Miracle-dz/UniFAR-FTUs huggingface dataset:
Anti‐inflammatory activities of cAMP‐elevating agents: enhancement of IL‐10 synthesis and concurrent suppression of TNF production

Interleukin‐10 (IL‐10) and tumor necrosis factor (TNF) exert key roles in some acute and chronic inflammatory diseases. In this study we investigated (1) the potency of different cAMP‐elevating agents in enhancing IL‐10 synthesis, (2) the involvement of protein kinase A in this enhancement, and (3) the mutual dependence of cAMP‐enhanced IL‐10 formation and cAMP‐suppressed TNF synthesis. Rolipram, a specific phosphodiesterase inhibitor and cicaprost, a prostacyclin analogue, were applied as cAMP‐elevating agents. The stable cAMP antagonist (Rp)‐cAMPS was used to abrogate activation of protein kinase A. Human peripheral blood mononuclear cells were stimulated with lipopolysaccharide (LPS). TNF was quantified by radioimmunoassay, IL‐10 by enzyme‐linked immunosorbent assay, and mRNA by reverse transcriptase‐polymerase chain reaction. After LPS stimulation alone 253 ± 45 pg/mL IL‐10 was synthesized, which increased to 644 ± 117 pg/mL in the presence of 1 μM rolipram. (Rp)‐cAMPS reversed this increase of IL‐10 formation. In the same samples, the LPS‐stimulated production of TNF was markedly attenuated by rolipram or cicaprost. A kinetic analysis revealed a significant increase in TNF production before IL‐10 formation was detectable. These results demonstrate that (1) cAMP‐elevating agents enhance IL‐10 synthesis and suppress TNF production; (2) these regulative functions of cAMP‐elevating agents are mediated by activation of protein kinases A; (3) suppression of TNF synthesis by cAMP in the early phase is not mediated by endogenous IL‐10. Taken together, rolipram and cicaprost exert a dual regulatory function by enhancing IL‐10 formation and attenuating TNF synthesis. J. Leukoc. Biol. 63: 101–107; 1998.
Solar Mn I 5432/5395 A line formation explained

We present a solution for the long standing problem concerning the \chromospheric" behaviour of the Mn i 5395/5432 A lines in the solar spectrum using multi-line/multi-species NLTE modelling. Using comprehensive spectral line formation modelling, we show that the Mn i lines are very sensitive to optical pumping in a transition which overlaps with Mg ii k. It therefore follows that one has to be careful with the choice of lines as temperature indicators and for the determination of the Mn abundances although on the other hand, due to the formation process of these lines they may be useful as a solar and stellar activity diagnostic.
Emotion-regulation knowledge predicts perceived stress early but not later in soldiers’ careers

Abstract Although emotion-regulation competencies have been found to help people overcome negative experiences, such benefits may depend on the context. In the present study, the authors examined whether knowledge about effective emotion regulation would be associated with lower perceived stress in a population with extremely high job demands. The authors studied 492 German soldiers. Results showed that soldiers with higher emotion-regulation knowledge reported lower levels of perceived stress, which was partly due to a greater tendency to use effective emotion-regulation strategies such as reappraisal instead of suppression. When the authors distinguished career stages, however, the authors found that emotion-regulation knowledge was a significant predictor of perceived stress for soldiers in early but not in later career stages. The authors interpret this finding in terms of the context-dependency of emotion-regulation effectiveness. Especially young soldiers can benefit from higher emotion-regulation knowledge possibly due to the fact that they have fewer job resources overall than their senior colleagues.
An Object Assignment Algorithm for Tracking Performance Evaluation

Performance evaluation of detection and tracking methods is a crucial issue. However, despite the efforts of the research community, there is still a lack of widely adopted methods, measures and benchmark data for this purpose. Most contributions have embraced pixel-based method, and do not report their results in terms of objects. The latter requires the assignment of ground truth objects to the detected objects, which can be very complex. To the authors’ knowledge, this paper is the first to describe an algorithm for the explicit unique assignment of objects, including oneto-one (correct) assignments, one-to-many and many-toone assignments (over-segmentations and over-groupings), missed and false detections. Quantitative performance measures are also presented, and the approach is illustrated on a set of traffic videos recorded at two different locations.
Quantum walks public key cryptographic system

Quantum Cryptography is a rapidly developing field of research that benefits from the properties of Quantum Mechanics in performing cryptographic tasks. Quantum walks are a powerful model for quantum computation and very promising for quantum information processing. In this paper, we present a quantum public-key cryptographic system based on quantum walks. In particular, in the proposed protocol the public-key is given by a quantum state generated by performing a quantum walk. We show that the protocol is secure and analyze the complexity of public key generation and encryption/decryption procedures.
Modeling of student academic achievement in engineering education using cognitive and non-cognitive factors

Purpose The retention and success of engineering undergraduates are increasing concern for higher-education institutions. The study of success determinants are initial steps in any remedial initiative targeted to enhance student success and prevent any immature withdrawals. This study provides a comprehensive approach toward the prediction of student academic performance through the lens of the knowledge, attitudes and behavioral skills (KAB) model. The purpose of this paper is to aim to improve the modeling accuracy of students’ performance by introducing two methodologies based on variable selection and dimensionality reduction. Design/methodology/approach The performance of the proposed methodologies was evaluated using a real data set of ten critical-to-success factors on both attitude and skill-related behaviors of 320 first-year students. The study used two models. In the first model, exploratory factor analysis is used. The second model uses regression model selection. Ridge regression is used as a second step in each model. The efficiency of each model is discussed in the Results section of this paper. Findings The two methods were powerful in providing small mean-squared errors and hence, in improving the prediction of student performance. The results show that the quality of both methods is sensitive to the size of the reduced model and to the magnitude of the penalization parameter. Research limitations/implications First, the survey could have been conducted in two parts; students needed more time than expected to complete it. Second, if the study is to be carried out for second-year students, grades of general engineering courses can be included in the model for better estimation of students’ grade point averages. Third, the study only applies to first-year and second-year students because factors covered are those that are essential for students’ survival through the first few years of study. Practical implications The study proposes that vulnerable students could be identified as early as possible in the academic year. These students could be encouraged to engage more in their learning process. Carrying out such measurement at the beginning of the college year can provide professional and college administration with valuable insight on students perception of their own skills and attitudes toward engineering. Originality/value This study employs the KAB model as a comprehensive approach to the study of success predictors. The implementation of two new methodologies to improve the prediction accuracy of student success.
Evolution of Oleosin in Land Plants

Oleosins form a steric barrier surface on lipid droplets in cytoplasm, preventing them from contacting and coalescing with adjacent droplets. Oleosin genes have been detected in numerous plant species. However, the presence of oleosin genes in the most basally diverging lineage of land plants, liverworts, has not been reported previously. Thus we explored whether liverworts have an oleosin gene. In Marchantia polymorpha L. , a thalloid liverwort, one predicted sequence was found that could encode oleosin, possessing the hallmark of oleosin, a proline knot (-PX5SPX3P-) motif. The phylogeny of the oleosin gene family in land plants was reconstructed based on both nucleotide and amino acid sequences of oleosins, from 31 representative species covering almost all the main lineages of land plants. Based on our phylogenetic trees, oleosin genes were classified into three groups: M-oleosins (defined here as a novel group distinct from the two previously known groups), low molecular weight isoform (L-oleosin), and high molecular weight isoform (H-oleosin), according to their amino-acid organization, phylogenetic relationships, expression tissues, and immunological characteristics. In liverworts, mosses, lycophytes, and gymnosperms, only M-oleosins have been described. In angiosperms, however, while this isoform remains and is highly expressed in the gametophyte pollen tube, two other isoforms also occur, L-oleosins and H-oleosins. Phylogenetic analyses suggest that the M-oleosin isoform is the precursor to the ancestor of L-oleosins and H-oleosins. The later two isoforms evolved by successive gene duplications in ancestral angiosperms. At the genomic level, most oleosins possess no introns. If introns are present, in both the L-isoform and the M-isoform a single intron inserts behind the central region, while in the H-isoform, a single intron is located at the 5′-terminus. This study fills a major gap in understanding functional gene evolution of oleosin in land plants, shedding new light on evolutionary transitions of lipid storage strategies.
Phylogenetic networks based on the molecular clock hypothesis

A classical result in phylogenetic trees is that a binary phylogenetic tree adhering to the molecular clock hypothesis exists if and only if the matrix of distances between taxa is ultrametric. The ultrametric condition is very restrictive. In this paper we study phylogenetic networks that can be constructed assuming the molecular clock hypothesis. We characterize distance matrices that admit such networks for 3 and 4 taxa. We design an efficient algorithm for a special class of phylogenetic networks that can detect the existence of a network and constructs it.
A comparative analysis of QRS and Cardioid Graph Based ECG Biometric Recognition in different Physiological conditions

This paper performs a comparative analysis of QRS and Cardioid Graph Based ECG Biometric Recognition incorporating Physiological variability. Data was acquired from 30 subjects, where each subject performed six types of physical activities namely walking, going upstairs, going downstairs, natural gait, lying with position changed and resting while watching TV. Then from the signals of these physiological conditions specific features exclusive to each subject were extracted employing the Cardioid graph based model. In this model, features were extracted solely from the graph derived of the QRS complexes. Subjects were recognized with Multilayer Perceptron classification algorithm. Results were obtained through two approaches. Classification was performed on the whole dataset, Cardioid graph based method resulted in 96.4% of correctly classified instances, whereas QRS complex based ECG produced 94.7% accuracy rates. Later, sensitivity and specificity analysis was done to determine the robustness of the model which produced higher outcomes for Cardioid graph based technique of 96.4% and 99.9% respectively. These results suggest that subject identification in different physiological conditions with Cardioid graph based technique produces better classification rates than that of employing only QRS complexes.
Quantization and reliability-aware iterative majority-logic decoding algorithm for LDPC code in TLC NAND flash memory

Multi-level per cell (MLC) /Triple-Level per cell (TLC) technique significantly improves storage density with low cost increases, which stores more than one bit per cell, but also drastically decreases reliability in NAND flash memory. As the bit number per cell increases, correspondingly cell-to-cell interference (CCI) becomes the major challenge for NAND flash memory technology scaling. Recently, low-density parity-check (LDPC) code is considered as the most appropriate scheme of next generation Error Correcting Code (ECC) in NAND flash memory. In this paper, by exploiting the intra-cell characteristics in TLC NAND flash memory channels, a low-complexity quantization and reliability-Aware iterative majority-logic decoding (QR-IMLGD) algorithm for LDPC code is proposed to reduce the memory read latency and effectively improve the throughput of LDPC decoding. The proposed algorithm takes advantage of highly unequal error probability of input log-likelihood-ratios (LLRs) in the same cells, employ small bit-level quantizer and update only less reliable variable nodes that are initiated with higher error probability LLR values. Simulation results show that the proposed QR-IMLGD algorithm can yield a noticeable improvement in decoding convergence rate without compromising the error performance in TLC NAND flash memory channels.
Gesture Based Operating System Control

Human Computer Interaction keeps moving toward interfaces which are more natural and intuitive to use, in comparison to traditional keyboard and mouse. Hand gestures are an important modality for human computer interaction (HCI) [1]. Compared to many existing interfaces, hand gestures have the advantages of being easy to use, natural, and intuitive. Successful applications of hand gesture recognition include computer games control [2], human-robot interaction [3], and sign language recognition [4], to name a few. Vision-based recognition systems can give computers the capability of understanding and responding to hand gestures. The aim of this technique is the proposal of a real time vision system for its application within visual interaction environments through hand gesture recognition, using general-purpose hardware and low cost sensors, like a simple personal computer and an USB web cam, so any user could make use of it in his office or home. The basis of our approach is a fast segmentation process to obtain the moving hand from the whole image, which is able to deal with a large number of hand shapes against different backgrounds and lighting conditions, and a recognition process that identifies the hand posture from the temporal sequence of segmented hands. The use of a visual memory (Stored database) allows the system to handle variations within a gesture and speed up the recognition process through the storage of different variables related to each gesture. In this paper, we have successfully implemented a vision-based system that can interpret a user's gestures in real time with Speech Application Programming Interface (SAPI) to control windows O.S. actions like single click, double click, forward, backward, media player, notepad, calculator.
Author verification by linguistic profiling: An exploration of the parameter space

This article explores the effects of parameter settings in linguistic profiling, a technique in which large numbers of counts of linguistic features are used as a text profile which can then be compared to average profiles for groups of texts. Although the technique proves to be quite effective for authorship verification, with the best overall parameter settings yielding an equal error rate of 3% on a test corpus of student essays, the optimal parameters vary greatly depending on author and evaluation criterion.
Aspect-oriented modeling method for real-time information systems

To address real time information system development, principled methods are needed to specify, develop, compose, integrate, and validate the application and system software based on MDA approach. These methods must enforce the component composition of real time systems, as well as satisfy the system's stringent functional and nonfunctional requirements. Achieving these goals requires aspect-oriented Model Driven System (MDM) methods that allow developers to specify application and system non-functional requirements. In this paper, we propose a four-stage method of aspect-oriented MDA for non-functional properties to develop real-time information systems. Four stages of the proposed aspect-oriented method are: ACIM stage, APIM stage, APSM stage, aspects of the code model stage. We illustrated the proposed method by the development of EAS and demonstrated four-stage method of aspect-oriented MDA that can be used for modeling complex system' non-functional characteristics, effectively reduce the complexity of software development and coupling between modules to enhance the system's modular.
AN INFORMATION-THEORETIC APPROACH TO MULTI-EXPOSURE FUSION VIA STATISTICAL FILTERING USING LOCAL ENTROPY

An adaptive and parameter-free image fusion method for multiple exposures of a static scene captured by a stationary camera is described. The notion of a statistical convolution operator is discussed and convolution by entropy is introduced. Images are fused by weighting pixels with the amount of information present in their local surroundings. The proposed fusion approach is solely based on non-structural histogram statistics. Its purely information-theoretic view contrasts the phyiscally-based photometric calibration method of high dynamic range (HDR) imaging.
The capital structure of Hungarian firms

In this paper we investigate the capital structure of Hungarian firms using a cross-section and a panel data approach. The data set constitutes of balance sheet data and information on market structure for 1100 firms from 1992 to 1996. We find evidence of forms of financial market imperfections, but also that banks are positively and actively involved in resolving the informational problems that are afflicting the credit market Keywords; transitional economies, Hungary, capital structure, panel data
Comparing the collaborative and independent viewing of program visualizations

In this paper, we report a study on the differences of using a program visualization tool collaboratively or independently. We conducted a study, where students were divided randomly into two groups: the treatment group used a visualization tool called ViLLE in collaboration with another student, while the control group used the tool alone. During the study, we recorded screen captures and students' conversations. Our previous results confirmed that the treatment group outperformed the control group in the post-test in questions related to functions and in total score. Thus, we now annotated and tagged students' actions in answering the exercises, trying to find out an explanation for the difference in learning results. The results show, that the students working in collaboration spent more time answering the difficult exercises than the students working alone, and moreover, spent more time in higher level of engagement, both relatively and absolutely measured. Furthermore, we found out that the students working in pairs discussed the most when in the higher level of engagement and that almost all discussion was related to the exercise they were doing.
Mobile device-based digital microscopy for education, healthcare, and agriculture

This paper shows for the first time how a mobile device such as a smart cell phone and a tablet can be used to realize such a highly-sought-after high-resolution digital microscope. Demonstration based on a low-cost molded plastic convex lens combined with our design packaging style shows that a portable digital microscope can be easily implemented featuring a measured high image resolution of >; 4.40 μm and a measured field of view of 5×5 mm2. Applications include biology study, skin analysis, and pest detection, to name just a few.
The trustworthiness analyzing of interacting business process based on the induction information

Under the open environments, it is very difficult to guarantee the trustworthiness of interacting business process using traditional software engineering methods, at the same time, for dealing with the influence of external factors, some proposed business process mining methods are only effective 1-bounded business process, and some behavior dependent relationships are ignore. A behavior trustworthiness analysis method of business process based on induction information is presented in the paper. Firstly, aimed to the internal factors, we analyze the consistent behavior relativity to guarantee the predictable function. Then, for the external factors, in order to analyze the behavior change of business process, we propose a process mining methods based on induction information. Finally, experiment simulation is given out, and compares our method with genetic process mining methods. Theoretical analysis and experimental results indicate that our method is better than the genetic process mining method.
Interpolation algorithm of Zadoff-Chu sequence

HF channel sounding requires perfect autocorrelation property of the sounding sequences. Compared with other pseudonoise sounding sequences, Zadoff-Chu sequence gets great attention due to its predominant periodic autocorrelation property. In order to adapt the spectrum property of Zadoff-Chu sequence to the requirement of HF channel sounding transmitter-receiver, the Formula Direct Interpolation Algorithm (FDIA) is put forward by which the amplitude frequency characteristic of Zadoff-Chu sequence can be enhanced. Then the comparison of spectra of the sequences respectively interpolated by FDIA and commonly used interpolation algorithm is conducted, which affirms the superiority of FDIA. Finally, an effective method of achieving best decimation of the sequence interpolated by FDIA is provided. All these lay primary theory foundation for the application of Zadoff-Chu sequence to HF channel sounding.
Towards persistent indoor appearance-based localization, mapping and navigation using CAT-Graph

The challenge of persistent appearance-based navigation and mapping is to develop an autonomous robotic vision system that can simultaneously localize, map and navigate over the lifetime of the robot. However, the computation time and memory requirements of current appearance-based methods typically scale not only with the size of the environment but also with the operation time of the platform; also, repeated revisits to locations will develop multiple competing representations which reduce recall performance. In this paper we present a solution to the persistent localization, mapping and global path planning problem in the context of a delivery robot in an office environment over a one-week period. Using a graphical appearance-based SLAM algorithm, CAT-Graph, we demonstrate constant time and memory loop closure detection with minimal degradation during repeated revisits to locations, along with topological path planning that improves over time without using a global metric representation. We compare the localization performance of CAT-Graph to openFABMAP, an appearance-only SLAM algorithm, and the path planning performance to occupancy-grid based metric SLAM. We discuss the limitations of the algorithm with regard to environment change over time and illustrate how the topological graph representation can be coupled with local movement behaviors for persistent autonomous robot navigation.