Miracle-dz/UniFAR-FTUs huggingface dataset:
Inkjet printing in polymer electrolyte membrane electrolysis

In proton exchange membrane fuel cells (PEFCs), the catalyst and electrolyte loading have been shown to have an important effect in the performance and efficiency of the device. On the contrary, literature analyzing the effect of the fabrication method, catalyst and ionomer loading in proton exchange membrane electrolysis (PEME) scarce. The focus of this research is an empirical study of the catalyst and electrolyte loading on the anode of a PEME manufactured using an inkjet printer. Characterizing the effect and interaction of both parameters will help to optimize the fabrication of the membrane electrolyte assembly (MEA). Results show a best performance using 2%wt NafionQR while 1.5 mg IrO2/cm2 catalyst loading. A voltage of 1650 mV at 1A/cm2 and 1760 mV at 2A/cm2 were achieved for an anode loading of 1.1 mg IrO2/cm2. Decreasing the drop size in the printing procedure leads to a greater thickness of the electrodes and a better performance of the cell. Using this new printing method, the efficiency of the PEME was improved from a 70.8% to a 74.4% at 1A/cm2 using the same amount of catalyst.
Human Monoclonal Antibodies Directed against Toxins A and B Prevent Clostridium difficile-Induced Mortality in Hamsters

ABSTRACT Clostridium difficile is the leading cause of nosocomial antibiotic-associated diarrhea, and recent outbreaks of strains with increased virulence underscore the importance of identifying novel approaches to treat and prevent relapse of Clostridium difficile-associated diarrhea (CDAD). CDAD pathology is induced by two exotoxins, toxin A and toxin B, which have been shown to be cytotoxic and, in the case of toxin A, enterotoxic. In this report we describe fully human monoclonal antibodies (HuMAbs) that neutralize these toxins and prevent disease in hamsters. Transgenic mice carrying human immunoglobulin genes were used to isolate HuMAbs that neutralize the cytotoxic effects of either toxin A or toxin B in cell-based in vitro neutralization assays. Three anti-toxin A HuMAbs (3H2, CDA1, and 1B11) could all inhibit the enterotoxicity of toxin A in mouse intestinal loops and the in vivo toxicity in a systemic mouse model. Four anti-toxin B HuMAbs (MDX-1388, 103-174, 1G10, and 2A11) could neutralize cytotoxicity in vitro, although systemic toxicity in the mouse could not be neutralized. Anti-toxin A HuMAb CDA1 and anti-toxin B HuMAb MDX-1388 were tested in the well-established hamster model of C. difficile disease. CDA1 alone resulted in a statistically significant reduction of mortality in hamsters; however, the combination treatment offered enhanced protection. Compared to controls, combination therapy reduced mortality from 100% to 45% (P < 0.0001) in the primary disease hamster model and from 78% to 32% (P < 0.0001) in the less stringent relapse model.
Interactive visualization of scattered moment tensor data

Moment tensors derived from seismic measurements during earthquakes are related to stress tensors and keep important information about surface displacement in the earth's mantle. We present methods facilitating an interactive visualization of scattered moment data to support earthquake and displacement analysis. For this goal, we combine and link visualizations of spatial location and orientation information derived from moment tensor decompositions. Furthermore, we contribute new tensor glyphs highlighting the indefinite character of moment tensors as well as novel tensor clustering and averaging techniques to aid interactive visual analysis and ease the challenges of interpreting moment tensor data.
The methodology for defect quantification in concrete using IR thermography

AbstractThis paper presents a procedure for detecting and quantifying defects in reinforced concrete structures by using the method of active infrared thermography (IRT). For quantitative analysis, a methodology of thermal stimulation of concrete specimens and post-processing of the gathered data was developed. Presented methodology uses principles of step heating (SH) thermography, pulsed phase (PPT) thermography, principal component thermography (PCT) and correlation operators technique. A short descriptions of the post-processing methods used in the research is also provided in the paper. All three post-processing methods i.e. PPT, PCT and correlation operators technique have shown the possibility to enhance the defect detection in concrete structures in comparison to raw thermograms. According to the data accessible to the authors, in presented research, correlation operators and PCT post-processing techniques are being successfully used for the first time for defect detection within concrete structur.
Toward the virtual cell: Automated approaches to building models of subcellular organization “learned” from microscopy images

We review state‐of‐the‐art computational methods for constructing, from image data, generative statistical models of cellular and nuclear shapes and the arrangement of subcellular structures and proteins within them. These automated approaches allow consistent analysis of images of cells for the purposes of learning the range of possible phenotypes, discriminating between them, and informing further investigation. Such models can also provide realistic geometry and initial protein locations to simulations in order to better understand cellular and subcellular processes. To determine the structures of cellular components and how proteins and other molecules are distributed among them, the generative modeling approach described here can be coupled with high throughput imaging technology to infer and represent subcellular organization from data with few a priori assumptions. We also discuss potential improvements to these methods and future directions for research.
Ageing Populations and Intergenerational Risk-sharing in PAYG Pension Schemes

The purpose of this paper is to compare pension schemes with respect to their intergenerational redistributive effects caused by economic and demographic changes. It is shown how these effects depend on the specific design of the pension scheme, with special attention devoted to the indexation problem. There is a potential trade-off between financial stability of the pension system and a “desired” distribution between generations. A buffer fund is often seen as the remedy to demographic strain and potential conflict. Therefore, the possibility of accumulating (and de-cumulating) a buffer fund is included. A lifecycle perspective is applied and the risk-sharing is measured by different generations’ rate of return. The analysis is carried out within the framework of an over-lapping generation model in the setting of a stylised economy.
A Comparative Study in Classification Techniques for Unsupervised Record Linkage Model

Problem statement: Record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. To find out whether two records are duplicate or not, supervised and unsupervised classification techniques are utilized in different studies. In order to utilize the supervised classification algorithms without consuming a lot of time for labeling data manually, a two step method which selects the training data automatically has been proposed in previous studies. However, the effectiveness of different classification techniques is the issue which should be taken into accounts in record linkage systems in order to classify records more accurately. Approach: To determine and compare the effectiveness of different supervised classification techniques in an unsupervised manner, some of the prominent classification methods are applied in duplicate records detection. Duplicate detection and classification of records in two real world datasets, namely Cora and Restaurant is experimented by Support Vector Machines, Naive Bayes, Decision Tree and Bayesian Networks which are regarded as some prominent classification techniques. Results: As experimental results show, while Support Vector Machines outperforms with F-measure of 96.27% in Restaurant dataset, for Cora dataset, the effectiveness of Naive Bayes is the best and it leads to an improvement with F-measure of 89.7%. Conclusion/Recommendation: The result of detecting duplicate records with different classification techniques tends to fluctuate depending on the dataset which is used. Moreover, Support Vector Machines and Naive Bayes outperform other methods in our experiments.
Implementation of Dynamic Voltage Restorer ( DVR ) and Distribution Static Compensator ( D-STATCOM ) for Power Quality Improvement

Power quality has become an important issue in recent times when many utilities around the world find very difficult to meet energy demands which leads to load shedding and power quality problem. Utility distribution networks, sensitivity industrial loads and critical commercial operations suffer from various types of outages and service interruptions which can cost significant financial losses. Voltage sags, swell, are the most important power quality problems which are seen in industrial and commercial installations. This research describes the improvement of power quality in a distribution system byusing Dynamic Voltage Restorer (DVR) compensation and Distribution Static Compensator (D-STATCOM). From the simulation results, the voltage sags before and after compensation is improved from 0.236 per unit to 0.923 per unit respectively, while voltage swell is improved from 1.462 per unit to 1.122 per unit respectively. PSCAD/EMTDC software is using for simulation purposes.
Preparation of Activated Carbon from Sugarcane Bagasse Waste for the Adsorption Equilibrium and Kinetics of Basic Dye

This research aimed to study the preparation of activated carbon from sugarcane bagasse waste. The sugarcane bagasse adsorbent was prepared by calcination at 600°C for 2 hours with the use of sulfuric acid (H2SO4) as a chemical activation. The adsorption surface possessed high specific surface area (838 m2/g) with mesoporous diameter. Factors explaining adsorption including adsorption isotherm, adsorption kinetic and adsorption mechanism were constructed from methylene blue adsorption experiments. It was found that the equilibrium data was best represented by Freundlich isotherm, showing multilayer coverage of dye molecules at the outer surface of adsorbent with a cooperative adsorption (physisorption and chemisorption). The kinetic of methylene blue adsorption was found to follow pseudo-second-order rate kinetic model, with a good correlation coefficient. This indicated that the overall rate of the dye adsorption process was controlled by the chemisorption process.
Synthesis of spherical microscale and nanoscale modified silica particles using spray-drying and spray-pyrolysis process

In the present work, we prepared modified and unmodified microscale and nanoscale silica particles using spray-drying and the spray-pyrolysis process, respectively, which could be an alternative for the production of this kind of product in industrial scale. For it, modified Stöber method was used to synthetize the precursor solution including tetraethyl orthosilicate (TEOS) and triethoxy(octyl)silane (ETOS) as precursors and 3-(Trimethoxysilyl)propyl methacrylate (γ-MPS) as template for the functionalization. The silica sol passed into both equipment to obtain the final powder. The surface morphology was investigated with Scanning Electron Microscopy (SEM), and the Fourier Transform Infrared spectroscopy (FT-IR) was used to describe the functionalization of the final powder. SEM results show that we successfully synthetized spherical microscale and nanoscale particles with spray-drying and spray-pyrolysis process, respectively. The FT-IR analysis show the functionalization of the silica powder obtained with both technologies. It is possible to consider these technologies as a simple way to produce modified spherical silica particles in an industrial scale.
On Mining Satellite and other Remotely Sensed Images

Advanced data mining technologies and the large quantities of Remotely Sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data, can be of importance in precision agriculture, community planning, resource discovery and other areas. However, in most cases the image data sizes are too large to be mined in a reasonable amount of time using standard methods. A new spatial data organization, bit Sequential organization (bSQ) and a new “data-mining ready” data structure, the Peano Count Tree (Ptree) provide a lossless and compressed representation of image data which facilitate association rule mining, classification and other data mining techniques markedly. In this paper we propose a new model for association rule mining and classification on spatial datasets using Ptrees. Experimental results show the new model applies well to data mining on Remotely Sensed Imagery data.
Parallelism in the front-end

As processor back-ends get more aggressive, front-ends will have to scale as well. Although the back-ends of superscalar processors have continued to become more parallel, the front-ends remain sequential. We describe techniques for fetching and renaming multiple noncontiguous portions of the dynamic instruction stream in parallel using multiple fetch and rename units. It demonstrates that parallel front-ends are a viable alternative to high performance sequential front-ends. Compared with an equivalently sized trace cache, our technique increases cache bandwidth utilization by 17%, front-end throughput by 20%, and performance by 5%. Parallelism also enhances latency tolerance: a parallel front-end loses only 6% performance as the cache size is decreased from 128 KB to 8 KB, compared with a 50-65% performance loss for sequential fetch mechanisms.
Hybrid Wireless-Optical Broadband-Access Network (WOBAN): A Review of Relevant Challenges

The hybrid wireless-optical broadband-access network (WOBAN) is a promising architecture for future access networks. Recently, the wireless part of WOBAN has been gaining increasing attention, and early versions are being deployed as municipal access solutions to eliminate the wired drop to every wireless router at customer premises. This architecture saves on network deployment cost because the fiber need not penetrate each end-user, and it extends the reach of emerging optical-access solutions, such as passive optical networks. This paper first presents an architecture and a vision for the WOBAN and articulates why the combination of wireless and optical presents a compelling solution that optimizes the best of both worlds. While this discussion briefly touches upon the business drivers, the main arguments are based on technical and deployment considerations. Consequently, the rest of this paper reviews a variety of relevant research challenges, namely, network setup, network connectivity, and fault-tolerant behavior of the WOBAN. In the network setup, we review the design of a WOBAN where the back end is a wired optical network, the front end is managed by a wireless connectivity, and, in between, the tail ends of the optical part [known as optical network unit (ONU)] communicate directly with wireless base stations (known as ldquogateway routersrdquo). We outline algorithms to optimize the placement of ONUs in a WOBAN and report on a survey that we conducted on the distribution and types of wireless routers in the Wildhorse residential neighborhood of North Davis, CA. Then, we examine the WOBAN's routing properties (network connectivity), discuss the pros and cons of various routing algorithms, and summarize the idea behind fault-tolerant design of such hybrid networks.
DIVERSITY IN THE WEAPONS OF SEXUAL SELECTION: HORN EVOLUTION IN THE BEETLE GENUS ONTHOPHAGUS (COLEOPTERA: SCARABAEIDAE)

Abstract Both ornaments and weapons of sexual selection frequently exhibit prolific interspecific diversity of form. Yet, most studies of this diversity have focused on ornaments involved with female mate choice, rather than on the weapons of male competition. With few exceptions, the mechanisms of divergence in weapon morphology remain largely unexplored. Here, we characterize the evolutionary radiation of one type of weapon: beetle horns. We use partial sequences from four nuclear and three mitochondrial genes to develop a phylogenetic hypothesis for a worldwide sample of 48 species from the dung beetle genus Onthophagus (Coleoptera: Scarabaeidae). We then use these data to test for multiple evolutionary origins of horns and to characterize the evolutionary radiation of horns. Although our limited sampling of one of the world's most species-rich genera almost certainly underestimates the number of evolutionary events, our phylogeny reveals prolific evolutionary lability of these exaggerated sexually selected weapons (more than 25 separate gains and losses of five different horn types). We discuss these results in the context of the natural history of these beetles and explore ways that sexual selection and ecology may have interacted to generate this extraordinary diversity of weapon morphology.
On the uniqueness of solutions to quadratic BSDEs with convex generators and unbounded terminal conditions: the critical case

In [3], the authors proved that uniqueness holds among solutions whose exponentials are $L^p$ with $p$ bigger than a constant $\gamma$ ($p\textgreater{}\gamma$). In this paper, we consider the critical case: $p=\gamma$. We prove that the uniqueness holds among solutions whose exponentials are $L^\gamma$ under the additional assumption that the generator is strongly convex.
Towards Modeling and Validating Analysis Processes for Software Adaptation

With the complexity and the dynamic analysis requirements during software adaptation for software in the open and dynamic environment, the software analysis requires integrating multiple analysis methods and controlling the execution of analysis methods in specific sequence. As a result, the analysis process is hard to be communicated to its designers, implementers and users without an explicit model. In addition, if dependent methods are not included or encounter runtime failure, the data dependency and control dependency between analysis methods may cause correctness problem. In this paper, we proposed a domain-specific language for modeling the analysis process using subset of notations from BPMN. In order to cope with the dependency problem in model and implementation level, the dependency relationships are divided into static dependency and dynamic dependency. Dependency identification and matching algorithm is provided to assure the static dependency in the analysis process model. For the dynamic dependency, we provide a service to detect the analysis failure caused by dynamic dependency. We model and validate two analysis processes supporting software adaptation with performance and reliability concerns, and apply the analysis processes in analyzing a running system ECPerf. Keywordssoftware analysis; analysis process, process validation, analysis process modeling
Spatio-Temporal Bias-Tunable Readout Circuit for On-Chip Intelligent Image Processing

A new 96 × 96 array of 30 μm × 30 μm readout integrated circuit (ROIC) with an individual pixel tunable bias control is demonstrated. Detailed IC design, test structures, readout circuit building blocks, and applied techniques are discussed. The new ROIC is capable of providing a large voltage swing for the bias in both positive and negative polarities to each individual pixel, independently. These enhanced functionalities are achieved by modifying a capacitive transimpedance amplifier (CTIA) CMOS ROIC architecture. An FPGA-based test bench has also been developed to test and characterize the new ROIC system, for which software and hardware are described in detail. The test chip has been fabricated with 2P4M 0.35 μm high-voltage CMOS technology, where the bias voltage range is ±5 V and the output swing range is ±3.9 V. The demonstrated ROIC is an ideal infrastructure for implementation of region of interest enhancement and a solid base for infrared multispectral acquisition targeting an infrared retina.
A comparative study of the interaction of 5, 10, 15, 20-tetrakis (N- methylpyridinium-4-yl)porphyrin and its zinc complex with DNA using fluorescence spectroscopy and topoisomerisation

Binding of 5,10,15,20-tetrakis (N-methylpyridinium-4-yl)porphyrin (H2TMPyP4+) and its zinc complex (ZnTMPyP4+) to DNA is demonstrated by their coelectrophoresis and by absorption and fluorescence spectroscopic methods. Topoisomerisation of pBR322 DNA shows that H2TMPyP4+ unwinds DNA as efficiently as ethidium bromide showing that it intercalates at many sites. ZnTMPyP4+ may cause limited unwinding. Marked changes in the fluorescence spectra of the porphyrins are found in the presence of DNA. The fluorescence intensity of either H2TMPyP4+ or ZnTMPyP4+ is enhanced in the presence of poly (d(A-T)), whereas in the presence of poly (d(G-C] the fluorescence intensity of ZnTMPyP4+ is only slightly affected and that of H2TMPyP4+ markedly reduced. Both the porphyrins photosensitize the cleavage of DNA in aerated solution upon visible light irradiation.
Modeling and Analysis for Cache-Enabled Networks With Dynamic Traffic

Instead of assuming fully loaded cells in the analysis on cache-enabled networks with tools of stochastic geometry, we focus on the dynamic traffic in this letter. With modeling traffic dynamics of request arrivals and departures, probabilities of full-, free-, and modest-load cells in the large-scale cache-enabled network are elaborated based on the traffic queue state. Moreover, we propose to exploit the packets cached at cache-enabled users as side information to cancel the incoming interference. Then, the packet loss rates for both the cache-enabled and cache-untenable users are investigated. The simulation results verify our analysis.
Molecular Dynamics Studies of Nanofluidic Devices

Nanotechnology and fluid mechanics are two scientific areas where recent progress has disclosed a variety of new posibilities. The advances in both fields stablished the grounds for interdisciplinary approaches and recent findings promise novel applications that are leading to a technological revolution. Novel nanofabrication techniques have opened up possibilities for the development of small-scale integrated devices, such as lab-on-a-chip for biochemical synthesis and analysis, the integration is achieved by miniaturization of the functional elements e.g., of the channels transporting the fluid and of the sensors performing the analysis, and as the size of these devices reaches the sub-micron range we enter the field of nanofluidics. Nanofluidics is defined as the study of flows in and around nanosized objects. Modeling of transport in nanofluidic systems differs from microfluidic systems because changes in transport caused by the walls become more dominant and the fluid consists of fewer molecules. Carbon nanotubes are tubular graphite molecules which can be imagined to function as nanoscale pipes or conduits. Another important material for nanofluidics applications is silica. Nowadays, silica nanochannels are produced in nanometer scale using different nanofabrication techniques. Silica nanochannels are being implemented in several nanotechnology applications such as nanosensor devices, nano separators, nanofilters and a plethora of devices for nanobiological and biochemical applications. Experiments at the nanoscale are expensive and time consuming moreover the time scale associated to several nanoscale phenomena requires a very high time resolution of the devices performing nanoscale measurements. Computational nanofluidics is the enabling technology for fundamental studies, development, and design of such devices. Computational nanofluidics complements experimental studies by providing detailed spatial and temporal information of the nanosystem. In this thesis, we conduct molecular dynamics simulations to study basic nanoscale devices. We focus our studies