OF FINANCIAL POLICIES ON NIGERIA’S ECONOMIC GROWTH Igbinosa,

The period 1981 to 2009 witnessed various financial developments meant to attract foreign capital inflows, promote the stability of the financial sector and to enhance the growth of the Nigerian economy. A review of extant literature on economic growth suggests positive relationships between financial activities and economic growth. Thus, this study sought to determine the extent to which the Nigerian economy has been impacted by financial developments arising mainly from the various financial policy measures in recent years. The aim was to assess the impact of financial policy measures on the growth of the national economy. This study covered the period 1981 to 2009. Using gross domestic product GDP as a proxy for economic growth and some financial variables as indicators of financial policy measures, it used the ordinary least square (OLS) estimation technique, Engle and Granger (1987) two-stage technique and the Granger causality tests to process a time series data set of 29-year range. The results show, in general, that financial policies have not significantly impacted economic growth in Nigeria. The study recommends, amongst others, some guided regulation of financial liberalization to ensure that the economy not only grows but develops to improve the wellbeing of the citizens. Furthermore, it calls for effective implementation and monitoring of financial policies as well as adequate supervision of the financial sector by the relevant authorities to avoid lopsided compliance with financial and monetary guidelines.
The Biomechanics of Spinal Deformity in Adolescent Idiopathic Scoliosis

Given the variety of anatomic and physical variations that exist, the biomechanics of Adolescent Idiopathic Scoliosis (AIS) comprise a complex topic. Representing the fundamental mechanism behind the three-dimensional deformities observed in this condition, AIS develops as a result of these complex interactions between pathoanatomy and the developmental biomechanics of the spine. The progressive nature of the deformity relates to the interplay between bony anatomical alterations and the surrounding soft tissue response. Various classification systems have evolved to better understand AIS and provide guidance for its management, and myriad techniques have been developed to address the correction of spinal deformity in these patients. For appropriately selected patients, the treating surgeon must exploit all biomechanical advantages available t counteract these deforming forces, and it is important that the biomechanics contributing to the progression of this condition be understood and corrected. All aspects of the case, including preoperative positioning and implant utilization, play a role in the amount of correction that can be obtained and maintained. These implants affect— and are affected by the forces present on the deformed spine, and manipulation of the surrounding anatomy may aid in obtaining the best surgical outcome.
A memory saving vector fast multipole algorithm for solving the augmented EFIE

An augmented EFIE (A-EFIE)[9], [10] has been proposed to separate the contributions of the vector potential and the scalar potential for avoiding the imbalance at low frequencies. The corresponding low frequency fast multipole algorithm (LF-FMA) [11] was also developed for solving the A-EFIE. Instead of the factorization of the scalar Green's function by using scalar addition theorem in the LF-FMA, we adopt the vector addition theorem for the factorization of the dyadic Green's function to realize memory savings. We are to develop a vector fast multipole algorithm for solving the A-EFIE.
Japan’s Lay Judge System: Expectations, Accomplishments, Shortfalls, and Possible Expansion

Japan’s efforts over the past decade to integrate citizens into its criminal justice system represent one of the most fascinating modern experiments in judicial reform. In 2009, when Japan formally reintroduced lay participation into criminal trials after a six decade hiatus through its or “saiban-in seido” or lay judge system, the domestic stakeholders affected by this change greeted the new quasi-jury system with mixed messages. Political reformers, bureaucrats, many attorneys, the Japan Federation of Bar Associations (“JFBA”), and scholars were excited and encouraged about the potential of the new system. Conversely, the majority of Japanese citizens, the courts, the media, and others were much more critical. These skeptics contended that Japan’s reforms and sizeable investment in citizen participation would be futile based on cultural traditions and institutional impediments. At the same time, there was much interest in the judicial reforms and new lay judge system outside of Japan. Countries across Asia and around the world watched the move towards greater democratic participation in the judicial system with much anticipation. Going forward, the world will continue to study the country’s involvement of average citizens in the judicial decision-making process. As the lay judge system has reached its fifth anniversary of operation, now is an excellent time to scrutinize its accomplishments and shortfalls. This paper will explain how Japan has accomplished, at least in part, the original goals underlying the lay judge system, including making the justice system “easier to use, easier to understand, and more reliable. ” It will also examine how Japan’s new lay judge system has increased citizen interest in the judicial process and largely enhanced citizens’ trust in the legal system. Additionally, this paper will explore the challenges facing the system and discuss whether additional steps might be taken to more fully advance these goals, including the expansion of citizen participation into the civil justice realm.
Progressing the understandings of sea spray aerosol through model systems and new methods of analysis

Currently, there exists a great deal of uncertainty regarding atmospheric aerosols and the role that they play within the Earth’s atmosphere. It is known that atmospheric aerosols can play a role in the Earth’s climate by scattering and absorbing solar radiation or acting as a cloud condensation nuclei. The purpose of this work is to obtain an improved understanding of the chemistry of atmospheric aerosols to better determine their impacts the environment, air quality, and climate. This work revolves around one specific type of atmospheric aerosol, i.e. sea spray aerosol. Sea spray aerosol is generated via breaking waves, through wind-driven mechanisms. Ocean water covers roughly 71% of the Earth’s surface, and from this over 1300 Tg of sea spray aerosols is emitted into the atmosphere every year. However, until recently, the study of sea spray was very challenging and often inconclusive due to the inability to filter background particles out. In this work, the understanding of sea spray aerosol is progressed by taking a two-pronged approach. First, this work focuses on the study of model systems of simple ocean surfactants and NaCl and the change in chemistry that occurs when the two are in the presence of each other. Second, sea spray samples generated during a biological bloom are isolated and analyzed. Using this two pronged approach, it is shown that model systems can provide supporting evidence for hypotheses created from trends discovered in more complex samples. Finally, common aerosol generation, storage, and analysis techniques are studied in order to improve our understanding of their effects on aerosol particles.
A Large Scale Gathering System for Activity Data with Mobile Sensors

In this paper, we show a large-scale activity gathering system with mobile sensor devices such as smart phones and accelerometers. We gathered over 35,000 activity data points from more than 200 people over approximately 13 months. We describe the design rationale of the system, and analyze the gathered data through statistics, clustering, and application of an existing activity recognition method. Our results show that there is a challenging field for activity recognition in larger-scale activity data.
Experiences and perception of economic hardship and rural people's opinion. A study in two Egyptian villages.

During the last decades, Egypt experienced a profound economic transformation including privatization, macroeconomic stabilization, and trade openness. Despite the impressive performance in implementing economic reforms, Egypt faces considerable challenges in the area of poverty and food security. This study questioned the extent to which rural people's experiences and perceptions of economic conditions are associated with their opinions toward Government policies and performance. The study was conducted on a randomly selected sample of 165 families from two villages (El-Talat village at Fayoum Governorate, and in Kafr-Mekawy village at Sharqia Governorate). The data were collected by personal interview using a pre-tested structured questionnaire. The study revealed that rural people’s objective economic conditions including net family income, occupation, and adaptation strategies, accompanied with perception of economic hardships, including perception of economic hardship, community hardship and feeling of inflation have a relation with people’s opinions toward government policies and performance.The study also revealed that, dissatisfaction in the community as well as feeling of powerlessness, and socio-demographic characteristics affect respondent’s political consciousness reflected in their opinions toward government policies and actions.
3 D FOREST STRUCTURE ANALYSIS FROM OPTICAL AND LIDAR DATA

In Austria about half of the entire area (46 %) is covered by forests. The majority of these are highly managed and controlled in growth. But besides timber production forest ecosystems play a multifunctional role including climate control, habitat provision and, especially in Austria, protection of settlements. The interrelationships among climatic, ecological, social and economic dimensions of forests require technologies for monitoring both the state and the development of forests. This comprises forest structure, species and age composition and, forest integrity in general. Assessing forest structure for example enables forest managers and natural risk engineers to evaluate whether a forest can fulfil its protective function or not. Traditional methods for assessing forest structure like field inventories and aerial photo interpretation are intrinsically limited in providing spatially continuous information over a large area. The Centre for Geoinformatics (Z_GIS) in collaboration with the National Park Bayerischer Wald, Germany and the Stand Montafon, Austria, has tested and applied advanced approaches of integrating multispectral optical data and airborne laser scanning (ALS) data for (1) forest stand delineation, (2) single tree detection and (3) forest structure analysis. As optical data we used RGBI line scanner data and CIR air-photos. ALS data were raw point data (10 pulses per sqm) and normalised crown models (nCM) at 0.5 m and 1 m resolution. (1) Automated stand delineation was done by (a) translating a key for manual mapping of forest development phases into a rule-based system via objectrelationship modelling (ORM); and (b) by performing multi-resolution segmentation and GIS analysis. (2) Strategies for single tree detection using raw ALS data included (a) GIS modelling based on a region-growth local maxima algorithm and (b) object-based image analysis using super class information class-specific rule sets. (3) Vertical forest structure has been assessed statistically by (a) applying basic statistics (like mean, standard deviation, and variation coefficient) on the raw data using a moving window approach; and (b) by applying landscape metrics (Shannon Evenness Index, SHEI, and division index, DIVI) for different strata extracted from the nCM.
Locally optimal heuristic for modularity maximization of networks.

Community detection in networks based on modularity maximization is currently done with hierarchical divisive or agglomerative as well as partitioning heuristics, hybrids, and, in a few papers, exact algorithms. We consider here the case of hierarchical networks in which communities should be detected and propose a divisive heuristic which is locally optimal in the sense that each of the successive bipartitions is done in a provably optimal way. This heuristic is compared with the spectral-based hierarchical divisive heuristic of Newman [Proc. Natl. Acad. Sci. USA 103, 8577 (2006). ] and with the hierarchical agglomerative heuristic of Clauset, Newman, and Moore [Phys. Rev. E 70, 066111 (2004). ]. Computational results are given for a series of problems of the literature with up to 4941 vertices and 6594 edges. They show that the proposed divisive heuristic gives better results than the divisive heuristic of Newman and than the agglomerative heuristic of Clauset et al.