Miracle-dz/UniFAR-FTUs huggingface dataset:
Production of Hydrogen from Aqueous Phase Reforming of Glycerol: Economic Evaluation

Glycerol is the main byproduct from the production of biodiesel by transesterification of vegetable oils, and approximately 10% of total biodiesel production volume corresponds to glycerol. The profitability of various chemical processes depends, in part, on the sale of byproducts, which enables a reduction in the production costs and consequently, in the product’s final price. Thus, it is necessary to look for alternatives to solve the problem of glycerol buildup, in order to avoid future environmental impacts and make biodiesel competitive in the growing market of biofuels. In this context, this study’s objective is the development of a low cost and environmental clean technology that allows the conversion of glycerin into a greater value product. In this paper, an economic evaluation of production hydrogen using Aqueous Phase Reforming (APR) was conducted. Firstly, we detailed the technical assumptions in the study. Reactions were performed in batch reformer of 10 liters of capacity, at the temperature of 250℃ and pressure of 38 atm. Finally, a sensitivity analysis was performed. The results from economic evaluation show that APR of glycerol, using nickel catalysts supported on alumina or zirconium oxide, is a promising and competitive technology for hydrogen production.
Progenitor delay-time distribution of short gamma-ray bursts: Constraints from observations

Context. The progenitors of short gamma-ray bursts (SGRBs) have not yet been well identified. The most popular model is the merger of compact object binaries (NS-NS/NS-BH). However, other progenitor models cannot be ruled out. The delay-time distribution of SGRB progenitors, which is an important property to constrain progenitor models, is still poorly understood. Aims. We aim to better constrain the luminosity function of SGRBs and the delay-time distribution of their progenitors with newly discovered SGRBs. Methods. We present a low-contamination sample of 16 Swift SGRBs that is better defined by a duration shorter than 0.8 s. By using this robust sample and by combining a self-consistent star formation model with various models for the distribution of time delays, the redshift distribution of SGRBs is calculated and then compared to the observational data. Results. We find that the power-law delay distribution model is disfavored and that only the lognormal delay distribution model with the typical delay τ 3Gyr is consistent with the data. Comparing Swift SGRBs with T90 > 0.8s to our robust sample (T90 < 0.8s), we find a significant difference in the time delays between these two samples. Conclusions. Our results show that the progenitors of SGRBs are dominated by relatively long-lived systems (τ 3Gyr), which contrasts the results found for Type Ia supernovae. We therefore conclude that primordial NS-NS systems are not favored as the dominant SGRB progenitors. Alternatively, dynamically formed NS-NS/BH and primordial NS-BH systems with average delays longer than 5Gyr may contribute a significant fraction to the overall SGRB progenitors.
Existence of Renormalized Solutions for p(x)-Parabolic Equation with three unbounded nonlinearities

In this article, we study the existence of renormalized solution for the nonlinear $p(x)$-parabolic problem of the form:\\ $\begin{cases} \frac{\partial b(x,u)}{\partial t} - div (a(x,t,u,\nabla u)) + H(x,t,u,\nabla u) = f - divF $ \; in $Q= \Omega\times(0,T)\\$ $b(x,u)\mid_{t=0} = b(x,u_{0})$ \; in $\Omega\\$ $ u = 0 $ \quad on $\partial\Omega\times(0,T)\\$ $\end{cases}$ with $ f $ $ \in L^{1} (Q),$\; $b(x,u_{0}) \in L^{1} (\Omega)$ and $ F \in (L^{P'(.)}(Q))^{N}. $\\ The main contribution of our work is to prove the existence of renormalized solution of the variable exponent Soblev spaces, and we suppose that\;$ H(x,t,u,\nabla u)$\; is the non linear term satisfying some growth condition but no sig
Impacts of Unionization on Employment, Product Quality and Productivity: Regression Discontinuity Evidence from Nursing Homes

This paper studies the effects of nursing home unionization on numerous labor, establishment, and consumer outcomes using a regression discontinuity design. We find negative effects of unionization on staffing levels and no decline in care quality, suggesting positive labor productivity effects. Some evidence suggests that nursing homes in less competitive local product markets and those with lower union density at the time of election experienced stronger union employment effects. Unionization appears to raise wages for a given worker while also shifting the composition of the workforce away from higher-earning workers. By combining credible identification of union effects, a comprehensive set of outcomes over time with measures of market-level characteristics, this study generates some of the best evidence available on many controversial questions in the economics of unions. Furthermore, it generates evidence from the service sector, which has grown in importance and where evidence has been thin.
APPLICATION OF BIOTECHNOLOGICAL TOOLS FOR EVALUATION OF GENETIC DIVERSITY, IN VITRO PROPAGATION AND GENETIC TRANSFORMATION IN PARKIA TIMORIANA (DC.) MERR. : A REVIEW

Parkia timoriana (DC.) Merr. , commonly known as tree bean, is a multipurpose leguminous tree commonly found throughout the northeastern Indian region. Its pods are consumed as vegetables and fetch high market price during the season. However in recent years the tree is reported to be associated with various pests and infestations accompanied with die-back symptoms leading to mass death in many locations. Thus there is an urgent need to address the issues for the multiplication and conservation of this tree. The rapid multiplication and improvement through conventional means are difficult and limited. The use of biotechnological tools for the evaluation of the genetic status, mass production and genetic improvement provides a viable option. Advances in the studies of genetic diversity, in vitro regeneration and genetic transformation in tree beans are discussed in this paper.
Using Continuous Wavelet Transform and Short Time Fourier Transform as Spectral Decomposition Methods to Detect of Stratigraphic Channel in One of the Iranian South-West Oil Fields

Classical seismic methods for characterization of hydrocarbon reservoirs have been used for decades. Stratigraphic events affect seismic sections in addition to structural events. Today the necessity of usage of seismic sections to determine reservoir extension and stratigraphic characteristics is increasing. Conventional seismic sections cannot display most of the important events in reservoir studies. The study of frequency content of seismic sections can provide better understanding to geoscientists, as well as interpreters in the field of petroleum engineering studies. An isofrequency process is a powerful tool in terms of reservoir imaging. One of the methods that provides isofrequency slice is Spectral Decomposition (SD). SD is a comprehensive method that eliminates most of limitations encountered in seismic data to reveal geological information. SD provides continuous analysis of amplitude, frequency, phase, and energy spectrum. Therefore, SD is applied to obtain an amplitude spectrum of frequency content of seismic trace which is attributed to the temporal center of the sample trace, so higher frequency resolution is obtained at lower frequencies and higher time resolution at higher frequencies. In this paper, Short Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) as SD methods were used in order to detect stratigraphic channel at one of the Iranian South-West oil fields for which it has the potential to be considered as a reservoir.
Surface Fuel Sampling Strategies: Linking Fuel Measurements and Fire Effects

Abstract We assessed the effectiveness of different sampling strategies in linking fine fuel load and crown scorch of ashe (Juniperus ashei) and redberry juniper (J. pinchotii) for prescribed fires conducted in wet and dry periods of the growing season on the Edwards Plateau, Texas, USA. Our aim was to determine if spatial and temporal variation in crown scorch was best predicted by estimates of fuel load sampled with spatially explicit, multiscale sampling strategies or with traditional, simple random sampling of fuel load. We found that multiscale sampling of fuel load underneath and adjacent to juniper crowns was more effective than simple random sampling in predicting crown scorch for the 14 fires conducted in the wet period and the five conducted in the dry period. The type of sampling strategy employed was critical in relating fuel load to crown scorch during the wet period. Percent crown volume scorched ranged from 0% to 100% in these conditions. In contrast, the type of sampling strategy was less important in the dry period when crown scorch was >90% for all juniper trees. We use these findings to illustrate how a multiscale sampling design can increase prediction power, thereby improving our ability to provide resource professionals with critical values to target in management. Using such a strategy in this study revealed that fine fuel loading of 2 670 kg · ha–1 were needed to scorch juniper trees 100% for the conditions present in the wet period, whereas only 1 280 kg · ha–1 were needed in the dry period. To provide managers with this type of information, we suggest that researchers shift from simple, random sampling of fuels to alternate sampling designs where randomization is maintained in the designation of treatments or selection of observations (i.e., individual juniper trees) but where fuel is systematically sampled at the location of the observation of interest.
Supporting Real-Time Visual Analytics in Neuroscience*

EXTENDED ABSTRACT Neuroscience, as other experimental sciences, supports, refutes or validates hypotheses by conducting experiments on living organisms. For instance, by connecting electrical sensors to a cat’s spinal cord, and monitoring its neurons activities, neuroscientists can determine whether capsaicin (chili pepper active component) has the same effect as anesthesia in the presence of pain [1]. In a typical neuroscience experiment, a neuroscientist is responsible of: (i) preparing the subject; (ii) connecting and calibrating sensors; (iii) collecting and storing the experiment data (e.g. file, database); (iv) applying algorithms and statistics for discovering meaningful patterns. Because of the volume of the resulting data, and the complexity of the algorithms used for finding patterns, the data analysis is usually done postmortem. Yet, given the complexity of setting an experiment (e.g., special and expensive equipment, juridical protocols concerning experiments using animals, gathering together field experts), its duration (e.g., 8 hours), and the fact that each experiment is unique (e.g., every subject has its own characteristics), neuroscientists require novel tools for processing and exploring data in real-time so that they can better control the progress of an experiment. Although there has been a lot of progress in the domain of automatic knowledge discovery (e.g., deep learning), we believe humans play a central role in the data analysis task. Therefore, we propose to build a visual stream processing system for supporting the analysis and exploration of data streams in real-time, by exploiting human’s natural ability for discovering patterns. Our work combines stream processing and data storage techniques [2, 3], with data visualization theory. We study strategies for visualizing different types of data considering constraints related to real time and data volume. This paper presents our stream processing and visualization system adapted to the requirements of the neuroscience domain.
Optical Measurement of Amplitude of Vibration of Machine

In the paper the application of 2D and 3D vision techniques for amplitude vibration measurements of vibratory machine working under operating conditions was presented. For this purpose method and algorithms were developed of image analysis and discrete epipolar geometry with the usage of one camera. They were implemented in programming environment { MATLAB and tested on experimental set{up.
Plant-soil biota interactions and spatial distribution of black cherry in its native and invasive ranges

One explanation for the higher abundance of invasive species in their non-native than native ranges is the escape from natural enemies. But there are few experimental studies comparing the parallel impact of enemies (or competitors and mutualists) on a plant species in its native and invaded ranges, and release from soil pathogens has been rarely investigated. Here we present evidence showing that the invasion of black cherry (Prunus serotina) into north-western Europe is facilitated by the soil community. In the native range in the USA, the soil community that develops near black cherry inhibits the establishment of neighbouring conspecifics and reduces seedling performance in the greenhouse. In contrast, in the non-native range, black cherry readily establishes in close proximity to conspecifics, and the soil community enhances the growth of its seedlings. Understanding the effects of soil organisms on plant abundance will improve our ability to predict and counteract plant invasions.
Financial Product Preferences of Japanese Households for Long-term Investments: Internet Choice Experiments *

We investigate financial product preferences of Japanese households by using choice experiments. We examine the preference for the risk and return relationship as well as other influencing factors for investment decisions, such as the existence of principal guarantee and countries invested in. We also consider personal characteristics, such as age, gender, and stock investment experience. Japanese households have approximately 19 trillion USD financial assets which make up of approximately 20% of all assets in developed countries. However, they have the fewest equity related products. Investigating Japanese household financial product preference is important because their decisions potentially have a large impact on global equity markets. We find three main results. First, the relationship between risk and expected return is clearly an important factor for choosing financial products. Households also have a strong preference for the existence of principal guarantee and for domestic investments. Second, households exhibit different preferences according to whether they have stock investment experience or not. Third, compared to working households, retired households require a larger increase of the expected return for a given increase of risk, and have a stronger preference for principal guarantee, domestic investments, and shorter investment time horizon of products. If financial institutions can offer the financial products which satisfy those preferences, the investment behavior of Japanese households may change considerably.
Application of dynamic value-attribute modeling in a product family

Product families are used as a solution to cater the needs of diversified user groups, while minimizing the usage of resources. However, today's design decision makers require additional capabilities to manage the uncertainties brought by highly dynamic nature of the technological markets. Therefore, understanding the time varying behavior of preferences, in addition to the preference differences across market segments, has become an essential tool to survive the intense competition. This paper provides a new approach to add time varying behavior of preferences to extend the currently two dimensional market segmentation grids. The newly added time dimension provides more information to the design decision makers, while minimizing uncertainties due to the dynamic market behavior. A precursor case study, using the US light truck market data from 2004-2010 was conducted to assess the dynamic nature of the preferences in the market niches. The case study results provide strong evidences of presence of the time variance preference in market niches. A dynamic preference modeling case study, with an extended set of market segment observations, is proposed as the immediate future work.
Force Measurement Methods in Telerobotic Surgery: Implications for End-Effector Manufacture

Haptic feedback in telesurgical applications refers to the relaying of position and force information from a remote surgical site to the surgeon in real-time during a surgical procedure. This feedback, coupled with visual information via microscopic cameras, has the potential to provide the surgeon with additional ‘feel’ for the manipulations being performed at the instrument-biological tissue interface. This increased sensitivity has many associated benefits which include, but are not limited to; minimal tissue damage, reduced recuperation periods, and less patient trauma. The inclusion of haptic feedback leads to reduction in surgeon fatigue which contributes to enhanced performance during operation. Commercially available Minimally Invasive Robotic Surgical (MIRS) systems are being widely used, the best-known examples being from the daVinci by Intuitive Surgical Inc. However, currently these systems do not possess force feedback capability which therefore restricts their use during many delicate and complex procedures. The ideal system would consist of a multi-degree-of-freedom framework which includes end-effector instruments with embedded force sensing included. A force sensing characterisation platform has been developed by this group which facilitates the evaluation of force sensing technologies. Surgical scissors have been chosen as the instrument and biological tissue phantom specimens have been used during testing. This test-bed provides accurate, repeatable measurements of the forces produced at the interface between the tissue and the scissor blades during cutting using conventional sensing technologies. The primary focus of this paper is to provide a review of the traditional and developing force sensing technologies with a view to establishing the most appropriate solution for this application. The impact that an appropriate sensing technology has on the manufacturability of the instrument end-effector is considered. Particular attention is given to the issues of embedding the force sensing transducer into the instrument tip.
BIOFILM FORMATION OF METHICILLIN AND VANCOMYCIN RESISTANT STAPHYLOCOCCUS SPECIES ISOLATED FROM CELLULAR PHONES

Objective: The goal of the study was to explore the occurrence of methicillin and vancomycin-resistant Staphylococcus species from cellular phones and preventive measures to avoid contamination. Methods: The issues addressed in this investigation are i) Isolation of bacteria from 70 cellular phones through swab culture method ii) Characterization of the isolates by standard biochemical test iii) Antibiogram pattern study of the isolates iv) Molecular identification of the selected isolate through 16s rDNA sequencing v) Virulence study through biofilm assay vi) Susceptibility of the isolates against commonly used disinfectants and essential oils through disc diffusion. Results: All 70 different cellular phone used in this study harbored 120 isolates of bacteria. Of which, we recorded high incidence of Gram-positive cocci (51.6%) and 22 isolates were identified as Staphylococcus species. Three isolates (52N6, 53N9 and 53N6) were resistant to both methicillin and vancomycin, in addition, showed resistance against several other antibiotics. The strain 53N6 that exhibited multidrug resistance was further identified as Staphylococcus sp. strain CPC53N6 through 16s rDNA sequencing with NCBI accession no. KX858346. Virulence activity of the isolate was observed by its biofilm forming capacity as revealed from SEM imaging and the biofilms were composed of aggregated cocci and fibriform extracellular matrix. All the Staphylococcus isolates, including CPC53N6, were sensitive to disinfectants like dettol and cinnamon ( Cinnamon zeylanicum ) oil indicating their use as preventive measures. Conclusion: Thus, the methicillin and vancomycin-resistant Staphylococcus species of cellular phones can be decontaminated through cinnamon oil to minimize further transmission.
A Fourier Approach to the Computation of CV@R and Optimized Certainty Equivalents

We consider the class of risk measures associated with optimized certainty equivalents. This class includes several popular examples, such as CV@R and monotone mean-variance. Numerical schemes are developed for the computation of these risk measures using Fourier transform methods. This leads, in particular, to a very competitive method for the calculation of CV@R which is comparable in computational time to the calculation of V@R. We also develop methods for the efficient computation of risk contributions.
KNOWLEDGE AND ECONOMIC GROWTH : THE EVIDENCE ACROSS THE ITALIAN REGIONS 1900-19591

The analysis of the evolution of the academic chairs of an academic system is a promising area of investigation. The exploration of the evolution of the size and the disciplinary composition of the stock of academic chairs in Italy in the years 1900-1959 provides an opportunity to understand the contribution of scientific knowledge to economic growth. The basic assumption is that knowledge is not a homogeneous activity, but rather a bundle of highly differentiated disciplines that have different characteristics both in terms of generation and exploitation that bear a differentiated impact on economic growth. Advances in scientific knowledge are likely to have a direct, positive effect on economic growth according to their fungibility, appropriability and complementarity with other sources of technological knowledge and hence exploitation conditions. Advances in scientific knowledge that can be converted into technological knowledge with high levels of fungibility, appropriability and complementarity have a higher chance to affect economic growth. The econometric analysis confirms that advances in engineering and chemistry, as proxied by the number of chairs, had much a stronger effect on economic growth than in other scientific fields. These results have important implications for research policy as they highlight the differences in the economic effects of academic disciplines.