Miracle-dz/UniFAR-FTUs huggingface dataset:
The Development of near Infrared Reflectance Spectroscopy Calibrations for Undried Grass Silage and Their Transfer to Another Instrument Using Multiple and Single Sample Standardisation

This study was undertaken to explore the possibility of developing accurate, robust near infrared (NIR) spectroscopy calibrations for undried grass silage (a very heterogeneous, high moisture forage) without costly or lengthy pre-treatment of the sample. This was achieved by scanning a large surface area of the sample using a coarse transport cell in conjunction with a Foss NIRSystems 6500 scanning monochromator, which moves the sample vertically past the light source. Equations were produced for alcohol corrected toluene dry matter, pH, N2, neutral detergent fibre, acid detergent fibre, D-value (digestible organic matter in the dry matter) and potential metabolic intake with accuracy comparable to finely comminuted undried grass silage. The second objective of this study was to examine the possibility of transferring the undried grass silage calibrations developed on the 6500 spectrophotometer across NIR instruments and cell types. The cloning technique of Shenk was used to match spectrally the 6500 spectrophotometer and a Foss NIRSystems 5000 NIR spectrophotometer. Seventy undried grass silage samples, typical of the calibration set, were scanned through both instruments using a coarse transport cell and a natural product cell. Cloning was based on (a) 30 samples and (b) one central sample. Standardisation files were produced (using the ISI software) and applied to the spectra of the remaining 40 validation samples, scanned on the 5000 spectrophotometer (regarded as the slave instrument). These standardised spectra were predicted by the master equations developed on the 6500 instrument and the results compared to the corresponding master validation spectra (n = 40) scanned in the coarse transport cell and predicted by the master equations (regarded as the reference values). An alternative approach of standardising the master calibration set spectra, to look like they were scanned in a natural product cell and rerunning the calibrations, was also performed and the master natural product spectra predicted using the new natural product equations and compared to the reference values. In all instances, this cloning technique proved very successful, clearly indicating that undried grass silage calibrations can be transferred across these NIR instruments with little loss in accuracy of prediction.
The OpenModelica Integrated Environment for Modeling, Simulation, and Model-Based Development

OpenModelica is a unique large-scale integrated open-source Modelicaand FMI-based modeling, simulation, optimization, model-based analysis and development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; ModelicaUML integration; requirement verification; and generation of parallel code for multi-core architectures. The environment is based on the equation-based object-oriented Modelica language and currently uses the MetaModelica extended version of Modelica for its model compiler implementation. This overview paper gives an up-to-date description of the capabilities of the system, short overviews of used open source symbolic and numeric algorithms with pointers to published literature, tool integration aspects, some lessons learned, and the main vision behind its development.
Influence of Isosorbide on Glass‐Transition Temperature and Crystallinity of Poly(butylene terephthalate)

Copolyesters of isosorbide and 1,4‐butane diol were prepared by Ti(OBu)4‐catalyzed transesterifications with dimethyl terephthalate in bulk at temperatures up to 250°C. The content of isosorbide was considerably lower than expected from the feed ratio and the molar masses were low, so that no DSC measurements were conducted. Copolycondensations of isosorbide and 1,4‐butane diol with terephthaloyl chloride were either performed in dichloromethane at 40°C or in toluene at 100°C. The second method gave the higher molar masses. However, both series of polycondensations had the content of isosorbide roughly paralleled the feed ratios in common. The DSC measurements revealed that even 6 mol% of isosorbide is sufficient to raise the glass‐transition temperature (Tg) by 10–12°C (up to 55°C). With 50 mol% of isosorbide, the Tg reaches 100°C. Yet, incorporation of isosorbide also reduces the melting temperature Tm and the degree of crystallinity, and a mol percentage above 30% prevents crystallization completely. In summary, incorporation of isosorbide allows for fine‐tuning of Tg and Tm of poly(butylene terephthalate) over a wide range.
Pengaruh Penerapan Pendidikan Matematika Realistik terhadap Hasil Belajar Matematika dengan Kovariabel Kemampuan Numerik

Penelitian ini bertujuan untuk mengetahui pengaruh penerapan pendidikan matematika realistic terhadap hasil belajar matematika dengan kovariabel kemampuan numerik pada siswa kelas V Gugus I Kubu. Rancangan penelitian ini menggunakan pola dasar The Posttest Only Control Group dengan kovariabel kemampuan numerik. Sampel penelitian berjumlah 59 siswa. Data dikumpulkan dengan tes dan kuesioner. Data dianalisis dengan anava, anakova dan analisis regresi. Hasil Penelitian menunjukkan bahwa: (1) ada perbedaan hasil belajar matematika antara siswa yang mengikuti pelajaran dengan penerapan pendidikan matematika realistik dan pembelajaran konvensional (F=4,585, p <0,05), (2) setelah kovariabel kemampuan numerik dikendalikan, terdapat perbedaan hasil belajar matematika siswa yang mengikuti penerapan pendidikan matematika realistik dan pembelajaran konvensional (F=46,239, p <0,05), dan (3) terdapat kontribusi yang signifikan antara kemampuan numerik dengan hasil belajar matematika siswa sebesar 10,6%.
How Attribute-Based Design Perceptions and Consumer-Brand Relationship Affected on Brand Equity?

Consumers act differently in choosing brands. Some like certain brands but some do not. A major reason is the design of products made by brands and the quality of experience. In general, companies can differentiate their products from competitors by focusing on physical features such as taste, design, and non-physical features such as price, brand, and country of origin. this research investigates design perception including (five design perceptual dimensions, namely visual, functional, kinesthetic, interface and information) and its effects on brand equity and experience. User expertise was considered as a mediating variable. Partial least squares path modeling (PLS) was used to test the research model. Samples were randomly collected from GLX smartphone phone consumers, and 367 samples included in this research. The reliability and validity of the questionnaire were evaluated using Cronbach's alpha coefficient, combined reliability, divergent validity and confirmatory analysis. The results showed an acceptable reliability and validity. Pearson correlation coefficient and PLS software were used to analyze the data. The outcomes showed that design perception positively and significantly affects the experimental value and brand equity and experimental value positively affect brand equity. Finally, moderating user expertise's vivacious and significant role in the relationship between design perception and the experimental value confirmed.
A 6.9-μm2 3.26-ns 31.25-fj Robust Level Shifter With Wide Voltage and Frequency Ranges

This brief presents an area- and energy-efficient level shifter (LS) with wide voltage and frequency ranges. The proposed LS removes the static current with a cut-off head PMOS. The LS also provides a robust internal node compared to other state-of-the-art LSs, where the internal node is floated. To reduce the delay and energy consumption in the proposed LS, the contention between the pull-up and pull-down networks at the internal node is reduced by using a ‘low’ to ‘high’ transition error correction circuit (LtH ECC), which also enables high frequency operation at near- and sub-threshold voltages. The proposed LS is implemented in 65 nm CMOS technology, having the smallest area of <inline-formula> <tex-math notation="LaTeX">$6.90~\mu \mathrm {m}^{2}$ </tex-math></inline-formula>among state-of-art LSs. The measurement results demonstrate that the minimum low-level supply voltage (<inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm{ DDL,MIN}}$ </tex-math></inline-formula>) values are 120 mV and 300 mV with input frequency (<inline-formula> <tex-math notation="LaTeX">${f} _{\mathrm{ IN}}$ </tex-math></inline-formula>) of 1 MHz and 100 MHz, respectively, at a high-level supply voltage of 1.2 V. The delay and energy consumption at V<sub>DDL</sub> of 120 mV and 300 mV are 207 ns and 1040 fJ, and 3.26 ns and 31.25 fJ, respectively. The static power consumption is less than 3 nW at V<sub>DDL</sub> ranging from 120 mV to 700 mV.
Robustification of Continuous-Time ADMM against Communication Delays under Non-Strict Convexity: A Passivity-Based Approach

: In this paper, we address a class of distributed optimization problems with non-strictly convex cost functions in the presence of communication delays between an agent and a coordinator. To this end, we focus on a continuous-time optimization algorithm that mirrors the alternating direction method of multipliers. We ﬁrst redesign the algorithm so that the dynamics ensures smoothness and a sub-block for primal optimization includes stable zeros. It is then revealed that the algorithm is composed of feedback interconnection of passive systems. We next robustify the algorithm against communication delays by applying the so-called scattering transformation. The smoothness of the dynamics allows one to use the invariance principle for delay systems, and accordingly, the state trajectories are shown to converge to an optimal solution even without the strict convexity assumption. Finally, the presented method is demonstrated via simulation of an environmental-monitoring problem.
CT Super Resolution via Zero Shot Learning

Computed Tomography (CT) is an advanced imaging technology used in many important applications. Here we present a deep-learning (DL) based CT super-resolution (SR) method that can reconstruct low-resolution (LR) sinograms into high resolution (HR) CT images. The method synergistically combines a SR model in sinogram domain, a deblur model in image domain, and the iterative framework into a CT SR algorithm super resolution and deblur based iterative reconstruction (SADIR). We incorporated the CT domain knowledge into the SADIR and unrolled it into a DL network (SADIR Net). The SADIR Net is a zero shot learning (ZSL) network, which can be trained and tested with a single sinogram in the test time. The SADIR was evaluated via SR CT imaging of a Catphan700 physical phantom and a biological ham, and its performance was compared to the other state of the art (SotA) DL-based methods. The results show that the zero-shot SADIR-Net can indeed provide a performance comparable to the other SotA methods for CT SR reconstruction, especially in situations where training data is limited. The SADIR method can find use in improving CT resolution beyond hardware limits or lowering requirement on CT hardware.
DECOR-GAN: 3D Shape Detailization by Conditional Refinement

We introduce a deep generative network for 3D shape detailization, akin to stylization with the style being geometric details. We address the challenge of creating large varieties of high-resolution and detailed 3D geometry from a small set of exemplars by treating the problem as that of geometric detail transfer. Given a low-resolution coarse voxel shape, our network refines it, via voxel upsampling, into a higher-resolution shape enriched with geometric details. The output shape preserves the overall structure (or content) of the input, while its detail generation is conditioned on an input "style code" corresponding to a detailed exemplar. Our 3D detailization via conditional refinement is realized by a generative adversarial network, coined DECOR-GAN. The network utilizes a 3D CNN generator for upsampling coarse voxels and a 3D PatchGAN discriminator to enforce local patches of the generated model to be similar to those in the training detailed shapes. During testing, a style code is fed into the generator to condition the refinement. We demonstrate that our method can refine a coarse shape into a variety of detailed shapes with different styles. The generated results are evaluated in terms of content preservation, plausibility, and diversity. Comprehensive ablation studies are conducted to validate our network designs. Code is available at https://github.com/czq142857/DECOR-GAN.
Family Business and Financial Performance: What are the Effects of Tax Cut Policy on Them in Uzbekistan?

This study is the first comprehensive empirical study to examine the relationship between the family business and the firm’s performance in Uzbekistan. In this research, we investigate the relationship between family firms and financial performance using enough extensive unbalanced panel data from 2012 through 2015 on 3148 non-banking/non-government firms. Moreover, we analyze the impact of tax cut policy on SMEs, including family firms from a case study of Uzbekistan by using the difference-in-difference estimator. These two will be a major contribution to the family business study field in Uzbekistan.
Assessment of the quality of administrative data for use in a population census; applying census test results in Indonesia

BPS-Statistics Indonesia plans to carry out its seventh population census in 2020. In contrast to the traditional method in previous censuses, it will use administrative data obtained from the Ministry of Home Affairs combined with field enumeration. Individual information recorded in the administrative data will be used as the initial data source for the field enumeration as well as to ensure adequate coverage. These changes could be a step towards a register-based census in the future. Given the important role of register data in the upcoming Indonesian census, it is necessary to assess the quality of the administrative data which have been recorded by the Ministry of Home Affairs. Therefore, this study aimed to analyze whether there are significant differences on selected individual variables between the data from the administrative source and the census test results. The census test was conducted in three selected villages using multi-mode data collection. The comparison of the selected individual variables and the statistical test results indicate that this administrative data is of sufficient quality to be used as the data source for a combined method census in Indonesia.
FT-Raman, FT-IR and normal-mode analysis of carcinogenic polycyclic aromatic hydrocarbons. Part II—a theoretical study of the transition states of oxygenation of benzo(a)pyrene (BaP)

The first process in polycyclic aromatic hydrocarbons (PAH) metabolism is believed to be the oxygenation that leads to several structural isomeric epoxides. Most of these intermediates will be converted into non-toxic hydrophilic metabolites and be excreted. Because of this, metabolism has been considered to be primarily a detoxification mechanism. However, some may be activated to become ultimate carcinogens. Knowledge of the identities of these intermediates and their probabilities of formation will be of vital importance in mechanism elucidation and cancer prevention. Theoretically, epoxidation of benzo(a)pyrene (BaP) can take place at any one of the sites: 1,2-, 2,3-, 4,5-, 7,8-, 8,9-, 9,10- and 11,12-, leading to seven possible isomeric epoxides. The conformations of these isomers formed from direct oxygenation were simulated and their activation energies calculated. Among them, the 4,5-epoxide appears to be the most and the 8,9-complex the least energetically favorable. The 11,12-, 9,10- and 7,8-isomers are almost equally energetic. The rate of formation of the 7,8-isomer, which is believed to be the precursory carcinogen, relative to the 4,5-epoxide is estimated to be 9.1 × 10−4 : 1. On the other hand, the relative rates of 1,2- and 2,3-complexes are extremely low. When the protoporphyrin group is used for simulation, the BaP plane is seen parallel to the porphyrin plane in the 1,2- and 2,3-complexes, but angled away to various degrees in all other epoxides. The parallel orientation results in a significant lowering of the activation energy, making 1,2- and 2,3-complexes the most favorable intermediates. This is in agreement with chromatographic analyses of BaP metabolism in liver microsomes. In these experiments, 3-hydroxy-BaP is the major product. Copyright © 2001 John Wiley & Sons, Ltd.
Straightforward Synthesis of Poly(dimethylsiloxane) Phases with Immobilized (1R)‐3‐(Perfluoroalkanoyl)camphorate Metal Complexes and Their Application in Enantioselective Complexation Gas Chromatography

A straightforward synthesis of novel chiral polysiloxane-based metal stationary phases immobilized through a propylenoxy linker (Chirasil-Metal-OC3) to the polymeric backbone is presented. Synthesis was accomplished in six steps with high overall yields starting from commercially available, enantiopure (+)-(1S)-camphorsulfonic acid. Two different approaches towards Chirasil-Metal phases featuring either a propylenoxy or propylenthio linker used for immobilization through hydrosilylation are presented. Furthermore, a new protocol for the fluoroacylation, which is one of the key steps in the synthesis of (1R)-3-(perfluoroalkanoyl)camphorate metal complexes, was developed to improve the isolation and overall yield. The immobilization of (1R,4S)-10-(allyloxy)-3-(heptafluorobutanoyl)camphor – 10-(allyloxy)-hfbc – onto polysiloxanes as well as the incorporation of nickel(II), oxovanadium(IV), europium(III), and lanthanum(III) was characterized by FT ATR IR and NMR spectroscopy. Overall, seven different Chirasil-Metal-OC3 polymers with different separation properties were prepared by metal incorporation and variation of the amount of immobilized (1R,4S)-10-(allyloxy)-3-(heptafluorobutanoyl)camphor (10-allyloxy-hfbc: 3.5, 10.2, and 20.0 %). Their performance in enantioselective complexation gas chromatography was systematically studied and excellent enantioselectivity was found for Chirasil-Nickel-OC3. Separation of 29 small-sized compounds, encompassing, among others, epoxides, substituted alkenes and alkynes as well as alcohols and amides, was achieved with high separation factors α. The synthetic strategy, enantiomer separations and thermal stability (up to 160 °C) demonstrates the versatility of the newly derived Chirasil-Metal-OC3 phases.
Using Meta-Knowledge Mined from Identifiers to Improve Intent Recognition in Neuro-Symbolic Algorithms

In this paper we explore the use of meta-knowledge embedded in intent identifiers to improve intent recognition in conversational systems. As evidenced by the analysis of thousands of real-world chatbots and in interviews with professional chatbot curators, developers and domain experts tend to organize the set of chatbot intents by identifying them using proto-taxonomies, i.e., meta-knowledge connecting high-level, symbolic concepts shared across different intents. By using neuro-symbolic algorithms able to incorporate such proto-taxonomies to expand intent representation, we show that such mined meta-knowledge can improve accuracy in intent recognition. In a dataset with intents and example utterances from hundreds of professional chatbots, we saw improvements of more than 10% in the equal error rate (EER) in almost a third of the chatbots when we apply those algorithms in comparison to a baseline of the same algorithms without the meta-knowledge. The meta-knowledge proved to be even more relevant in detecting out-of-scope utterances, decreasing the false acceptance rate (FAR) in more than 20\% in about half of the chatbots. The experiments demonstrate that such symbolic meta-knowledge structures can be effectively mined and used by neuro-symbolic algorithms, apparently by incorporating into the learning process higher-level structures of the problem being solved. Based on these results, we also discuss how the use of mined meta-knowledge can be an answer for the challenge of knowledge acquisition in neuro-symbolic algorithms.
Lightweight Grid Computing for Small Group Use Cases

Grid computing provides important data analysis infrastructure for many physics experiments. Small groups may only have several hosts that may exist in diﬀerent private isolated networks. The existing solutions are complex or heavy to run for small groups. Our project focuses on small-scale grid computing, using several oﬃcial Debian packages, to construct the whole system. The system is designed to be lightweight and scalable.
Systematics-insensitive Periodogram for Finding Periods in TESS Observations of Long-period Rotators

NASA's TESS mission \citep{tess} has produced high precision photometry of millions of stars to the community. The majority of TESS observations have a duration of $\approx$27 days, corresponding to a single observation during a TESS sector. A small subset of TESS targets are observed for multiple sectors, with approximately 1-2\% of targets falling in the Continuous Viewing Zone (CVZ) during the prime mission \citep{yield}, where targets are observed continuously for a year. These targets are highly valuable for extracting long period rotation rates, which can be linked to stellar ages. We present a pip installable Python tool for extracting long period rotation rates in the TESS CVZ, while simultaneously mitigating instrument systematics.
AN ELECTRICALLY SMALL DUAL-BAND ANTENNA COVERED WITH SRS AND SRR

A dual-band antenna operating in dual bands is presented. The antenna is composed of two substrate layers covered with three printed patch layers. The top layer is an electrically small ring; the middle consists of four spiral resonators (SRs); and the bottom is a split-ring resonator (SRR). Inductive couplings between layers change the radiation Q factor of the original ring antenna and promote resonating modes in UHF and S bands. Besides, the input matching property is also improved. The measured return loss agrees well with the calculated results, and the radiation patterns are also presented. From experiments it is found that the proposed antenna is electrically small at operation dual-bands.
A Synergistic Kalman- and Deep Postfiltering Approach to Acoustic Echo Cancellation

We introduce a synergistic approach to double-talk robust acoustic echo cancellation combining adaptive Kalman filtering with a deep neural network-based postfilter. The proposed algorithm overcomes the well-known limitations of Kalman filter-based adaptation control in scenarios characterized by abrupt echo path changes. As the key innovation, we suggest to exploit the different statistical properties of the interfering signal components for robustly estimating the adaptation step size. This is achieved by leveraging the postfilter near-end estimate and the estimation error of the Kalman filter. The proposed scheme allows for rapid reconvergence of the adaptive filter after abrupt echo path changes without compromising the steady-state performance achieved by state-of-the-art approaches in static scenarios.