Miracle-dz/UniFAR-FTUs huggingface dataset:
New aspects of aging in epoxy networks. II. Hydrothermal aging

The thermal aging of an amine-cured epoxy in the glassy state is studied for two network states by using DSC and attenuated total reflection-infrared (IR-ATR). The “low-crosslinked” network possesses a relatively high molecular mobility and a considerable amount of residual reactive groups. In the low crosslinked matrix, the presence of high crosslinked regions is revealed. In contrast, the “highly crosslinked” epoxy system has a reduced molecular mobility and only small reactive groups. The high crosslinked matrix contains low crosslinked regions. Thermal loading for both networks is performed below their glass transition. During thermal aging, an ongoing curing reaction takes place in the low-crosslinked epoxy. Thermooxidative degradation and the disintegration of short-range ordering are observed as well. The highly crosslinked epoxy system undergoes a phase separation of relatively mobile segments in the low mobile matrix, which is a reversible process on heating. Thermooxidative degradation is also detected for this kind of network. In summary, for the “low” and the “highly” crosslinked epoxy, significant chemical and structural changes take place during thermal aging even though the networks are vitrified. It is convincing that these changes in the cured epoxy should exert an influence on the mechanical properties of a bonded structure. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 91: 361–368, 2004
The thing-in-itself. A reaction to current use of the term in archaeology

Abstract Scholars writing within symmetrical archaeology, or speculative realism, have lately claimed that archaeology should strive to grasp the thing-in-itself. This paper questions the rationale of this claim. It presents the philosophical definition of the concept of a thing-in-itself and a short presentation of its reception. The author argues that the concept of the thing-in-itself has nothing to offer archaeology, and questions why contemporary theoretical archaeologists show such an interest in this term.
Comparative structural studies of 4-diazopyrazole derivatives by X-ray diffraction and theoretical investigation

The X-Ray crystal and molecular structures of the 4-pyrazol derivatives 3-methyl-4-diazo-5-benzamido-1H-pyrazole (4) and 3-benzamido-5-methyl-1H-pyrazole (3) have been determined. A dimeric structure has been found for the first and polymeric for the second. A comparison of 4 with 1,3-dimethyl-4-diazo-5-benzamido-lH-pyrazole (2) shows differences in the geometrical parameters of the pyrazole ring due to electron delocalization in 2 consequent to the nitrogen negative charge in the latter. Theoretical investigation at the density functional theory (DFT) level shows difference in the molecular electronic distribution of 2 and 4, in agreement with the structural parameters and the IR stretching frequencies of the respective carbonyl moieties.
HAZOP Text Named Entity Recognition using CNN-BilSTM-CRF Model

Hazard and Operability Study (HAZOP) is a Hazard analysis method based on system engineering, which analyzes the potential risks that may exist in the process of technological operation through a certain joint, and provides guidance for subsequent control and management. However, for a long time, the form of HAZOP analysis results is difficult to unify. In order to solving this problem, information needs to be extracted to establish a database, and Named Entity Recognition (NER) is a key step in this process. In this paper, a CNN-Bilstm-CRF neural network model is proposed for entity recognition of HAZOP text. A novel activation function is used in the convolutional neural network (CNN) for parameter optimization, and different weight initialization methods are selected to optimize the results. The corpus used in this paper is the HAZOP analysis report of the oil synthesis equipment of the self-marked coal seam indirect liquefaction project. Verified on the Tensorflow, the experimental results show that this method has a good recognition effect on HAZOP text entities, and the F1 value reaches 91.11%.
A Machine Learning Approach Using Effective Connectivity to Predict Response to Clozapine Treatment

Clozapine is an anti-psychotic drug that is known to be effective in the treatment of patients with chronic treatment-resistant schizophrenia (TRS-SCZ), commonly estimated to be around one third of all cases. However, clinicians sometimes delay the initiation of this drug because of its adverse side-effects. Therefore, identification of predictive biological markers of clozapine response are extremely valuable to aid on-time initiation of treatment. In this study, we develop a machine learning (ML) algorithm based on pre-treatment electroencephalogram (EEG) data sets to predict response to clozapine treatment in 57 TRS-SCZs, where the treatment outcome, after at least one-year follow-up is determined using the positive and negative syndrome scale (PANSS). The ML algorithm has three steps: 1) a brain source localization (BSL) procedure using the linearly constrained minimum variance (LCMV) beamforming approach is employed on the EEG signals to extract source waveforms from 30 specified brain regions. 2) An effective connectivity measure named symbolic transfer entropy (STE) is applied to the source waveforms. 3) A ML algorithm is applied to the STE matrix to determine whether a set of features can be found to discriminate most-responder (MR) SCZ patients from least-responder (LR) ones. The findings of this study reveal that STE features can achieve an accuracy of 95.83%. This finding implies that analysis of pre-treatment EEG could contribute to our ability to distinguish MR from LR SCZs, and that the source STE matrix may prove to be a promising tool for the prediction of the clinical response to clozapine.
Modeling, Analysis and Control of Networked Discrete Event Systems: A Comprehensive Survey

Discrete event systems (DES) are of highly logics and complexity, since their activities are precisely characterized by asynchronous event occurrences constrained by supervisors that issue control decisions. In practice, we face networked environments with rapid evolution of computation and communication technologies, which leads to the proliferation of networked discrete event systems (NDES) where plant(s) and supervisor(s) are communicated via wired or wireless networks. Although the network connection introduces more uncertainties than conventional DES, NDES have been extensively investigated in the past few years for their conveniences and flexibilities such that various achievements are obtained. Therefore, in this paper, we review existing works on NDES from perspectives of system modeling, property analysis and supervisory control.
A Radio Frequency Analog Computer for Computational Electromagnetics

Software-programmable analog computing is proposed for power- and area-efficient acceleration of computational electromagnetics. All-pass filters are employed to realize a continuous-time finite-difference time-domain (FDTD) algorithm. A CMOS realization of an analog computer (AC) that solves the 1-D wave equation using this time-continuous FDTD algorithm at an equivalent temporal update rate of 625 MHz is reported (180-nm CMOS, chip area of 4 mm<sup>2</sup>, supply voltage = 1.8 V, and power = 200 mW). The AC operates at up to 30 MHz over 18 discrete spatial points. Analog arithmetic operations (multiply and add) are realized in parallel using op-amps with gain–bandwidth product > 500 MHz. Computational grid boundaries can be configured to simulate multiple propagation scenarios. The AC is calibrated using a stochastic optimization algorithm. The normalized mean squared error of the AC varies between −10 and −20 dB within the computational grid. The power- and area-normalized performance of the design improves on earlier integrated ACs by up to three orders of magnitude. The chip is also 26<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> faster than a C-based software FDTD solver running on an Intel Xeon CPU and <inline-formula> <tex-math notation="LaTeX">$420\times $ </tex-math></inline-formula> faster than CUDA FDTD code running on an NVIDIA GeForce GTX 1080 Ti GPU, albeit at lower accuracy (~6 bits). Finally, the AC is <inline-formula> <tex-math notation="LaTeX">$2.8\times $ </tex-math></inline-formula> faster than a digital systolic array FDTD processor realized using a Xilinx RFSoC ZCU1275 and has 15<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> better power efficiency (computations/W).
Detection and Validation of Cloud Top Height From Scanning Ka-Band Radar Measurements Using Digital Image Processing Technique

A method is proposed, which uses the digital image processing technique to identify cloud boundaries from scanning Ka-band (∼35.29 GHz) radar imagery dataset. In this method, a cloud is considered as an uninterrupted region of radar echoes with radar reflectivity higher than −34 dBZ and area greater than 3 km2. The proposed algorithm involves 1) conversion of radar RGB image to grayscale by removing white background and noise, 2) identification of cloud boundaries by canny edge detection, and 3) estimation of cloud cross-section area (CCSA) and cloud top height (CTH) based on the pixel width. This method is effectively applied to Ka-band radar images collected over Mandhardev, a high altitude scanning station in the Western Ghats (WGs), India to derive CTH and CCSA. CTH distribution shows three peaks, one at about 2 km with others at about 7–8 km, and 12 km. The cloud occurrence shows an apparent diurnal variation with a maximum in the afternoon hours while a semidiurnal variation is observed in CCSA. The proposed method shows consistent statistics with Global Precipitation Measurement Ka-band radar observations and thus suitable to build robust cloud climatology over the WGs. Such cloud statistics are essential to validate the representation of clouds in weather and climate models.
Assessing the Importance of Diffusion‐Controlled Effects on Polymerization Rate and Molecular Weight Development in Nitroxide‐Mediated Radical Polymerization of Styrene

A previously derived kinetic model for the nitroxide‐mediated radical polymerization (NMRP) of styrene has been modified by considering diffusion‐controlled (DC) effects on the bimolecular radical termination, monomer propagation, dormant polymer activation, and polymer radical deactivation reactions. Free‐volume theory was used to incorporate the DC‐effects into the model. It was found that DC‐termination enhances the living behavior of the system, whereas DC‐propagation, DC‐activation and DC‐deactivation worsen it. Although the inclusion of overall DC‐effects into the kinetic model improved the performance of the model by slightly reducing the deviations obtained from experimental data of polymerization rate and molecular weight in the bimolecular NMRP of styrene with 2,2,6,6‐tetramethyl‐1‐piperidinyloxy (TEMPO) and dibenzoyl peroxide (BPO), it does not seem to justify adding the extra four free‐volume parameters. In the case of the semi‐batch addition of azo‐bis‐iso‐butyronitrile (AIBN) (several single shots at definite time intervals) in the NMRP of styrene, recently reported in the literature, it was found that DC effects are more significant, but it was observed that there was a strong dependence of polymerization rate on the frequency of addition of the shots of initiator (a maximum on polymerization rate being observed at a given frequency of addition of the shots), which could not be adequately explained in terms of DC‐effects.
Mach Number Prediction and Analysis of Multi-Mode Wind Tunnel System

The Mach number is one of the most important variables in the wind tunnel system, which needs to be controlled precisely. Although there are mechanical principals to present the relationship between the Mach number and other process variables, it is hard to obtain the Mach number online directly, especially when the wind tunnel system operations in multiple modes. Therefore, in this paper, a Mach number prediction algorithm based on PLS is proposed for the multi-mode wind tunnel system, as well as the analysis strategy. First, on the premise of considering the control accuracy of the Mach number as well as the process characteristics, certain modes are identified and modelled for the Mach number prediction. Second, to reflect the real-time changes of the Mach number, time-slice-based PLS regression method is adopted. And then to further enhance the prediction accuracy, the analysis of process variables influence variance is carried out, and the variables with stable regression parameter are selected in the predictive model to reconduct the prediction. The method has been adopted to the real wind tunnel system, and the outcome demonstrates the effectiveness of the method.
Effects of Bicarbonate Content of Irrigation Water on Nutritional Disorders of Some Apple Varieties

ABSTRACT Effects of varying concentrations of bicarbonate in the irrigation water on seedlings of ‘Red Delicious,’ ‘Golden Delicious,’ and ‘Golab-e-Kohanz’ apple cultivars, grown in a greenhouse, were studied. To conduct this experiment, ammonium bicarbonate was used in order to obtain bicarbonate concentrations at 5, 10, 15, and 30 meq/L, and sulfuric acid was used to obtain a 0 level of bicarbonate in water. The electrical conductivity (EC) of the leachate water was nearly the same for 0, 5, and 10 meq/L bicarbonate, but doubled with the increase from 10 to 30 meq/L. Also, the bicarbonate concentration in the leachate increased with increasing levels of irrigation water bicarbonate, even though it was much lower in the leachates. Different bicarbonate levels in the irrigation water significantly reduced chlorophyll development. The difference was significant only between 30 mg/L and other levels after 40 d, but after 120 d (except for 0 and 5 meq/L) treatments at all other levels showed reduced chlorophyll intensities. There were also significant differences in chlorophyll intensities between different apple varieties before and up to 40 d of bicarbonate treatment, with ‘Golden Delicious’ having the most chlorophyll among the three varieties. The different intensities, however, were not significant after 80 and 120 d of bicarbonate treatments. After 120 d, the 0, 5, 10, 15, and 30 meq/L of bicarbonate had reduced the chlorophyll intensities by 4%, 6.5%, 18.2%, 35.6%, and 59.4%, respectively. Increasing levels of bicarbonate increased the leaf concentrations of nitrogen (N), potassium (K), and phosphorus (P), but lowered the concentrations of iron (Fe), magnesium (Mg), and manganese (Mn) and did not affect calcium (Ca), copper (Cu), or zinc (Zn) levels. Considering the equilibrium level of 3.5–4 mmole bicarbonate per liter of soil solution in calcareous soils brought about by CO2 pressures and calcium carbonate (CaCO3) minerals in the solid phase, it would not seem necessary to neutralize the irrigation water bicarbonates for concentrations below 5 meq/L. Instead, improvements in root development by improved soil aeration and prevention of excessive irrigation is probably beneficial. However, when the concentration of bicarbonate exceeds 5 meq/L in irrigation water, it is probably necessary to neutralize the bicarbonates for long-term irrigation purposes. *This article was extracted from a P.D. thesis in soil, Tarbiat Modarres University, Tehran, Iran.
Bone Age Assessment based on SuperPoint Features

Convolutional neural network-based bone age assessment (BAA) algorithms have been researched in recent years. However, current state-of-the-art algorithms always have unacceptably large amount of parameters, so their performance will degrade when training on small scaled X-ray photographs datasets. In this paper, we aim to propose a light convolutional neural network to assess bone ages automatically. The proposed network consists of two components. The first module uses a pre-trained SuperPoint network to extract robust feature maps. The second module reduces the dimension of the feature maps and generate the final prediction by improving a classification network. Besides, a weighted loss function based on term-frequency index theory is designed to avoid over-fitting caused by uneven distribution of the training set. The parameters to be trained in our architecture is much fewer than state-of-the-art BAA networks. Experimental results on open-source X-ray dataset demonstrated that the proposed network can be trained on existing small scaled BAA datasets and achieves a comparable performance with those large scaled models for bone age assesment.
Low-cost MIMO-RoF-PON architecture for next-generation integrated wired and wireless access networks

Next-generation integrated fiber-wireless access networks will require low-cost and high-capacity deployment to meet customer demand. A new configuration of radio over fiber–passive optical network (RoF-PON) architecture, including two 60 GHz multiple-input multiple-output (MIMO) based on a 5G universal filtered multicarrier waveform and wired signal utilizing orthogonal frequency division multiplexing (OFDM), is described. At the optical line terminal, MIMO signals are integrated as upper and lower sidebands of the wired OFDM signal. This integration approach, employing single-sideband frequency translation, reduces the complexity of the transceiver design and provides high spectral efficiency because the two MIMO-RoF and wired signals transmit at the same frequency. Improved techniques are also employed to upconvert and downconvert the 60 GHz millimeter wave (MMW), being remote optical heterodyning and self-heterodyning, respectively. The MIMO-RoF signals are therefore transmitted at low frequency over the standard single-mode fiber to avoid the impairments induced at higher frequencies, and the remote optical local oscillator is reused to downconvert the two 60 GHz MMWs, producing a cost-effective system. Simulation results demonstrate very satisfactory network performance when using a downstream link over a 20 km span standard PON.
Unsupervised learning for monocular depth and motion with real scale

In Computer Vision, the method of using a single image to learn depth information through the CNNs has gradually improved, especially for the unsupervised learning methods which trains without the ground-truth are based on the image process and vision. However, the depth map generated from these methods are relative depth values instead of absolute depths, therefore these methods can’t be well applied to practical applications.In this paper, we use the monocular video sequence as input, and get partial true depth value by using a prior conditions, so as to constrain the depth and the relative pose of the entire sequence with the "real" scale. Here we solve the previous scale ambiguous problem by fusing the geometry information, which correct the scale of the entire sequence by our rescaled module. This paper only uses monocular sequences to accomplish these tasks.Moreover, our method is specifically effective in the field of automated guided vehicles with only a camera as the requirement which reducing the dependence on other devices but improved the quality.
Tolerance and detection for the edge disconnection in consensus problems of multi-agent systems with the time-delay*

In this paper, tolerance and detection problems for the edge disconnection in consensus issues of discrete-time multi-agent systems with the time-delay are investigated. We first discuss the tolerance of the edge disconnection in consensus problems. For the case with the strongly connected communication topology, the faulty system can still achieve consensus if the connectedness of the multi-agent system is not changed as the edge disconnection, but the consensus value of the faulty system might be different from the original one. Especially, the consensus value of the system with the edge disconnection will be consistent with the original one if the communication topology of the faulty system is undirected and connected. In addition, the detection problem of the edge disconnection in multi-agent systems is considered by transforming the detection problem into the discernibility problem between the faulty system and the original system. By the state augmentation method and observability properties of the system, some equivalent conditions for the discernibility of the edge disconnection are established.
KINETIKA ADSORPSI ION EMAS(III) OLEH HIBRIDA MERKAPTO SILIKA

A bstrak: Telah dilakukan kajian kinetika adsorpsi ion emas(III) oleh adsorben hibrida merkapto silika (HMS). HMS disintesis melalui proses sol-gel dengan prekursor natrium silikat (Na 2 SiO 3 ) dari abu sekam padi. HMS dibuat dengan menambahkan asam klorida pada campuran senyawa 3-(trimetoksilil)-1-propantiol (TMSP) dan larutan Na 2 SiO 3 . Kinetika adsorpsi ditentukan dengan melakukan adsorpsi sistem statik ( batch ) dengan variasi waktu. Jumlah ion emas yang teradsorpsi dihitung secara kuantitatif berdasarkan selisih konsentrasi logam sebelum dan setelah adsorpsi yang dianalisis dengan spektroskopi serapan atom (SSA). Data menunjukkan interaksi HMS dengan ion emas cenderung mengikuti pola kinetika reaksi pseudo orde-2 dengan nilai konstanta laju reaksi (k) = 1x10 -2 g mg -1 min -1 . Berdasarkan nilai perubahan energi bebas Gibbs adsorpsi standar (-ΔG°= 34,63-37,99 kJ/mol) menunjukkan bahwa adsorpsi berlangsung secara kimia (kemisorpsi). Kata kunci : kinetika, emas, merkapto, silika, abu sekam padi, pseudo orde-2. Abstract: Adsorption kinetics study has been done of gold(III) ions by mercapto silica hybrid (MSH) adsorben. MSH was synthesized by sol-gel process with sodium silicate (Na 2 SiO 3 ) from rice husk ash as a precursor. MSH made by adding hydrochloric acid to 3-(trimetoksilil)-1-propantiol (TMSP) compounds and Na 2 SiO 3 solution. Adsorption kinetics are determined by adsorption static system (batch) with variation of time. The amount of the adsorbed gold ions is quantified by the difference in metal concentration before and after adsorption analyzed by atomic absorption spectroscopy (AAS). The data showed, MSH interaction with gold ion tends to follow the pattern of reaction kinetics pseudo-second-order with rate constant (k) =1x10 -2 g mg -1 min -1 . Based on the value of the standard Gibbs free energy for adsorption (-ΔG°= 34,63-37,99 kJ/mol) showed that the adsorption takes place chemically (chemisorption). Keywords: kinetics, gold, mercapto, silica, rice husk ash, pseudo-second-order.
THE LONG-TERM IMPACT OF SOCIAL MOVEMENTS AND REPRESSION ON DEMOCRATIC ATTITUDES

Abstract Democracy movements in authoritarian regimes usually fail and are repressed, but they may still affect attitudes and norms of participants and bystanders. We exploit several features of a student movement to test for enduring effects of social movements on democratic attitudes. College students were the core of the movement and had wide exposure to the ideas and activities of the movement, as well as the suppression of the movement. College-bound high school students had limited exposure to the movement and its activities. Time of college entry could in theory be manipulated and endogenous, so we also use birthdate as an exogenous instrument for enrollment year. Applying a fuzzy regression discontinuity, we test for the impact of exposure to the movement on long-term attitudes. We find significant attitudinal differences between those in college during the movement, and those who started college post-movement. These results are strongest for alumni of the four universities that were most connected to the movement.