Miracle-dz/UniFAR-FTUs huggingface dataset:
How Does a Banks' Risk Profile Influence the Effect of Credit Risk? Evidence from Bank Stock Market Returns

As delegated monitors, banks may incur substantial losses when the credit quality of their borrowers deteriorates. The credit risk shocks leading to bank distress may be caused by both domestic and foreign adverse economic events, especially in view of the increased international lending exposure of many banks headquartered in developed countries. Using a multi-factor model, we analyze the sensitivity of the stock returns of a large sample of banks in 20 industrialized countries to shifts in both regional and world credit risk, measured by corporate bond spreads. We examine whether or not functional diversification and capital provide banks with a structural protection against credit risk changes. According to the theory, the preliminary results indicate that there is a negative, however non-significant, correlation between bank returns and credit spreads in the case of US.
Running Large Sparse Problems on Shared Memory Computers

It is hard to achieve high efficiency when large sparse problems are solved on parallel computers. There are three major reasons for this:• one must use indirect addressing in all sparse matrix techniques,• the data involved in computations are irregularly distributed, which means that there arise cache problems,and• it is difficult to find parallel tasks, and when such tasks are found they are normally small (this means that the time for starting the parallel execution is rather considerable compared with the actual time for performing the parallel computations). The computations can be organized as successive factorizations of dense rectangular blocks. Subroutines for performing QR factorization from the well-known LAPACK Library can be applied during the factorization of any dense block. The three disadvantages that are listed above are completely removed during this part of the computations.Two additional tasks are to be carried out: (i) to prepare the dense blocks and to put the involved data in a buffer, where the dense computations are to be carried out and (ii) to restore the data in the sparse matrix arrays when the dense matrix computations for the current dense block are finished. It will be shown that the dense matrix computations are dominating. The extra benefit of using dense blocks is a consequence of the fact that the computations within the dense blocks can easily be carried out in parallel. Numerical results, which illustrate this, will be given. The computations have been performed on SUN shared memory computers.The algorithm based on using dense blocks is derived from an algorithm, which has been developed for vector processors. Some changes were needed to make this algorithm efficient for computers with shared memory. These changes will be explained.
Grogra and Genesis: Grown Neurons Used for Realistic Compartmental Modeling

We report on the novel use of the existing growth grammar interpreter GROGRA for neuroanatomical simulations of pyramidal cells, interneurons and purkinje cells. Growth parameters for these cell types result from analyzing web-based cell reconstructions by means of a custom made Matlab-program and corroborate existing literature data. Synthetic cells are displayed and studied in a VRML-browser. GENESIS simulations of several sets of synthetic morphologies are then used to shed light on the question, how much influence morphology needs to have in a truly realistic network simulation.
Illiquidity and Corporate Bond Spreads after the Fed Tightening

We find that the Fed tightening period has the strongest effect on the illiquidity spreads for corporate bonds compared with other recent periods of crisis. We use transactions data to calculate illiquidity measures of corporate bond issues from 2007 to 2017. There are peaks of illiquidity during the financial crisis in 2008, around the regulatory changes and the European debt crisis in 2010, and after the Fed tightening in 2015. The impact for the Fed tightening period is higher even comparing with the period of the financial crisis. A one standard deviation increase of the illiquidity measure increases yield spreads by 12% during the 2008 crisis and 11% in the post-crisis period after 2010. The same increase in the bond illiquidity measure increases yield spreads by 18% during the monetary tightening period. We discuss reasons for the impact of the Fed tightening and further analyze factors that correlate with individual and aggregate measures of illiquidity.
Revealing Corruption: Firm and Worker Level Evidence from Brazil

We study how the disclosure of corrupt practices affects firms. We construct novel firm-level measures of involvement in corrupt practices using randomized audits of public procurement in Brazil. On average, firms exposed by the anti- corruption program grow larger after the audits, despite experiencing a decrease in procurement contracts. Using investment-, loan-, and worker- level data, we show that exposed firms adapt to the loss of government contracts by changing their investment strategy. They increase capital investment and borrow more to finance such investment, while we see no change in their internal organization. We provide qualitative support to our results by conducting new face-to-face surveys with business owners of government-dependent firms.
Theories and Practices

This chapter develops a conceptual framework based on different dynamics in consumer attitudes. Empirical analysis seeks to illustrate this framework with emerging and mature market data for the same brands over the same time period. The results generate important implications, especially for brand management in emerging markets. First, the emotional brand connection, judged so important in mature markets, is substantially less important than securing the brand’s spot in the consumers’ consideration set. Second, emerging market consumers are more willing to seek out distribution channels for their brands, reducing the “compromised choice” due to less-than-perfect distribution coverage. Third, price is a double-edged sword in emerging markets: a high price benefits sales through consideration but hurts sales through liking. The net impact of these influences shapes the long-run sales effects of marketing. In particular, long-run advertising and price elasticity is higher, while long-run distribution elasticity is lower in emerging markets compared to mature markets.
Distribution of Nitrate, Phosphate and N/P Ratio in Maninjau Lake, West Sumatra, Indonesia

This research aim to study of spatial distribution of Nitrate and Phosphate concentration, and also N/P ratio in waters of Maninjau Lake (0°19’ S; 100°12’E)), West Sumatera Province, Indonesia, collected from 11 sampling points of water samples which were performed during 3 (three periods) May, June and July 2017. Other major sources of environmental nitrogen and phosphate are fertilizers and wastewater discharged from farms and livestock facilities, and sewage from residential areas which leak into lakes. The Nitrate and phosphate concentrations in Maninjau Lake waters, the results of the analysis found that Nitrate values ranged from 0.02-0.40 mg/L mg/L (quality standard 10 mg/L), while phosphate ranged from 0.12-0.54 mg/L mg/L (quality standard 0.2 mg / L). Nitrogen (N) and phosphorus (P) generally limit the main productivity in lakes. The N/P Ratio calculation results are known that 0.29-0.58, the value shows that there has been an excessive addition of phosphate elements into the waters, so that it appears that the N element is a limiting element that affects the biological conditions of ecosystems such as phytoplankton biomass, species composition which is likely to occur dominance of certain types. This situation is quite reasonable, considering that around the study site is a residential area that discharges household wastewater that uses detergents into the waters. Anthropogenic nitrogen and phosphorus supply to natural ecosystems has increased them in many lakes.
International Journal of Food Engineering Simulation of the Transport Phenomena during Food Drying with Ohmic Heating in a Static System

In this article, the computational fluid dynamics (CFD) technique was used to simulate mass and heat transfer during the food drying via ohmic heating process. The effects of electrical field intensity, electrical conductivity, solid heating, liquid-solid conductivity and some parameters such as drying rate, moisture content and temperature changes on drying process of potato were investigated. The partial differential equations for the unsteady-state system were solved by the finite element method. In this modeling, simultaneous solution of the equations of heat transfer, moisture and electrical field was achieved. The results showed that ohmic heating process reduced drying time and accelerate the diffusion in the entire product in comparison with the other conventional methods. Therefore, heat and mass transfer were simultaneously and approximately conducted with the same rate in both phases of solid and liquid.
An Identity Authentication Method Based on Multi-modal Feature Fusion

At present, many judicial organs have adopted the daily attendance system based on face recognition to strengthen the supervision of community correction personnels. In order to prevent a few personnels from using pre-prepared photos and videos to deceive the face recognition system, this paper proposes an identity verification scheme with liveness detection based on dynamic combination of multimodal features. The main idea is as follows. Firstly, during face verification, the user is required to read out random numbers on the screen. Secondly, generating dynamic combination of speech, voiceprint, lip-reading and other verification methods according to the user’s risk personas, so as to achieve a balance between convenience and security. In addition, in view of the low accuracy of lip-reading recognition in practice, this paper changes the traditional lip-reading recognition based on morpheme to lip-reading recognition based on classifier. By optimizing the interactive content, the distinction of pronunciation between different Chinese characters is increased, and the accuracy of lip-reading recognition is significantly improved.
Evaluation and Determination of Total Antioxidant in Anting-Anting (Acalypha indica L.) Leaf Extract

Acalypha indica L. is one of herbal plants found in wet, moderate, tropical areas which grows as a weed. This herb has been used traditionally to treat dysentery, diarrhea, malnutrition, and malaria. But chemical compounds in Acalypha indica L. hasn’t been completely reported yet. This study aims to evaluate chemical compounds and total antioxidant of Acalypha indica L. extract. The extraction of Acalypha indica L. was carried out by maceration method using methanol and ethanol as solvent. The rendemen, water and ash content of Acalypha indica L. extract determined by gravimetric methods. The DPPH method was used to determine total antioxidant and the X-Ray Fluorescence method was used to analyze of the elements contained in the extract. The yield of methanol extract was 14.83%, this was greater than the ethanol extract of Acalypha indica L. which was 5.94%. The water and ash content of the methanol extract were obtained 10.57% and 17.44% respectively, while the ethanol extract was 35.66% and 17.93%. Phytochemical screening of Acalypha indica L. in methanol and ethanol extracts showed that the extracts contained phenolic, flavonoids, steroids, terpenoids and alkaloids compounds. The total antioxidant was obtained 1.59 mg/gDW and 3.11 mg/gDW in methanol and ethanol extract. XRF analysis results showed that methanol and ethanol extract contained elements Mg, Si, Cl, K, Mn and Fe. Based on the result, it can be concluded that Acalypha indica L. extract contained some compounds and elements which is beneficial for health.
Analysis and Application of Dynamic Programming

Dynamic programming is a part that is not well understood in the introductory learning of algorithms, but it is also a part worth learning. It has been successfully applied in many fields, such as gene sequencing, human flow control, and hydropower resource allocation. This article systematically explains the principle of dynamic programming. At the same time, through the comparison with other algorithms, we can deeply understand the nature of dynamic programming and its advantages and disadvantages in solving problems compared with other algorithms. Finally, it analyzes the problem-solving methods and steps of dynamic programming based on relevant application examples.
Channel Estimation Based on Compressive Sensing for Multi-User Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) is becoming a key technology for future wireless communications. Channel feedback for massive MIMO is a challenging task due to the increased dimension of MIMO channel matrix. By exploiting the channel sparsity, channel estimation based on compressive sensing (CS) aims to reduce the feedback overhead in massive MIMO systems. In this paper, various CS algorithms for channel estimation in massive MIMO systems are summarized, and a novel CS algorithm, i.e. modified sparsity adaptive matching pursuit (MSAMP), is proposed hereupon. Moreover, various measurement matrices are introduced in the CS scheme. The performances of channel estimation and recovery are simulated and compared. It is inferred from simulation that, SAMP is very appropriate for reconstructing sparse channel information in massive MIMO system, especially the modified SAMP can give higher reconstruction, and some measurement matrix is suitable for certain optimal CS algorithms.
Increasing the economic efficiency of design and construction solutions due to the automated identification of construction works and structural elements of information models

Currently in many countries around the world there is an active introduction of information modeling technologies in the construction industry. This process is largely aimed at optimizing approaches to the formation of design estimates for capital construction objects. However the established views on the development of project documentation do not always fit into the concept of new approaches. In an attempt to fit traditional processes of identification of construction works and structural elements into information modeling technologies modern engineers are faced with the problems of optimizing and automating established processes. Modern software for the identification of construction work and structural elements although is developed taking into account the interaction with information models, does not change the previously established design approaches. This article explores a methodology that can significantly increase the economic efficiency of design and construction solutions by automating the identification of construction work and structural elements using information modeling technologies.
Analysis of jet suppressing root leakage in plane cascade

The three-dimensional numerical simulation of the sealing structure of compressor cascade with jet structure is carried out to study the flow structure of the tooth cavity under the influence of jet. Based on this, the influence of jet on the flow performance in the tooth cavity was analyzed from four aspects of vorticity distribution, turbulent kinetic energy distribution, Mach number distribution and static pressure distribution. The results show that the interaction of the jet flow and the leakage flow makes the internal flow structure of the tooth cavity complicated and changeable. The two fluids are connected and mixed with each other and keep separating and converging, which makes the flow loss increase sharply and the leakage coefficient is greatly reduced. The jet flow drastically changes vorticity distribution and static pressure distribution in the tooth cavity. In the jet-affected section, the jet-affected range is approximately 2 times the circumferential width of the jet port.
Silencing of Nicotiana benthamiana phytoendesaturase using dsRNA synthesized in vivo

RNA interference (RNAi) using exogenous double-stranded RNA (dsRNA) has been used to silence the model gene of Nicotiana benthamiana phytoendesaturase. Here we report on an efficient technique for dsRNA synthesis using E. coli HT115 strain. This strain is deficient in RNase III, an enzyme that normally destroys most dsRNA in a bacterial cell and has been engineered to produce big quantities of dsRNA. We also used root treatment for dsRNA delivery to N. benthamiana plants. We found this method to be one of the most efficient ways to deliver dsRNA for plants.
Principles of Nuclear Magnetic Resonance Microscopy

now a well-established method of whole-body scanning in medicine. On the other hand. NMRI can also be applied at small scale and then at relatively high spatial resolution to small animals, natural products, porous solids, minerals, polymers and others. It is this latter branch of NMRI which has been coined as NMR microscopy by the author. The essential point in these experiments is the acquisition of the NMR signal under the influence of a magnetic field gradient so that via Larmor's equation the resonance frequency is directly related to the space coordinate along the field gradient. The author denotes this procedure as "k-space" acquisition. A dynamic analogue is the pulsed field gradient (PFG) NMR spectroscopy in which the self-correlation function of the spinbearing particles can be obtained and which has been termed "q-space" imaging by the author. This type ofexperiment can be used to study the spectrum of translational motion of the particles as well as the morphology in porous systems. The fascinating concept of the present book is to group together these two apparently very different applications of magnetic field gradients, showing the common physical principles which determine the imaging of static density distributions via "k-space" and dynamic displacements via "qsqace" acquisition. Chapters 1 and 2 of the book provide basic principles both of imaging and of nuclear magnetic resonance spectroscopy. In chapter 3 the influence of magnetic field gradients is described on the evolution of the nuclear magnetization, and it is shown in what
Solar Energetic Electron Events Associated with Hard X-Ray Flares

We investigate 16 solar energetic electron (SEE) events measured by WIND/3DP with a double-power-law spectrum and the associated western hard X-ray (HXR) flares measured by RHESSI with good count statistics, from 2002 February to 2016 December. In all the 16 cases, the presence of an SEE power-law spectrum extending down to ≤5 keV at 1 au implies that the SEE source would be high in the corona, at a heliocentric distance of ≥1.3 solar radii, while the footpoint or footpoint-like emissions shown in HXR images suggest that the observed HXRs are likely produced mainly by HXR-producing electrons via thick-target bremsstrahlung processes very low in the corona. We find that for all the 16 cases, the estimated power-law spectral index of HXR-producing electrons is no less than the observed high-energy spectral index of SEEs, and it shows a positive correlation with the high-energy spectral index of SEEs. In addition, the estimated number of SEEs is only ∼10−4–10−2 of the estimated number of HXR-producing electrons at energies above 30 keV, but with a positive correlation between the two numbers. These results suggest that in these cases, SEEs are likely formed by upward-traveling electrons from an acceleration source high in the corona, while their downward-traveling counterparts may undergo a secondary acceleration before producing HXRs via thick-target bremsstrahlung processes. In addition, the associated 3He/4He ratio is positively correlated with the observed high-energy spectral index of SEEs, indicating a possible relation of the 3He ion acceleration with high-energy SEEs.
Investigating students’ concept image in understanding variables

Concept image is the overall structure associated with a concept, including all mental images and their related properties and processes. The concept image develops continuously through experience and changes as the individual faces stimulation and maturity. This study aims to analyze and describe the concept image of students in understanding the variable concept. This study is qualitative research with a phenomenological method. Data were collected by means of interviews and tests, then analyzed using the content analysis method. Participants involved in this study were ten eighth-grade students, while the object in this study was students’ concept image in understanding the variable concept. The findings revealed that most of the students understood a variable as something whose value is unknown, whilst some other students comprehend a variable as a substitute for something whose value is unknown. Understanding students’ thinking or concept image provides educators with an insight of the learning process aligned with students’ needs as a way to increase their understanding of mathematical concepts.
Effects of resource-based learning strategy on the performance in biology of Grade 8 learners

This study aims to find out the effectiveness of Resource-Based Learning Strategy on the performance in Biology. Specifically, to find out the significant difference on the pretest and posttest scores in Biology of the learners. Experimental research design, the pretest posttest control group design was used. The study was conducted at Manticao National High School, Grade 8 learners section Faith and Generous. There were thirty-five randomly selected learners taught using Resource-Based Learning and thirty-five learners exposed to Lecture Method respectively. T-test revealed showed that there was no significant difference on the learners’ pretest scores of the two groups, since the p-value is 0.1474 which it is greater than 0.05. Moreover, there was a significant difference on the learners’ posttest scores in Biology when taught using Resource-Based Learning and Lecture Method as shown with the p-value of 0.0228 which is lesser than 0.05 level of significant. Paired T-test showed that there was a significant difference on the learners’ pretest and posttest scores in Biology when taught using Resource-Based Learning and Lecture Method. Resource-Based Learning strategy on enhancing learners’ performance in experimental group, as shown in the p-value of 5.18X1007 and Lecture Method has a p-value of 0.0005 and both p-value is less than 0.05 level of significance. This study concluded that Resource-Based Learning strategy can improve the learners ’ performance in Biology by the use of more resources that helps them dis cover further definitions, concepts and ideas and making their learnings more meaningful by sharing their ideas on what they have researched to the class and would help the learners developed their communication skills and to have a lifelong learning.