Miracle-dz/UniFAR-FTUs huggingface dataset:
Studies on multiphased mixed crystals of NaCl, KCl and KI

Multiphased mixed crystals of NaCl, KCl and KI were grown by the melt method, for the first time. Densities and refractive indices of all the grown crystals were determined and used for the estimation of the composition in the crystal. Atomic absorption spectroscopic measurements were done to estimate the metal atom contents in the crystal. Lattice parameters and thermal parameters (Debye‐Waller factor, mean square amplitude of vibration, Debye temperature and Debye frequency) were determined from the X‐ray powder diffraction data. DC and AC electrical measurements were done at various temperatures ranging from 40 to 150°C. Activation energies were also estimated. The observed lattice parameters showed that the system exhibits three phases each nearly corresponds to NaCl, KCl and KI. The thermal and electrical parameters show a highly nonlinear bulk composition dependence. Results are reported. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Future directions for in‐situ product removal (ISPR)

This paper summarizes the main findings of a round-table discussion held to examine the key bottlenecks in the further application and industrial implementation of in-situ product removal (ISPR) techniques. ** It is well established that ISPR can yield great benefits for processes limited by inhibitory or toxic products, as well as unstable products or reactions that are thermodynamically unfavorable. However, several issues for industrial implementation were revealed in the discussion. Most notably implementation will be dependent on (1) research into the appropriate process structure, (2) methods to achieve process robustness, (3) systematic selection methods for separation operations and (4) the nature of the product market. Here, these four issues will be discussed as a basis for future work in this area. Copyright © 2007 Society of Chemical Industry
Molecular Arrangements in Polymer-Based Nanocomposites

Monte Carlo computer simulations have been performed for model polymers containing randomly distributed spherical filler particles of diameter 8 times the transverse diameter of the polymer chains. The partial volume of the filler has been varied from 10% to 50%. The polymer/filler interface is characterized by densely packed and ordered shells of polymer units of thickness nearly twice the diameter of the units. The chain dimensions in filled systems are always found to be slightly smaller than in the unfilled melt. The behavior of various parameters chosen such to characterize the molecular arrangements in polymer-based nanocomposites is analyzed, leading to a general picture in which the chains are considered to be sequences of interface, bridge and loop segments. The relative abundance of segments of each type, their average length and the way they are allocated in sequence change with changing the partial volume of filler.
Tuneable mechanical properties in low molecular weight gels

The mechanical properties of gels are critical to the final targeted applications. Depending on the application, different properties may be required. Here, we show that the mechanical strength and ability to recover of gels formed using a low molecular weight gelator can be controlled by two independent factors (i) the volume fraction of co-solvent (in this case DMSO) in the system and (ii) the temperature cycle used. These differences correlate with the large scale structure of the network that is formed from the self-assembled fibres. This opens up the potential to prepare gels with very different properties at the same final conditions, allowing the effect of microstructure to be probed.
Determination of Iridoid Glycosides from Four Turkish Lamium Species by HPLC-ESI/MS

An HPLC-ESI/MS method that enables fast detection and identification of iridoid glycosides is described. Eleven iridoid glycosides known to occur in the genus Lamium-lamalbide, sesamoside, 6-b-OH ipolamiide, shanzhiside methyl ester, dehydropenstemoside, barlerin (= 8-O-acetylshanzhiside methyl ester), 6-O-syringyl-8-O- acetylshanzhiside methyl ester, lamerioside, lamiide, eriobioside, and ipolamiide, were identified by means of their retention time and ESI/MS data. This method was successfully applied to the identification of the iridoid composition of the n-butanol extracts of Lamium eriocephalum Bentham subsp. eriocephalum, L. garganicum L. subsp. pulchrum R. Mill, L. garganicum L. subsp. laevigatum Arcangeli, and L. purpureum L. var. purpureum from the Turkish flora.
Effect of light supply and carbon source on cell growth and cellular composition of a newly isolated microalga Chlorella vulgaris ESP‐31

Light supply is one of the most important factors affecting autotrophic growth of microalgae. This study investigated the effect of the type and light intensity of artificial light sources on the cell growth of an indigenous microalga Chlorella vulgaris ESP‐31 obtained from southern Taiwan. In addition, a dissolved inorganic carbon source (i.e. sodium bicarbonate) was used to improve the biomass production of strain ESP‐31. The results show that a new fluorescent light source (TL5) was effective in indoor cultivation of microalgae. Better overall productivity of 0.029 g dry cell weight/L‐d was obtained when using TL5 lamps as the light source with a light intensity of 9 W/m2. A carbon source (sodium bicarbonate) concentration of 1000 mg/L was found to be optimal for the growth of strain ESP‐31 in terms of both biomass production and carbon source utilization. Under the optimal growth conditions, the resulting microalgal biomass consisted of 25–30% protein, 6–10% carbohydrate, and 30–40% lipid.
“ Profitable , Return Enhancing ” Portfolio Adjustments – An Application of Genetic Programming with Constrained Syntactic Structure

class Node () { protected Class returnType; protected int arity; protected Node[] children; protected Node (int arity, Class type) { if (arity ! =0) children = new Node[arity]; returnType = type; this.arity = arity; } } 4.3. 1.2 How Each Node Is to Be Executed Functions and terminals are executed differently. A function, either “+” or “*” in this system, takes its left and right children as its arguments and returns the result of the appropriate arithmetic operation on the two children. A terminal provides a value to the system. A terminal represents either a weight coefficient or a trading indicator. A weight terminal is defined as a numerical constant and it returns an integer value from 0 to 10 inclusive. A indicator terminal is defined as numerical variable and its return values depending on the specific properties of the rule and input data. The execution of functions and terminals in the system requires a specific context (implemented as parameters to the execution methods) to determine where and when they are to be executed. 1) It needs to know the current chromosome where the functions and terminals executes. 2) It also needs to know the child number of the
The mean flow field generated by a pitched blade turbine: Changes in the circulation pattern due to impeller geometry

The mean flow field in a tank stirred with a pitched blade turbine was measured using a two-component Laser Doppler Anemometer system (LDA). The effects of impeller clearances and impeller geometries (number of blades, blade angle and blade size) on the mean flow field have been studied. The primary pumping number, induced pumping number of the primary circulation loop and the induced pumping number of the secondary circulation loop, which often has been ignored, are reported. The flow patterns and circulation loops are more complex than those traditional ones, which vary with the geometries of the PTD and the clearances. On a mesure le champ d'ecoulement moyen dans un reservoir agite muni d'une turbine a pales inclinees a l'aide d'un anenometre laser Doppler bicomposantes. Les effets du degagement de la turbine par rapport aux parois et de la geometrie de la turbine (nombre, angle et dimension des pales) sur le champ d'ecoulement moyen ont ete etudies. Le nombre de pompage primaire, le nombre de pompage induit de la boucle de circulation primaire ainsi que le nombre de pompage induit de la boucle de circulation secondaire, qui sont souvent ignores, sont presentes ici. Les profils d'ecoulement et les boucles de circulation sont plus complexes que ceux des cas classiques, qui varient selon la geometrie de la turbine a pales inclinees (TPI) et les degagements par rapport aux parois.
Etching Kinetics of Silicon Dioxide in Aqueous Fluoride Solutions: A Surface Complexation Model

A molecular-level model of SiO 2 dissolution in aqueous fluoride solutions is presented. The model recognizes the fact that the SiO 2 /water interface contains neutral hydroxylated surface groups (Si-OH) which can protonate to give positively charged sites (Si-OH 2 + ) or deprotonate to give negatively charged sites (Si-O - ), depending on the pH. The adsorption of the fluoride ion, which is formulated as a surface ligand exchange reaction (Si-OH + HF = Si-F + H 2 O), results in the polarization of the underlying Si-O bonds. The subsequent detachment of the surface Si-F complex constitutes the effective dissolution event. It is shown that the effects of aqueous phase variables (e.g., pH) on the dissolution rate are correlated with the effects of these same variables on the surface concentration of adsorbed fluoride. The model is compared with published experimental results, and it is demonstrated that a unified theory is obtained when the role of surface complexation is incorporated into the dissolution mechanism. The frequently reported observation of a decline in etching rate at elevated NH 4 F concentrations (and therefore high pH) is attributed to a competition between OH - ions and F - ions for adsorption sites.
Relationships between rock fragment cover and soil hydrological response in a Mediterranean environment

Abstract Rock fragments are a key factor for determining erosion rates, particularly in arid and semiarid environments where vegetation cover is very low. However, the effect of rock fragments in non-cultivated bare soils is still not well understood. Currently, there is a need for quantitative information on the effects of rock fragments on hydrological soil processes, in order to improve soil erosion models. The main objective of the present research was to study the influence of rock fragment cover on run-off and interrill soil erosion under simulated rainfall in Mediterranean bare soils in south-western Spain. Thirty-six rainfall simulation experiments were carried out at an intensity of 26.8 mm h−1 over 60 min under three different classes of rock fragment cover (<50%, 50–60% and >60%). Ponding and run-off flow were delayed in soils with high rock fragment cover. In addition, sediment yield and soil erosion rates were higher in soils with a low rock fragment cover. The relationship between soil loss rate and rock fragment cover was described by an exponential function. After this first set of experiments, rock fragments were removed from sites with the highest cover (>60%) and the rainfall simulation experiments were repeated. The steady-state run-off rate and soil loss increased significantly, showing that run-off and soil erosion were partly conditioned by rock fragment cover. These results have significant implications for erosion modelling and soil conservation practices in areas with the same climate and soil characteristics.
STABILIZATION OF THE ADSORPTION COMPLEXES OF BIOMOLECULES ON THE SURFACE OF PARTIALLY HYDROPHOBIZED SILICA IN AN AQUEOUS MEDIUM: A QUANTUM CHEMICAL STUDY

The influence of the degree of hydrophobization of silica surface trimethylsilyl groups on the stability of adsorption complexes with molecules of vitamins C, B 1 , B 6 , E and the bile acids in an aqueous medium has been studied by quantum chemical methods using Hartree-Fock theory with the 6-31G (d) basis set and PM3 semiempirical method and SM5.42R solvation model. It was shown that the appearance of these groups on the silica surface stabilizes the adsorption complex due to interaction of the hydrophobic groups with hydrogen-carbon fragments of the vitamin and bile acid molecules. It was found that for taurocholic acid dependence of the free energy of adsorption on the degree of surface hydrophobization is stronger than for deoxycholic, cholic and glycocholic ones.
A novel face anti-spoofing method using multiple color space models

The importance of face recognition algorithms in biometric authentication systems has become increasingly prominent. In order to ensure the security of face authentication, it is crucial to detect spoof attacks before performing face recognition. In this paper, we propose a 9-layer convolutional neural network (CNN) architecture using end-to-end learning for face anti-spoofing applications in small-scale datasets, which can directly judge the corresponding output class of the raw input face image. In addition, we believe that real faces and fake faces are well distinguishable in color spaces other than the RGB space. Therefore, we propose a novel face anti-spoofing method using multiple color space models to provide complementary features. Extensive experiments on mixed dataset for CASIA-FASD database and Replay-Attack database showed excellent face spoofing detection result comparing with other similar approaches.
A review on assessment, early warning and auxiliary diagnosis of depression based on different modal data

Depression is a widespread mental health disorder. At present, the clinical diagnosis of depression mainly depends on the interview between doctors and patients and the self-report of patients, so the diagnosis is subjective to a certain extent. This paper summarizes the scales of self-assessment for depression and the methods of relevant health data collection. This paper discusses the research status of the auxiliary diagnosis of depression based on voice data and social network data, and summarizes the basic process of the auxiliary diagnosis using the above data. The application cases of some machine learning algorithms and their evaluation indexes are counted. The machine learning algorithm can objectively predict and assist the diagnosis of depression. The convenience and economy of collecting depression health information should be fully considered. In the actual analysis, data acquisition cost, difficulty, application purpose and application population should be taken into comprehensive consideration, and data used for auxiliary diagnosis should be designed. When necessary, multi-modal data combined with several data forms can be used. In this paper, different methods are proposed to evaluate depression in different populations, and at the same time, early warning and health intervention should be carried out on the basis of the assessment, so as to bring a new way of thinking for the economic and rapid objective evaluation of depression.
False alarm sources detection based on LNIP and local probability distribution in infrared image

Given that the infrared radiation energy of false alarm sources such as rivers, high-altitude cirrus clouds and icy lakes is similar to that of the infrared targets, the false alarm sources seriously affect the accurate detection and tracking of the target by Infrared Search and Track (IRST) system. To reduce the false alarm rate in infrared target detection, a pixellevel algorithm is proposed in this paper to detect and eliminate false alarm sources. Firstly, we use histogram equalization and gray stretch to enhance the infrared image. The next step is to locate the false alarm source based on Local Neighborhood Intensity Pattern (LNIP) and local probability distribution, which is critical in false alarm source detection. Finally, we use region growing based on fused saliency feature to strengthen the accuracy of the location. Numerous experimental results manifest that the algorithm proposed in this paper boasts a detection rate of more than 96% for multiple false alarm sources, and performs better on the Precision-Recall (PR) curve and the Receiver Operating Characteristic (ROC) curve among the algorithms based on texture analysis.
Validation of vehicle detection and distance measurement method using virtual vehicle approach

By the end of 2019, the total number of motor vehicles in China had reached 340 million, of which 250 million were cars. In order to reduce the occurrence of road traffic accidents, more and more automobile manufacturers have begun to develop vehicle-mounted image-assisted driving technology based on dashcam. The most important part of the collision avoidance system is its visual recognition and ranging. Therefore, it is of great significance to study the range finder system based on vision. This paper builds a 3D simulation simulator based on Unreal Engine and uses specific data sets to test and verify various classic algorithms of vision-based identification and ranging. According to different operating conditions, the advantages and disadvantages of each algorithm are listed and summarized, and the limitations of their application are pointed out. As for the detection part, this paper conducts experimental verification on SVM+HOG and LBP+Cascade detection algorithms to obtain their recognition accuracy, positioning accuracy and calculation time information, and analyzes their advantages and disadvantages. As for the ranging part, this paper conducts ranging tests on monocular and binocular ranging algorithms, obtains ranging errors at different positions and analyzes the advantages and disadvantages of different algorithms. Experimental results show that the monocular distance requires a more accurate identification frame than the binocular distance measurement. Binocular distance measurement can measure the distance information of the target more quickly and accurately when the identification frame is very small.
One-factor cancelable fingerprint template protection based on feature enhanced hashing

In the existing one-factor cancelable biometric template protection scheme, the hashing function used in the transformation of biometrics can’t preserve the original biometric features, which leads to low recognition rate. To make full use of biometric features by replication and extension, but too long feature vectors can cause low computational efficiency. Therefore, a one-factor cancelable fingerprint template protection based on feature enhanced hashing is proposed. Firstly, the extended binary biometric vectors are combined by sliding and extracting window, then converted into decimal system, in order to make full use of biometric features and increase non-invertibility. Secondly, the permutation factor is calculated by the feature enhanced hashing function and the random sequence is reordered, it can embed the information of the original biometric features into the random sequence better. Finally, a cancelable template is generated by reducing the same length of the first and last of reordered random sequence, in this way, some elements can be deleted to improve the computational efficiency and non-invertibility. The experimental results show that the recognition rate of the algorithm is improved on FVC2002 and FVC2004 fingerprint databases, which meets the design standards of cancelable biometric recognition and can defend against security attacks.
Semantic segmentation of road surface crack images using RU-Net model

Semantic segmentation is a technique for classifying images pixel by pixel. The road surface cracks are difficult to extract with traditional method because they are exposed to more environmental factors such as light and more interference noise. This paper proposes a road surface crack detection technology based on RU-Net. The impact of environmental factors is effectively reduced by this network, and it realizes the classification of cracks from end to end and pixel by pixel. The network mainly includes two parts which are encoder and decoder. The encoder part is mainly used for feature extraction, and the decoder part is mainly used to recover spatial information. The results of the experiment show that the RU-Net achieves an accuracy of more than 98% and an MIoU of more than 73%.
Integrated optical filter consisting of micro-ring resonator embedded in Fabry-Perot cavity

An optical filter is proposed and demonstrated based on a micro-ring resonator (MRR) embedded in a Fabry-Perot (FP) cavity. By exploiting coherent interference within the FP cavity to reconstruct the transmission spectrum of the MRR, high extinction ratio (ER) and narrow bandwidth for periodic notch filtering is obtained. The FP cavity is composed by two circular Bragg grating (CBG) mirrors, and the two mirrors are well placed so that the light wave can be constantly reflected between the two mirrors to generate resonance. The device is simulated theoretically and fabricated on a silicon-on-insulator (SOI) platform. The proposed optical filter has an ER up to 31dB and a minimum 3dB bandwidth of 10pm according to the simulation result.
Untargeted attack on targeted-label for multi-label image classification

The current 3D point cloud feature extraction algorithms are mostly based on geometric features of points. And the distribution of feature points is so messy to accurately locate. This paper proposes a point cloud feature extraction algorithm using 2D-3D transformation. By selecting three pairs of 2D image and 3D point cloud feature points, the conversion matrix of image and point cloud coordinates is calculated to establish a mapping relationship and then we realize the extraction of point cloud features. Experimental results show that compared with other algorithms, the algorithm proposed in this paper can extract the detailed features of point cloud more accurately.
Lung fields segmentation in chest radiographs using Dense-U-Net and fully connected CRF

Computer-Aided Diagnosis (CAD) benefits from its early diagnosis and accurate treatment of lung diseases. Accurate segmentation of lung fields is an important component in CAD for lung health, which facilitates subsequent analysis. However, most of the existing algorithms for lung fields segmentation are unable to ensure appearance and spatial consistency due to the varied boundaries and poor contrasts. In this paper, we propose a novel and hybrid method for lung fields segmentation by integrating Dense-U-Net network and a fully connected conditional random field (CRF). In order to realize the reuse of image features, the structure of densely-connected is added to the decoder, which ensures the object with varied shapes and sizes can be extracted without adding more parameters. To make full use of the mutual information among pixels of the original image, a fully connected CRF algorithm is adopted to further optimize the preliminary segmentation results according to the intensity and position of each pixel. Compared with some previous popular methods on JSRT dataset, the proposed method in this paper shows higher Jaccard index and Dice-Coefficient.