Miracle-dz/UniFAR-FTUs huggingface dataset:
ANALYZE AND EVALUATE THE IMPLEMENTATION OF CDS ALGORITHMS USING THE MOBILE AGENT . . 1

In this work, we identify, analysis and evaluate the role of mobile agent to solve the problem of selecting the minimum connected dominating set CDS better alternative approach than the exchange messages approach. The first problem concerns the nature of the CDS construction algorithms in question. Their design is justified as the purpose to construct a virtual infrastructure for wireless network with varied high cost in the permanent exchanged messages to select the CDS. The redundant broadcasting of the packets effects the overall network performance, increases the latency, the collision and the need of synchronization mechanism. Common techniques and algorithms such as marking process, Greedy Algorithms, Maximal Independent Set MIS, Pruning process, and Multipoint Relaying are exploited to select the potential nodes of the connected dominating set. We analyzed and implemented some of these techniques from the using perspective of the mobile agent. We shall argue that the mobile agent implements the CDS algorithms with less cost in its moves comparing with the cost of exchanged messages. Mobile agent just requires local information and a limited number of iterative rounds instead of the redundant broadcasting packets that imposed by other techniques. There is no work similar to our work that discusses the using of mobile agent to construct the connected dominating set based on those common techniques. We have made slight modifications on those algorithms, their notations and parameters to be appropriate through the implementation by the mobile agent. Using the mobile agent shows encouraging results for constructing connected dominating set with few iterations, eliminates the overhead caused by the large volume of message exchange, and improve the structure of the computed CDS. However, the agent by implementing those algorithms successfully constructs the connected dominating set; the constructed connected dominating nodes are still large set. The agent by implementing those algorithms could not construct the minimum CDS. KeywordsMobile Agent, Graphic Theory, Connected Dominating set, Maximal Independent Set, Whiteboard.
High performance quantum cascade lasers based on three-phonon-resonance design

A quantum cascade laser structure based on three-phonon-resonance design is proposed and demonstrated. Devices, emitting at a wavelength of 9 μm, processed into buried ridge waveguide structures with a 3 mm long, 16 μm wide cavity and a high-reflection (HR) coating have shown peak output powers of 1.2 W, slope efficiencies of 1 W/A, threshold current densities of 1.1 kA/cm2, and high wall-plug efficiency of 6% at 300 K. A 3 mm long, 12 μm wide buried-heterostructure device without a HR coating exhibited continuous wave output power of as high as 65 mW from a single facet at 300 K.
Efficiency Optimization of PMSM Drives Using Field-Circuit Coupled FEM for EV/HEV Applications

This paper proposes an efficiency optimization method for the permanent magnet synchronous motor (PMSM) based powertrain by using field-circuit coupled finite-element method (FEM) for electric vehicle or hybrid electric vehicle applications. In this paper, an alterable flux-weakening (FW) angle is employed in the armature current control strategy for the FW operation. The optimal FW angle for each certain operating condition can be obtained through the pre-selection, which improves the system efficiency compared to conventional FW methods. Then, the lookup table (LUT) for optimal armature current control commands is obtained. Through using this optimal LUT in the drive system, the system efficiency can be significantly improved for the entire operation range. The time-stepping FEM is used to simulate the PMSM system, which integrates the electromagnetic field analysis of the motor prototype and the control algorithm of the drive system. A 2-D transient FEM model is built for a 15 kW PMSM in ANSYS Maxwell, and a vector control circuit model is set up in ANSYS Simplorer. Experiments are carried out on the 15 kW PMSM prototype to verify the accuracy of the simulation results and the effectiveness of the proposed design method.
Does Politics Matter in the Conduct of Fiscal Policy? Political Determinants of the Fiscal Sustainability: Evidence from Seven Individual Central and Eastern European Countries (CEEC)

This paper aims at assessing the fiscal sustainability and its political determinants in seven Central and Eastern European Countries (CEEC), namely Estonia, Latvia, Lithuania, Poland, Slovenia, Slovakia and the Czech Republic. First, using the recent sustainability approach of Bohn (1998) based on fiscal reaction function, econometric findings using Ordinary Least Squares (OLS) reveal a positive response of the primary surplus to changes in debt in several countries. In other words, fiscal policy is sustainable in Baltic countries, Slovenia and Slovakia, but not in Poland and in the Czech Republic. Second, by introducing political dummy variables, we test the electoral budget cycle and the partisan cycle theories. We find the presence of electoral and partisan cycle in Poland but not in the rest of our countries.
Shaping single walled nanotubes with an electron beam

We show that electron irradiation in a dedicated scanning transmission microscope can be used as a nano-electron-lithography technique allowing the controlled reshaping of single walled carbon and boron nitride nanotubes. The required irradiation conditions have been optimized on the basis of total knock-on cross sections calculated within density functional based methods. It is then possible to induce morphological modifications, such as a local change of the tube chirality, by sequentially removing several tens of atoms with a nanometrical spatial resolution. We show that electron beam heating effects are limited. Thus, electron beam induced vacancy migration and nucleation might be excluded. These irradiation techniques could open new opportunities for nanoengineering a large variety of nanostructured materials.
CONSUMER‐CONTROLLED COMMUNITY STATES ON GULF OF MAINE ROCKY SHORES

Mussel beds and algal canopies on Gulf of Maine (USA) rocky shores have been hypothesized to represent stochastically determined community states, but we recently found that they were highly deterministic, consumer-controlled states in a tidal river. Mussel beds dominated high-flow habitats with high larval delivery and low consumer pressure, whereas algal canopies dominated low-flow habitats with high consumer pressure. In this paper we examine the alternative-community-state hypothesis on rocky shores on the open coast of Maine. We hypothesized that community states would be less deterministic due to reduced consumer pressure and more stochastic flow patterns. At 10 mussel-bed and 10 seaweed-canopy sites on the open coast of central Maine, we created 9-m2 and 1-m2 clearings and an unmanipulated control area, each containing control (no caging), caged, and cage-control quadrats. Independent of disturbance patch size, mussel beds and seaweed canopies rapidly began to return to their original community type in the absence of consumers (crabs and snails). With consumers present, recovery of the original communities did occur, but at a much slower pace. Our results suggest that mussel beds and algal canopies in the Gulf of Maine are deterministic consumer-controlled states, rather than being stochastically determined. If stochastic alternative community states exist in this system, they occur in a very restricted subset of habitats where the strong consumer control and determinism we have found in both tidal river and open coast habitats are relaxed.
Exploiting semantic structure for mapping user-specified form terms to SNOMED CT concepts

The elements of clinical databases are usually named after the clinical terms used in various design artifacts. These terms are instinctively supplied by the users, and hence, different users often use different terms to describe the same clinical concept. This term diversity makes future database integration and analysis a huge challenge. In this paper, we study the problem of standardization of the terms used in a specific kind of user-designed artifact, the encounter forms or templates, using a popular clinical terminology, the SNOMED CT. In particular, we focus on the problem of mapping the terms on an encounter form to SNOMED CT concepts. Existing term mapping techniques are solely based on syntactic string similarity. Such techniques are unable to disambiguate among the terms that resemble one another linguistically, and yet differ semantically. To improve existing techniques, we consider the context of a term in the mapping process and propose a hybrid approach relying on linguistics as well as structural information. For a given form term, this approach (i) exploits the semantic structure of the form to derive the term's context, and (ii) maps the term to a linguistically- matching SNOMED CT concept that is compatible with the derived context. We test the approach on over 900 clinician-specified terms used in 26 forms. This method achieves 23% improvement in precision and 38% improvement in recall, over a pure linguistic-based approach. Our first contribution is that we introduce and address a new problem of mapping form terms to standard concepts. The second contribution is that the experimental evaluation confirms that structural information has a major role in improving mapping performance, and in addressing the key challenges associated with semantic mapping.
New detectors for electron microscopy

Detectors for Electron Microscopy have traditionally used a scintillator to generate photons from fast electrons, which are then detected by a sensor. However, in recent years direct detection has become an area of interest due to the potential improvements to detector performance. In this thesis various aspects of direct detection are presented. I will begin with simulations of direct detectors based on Joy’s model of straight trajectories between Rutherford scattering events, where signal is generated by inelastic scattering events. The effects of microscope operating voltage, detector thickness, a surface electrically dead layer and diode depth on detector performance are presented. A prototype detector was developed using the DUOS sensor, two thicknesses of the sensor were produced a 50μm thick detector and a 20μm thick detector. EBSD results are presented which show how the use of a reactive ion etch to reduce the dead layer thickness of a mechanically thinned sensor improve the detection efficiency of a sensor allowing EBSD work to be carried out at operating voltages as low as 5keV. The MTF and DQE of both thicknesses of DUOS sensor are measured at 80kV and 200kV, which show that there is little difference between the two thicknesses at 80kV, but at 200kV the thinner detector shows an improved MTF. The results are then and compared with the equivalent simulated detectors. I show how the high frame rate of a detector and rigid and non-rigid registration can be used to improve image quality, resolving the {331} lattice spacing which is not visible with a simple summation of frames. Detectors using gallium nitride rather than silicon as the base semiconductor are simulated. The MTF at the Nyquist frequency for a GaN detector is double that of a Si detector at an operating voltages of 80kV due to the smaller interaction volume of an electron in GaN. However, at higher voltages the improvement is much smaller as most electrons pass through the detector.
Laplacian Pyramid of Conditional Variational Autoencoders

Variational Autoencoders (VAE) learn a latent representation of image data that allows natural image generation and manipulation. However, they struggle to generate sharp images. To address this problem, we propose a hierarchy of VAEs analogous to a Laplacian pyramid. Each network models a single pyramid level, and is conditioned on the coarser levels. The Laplacian architecture allows for novel image editing applications that take advantage of the coarse to fine structure of the model. Our method achieves lower reconstruction error in terms of MSE, which is the loss function of the VAE and is not directly minimised in our model. Furthermore, the reconstructions generated by the proposed model are preferred over those from the VAE by human evaluators.
Optimal design of 5G superfluid networks: Problem formulation and solutions

The forthcoming 5G technology foresees the exploitation of solutions able to increase both the flexibility and the scalability of the network. In line with the current trend of softwarization, in this work we face the problem of designing a 5G network from the outcome of the Horizon 2020 project Super-fluidity. The core of the project is the definition of a 5G converged architecture based on virtual entities, called Reusable Functional Blocks (RFBs), which can be run on different HardWare (HW) and SoftWare (SW) execution environments. The exploitation of RFBs allows to achieve the required level of flexibility required by 5G. After optimally formulating the problem of minimizing the total installation costs of a SuperFluid network composed of RFBs and physical 5G nodes, we propose a new algorithm, called SFDA, to practically tackle the problem. Our results, obtained over a representative case study, show that SFDA is able to solve the problem in a reasonable amount of time, returning solutions very close to the optimum. In addition, we clearly show the trade offs that emerge between the need of providing a service level to users (in terms of downlink traffic or coverage) and the total costs incurred to install the elements of the network.
A Phase Field Approach for Modeling Melting and Re-Solidification of Ti-6Al-4V during Selective Laser Melting

A Multi Phase Field model is proposed to describe the microstructure evolution induced by laser-material interaction in Selective Laser Melting (SLM). On the basis of the free enthalpy, the nucleation and growth processes occurring during the relevant phase transformations are explicitly taken into account. Within this contribution, the focus is laid on the SLM processing of the titanium alloy Ti-6Al-4V with special emphasis on the transition between β-titanium and melt. The results are discussed and compared to those of more conventional modelling approaches.
Oxidation of glutathione (GSH) in blood plasma due to oxidative stressors: A case study of silver

1 Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Gomal University, D. I. Khan, Pakistan. 2 Department of Pharmaceutics, Faculty of Pharmacy, Gomal University, D. I. Khan, Pakistan. 3 Faculty of Pharmacy and Alternative Medicine, the Islamia University of Bahawalpur, Pakistan. 4 Department of Pharmacy, University of Baluchistan, Quetta, Pakistan. 5 Gomal Center of Biochemistry and Biotechnology, Gomal University, D. I. Khan KPK, Pakistan.
Discovering Program Topoi Through Clustering

Understanding source code of large open-source software projects is very challenging when there is only little documentation. New developers face the task of classifying a huge number of files and functions without any help. This paper documents a novel approach to this problem, called FEAT, that automatically extracts topoi from source code by using hierarchical agglomerative clustering. Program topoi summarize the main capabilities of a software system by presenting to developers clustered lists of functions together with an index of their relevant words. The clustering method used in FEAT exploits a new hybrid distance which combines both textual and structural elements automatically extracted from source code and comments. The experimental evaluation of FEAT shows that this approach is suitable to understand open-source software projects of size approaching 2,000 functions and 150 files, which opens the door for its deployment in the open-source community.
Absent but Not Gone

Spouses influence each other’s psychological functioning and quality of life. To explore whether this interdependence continues after a person becomes widowed, we tested whether deceased spouses’ characteristics were associated with their widowed partners’ later quality of life using couples drawn from a multinational sample of aging adults. Independent subsamples (ns = 221 and 325) were assessed before and after a spouse’s death. Regressions revealed that deceased partners’ quality of life prior to their death positively predicted their spouses’ quality of life after the partners’ death, even when we controlled for spouses’ prior quality of life to account for environmental factors shared within couples. Further, widowed participants’ quality of life was lower than nonwidowed couples’ 2 years before and after their partners’ death, but was equivalent 4 years prior. Finally, the strength of the association between partners’ earlier quality of life and participants’ later quality of life did not differ between widowed and nonwidowed participants. These findings suggest that interdependence in quality of life continues after one’s partner has passed away.
A mixed-methods framework for analyzing text data: Integrating computational techniques with qualitative methods in demography

BACKGROUND Automated text analysis is widely used across the social sciences, yet the application of these methods has largely proceeded independently of qualitative analysis. OBJECTIVE This paper explores the advantages of applying automated text analysis to augment traditional qualitative methods in demography. Computational text analysis does not replace close reading or subjective theorizing, but it can provide a complementary set of tools that we believe will be appealing for qualitative demographers. METHODS We apply topic modeling to text data from the Malawi Journals Project as a case study. RESULTS We examine three common issues that demographers face in analyzing qualitative data: large samples, the challenge of comparing qualitative data across external categories, and making data analysis transparent and readily accessible to other scholars. We discuss ways that new tools from machine learning and computer science might help qualitative scholars to address these issues. CONCLUSIONS We believe that there is great promise in mixed-method approaches to analyzing text. New methods that allow better access to data and new ways to approach qualitative data are likely to be fertile ground for research. CONTRIBUTIONS No research, to our knowledge, has used automated text analysis to take an explicitly mixed-method approach to the analysis of textual data. We develop a framework that allows qualitative researchers to do so. 1 Department of Sociology, Princeton University, USA. E-Mail: parijatc@princeton.edu. 2 Department of Sociology, Princeton University, USA. Chakrabarti & Frye: A mixed-methods framework for analyzing text data 1352 http://www.demographic-research.org
Statin use linked with a decrease in the conversion from high-grade prostatic intraepithelial neoplasia (HGPIN) to prostate cancer

The roles of obesity, metabolic dysregulation and systemic inflammation to advance prostate carcinogenesis are unclear. This study investigates metabolic and inflammatory factors in the transition from high-grade prostatic intraepithelial neoplasia (HGPIN) to prostate cancer (PC). We prospectively followed 160 men diagnosed with HGPIN at biopsy and therefore at high-risk and clinically monitored for PC. Analyses investigated body mass index (BMI), waist circumference, waist-hip ratio (WHR), height, fat mass, lean mass percent body fat, NSAIDs, statins, metformin, diabetes, hypertension, hypercholesterolemia representing metabolic dysregulation on the risk of a PC diagnosis during follow-up. Systemic inflammation was estimated through measurement of 13 plasma cytokine levels. Statin use was significantly linked with overall PC at follow-up [odds ratio (OR) = 0.45, (0.23, 0.91), P = 0.03], with a somewhat stronger link with high-grade [OR = 0.39, (0.15, 1.04), P = 0.06] PC compared with low-grade PC [OR = 0.50, (0.23, 1.12), P = 0.09]. Non-statin cholesterol-lowering medications, BMI, WHR, diabetes, hypertension and percent body fat were not significantly associated with PC. Although blood IL-12p70, IL-2 and IL-1β levels were significantly lower among statin users, inflammatory markers were not significantly linked with PC and did not explain the observed relationship between statins and lower PC risk. In summary, this prospective study of HGPIN patients at high risk for PC finds that statin use was significantly associated with reduced risk of PC detection at follow-up. Systemic markers of inflammation did not mediate this association, suggesting that statins affect PC progression through alternative pathways.
Robust automatic detection of P wave and T wave in electrocardiogram

The Electrocardiogram (ECG) is a significant tool to investigate the electrical activity of the heart. Even though P and T waves reveal very useful information, their accurate detection is a difficult and challenging task on account of noise, baseline drift and odd morphologies. The need for a rapid and effective detection algorithm motivated us to propose two automated methods: the percentile based Automatic Detection (pAD) and the Graphical based Automatic Detection (gAD). Both algorithms use statistical and probabilistic concepts to achieve adequate delineation and detection of the waves. The former uses the percentile as an adaptive threshold to define the location of these waves. The latter uses a "feature wave-bank" to train a graphical probabilistic model named as Hidden Conditional Random Field (HCRF). The gAD algorithm takes advantage of the monotonicity and the slope of an ECG to detect and collect waves, which imports to the graphical model and classifies them to P or T waves. The efficiency of our proposed algorithms has been evaluated on 10 long-term (24-hour) ECG recordings of MIT-BIH Normal Sinus Rhythm Database. The training set we used for gAD was very small, only the 0.2% of the total number of the available waves. The results show a significant and promising detection accuracy rate.
Predicting the State of Agents Using Motion and Occupancy Grids

This paper presents an approach to predicting the future state of dynamic agents using an extension to occupancy grids that we have called motion and occupancy grids. These grids capture both the location and motion of an agent. The basis of the prediction is to model the behaviour of an agent as the probability of transitions between the states represented in the grid. Prediction can then be made using a Markov chain. The potential state explosion inherent in this method is overcome by dynamically building the state transition matrix in a tree structure. The results show that the system is able to rapidly develop probabilistic models of complex agents and predict their future state.