Miracle-dz/UniFAR-FTUs huggingface dataset:
Dispersion Engineering: The Use of Abnormal Velocities and Negative Index of Refraction to Control Dispersive Effects

In recent years two discoveries have led to the possibility of manufacturing materials and structures with dispersive behaviors previously thought unattainable. These are media with an effective negative index of refraction (NIR) also known as the left handed media (LHM) or negative-refractive-index metamaterials [1–4], and the possibility of measuring superluminal 1 or negative group velocities also generically referred to as abnormal group velocities [5–9]. In this manuscript we study the underlying physics and manifestations of these rather unusual behaviors, and will see how a medium can be manufactured that simultaneously demonstrates both properties. But before proceeding, let us describe our motivation behind this approach and see how combining these two effects may lead to the design of new classes of materials with novel and counter-intuitive dispersive effects, a subject we have termed “Dispersion Engineering. ” The fact that any physically realizable medium must be dispersive is the consequence of the principle of causality which demands no effect to precede its cause [10]. In the simple case of one-dimensional analysis, the dispersive behavior of a medium can be described by the dependence of the propagation vector on frequency (or equally well
Wet scavenging limits the detection of aerosol–cloud–precipitation interactions

Satellite studies of aerosol–cloud interactions usually make use of retrievals of both aerosol and cloud properties, but these retrievals are rarely spatially co-located. While it is possible to retrieve aerosol properties above clouds under certain circumstances, aerosol properties are usually only retrieved in cloud free scenes. Generally, the smaller spatial variability of aerosols compared to clouds reduces the importance of this sampling difference. However, as precipitation generates an increase in spatial variability, the imperfect co-location of aerosol and cloud property retrievals may lead to changes in observed aerosol–cloud–precipitation relationships in precipitating environments. In this work, we use a regional-scale model, satellite observations and reanalysis data to investigate how the non-coincidence of aerosol, cloud and precipitation retrievals affects correlations between them. We show that the difference in the aerosol optical depth (AOD)-precipitation relationship between general circulation models (GCMs) and satellite observations can be explained by the wet scavenging of aerosol. Using observations of the development of precipitation from cloud regimes, we show how the influence of wet scavenging can obscure possible aerosol influences on precipitation from convective clouds. This obscuring of aerosol–cloud–precipitation interactions by wet scavenging suggests that even if GCMs contained a perfect representation of aerosol influences on convective clouds, the difficulty of separating the "clear-sky" aerosol from the "all-sky" aerosol in GCMs may prevent them from reproducing the correlations seen in satellite data.
A performance focused, development friendly and model aided parallelization strategy for scientific applications

The amelioration of high performance computing platforms has provided unprecedented computing power with the evolution of multi-core CPUs, massively parallel architectures such as General Purpose Graphics Processing Units (GPGPUs) and Many Integrated Core (MIC) architectures such as Intel’s Xeon phi coprocessor. However, it is a great challenge to leverage capabilities of such advanced supercomputing hardware, as it requires efficient and effective parallelization of scientific applications. This task is difficult mainly due to complexity of scientific algorithms coupled with the variety of available hardware and disparate programming models. To address the aforementioned challenges, this thesis presents a parallelization strategy to accelerate scientific applications that maximizes the opportunities of achieving speedup while minimizing the development efforts. Parallelization is a three step process (1) choose a compatible combination of architecture and parallel programming language, (2) translate base code/algorithm to a parallel language and (3) optimize and tune the application. In this research, a quantitative comparison of run time for various implementations of k-means algorithm, is used to establish that native languages (OpenMP, MPI, CUDA) perform better on respective architectures as opposed to vendor-neutral languages such as OpenCL. A qualitative model is used to select an optimal architecture for a given application by aligning the capabilities of accelerators with characteristics of the application. Once the optimal architecture is chosen, the corresponding native language is employed. This approach provides the best performance with reasonable accuracy (78%) of predicting a fitting combination, while eliminating the need for exploring different architectures individ-
Effects of humidity level and IBA dose application on the softwood top cuttings of white mulberry (Morus alba L.) and black mulberry (Morus nigra L.) types.

In this research, the effects of 85-90% relative humidity and indol-3-butyric acid (IBA) doses on softwood top cuttings of two black mulberry (Types 1 and 2) and one white mulberry (Type 3) types were studied. Cuttings were taken from early June (14 Haziran) and applied to the different IBA doses (0, 1000, 2000, 3000 and 4000 ppm). Cuttings were planted in pumice medium under misting system in the greenhouse for 48 days in order to root. The highest rooting percentage was determined from Type 1 (black mulberry) in 2000 and 3000 ppm IBA doses application (100%). The lowest one was control group from Type 2 (black mulberry) which was not rooted. Acording to increase liveliness of the cuttings, rooting percentage increased. Nearly all of the living cuttings were rooted. The highest ratio of cutting callus formation was found to be 2000 and 3000 ppm IBA doses (100%) from Type 1; the lowest one was determined control group of Types 2 and 3 (0.00%). The highest rooting area lenght was found from Type 3 (2.00 cm) and Type 1 (1.92 cm); the lowest one was control group of Type 2 (0.00 cm). With respect to root numbers, the highest value was found from Type 3 (21.73 number/cutting) and Type1 (16.42 number/cutting); the lowest one was control group of Type 2 (0.00 number/cutting). The longest root was determined from 3000 ppm IBA dose of Type 1 (11.23 cm); the highest root branching value was found from Type 3 in 3000 ppm IBA dose (16.20 number/cutting) application.
Predictive energy management in smart vehicles: Exploiting traffic and traffic signal preview for fuel saving

This master thesis proposes methods for improving fuel economy and emissions of vehicles via use of future information of state of traffic lights, traffic flow, and deterministic traffic flow models. The first part of this thesis proposes use of upcoming traffic signal information within the vehicle’s adaptive cruise control system to reduce idle time at stop lights and lower fuel use. To achieve this goal an optimization-based control algorithm is formulated for each equipped vehicle that uses short range radar and traffic signal information predictively to schedule an optimum velocity trajectory for the vehicle. The objectives are timely arrival at green light with minimal use of braking, maintaining safe distance between vehicles, and cruising at or near set speed. Three example simulation case studies are presented to demonstrate potential impact on fuel economy, emission levels, and trip time. The second part of this thesis addresses the use of traffic flow information to derive the fuelor time-optimal velocity trajectory. A vehicle’s untimely arrival at a local traffic wave with lots of stops and goes increases its fuel use. This paper proposes predictive planning of the vehicle velocity for reducing the velocity transients in upcoming traffic waves. In this part of the thesis macroscopic evolution of traffic pattern along the vehicle route is first estimated by combining a traffic flow model and real-time traffic data streams. The fuel optimal velocity trajectory is calculated by solving an optimal control problem with the spatiotemporally varying constraint imposed by the traffic. Simulation results indicate
Prognostic Values of LAPTM4B-35 in Human Cancer: A Meta-analysis

Background: Lysosome-associated protein transmembrane-4β-35(LAPTM4B-35) has been observed overexpressed in multiple malignant tumors. However, the prognostic value of LAPTM4B-35 remains controversial. Therefore, we conducted a meta-analysis to evaluate the prognostic value of LAPTM4B-35 in human cancers. Methods: The relevant publications were obtained by systematically searching the PubMed, Web of Science, Embase, Wanfang, and China National Knowledge Infrastructure (CNKI) databases. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated for the prognosis value of LAPTM4B-35 for cancer patient. Results: Our result suggest that LAPTM4B-35 overexpression is significantly associated with poor overall survival (OS) (HR = 2.49, 95% CI = 1.87-3.32, p < 0.001), disease-free survival (DFS) (HR = 2.43, 95% CI = 1.35-4.35, p = 0.003), and progression-free survival (PFS) (HR = 4.12, 95% CI = 2.30-7.37, p < 0.001). Moreover, subgroup analysis revealed significant association with poor OS in lung (HR = 2.05, 95% CI = 1.37-3.06, p < 0.001), gastric carcinoma (HR = 1.88, 95% CI = 1.01-3.50, p < 0.047) and ovarian cancer (HR = 4.94, 95% CI = 1.44-16.94, p = 0.011). Conclusion: LAPTM4B-35 may be a novel predictive biomarker and a potential target for treatment.
Methods to Identify User Needs and Decision Mechanisms for the Adoption of Electric Vehicles

The knowledge on user acceptance for electric vehicles is of high relevance for several stakeholders in this new vehicle market. This study provides an overview of applied methods in adoption research in the field of electric vehicles. These methods comprehend (1) experimental studies and lab-experiments, (2) interviews and focus groups, (3) surveys, (4) analyses of sales documentations and (5) social media analytics. We classify the data collection methods by two dimensions – (A) sample size and (B) degree of anonymity. We provide case study results for selected methods, identify the advantages, and show how new methods may complement the traditional approaches in future research.
Forensic Analysis of Smartphones: The Android Data Extractor Lite (ADEL)

Due to the ubiquitous use of smartphones, these devices become an increasingly important source of digital evidence in forensic investigations. Thus, the recovery of digital traces from smartphones often plays an essential role for the examination and clarification of the facts in a case. Although some tools already exist regarding the examination of smartphone data, there is still a strong demand to develop further methods and tools for forensic extraction and analysis of data that is stored on smartphones. In this paper we describe specifications of smartphones running Android. We further introduce a newly developed tool – called ADEL – that is able to forensically extract and analyze data from SQLite databases on Android devices. Finally, a detailed report containing the results of the examination is created by the tool. The whole process is fully automated and takes account of main forensic principles.
Image Denoising Algorithm Combined with SGK Dictionary Learning and Principal Component Analysis Noise Estimation

SGK (sequential generalization of -means) dictionary learning denoising algorithm has the characteristics of fast denoising speed and excellent denoising performance. However, the noise standard deviation must be known in advance when using SGK algorithm to process the image. This paper presents a denoising algorithm combined with SGK dictionary learning and the principal component analysis (PCA) noise estimation. At first, the noise standard deviation of the image is estimated by using the PCA noise estimation algorithm. And then it is used for SGK dictionary learning algorithm. Experimental results show the following: (1) The SGK algorithm has the best denoising performance compared with the other three dictionary learning algorithms. (2) The SGK algorithm combined with PCA is superior to the SGK algorithm combined with other noise estimation algorithms. (3) Compared with the original SGK algorithm, the proposed algorithm has higher PSNR and better denoising performance.
WP-EC 2009-12 Do process innovations boost SMEs productivity growth ? *

In this paper we explore in depth the effect of process innovations on total factor productivity growth for small and medium enterprises (SMEs), taking into account the potential endogeneity problem that may be caused by self selection into these activities. First, we analyse whether the ex-ante most productive SMEs are those that start introducing process innovations; then, we test whether process innovations boost SMEs productivity growth using matching techniques to control for the possibility that selection into introducing process innovations may not be a random process. We use a sample of Spanish manufacturing SMEs for the period 1991-2002, drawn from the Encuesta sobre Estrategias Empresariales. Our results show that the introduction of process innovations by a first-time process innovator yields an extra productivity growth as compared to a non-process innovator, and that the life span of this extra productivity growth has an inverted U-shaped form.
Damage caused by citrus canker on Valencia sweet orange yield

The citrus canker, caused by Xanthomonas axonopodis pv. citri, is one of the main citrus diseases and has threatened the world's citriculture. In this study, the damage caused by citrus canker was quantified in a sweet orange culture, cv. Valencia [Citrus sinensis (L.) Osb. ], grafted over 15 year-old Rangpur lime (C. limonia Osb.), in the municipality of Guatambu, SC, Brazil, in the crop of 2004/05. Evaluations of the number of fruits per plant (NF), fruit yield per plant (P), citrus canker incidence on the fruit (IFR), and incidence (IL) and severity (SV) of citrus canker on 80 leaves per orange tree were performed in the harvest period, applying diagrammatical scales. Plants had large variation in SV (0.16%-1.09%), IL (12.50%-56.25 %) and IFR (12.30%-56.09%). Linear regressions were significant between IL x SV, NF x SV, P x IFR, and NF x IFR. There was no significant difference (p>0.05) between the mean estimated values of IL in different quadrants of the crowns of the orange trees (N, S, L and O). Each 1% increase in IFR reduced 2.16 kg and 21.3 fruits per tree
Analysis of organic aerosol in Houston, TX, through aerosol mass spectrometry and proton nuclear magnetic resonance spectroscopy

ANALYSIS OF ORGANIC AEROSOL IN HOUSTON, TX, THROUGH AEROSOL MASS SPECTROMETRY AND PROTON NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY By Meredith J. Cleveland University of New Hampshire, August 2009 Organic aerosol from Houston, TX, was measured during August and September of 2006 as part of the Texas Air Quality Study II Radical and Aerosol Measurement Project. Aerosol size and composition were determined using an Aerodyne quadrupole aerosol mass spectrometer, and twenty-nine aerosol filter samples were analyzed using proton nuclear magnetic resonance (H-NMR) spectroscopy to determine the relative concentrations of functional groups. Results indicate that changes in Houston aerosol are due to anthropogenic activities resulting in hydrocarbon-like organic aerosol (HOA). Aerosols are less oxygenated than those observed in previous studies, with smaller concentrations of unsaturated groups, and do not fit H-NMR source apportionment fingerprints used for identification of secondary organic aerosol, marine organic aerosol, and biomass burning organic aerosol. It is recommended that a new fingerprint for highly urbanized locations be established utilizing these data and those from other large, polluted cities.
Simulated hail impact testing of photovoltaic solar panels

Techniques used to simulate and study the effect of hail on photovoltaic solar panels are described. Simulated hail stones (frozen ice spheres projected at terminal velocity) or steel balls were applied by air guns, gravity drop, or static loading. Tests with simulated hail and steel balls yielded different results. The impact strength of 10 commercially available flat-plate photovoltaic modules was tested. It was found that none of the six panel designs incorporating clear potting silicone material as the outermost layer remained undamaged by 1-in. simulated hailstones, while a photovoltaic module equipped with a 0.188-in. -thick acrylic cover sheet would be able to withstand the impact of a 2-in. -diameter hailstone.
Can we perceive changes in our moving speed: a comparison between directly and indirectly powering the locomotion in virtual environments

Many categories of the illusion of self-motion have been widely studied with the potential support of virtual reality. However, the effects of directly and indirectly powering the movement on the possibility of perceiving changes in moving speed and their relationship with sensory feedback on users' speed change perception have not been investigated before. In this paper, we present the results of our user study on the difference in perceiving changes in moving speed between two different movement techniques: "pedaling" and "throttling". We also explore the effects of different velocity gains, accelerations and speeds of airflow, and their interactions with the movement techniques on users' perception of speed changes in addition to user performance and perception. We built a bike simulator that supports both of the movement techniques and provides sensory feedback. In general, "pedaling" gave users more possibility to perceive changes in moving velocity than "throttling".
Metabolomic Profiling of Lipids for Biomarker Discovery

Volume 1 • Issue 5 • 1000e115 Biochem Anal Biochem ISSN:2161-1009 Biochem, an open access journal Biomarkers are key molecular or cellular substances that are evaluated as indicators of a biological state. They play an important role in understanding the biological processes, pathogenic processes, and pharmacologic responses. Some of the methods to discover biomarkers in different disease models include enzyme-linked immunosorbent assays (ELISA) [1], biosensors [2,3], gas chromatography/mass spectrometry (GC/MS) [4], liquid chromatography (LC) /MS [5], and LC/MS/MS [6,7]. LC/MS/MS is currently the most powerful tool for metabolomic profiling of biomarker discovery due to its specificity and high sensitivity. Metabolomics is the systematic study of the unique chemical fingerprints of small molecules or metabolite profiles that are related to a variety of cellular metabolic processes in a cell, organ, or organism. Metabolic profiling provides direct and indirect physiologic insights that can potentially be detectable in a wide range of biospecimens. Metabolomic platforms for lipids are important because these signaling molecules regulate many fundamental biological processes. For example, the lipids of the arachidonate cascade, which includes eicosanoids, are the targets of 75% of the world’s pharmaceuticals. This article is focused on the application of metabolomics profiling of lipids and the analytical method for lipids profiling is described elsewhere [8].
Impacts of climate change on fire activity and fire management in the circumboreal forest

Forest fires are a significant and natural element of the circumboreal forest. Fire activity is strongly linked to weather, and increased fire activity due to climate change is anticipated or arguably has already occurred. Recent studies suggest a doubling of area burned along with a 50% increase in fire occurrence in parts of the circumboreal by the end of this century. Fire management agencies' ability to cope with these increases in fire activity is limited, as these organizations operate with a narrow margin between success and failure; a disproportionate number of fires may escape initial attack under a warmer climate, resulting in an increase in area burned that will be much greater than the corresponding increase in fire weather severity. There may be only a decade or two before increased fire activity means fire management agencies cannot maintain their current levels of effectiveness.
A comparative study on pile group and piled raft foundations ( PRF ) behavior under seismic loading

Study on the seismic behavior of piled rafts and pile groups while the same amount of construction material and excavation is used in their construction, are the main objective of this research. The process where the raft interaction with soil can affect the seismic response and stress distribution is also discussed in the current study. By means, ABAQUS software was applied for the finite element modeling. Firstly, for calibration and verification of the procedure of modeling with two other experimental studies, results were compared by the analysis of models under single frequency sinusoidal dynamic loads. Moreover, analyses of the same models were applied under the acceleration time history of the El-Centro earthquake. Results indicate that the participation of the raft interaction with soil under seismic loading, well improves the seismic response and behavior of a piled foundation systems i.e. internal moments and shear forces as well as deflection. Reductions of maximum acceleration response, horizontal displacement and bending moment in the piled raft system, are some important gained results by this study. In addition, the more uniform stress distribution in soil deposit and prevention of stress concentration leads to the reduction of the piled rafts settlement during earthquakes.
OFDM S YSTEMS WITH A L ARGE N UMBER OF S UBCARRIERS

A major drawback of orthogonal frequency division multiplexing (OFDM) signals is extremely high peak-to-average power ratio (PAPR). Signals with high PAPR lead to a lowering of the energy efficiency of power amplifiers and the shortened operation time causes a serious problem in battery-powered wireless terminals. We have found the CAZAC precoding makes the PAPR of M-array quadrature amplitude modulation (M-QAM) OFDM signals into the PAPR of M-QAM single-carrier signals. Therefore, it can dramatically improve the PAPR of OFDM signals. However, to satisfy the 3GPP-LTE specification of frequency spectrum, severe bandpass filtering of CAZAC-OFDM signal lead to unacceptable regrowth of the PAPR. The paper provides available control procedure for PAPR and spectrum managements. It is confirmed that the CAZAC-OFDM signal controlled by our procedure maintains enough low PAPR and can provide comparable spectral specifications in the downlink channel of 3GPPLTE standard.
Gender Diversity: To Be Managed or Not?

The purpose of this paper is to examine women’s perceptions of the manufacturing industry in the UK. More specifically, the research analyses factors influencing women’s decision on pursuing a career in the manufacturing industry at a Multinational Company. The findings indicate that the factors impacting women to pursuing a career in manufacturing are underlined by a complex interrelated system and depend on both societal and organisational patterns of behaviours, values and norms. Insights of this are particularly useful for managers and organisations operating in the manufacturing industry. The study suggests underlying reasons and implications that can be implemented. This study is based on a convenience sample and cannot be treated as a representative for the entire UK manufacturing industry.