Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Analysis of Ionization Energy Correlations and of Integral Quantum Characteristics in the Series of Anthraquinone Derivatives

The classes of anthraquinone derivatives, containing OC6H4? (? 3)3 and NC5H10 groups have been investigated. Quantum-chemical calculations with the help of semiempirical method PM3 and absorption spectra in the visible and UV-areas have been carried out. With the use of single factor regression and correlation analysis, the linear correlations between the vertical ionization potentials and the integral strength of the oscillator have been ascertained. This fact indicates strong electron correlation between the highest and the low electron levels of molecules. The errors for the ionization potentials have been calculated.
Method for assessing the potential of miscanthus on marginal lands for high temperature heat demand: The case studies of France and Belgium

Energy crops on marginal lands are seen as an interesting option to increase biomass contribution to the primary energy mix. However, in the literature there is currently a lack of integrated assessments of margin land availability, energy crop production potential and supply chain optimisation. Assessing the potential and the cost of these resources in a given region is therefore a difficult task. This work also emphasises the importance on a clear definition and discussion about marginal lands and the related ethical issues embedded in the concept to ensure positive societal impacts of the results. This study proposes a methodology to estimate and analyse, in terms of economic costs, the potential of miscanthus grown on marginal lands from the production to the final point of use. Different datasets are assembled and a supply chain optimisation model is developed to minimize the total cost of the system. Miscanthus is used as a representative energy crop for the Belgian and French case studies. High temperature heat demand is considered as final use. The miscanthus can be traded by truck either in the form of chips or pellets. The results show that the miscanthus on marginal lands could supply high temperature heat up to 38 TWh in France and 1.4 TWh in Belgium with an average cost of around 50 €/t. The different sensitivity analyses showed that the yield variation has the strongest influence on the final cost, together with the distances and the cost of production of miscanthus. The main pattern observed is the local consumption of miscanthus chips and export of the surplus (if any) to the neighbouring regions. Pellets are only of marginal interest for France and are never observed for Belgium. Distances and availability of sufficient feedstocks are the two main parameters impacting the production of pellets.
Agile Methodologies Applied to the Development of Internet of Things (IoT)-Based Systems: A Review

Throughout the evolution of software systems, empirical methodologies have been used in their development process, even in the Internet of Things (IoT) paradigm, to develop IoT-based systems (IoTS). In this paper, we review the fundamentals included in the manifesto for agile software development, especially in the Scrum methodology, to determine its use and role in IoTS development. Initially, 4303 documents were retrieved, a number that was reduced to 186 after applying automatic filters and by the relevance of their titles. After analysing their contents, only 60 documents were considered. Of these, 38 documents present the development of an IoTS using some methodology, 8 present methodologies focused on the construction of IoTS software, and 14 present methodologies close to the systems life cycle (SLC). Finally, only one methodology can be considered SLC-compliant. Out of 38 papers presenting the development of some IoTS following a methodology for traditional information systems (ISs), 42.1% have used Scrum as the only methodology, while 10.5% have used Scrum combined with other methodologies, such as eXtreme Programming (XP), Kanban and Rapid Prototyping. In the analysis presented herein, the existing methodologies for developing IoTSs have been grouped according to the different approaches on which they are based, such as agile, modelling, and service oriented. This study also analyses whether the different proposals consider the standard stages of the development process or not: planning and requirements gathering, solution analysis, solution design, solution coding and unit testing (construction), integration and testing (implementation), and operation and maintenance. In addition, we include a review of the automated frameworks, platforms, and tools used in the methodologies analysed to improve the development of IoTSs and the design of their underlying architectures. To conclude, the main contribution of this work is a review for IoTS researchers and developers regarding existing methodologies, frameworks, platforms, tools, and guidelines for the development of IoTSs, with a deep analysis framed within international standards dictated for this purpose.
Transcriptome Analysis Reveals the Defense Mechanism of Cotton against Verticillium dahliae Induced by Hypovirulent Fungus Gibellulopsis nigrescens CEF08111

Verticillium wilt is a kind of plant vascular disease caused by the soilborne fungus Verticillium dahliae, which severely limits cotton production. Our previous studies showed that the endophytic fungus Gibellulopsis nigrescens CEF08111 can effectively control Verticillium wilt and induce a defense response in cotton plants. However, the comprehensive molecular mechanism governing this response is not yet clear. To study the signaling mechanism induced by strain CEF08111, the transcriptome of cotton seedlings pretreated with CEF08111 was sequenced. The results revealed 249, 3559 and 33 differentially expressed genes (DEGs) at 3, 12 and 48 h post inoculation with CEF08111, respectively. At 12 h post inoculation with CEF08111, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that the DEGs were enriched mainly in the plant–pathogen interaction, mitogen-activated protein kinase (MAPK) signaling pathway-plant, and plant hormone signal transduction pathways. Gene ontology (GO) analysis revealed that these DEGs were enriched mainly in the following terms: response to external stimulus, systemic acquired resistance, kinase activity, phosphotransferase activity, xyloglucan: xyloglucosyl transferase activity, xyloglucan metabolic process, cell wall polysaccharide metabolic process and hemicellulose metabolic process. Moreover, many genes, such as calcium-dependent protein kinase (CDPK), flagellin-sensing 2 (FLS2), resistance to Pseudomonas syringae pv. maculicola 1(RPM1) and myelocytomatosis protein 2 (MYC2), that regulate crucial points in defense-related pathways were identified and may contribute to V. dahliae resistance in cotton. Seven DEGs of the pathway phenylpropanoid biosynthesis were identified by weighted gene co-expression network analysis (WGCNA), and these genes are related to lignin synthesis. The above genes were compared and analyzed, a total of 710 candidate genes that may be related to the resistance of cotton to Verticillium wilt were identified. These results provide a basis for understanding the molecular mechanism by which the biocontrol fungus CEF08111 increases the resistance of cotton to Verticillium wilt.
Automatic left ventricular boundary detection in digital two-dimensional echocardiography using fuzzy reasoning techniques

Extraction of left ventricular endocardial and epicardial boundaries from digital two-dimensional echocardiography is essential in quantitative analysis of cardiac function. Automatic detection of these boundaries is difficult due to poor intensity contrast and noise inherent in ultrasonic images. In this paper, we present a new approach that employs fuzzy reasoning techniques to detect the boundaries automatically. In the proposed method, the image is firstly enhanced by applying the Laplasian-of- Gaussian edge detector. Secondly, the center of the left ventricle is determined automatically by analyzing the original image. Next, a search process radiated from the estimated center is performed to locate the endocardial boundary by using the zero-crossing points. After this step, the estimation of the range of radius of possible epicardial boundary is carried out by comparing the high-level knowledge of intensity changes along all directions with the actual image intensity changes. The high-level knowledge of global intensity change in the image is acquired from experts in advance and is represented in the form of fuzzy linguistic descriptions and relations. Knowledge of local intensity change can therefore be deduced from the knowledge of global intensity change through fuzzy reasoning. After the comparison, multiple candidate ranges as well as the grades of membership indicating confidence levels are obtained along each direction. The most consistent range in each direction is selected to guide the epicardial boundary search. Multiple candidate epicardial boundaries are then found by locating the zero-crossing points in the range. The one with best consistency is selected as the epicardial boundary. Both endocardial and epicardial boundaries are then smoothed based upon the radii of their spatial neighbors. The final boundaries are obtained by applying the cardinal spline interpolation algorithm. Since our approach is based on fuzzy reasoning techniques and takes global information into consideration, an accurate and smooth result is obtained.
Path following control for 4WID-EV based on extended state observer and sliding mode control considering yaw stability

Automatic driving technology has developed over time and the path-following problem for four-wheel independent drive electric autonomous vehicles (4WID-EV) is a topic of increasing interest. During the path-following process, a consideration of uncertainties in vehicle modeling including parameter variation, modeling error, and external disturbances is made, which have an important effect on path-tracking performance. As so, we proposed a new path following control strategy that can be applied to robotics applications. First, it was determined to establish a 2 DOF dynamic model and path following error model, and were then converted to yaw angle tracking problems. Therefore, the desired control input of steering angle was obtained via yaw angle tracking controller. To estimate and compensate the uncertainties associated with systems, the nonlinear extended state observer (NESO) was designed while the NTSM controller was used to realize yaw angle tracking. Next, considering the system stability, a sliding mode controller with modified reaching law was used to obtain the desired additional yaw moment. Then, the optimized torque distributor was designed for allocating optimal tire forces. Finally, the simulation experiments were carried out in Matlab/Simulink and Carsim joint simulation platform. In conclusion, the proposed control scheme exhibits highly accurate path following as well as strong robustness to speed, tire-road friction coefficient and external disturbance.
Adding articulatory features to acoustic features for automatic speech recognition

A hidden‐Markov‐model (HMM) based speech recognition system was evaluated that makes use of simultaneously recorded acoustic and articulatory data. The articulatory measurements were gathered by means of electromagnetic articulography and describe the movement of small coils fixed to the speakers’ tongue and jaw during the production of German V1CV2 sequences [P. Hoole and S. Gfoerer, J. Acoust. Soc. Am. Suppl. 1 87, S123 (1990)]. Using the coordinates of the coil positions as an articulatory representation, acoustic and articulatory features were combined to make up an acoustic–articulatory feature vector. The discriminant power of this combined representation was evaluated for two subjects on a speaker‐dependent isolated word recognition task. When the articulatory measurements were used both for training and testing the HMMs, the articulatory representation was capable of reducing the error rate of comparable acoustic‐based HMMs by a relative percentage of more than 60%. In a separate experiment, the a.
A Novel Reduction of the Simple Asian Option and Lie-Group Invariant Solutions

We develop the complete 6-dimensional classical symmetry group of the partial differential equation (PDE) that governs the fair price of a simple Asian option within a simple market model. The symmetries we expose include the 5-dimensional symmetry group partially noted by Rogers and Shi, and communicated implicitly by the change of numeraire arguments of Veceř (in which symmetries reduce the original 2 + 1 dimensional simple Asian option PDE to a 1 + 1 dimensional PDE). Going beyond this previous work, we expose a new 1-dimensional space of symmetries of the Asian PDE that cannot reasonably be found by inspection. We demonstrate that the new symmetry could be used to formulate a new, "nonlinear" derivative security that has a 1 + 1 dimensional PDE formulation. We indicate that this nonlinear security has a closed-form pricing formula similar to that of the Black–Scholes equation for a particular market dependent payoff, and show that hedging the short position in this particular exotic option is stable for all market parameters. We also demonstrate the patently Lie-algebraic method for obtaining the already well-known "Rogers–Shi–Veceř" reduction.
On central limit and iterated logarithm supplements to the martingale convergence theorem

Let {Sn , n ≧ 1} be a zero, mean square integrable martingale for which so that Sn → S ∞ a.s. , say, by the martingale convergence theorem. The paper is principally concerned with obtaining central limit and iterated logarithm results for Bn (Sn – S∞ ) where the multipliers Bn ↑ ∞ a.s. An example on the Pólya urn scheme is given to illustrate the results.
Colchicine as potential inhibitor targeting MMP-9, NOX2 and TGF-β1 in myocardial infarction: a combination of docking and molecular dynamic simulation study

Abstract The global data revealed that myocardial infarction (MI) in coronary heart disease has been the leading cause of mortality worldwide in both developing and developed countries. The remodeling process after MI is essential to be the leading cause of heart failure due to cardiac remodeling. The evidence showed the increment of MMP-9, NOX2 and TGF-β1 expressions are biomarkers that influence cardiac remodeling. Lately, colchicine is widely used in the treatment of cardiovascular diseases. The effects of colchicine on NOX2, MMP-9 and TGF-β1 in the molecular models are still not yet discussed. We proposed a molecular docking and molecular dynamics simulation study to show the interaction between colchicine, NOX2, MMP-9 and TGF-β1. Colchicine has a good binding affinity with MMP-9, NOX2 and TGF-β1 based on the value, which are −8.3 Kcal/mol, −6.7 Kcal/mol and −6.5 Kcal/mol, respectively. Colchicine also binds to some catalytic residues in MMP-9, NOX2 and TGF-β1 that are responsible for inhibitor effects. The RMSD values between colchicine and MMP-9, NOX2 and TGF-β1 are 2.4 Å, 2 Å and 2.1 Å, respectively. The RMSF values of ligand and receptors complex showed relatively similar fluctuations. The SASA analysis showed that colchicine could create a more stable interaction with MMP-9. PCA analysis revealed that colchicine is capable of creating a solid and stable interaction with MMP-9 mainly, also NOX2 and TGF-β1. In conclusion, docking and molecular dynamics analysis showed evidence of colchicine roles in the inhibition of MMP-9, NOX2 and TGF-β1 in order to inhibit the remodeling process after MI. Communicated by Ramaswamy H. Sarma
Prediction Models of Primary Membranous Nephropathy: A Systematic Review and Meta-Analysis

Background: Several statistical models for predicting prognosis of primary membranous nephropathy (PMN) have been proposed, most of which have not been as widely accepted in clinical practice. Methods: A systematic search was performed in MEDLINE and EMBASE. English studies that developed any prediction models including two or more than two predictive variables were eligible for inclusion. The study population was limited to adult patients with pathologically confirmed PMN. The outcomes in eligible studies should be events relevant to prognosis of PMN, either disease progression or response profile after treatments. The risk of bias was assessed according to the PROBAST. Results: In all, eight studies with 1237 patients were included. The pooled AUC value of the seven studies with renal function deterioration and/or ESRD as the predicted outcomes was 0.88 (95% CI: 0.85 to 0.90; I2 = 77%, p = 0.006). The paired forest plots for sensitivity and specificity with corresponding 95% CIs for each of these seven studies indicated the combined sensitivity and specificity were 0.76 (95% CI: 0.64 to 0.85) and 0.84 (95% CI: 0.80 to 0.88), respectively. All seven studies included in the meta-analysis were assessed as high risk of bias according to the PROBAST tool. Conclusions: The reported discrimination ability of included models was good; however, the insufficient calibration assessment and lack of validation studies precluded drawing a definitive conclusion on the performance of these prediction models. High-grade evidence from well-designed studies is needed in this field.
COMPARING THE PERFORMANCE OF ROOF SEGMENTATION METHODS IN AN URBAN ENVIRONMENT USING DIGITAL ELEVATION DATA

Abstract. In this paper, we present a novel 3D segmentation approach using digital elevation data. Building detection has been emerging as an important area of research. It has attracted many applications, such as geomatics, architectonics, computer vision, photogrammetry, remote sensing, industry, disaster management, and city planning. Building detection techniques can basically be divided into two categories: the classical approach and the deep learning approach. The main goal of this study is to compare some commonly used detection techniques in photogrammetry, like segmentation-based and classification-based methods using digital elevation data as input. The 4 different methods of roof detection with their detailed analysis and their final results are presented in this paper. This study encourages researchers to further advance research in building detection techniques. Results show that the 2D region growing can successfully segment the building components like the main facades of the complex roof and provide accurate qualitative and quantitative results compared to the other methodologies used in this study.
Current Advances in Technologies for Single Extracellular Vesicle Analysis and Its Clinical Applications in Cancer Diagnosis

Extracellular vesicles (EVs) have been regarded as one of the most potential diagnostic biomarkers for different cancers, due to their unique physiological and pathological functions. However, it is still challenging to precisely analyze the contents and sources of EVs, due to their heterogeneity. Herein, we summarize the advances in technologies for a single EV analysis, which may provide new strategies to study the heterogeneity of EVs, as well as their cargo, more specifically. Furthermore, the applications of a single EV analysis on cancer early diagnosis are also discussed.
Modulation of Notch Signaling at Early Stages of Differentiation of Human Induced Pluripotent Stem Cells to Dopaminergic Neurons

Elaboration of protocols for differentiation of human pluripotent stem cells to dopamine neurons is an important issue for development of cell replacement therapy for Parkinson’s disease. A number of protocols have been already developed; however, their efficiency and specificity still can be improved. Investigating the role of signaling cascades, important for neurogenesis, can help to solve this problem and to provide a deeper understanding of their role in neuronal development. Notch signaling plays an essential role in development and maintenance of the central nervous system after birth. In our study, we analyzed the effect of Notch activation and inhibition at the early stages of differentiation of human induced pluripotent stem cells to dopaminergic neurons. We found that, during the first seven days of differentiation, the cells were not sensitive to the Notch inhibition. On the contrary, activation of Notch signaling during the same time period led to significant changes and was associated with an increase in expression of genes, specific for caudal parts of the brain, a decrease of expression of genes, specific for forebrain, as well as a decrease of expression of genes, important for the formation of axons and dendrites and microtubule stabilizing proteins.
High degree-of-freedom dynamic manipulation

The creation of high degree of freedom dynamic mobile manipulation techniques and behaviors will allow robots to accomplish difficult tasks in the field. We are investigating the use of the body and legs of legged robots to improve the strength, velocity, and workspace of an integrated manipulator to accomplish dynamic manipulation. This is an especially challenging task, as all of the degrees of freedom are active at all times, the dynamic forces generated are high, and the legged system must maintain robust balance throughout the duration of the tasks. To accomplish this goal, we are utilizing trajectory optimization techniques to generate feasible open-loop behaviors for our 28 dof quadruped robot (BigDog) by planning the trajectories in a 13 dimensional space. Covariance Matrix Adaptation techniques are utilized to optimize for several criteria such as payload capability and task completion speed while also obeying constraints such as torque and velocity limits, kinematic limits, and center of pressure location. These open-loop behaviors are then used to generate feed-forward terms, which are subsequently used online to improve tracking and maintain low controller gains. Some initial results on one of our existing balancing quadruped robots with an additional human-arm-like manipulator are demonstrated on robot hardware, including dynamic lifting and throwing of heavy objects 16.5kg cinder blocks, using motions that resemble a human athlete more than typical robotic motions. Increased payload capacity is accomplished through coordinated body motion.
Ultrasonic Transmission Characteristics of In vitro Human Cancellous Bone

An ultrasonic wave transmitted through an in vitro human cancellous bone was experimentally investigated. An osteoporotic cancellous bone specimen was obtained from an in vitro femoral head. A narrow ultrasonic beam was scanned on the specimen surface over an area of 30×30 mm2 and the transmitted ultrasonic wave was obtained at an interval of 1 mm. Local bone densities corresponding to measurement points using the ultrasonic beam were obtained using a microfocus X-ray computed tomography system. Transmitted slow wave signals were detected at all measurements points; however, the measurable area of a fast wave was greatly reduced and limited because of the osteoporotic low-density specimen. The propagation speed of a slow wave was almost independent of bone density. The propagation speed of the fast wave and the amplitudes of the fast and slow waves considerably depended on bone density. The obtained results imply that the scattered values of the propagation speed of the fast wave and the amplitudes of the fast and slow waves reflect the ultrasonic characteristics of the cancellous bone, which depend on both the bone density and the trabecular macro- and micro-structures.