Miracle-dz/UniFAR-FTUs huggingface dataset:
Medical image fusion based on joint sparse method

In this paper, a novel joint image fusion algorithm which is the hybrid of Orthogonal Matching Pursuit (OMP) and Principal Component Analysis (PCA) is proposed to properly utilize the advantages and to overcome the disadvantages of both OMP and PCA methods. Firstly, common and innovative images are extracted from the source images. Secondly, sparse PCA method is employed to fuse the information of innovative features. Then weighted average fusion is used to fuse the sparse PCA result with the common feature thereby preserving the edge information and high spatial resolution. We demonstrate this methodology on medical images from different sources and the experimental results proves the robustness of the proposed method.
Simulation Analysis of Compression Refrigeration Cycle with Different Refrigerants

In this analysis, the performance of compression cycle is assessed theoretically with different refrigerants. In compression refrigeration system, hydrocarbon refrigerants such as R290 and R600a are considered as a refrigerant by mixing of these at different mass fractions about 20%+80%, 25%+75%, 50%+50% and 75%+25% respectively. Various performance measures like compressor discharge temperature, pressure ratio, volumetric cooling capacity (VCC), volumetric efficiency and mass flow rate are analyzed. The results are compared with halogenated refrigerants such as R134a, R12 for different condenser and evaporator temperatures. Halogenated compounds are having direct environmental impacts in turns of ODP and GWP. Among the hydrocarbon refrigerants group, the mixture of R290 and R600a at concentration of 50% each has optimum performance in terms of higher refrigeration effect, better heat transfer and COP.
Gene Expression Analysis of Troglitazone Reveals Its Impact on Multiple Pathways in Cell Culture: A Case for In Vitro Platforms Combined with Gene Expression Analysis for Early (Idiosyncratic) Toxicity Screening

Peroxisome proliferator-activated receptor gamma (PPARγ) agonists of the thiazolidinedione family are used for the treatment of type 2 diabetes mellitus due to their ability to reduce glucose and lipid levels in patients with this disease. Three thiazolidinediones that were approved for treatment are Rezulin (troglitazone), Avandia (rosiglitazone), and Actos (pioglitazone). Troglitazone was withdrawn from the market due to idiosyncratic drug toxicity. Rosiglitazone and pioglitazone are still on the market for the treatment of type 2 diabetes. The authors present data from a gene expression screen that compares the impact these three compounds have in rats, in rat hepatocytes, and in the clone 9 rat liver cell line. The authors monitored the changes in expression in multiple genes, including those related to xenobiotic metabolism, proliferation, DNA damage, oxidative stress, apoptosis, and inflammation. Compared to the other two compounds, troglitazone had a significant impact on many of the pathways monitored in vitro although no major perturbation was detected in vivo. The changes detected predict not only general toxicity but potential mechanisms of toxicity. Based on gene expression analysis, the authors propose there is not just one but multiple ways troglitazone could be toxic, depending on a patient’s environment and genetic makeup, including immune response-related toxicity.
Kraft Lignin Depolymerization in an Ionic Liquid without a Catalyst

In this paper, the depolymerization of lignin was successfully achieved by the thermal treatment of kraft lignin in butyl-1,8-diazabicyclo[5.4. 0]undec-7-enium chloride ([DBUC4+][Cl-]) without a catalyst. The thermal treatment experiments were performed in an oven at 150, 200, and 250 °C for 1 h. The changes in kraft lignin structure over the course of depolymerization were characterized by gel permeation chromatography (GPC), Fourier transform infrared (FTIR) spectroscopy, and 1H / 31P NMR analyses. GPC chromatograms indicated that the retention time of the original kraft lignin had shifted toward higher values after the thermal treatment, which indicated lignin depolymerization. The average molecular weight of the lignin obtained after 1 h reaction time decreased by 23, 70, and 58 wt% for the treatment at 150, 200, and 250 °C, respectively. FTIR spectra indicated the cleavage of β-O-4 bonds of kraft lignin. The 1H NMR spectra showed demethylation of all treated kraft lignins. Moreover, the 31P NMR analysis demonstrated that the demethylation phenomenon of the treated kraft lignin contributed to the formation of catechol groups.
Quantitative mass spectrometry of posttranslational modifications: Keys to confidence

Differences in equipment, sample preparation, and data analysis make reproducibility in mass spectrometry data of the proteome challenging. In this short Review, with 2 tables, 2 figures, and 31 references, we highlight how mass spectrometry analysis can be used to quantitatively study the proteome. In particular, we describe challenges to analyzing posttranslational modifications of proteins, which serve to transduce information through signaling pathways that control cellular behavior. Because posttranslational modifications serve as the language of cellular regulation, this systems-level approach reveals insights not only into basic cellular biology but also into how aberrations in these events can lead to disease. However, to leverage proteomic mass spectrometry data, the results need to be reliable, reproducible, and accurate, but technical limitations and variations in methodologies can make comparing data sets challenging. Posttranslational modifications (PTMs) of proteins represent an important level of cellular control. They participate in the efficient transduction of signals and form the basis of long-term cellular memory, allowing cells to adapt to a rapidly changing environment. More than 200 different PTMs have been described that affect many aspects of protein functions, and the importance of these modifications is evident from the number of diseases that arise from their deregulation. The proteome-wide analysis of certain PTMs, such as phosphorylation, acetylation, glycosylation, methylation, ubiquitination, and sumoylation, has become a standard procedure in many laboratories. We highlight and discuss some important aspects of systems-wide PTM analyses using mass spectrometry–based methods.
A Comparison of Three Methods for Calculating Confidence Intervals for the Benchmark Dose

Various methods exist to calculate confidence intervals for the benchmark dose in risk analysis. This study compares the performance of three such methods in fitting nonlinear dose‐response models: the delta method, the likelihood‐ratio method, and the bootstrap method. A data set from a developmental toxicity test with continuous, ordinal, and quantal dose‐response data is used for the comparison of these methods. Nonlinear dose‐response models, with various shapes, were fitted to these data. The results indicate that a few thousand runs are generally needed to get stable confidence limits when using the bootstrap method. Further, the bootstrap and the likelihood‐ratio method were found to give fairly similar results. The delta method, however, resulted in some cases in different (usually narrower) intervals, and appears unreliable for nonlinear dose‐response models. Since the bootstrap method is more time consuming than the likelihood‐ratio method, the latter is more attractive for routine dose‐response analysis. In the context of a probabilistic risk assessment the bootstrap method has the advantage that it directly links to Monte Carlo analysis.
The Multiplex Network of EU Lobby Organizations

The practice of lobbying in the interest of economic or social groups plays an important role in the policy making process of most economies. While no data is available at this stage to examine the success of lobbies in exerting influence on specific policy issues, we perform a first systematic multi-layer network analysis of a large lobby registry. Here we focus on the domains of finance and climate and we combine information on affiliation and client relations from the EU transparency register with information about shareholding and interlocking directorates of firms. We find that the network centrality of lobby organizations has no simple relation with their lobbying budget. Moreover, different layers of the multiplex network provide complementary information to characterize organizations’ potential influence. At the aggregate level, it appears that while the domains of finance and climate are separated on the layer of affiliation relations, they become intertwined when economic relations are considered. Because groups of interest differ not only in their budget and network centrality but also in terms of their internal cohesiveness, drawing a map of both connections across and within groups is a precondition to better understand the dynamics of influence on policy making and the forces at play.
Object transportation task by a human and a mobile robot

This paper addresses the human-robot cooperation problem on object transportation tasks, particularly when a human grasps one side of the object while the other extremity is carried by the robot. The robot is equipped with a pair of infrared sensors used to obtain the load's status and apply it as a feedback to accomplish a specific task. A nonlinear controller is proposed to allow the robot to perform coordinated movements and thus help a human to carry an object from an initial position to a final goal with a defined position and orientation. The controller is proved to be asymptotically stable at the equilibrium point, which guarantees the accomplishment of the task. In contrast to other methods, the approach presented in this paper does not use either force or visual information to estimate the status of the robot and the object. In order to validate the proposed method some experiments are shown.
Novel Point-to-Point Scan Matching Algorithm Based on Cross-Correlation

The localization of mobile robots in outdoor and indoor environments is a complex issue. Many sophisticated approaches, based on various types of sensory inputs and different computational concepts, are used to accomplish this task. However, many of the most efficient methods for mobile robot localization suffer from high computational costs and/or the need for high resolution sensory inputs. Scan cross-correlation is a traditional approach that can be, in special cases, used to match temporally aligned scans of robot environment. This work proposes a set of novel modifications to the cross-correlation method that extend its capability beyond these special cases to general scan matching and mitigate its computational costs so that it is usable in practical settings. The properties and validity of the proposed approach are in this study illustrated on a number of computational experiments.
A MECHANISTIC DERIVATION OF THE LOGISTIC MODEL

The purpose of this note is to mechanistically derive the logistic population growth models from the well tested and received Droop equation. 1. A mechanistic derivation of the logistic equation. Population growth involves and often is determined by the birth and death processes. Most of the existing studies focus on birth process on the combined birth and death processes (the growth process). In general, death mechanisms are more numerous and difficult to study then birth mechanisms in a lab or field setting. In a short time frame, growth dynamics can be approximated by a linear differential equation with the coefficient called growth rate. Longer term, this growth rate shall be regarded as time dependent, or density dependent. The so-called Droop equation provides a time and experiment tested simple mathematical expression for biomass growth rate. We shall show that it also provides a convenient base for deriving the classical logistic equation. This section is adapted from Kuang et al. (2004). In 1968, Droop reported some surprising findings based on his most ambitious and comprehensive chemostat experiment to date in terms of concept, technical difficulty and mathematical analysis, it was to surpass by far all that had gone before (Leadbeater, 2006). The experiment studied the kinetics of vitamin B12 limitation in Monochrysis lutheri in continuous and exponentially growing batch cultures and in washed cell suspensions. The aim of this experiments was to relate specific growth rate to substrate concentration (Droop 1968). Contrary to conventional belief, the specific growth rate (m) of Monochrysis in the chemostats was found not to depend directly on medium substrate concentration. However, the one relationship that did stand out was that growth depended on the intracellular concentration of vitamin B12 (cell quota Q). The relationship between specific growth rate (μ ) and cell quota (Q) took the following simple form (Droop 1973, 1974). μ = μm ( 1− q Q ) . (1.1) This equation is called the Droop equation. We call μm ( 1− q Q ) the Droop function. The parameter q is the minimum quota necessary for life (the subsistence quota) and represents the value of cell quote Q at zero growth rate. μm is the growth rate 2000 Mathematics Subject Classification. 92D25 and 34C60.
A Novel Time Synchronization Scheme in Wireless Sensor Networks

In recent years, wireless sensor networks have been an interesting and important research area. The time synchronization is an important problem for wireless sensor networks. In this paper, a novel time synchronization scheme in wireless sensor networks is proposed. First, we create a spanning tree of all the nodes in the network by broadcasting children-find packets. Then, the spanning tree is divided into multiple subtrees, in which two subtree synchronization algorithms can be performed. After that, time synchronization of the whole network is achieved. Performance analyses and simulations are presented in this paper, and demonstrate that our proposed scheme has much better performance than RBS in terms of both synchronization delay and synchronization error
Energy function construction and implementation for stock exchange prediction NNs

Neural networks (NN), with their parallel processing power, can be used as a tool to forecast stock exchange events (SEE), as a sub-domain of time-series (TS) forecasting. For the final product of SEE forecasts, other external economical factors have to be taken also into consideration and to be combined with the pure TS forecast. In this paper we present the energy function construction and implementation for SEE prediction. We focus on the mathematical deductions of the energy function and on the error minimization procedures. We present also some comparative results of our method, based on Lyapunov (also called infinite) norm, compared to the classical backpropagation method (BP), and to the random walk generator. We discuss some further optimisation of the system.
Seasonal dynamics in water quality and vegetation cover in temporary pools with variable hydroperiods in Kiskunság (Hungary)

The seasonal dynamics in habitat characteristics of temporary freshwater pools were studied in relation to hydroperiod and geographical location for a set of 36 pristine pools in and around the Kiskunság National Park (Hungary). The pools were geographically distributed over three clusters and their hydroperiod varied from seven to more than 18 weeks. Biweekly to monthly monitoring started two weeks after inundation (March) and lasted until most pools were dry again (July). Throughout the season, nutrient concentrations and conductivity increased in all study pools. Algal biomass increased after short hydroperiod pools were already dry, resulting in an increase in the amount of suspended solids and turbidity in pools with a relatively long hydroperiod. Both the longer inundation period and conditions later in the season may have contributed to the stronger algal growth in these pools. Oxygen was not depleted towards the end of the season, potentially due to growing algae and vegetation. The high buffering capacity of the water may have contributed to the near constant pH levels through time. Pools in one of the clusters were typically more turbid, less vegetated, and had higher amounts of suspended matter when compared to pools in the two other clusters. Temporary pool characteristics were related to local environmental conditions and seasonal dynamics differed according to the duration of inundation.
Nutritional composition and antioxidant properties of Raphionacme splendens (schl.) tubers

People of Western Kordofan (Sudan) are endowed with a deep knowledge concerning the use of wild plants. Tubers of Raphionacme splendens Schl. subspecies splendens Flickr (family Apocynaceae), locally known as Elfayo, are used as a food reserve during times of famine or poor harvest. The aim of this study was to analyze the nutritional composition and antioxidant capacity of root tubers of R. splendens. Samples were collected from South-West Kordofan. Analyses included determination of moisture, carbohydrate, crude protein, fat, fibre, ash, minerals, vitamin C, amino acids and fatty acids composition. Antioxidant activity was determined by the DPPH (1,1-diphenyl-2-picrylhydrazyl) and ABTS (2.2’-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) assays. The total phenolic content was also assessed. The results, which are referred to as (%) dry weight, showed that the tubers contained 3.2% protein, 18% carbohydrate, 0.5% lipid, 2.4% crude fibre, 3.5% ash, 79.2% moisture and gross energy 101.7 kJ/g. The total amino acids were 10776 mg/100g where the essential amino acids represented 28.2%. The more abundant essential amino acids were leucine (792mg/100g), isoleucine (712mg/100g) and threonine (536mg/100g). Methionine and lysine were the limiting amino acids. Minerals were potassium (259mg/100g), calcium (183mg/100g), magnesium (64mg/100g), phosphorus (37mg/100g), copper (3.6mg/100g), manganese (2.4mg/100g), zinc (1.8mg/100g) and iron (1.2mg/100g). Total saturated fatty acids were 45.6% whereas total unsaturated fatty acids were 54.4%. Oleic acid (32.56%) and palmitic acid (30.23%) were the most abundant fatty acids. Tubers displayed good antioxidant activity with IC 50 values 0.987 and 1.559mg/mL against DPPH and ABTS radicals respectively. Vitamin C was 31.5mg/100g and total phenolic content was 60mg gallic acid equivalent (GAE) per 100g dry sample and they could be the main contributor to the antioxidant capacity of the tubers. In conclusion, the results of this study suggested that tubers of R. splendens could have beneficial effect for food and/or nutraceutical application for normal growth and adequate protection against diseases associated with reactions of free radicals. Keywords: Raphionacme splendens , proximate analysis, amino acids, fatty acids, antioxidant activity
Characterization of the bacterial magnetosome membrane

Intact magnetosomes of Aquaspirillum magnetotacticum were purified from broken cells by a magnetic separation technique. Electron microscopic and chemical analyses revealed the magnetite to be enclosed by a lipid bilayer admixed with proteins. Lipids were recovered in fractions expected to contain (i) neutral lipids and free fatty acids, (ii) glycolipids and sulfolipids, and (iii) phospholipids (in a weight ratio of 1:4:6). Phospholipids included phosphatidylserine and phosphatidylethanolamine. Two of the numerous proteins detected in the magnetosome membrane were not found in other cell membranes or soluble fractions.
Evaluation of Lexical-Based Approaches to the Semantic Similarity of Malay Sentences

Abstract We evaluate existing and modified approaches for measuring the semantic similarity of sentences in the Malay language. These approaches are mainly used for English sentences and no studies to date have evaluated and compared their effectiveness when applied to Malay sentences. We used a pre-processed Malay machine-readable dictionary to calculate word-to-word semantic similarity with two methods: probability of intersection and normalization. We then used the word-to-word semantic similarity measure to identify semantic sentence similarity. We evaluated five measures of semantic sentence similarity: vector-based semantic similarity, word order similarity, highest word-to-sentence similarity, and combinations of vector-based and word-to-sentence similarity and of word order and word-to-sentence similarity. We also evaluated the effects of including and excluding lexical components such as prepositions, conjunctions, verbs, and morphological variants.
Individual class II-restricted antigenic determinants of the same protein exhibit distinct kinetics of appearance and persistence on antigen-presenting cells.

The kinetics of presentation of class II-restricted T cell determinants of influenza virus hemagglutinin (HA) was investigated over a 48-h time course after pulsing of A20 B lymphoma APC with non-replicative virus or isolated HA. At intervals after Ag pulse, APC were fixed with paraformaldehyde to arrest Ag processing and to preserve the expression levels of the presented determinants. Expression of T cell sites at each time point was probed by a panel of BALC/c T hybridomas specific for the HA of influenza A/Puerto Rico/8/34 virus, recognizing either site 1 (residues 111 to 119), site 2 (126 to 138), or site 3 (302 to 313). Characteristic patterns of presentation were observed for each site: sites 2 and 3 achieved maximal expression by 8 h post pulse, but declined thereafter, whereas site 1 presentation continued to increase over time. The quantitative expression of each T cell site was affected by the proteolysis inhibitor leupeptin, resulting in partial inhibition of site 1, complete blocking of site 2, but enhancement of site 3. However, the expression kinetics of sites 1 and 3, which could be observed in the presence of the inhibitor, remained qualitatively unchanged. These observations indicate that some T cell determinants (e.g., HA site 1) may exhibit a greater longevity of expression on APC than other antigenic sites of the same protein. Differences in the persistence of surface expression of distinct T cell sites may be a factor in their relative immunodominance.
Characterizing Forest Succession Stages for Wildlife Habitat Assessment Using Multispectral Airborne Imagery

In this study, we demonstrate the potential of using high spatial resolution airborne imagery to characterize the structural development stages of forest canopies. Four forest succession stages were adopted: stand initiation, young multistory, understory reinitiation, and old growth. Remote sensing metrics describing the spatial patterns of forest structures were derived and a Random Forest learning algorithm was used to classify forest succession stages. These metrics included texture variables from Gray Level Co-occurrence Measures (GLCM), range and sill from the semi-variogram, and the fraction of shadow and its spatial distribution. Among all the derived variables, shadow fractions and the GLCM variables of contrast, mean, and dissimilarity were the most important for characterizing the forest succession stages (classification accuracy of 89%). In addition, a LiDAR (Light Detection and Ranging) derived forest structural index (predicted Lorey’s height) was employed to validate the classification result. The classification using imagery spatial variables was shown to be consistent with the LiDAR derived variable (R2 = 0.68 and Root Mean Square Error (RMSE) = 2.39). This study demonstrates that high spatial resolution imagery was able to characterize forest succession stages with promising accuracy and may be considered an alternative to LiDAR data for this kind of application. Also, the results of stand development stages build a framework for future wildlife habitat mapping.