Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis of Unexpected Dimethyl 2-(4-Chlorophenyl)-2,3-dihydropyrrolo[2,1-a]isoquinoline-1,3-dicarboxylate via Hydrolysis/Cycloaddition/Elimination Cascades: Single Crystal X-ray and Chemical Structure Insights

Hydrolysis/[3 + 2] cycloaddition/elimination cascades employed for the synthesis of unexpected tricyclic compound derived from isoquinoline. Reaction of ethylene derivative 1 with the isoquinoline ester iminium ion 2 in alkaline medium (MeOH/NEt3) under reflux for 1 h resulted in the formation of the fused pyrrolo[2,1-a]isoquinoline derivative 3. Its structure was elucidated by X-ray single crystal and other spectrophotometric tools. Hirshfeld calculations for 3 and its crystal structure analysis revealed the importance of the short O…H (19.1%) contacts and the relatively long H…C (17.1%), Cl…H (10.6%) and C…C (6.1%) interactions in the molecular packing. DFT calculations were used to compute the electronic and spectroscopic properties of the studied system. The studied compound has polar nature (3.5953 Debye). TD-DFT calculations assigned the shortest wavelength band (220 nm) to the HOMO−1→LUMO+2 (57%), HOMO−1→LUMO+4 (14%) mixed excitations. The calculated NMR chemical shifts correlated very well with the experimental data (R2 = 0.93–0.94).
Waveform relaxation synthesis of time-domain characteristic model of loaded microstrip from FDTD simulation

From the finite-difference time-domain (FDTD) simulation of response voltages and currents of a microstrip terminated by a step-pulse excitation voltage source and a resistor load, the time-domain characteristic model (TDCM) of the microstrip is synthesized by use of the waveform relaxation method, which is based on the iteration and deconvolution techniques. As an example, the extracted model is applied to simulate the responses of the microstrip loaded by a capacitor and a resistor in parallel. The results are compared with the direct FDTD simulation to validate the accuracy of the model.
The role of fuel prices in spatial price transmission between horticultural markets: empirical analysis from a developing country

This article aims to analyze how fuel prices impact spatial price transmission between two Chilean horticultural wholesale markets. We implement a regime-dependent VECM where price transmission parameters depend on dynamics imposed by a stationary exogenous variable (fuel price). We identified two price transmission regimes characterized by different equilibrium relationships and short-run adjustment processes. This implies that fuel prices affect price transmission elasticities and intermarket adjustment speeds. Our results show increasing marketing costs as farm to market distance grows. This impact depends on each product’s attributes. Highlights This article analyzes the effect of fuel prices on the price transmission mechanism between the most relevant Chilean horticultural wholesale markets. A regime-dependent Vector Error Correction Model where price transmission parameters depend on fuel price was implemented. Clear evidence of the role played by fuel prices for in horizontal price transmission between the wholesale markets considered in this study was found. This situation supports the idea that regardless of quantities traded in regional markets, the major effect of price adjustment is a result of the high demand, distances and market concentration of a central market. This impact depends on each product’s attributes.
Rheological Behaviour of Cementitious Materials Incorporating Solid–Solid Phase Change Materials

Nowadays, thermal regulation of the indoor environment is mandatory to reduce greenhouse gas emissions. The incorporation of Phase Change Materials (PCMs) and especially solid–solid PCMs (s/s PCMs) into building materials can be a major step forward in reducing energy consumption. Such materials are used for their high latent heat to save and release heat during phase change. To integrate these products in the fabrication of cementitious materials, it is essential to predict their influence on the rheological behaviour of construction materials. In this work, rheological measurements were carried out on composite suspensions made of cement or mortar plus s/s PCMs. Results showed that the fitting of the Herschel–Bulkley model with a constant value of flow exponent was reliable. The s/s PCMs influenced the consistency and the yield strength values, with the yield strength value being only slightly affected. The adaptation of an existing viscosity model is proposed to predict the consistency value of suspensions. Finally, an innovative approach to predict the flow behaviour is proposed and we highlight the research needs to mainstream the use of s/s PCMs in construction materials.
Agriculture Production Planning Using a Hybrid Simulation and Genetic Algorithm Approach

One of the oldest and most powerful optimizing methods is mathematical programming which used as a powerful tool in decision making. In spite of widespread use of these models, these models are not flawless. Simplifying hypothesizes in approaches like Minimization of Total Absolute Deviation (MOTAD) and Expected Value Variance (EV) reduce the reliability of proposed programs. The hybrid of Genetic Algorithm (GA) and Monte Carlo Simulation (MCS) improve decisions by recognizing the best accidental processes of production planning. The goal of this research is to determine the optimal cropping pattern of agricultural production in Mashhad plain. Data were gathered from Agricultural Jihad Organization of Khorasan Razavi province of Iran including time series of main seven crops in Mashhad plain from 1982 to 2007. Simulating the program was done by using The Decision Tools Suite ver 4.5. 2 and improving accidental processes were attained by MATLAB. The linear and quadratic risky programming model were also attained and solved by using WINQSB software. Finally, the results of hybrid model were compared with the result of quadratic risky and linear programming model. Given the stochastic processes without any presumption, the results are more reliable and more realistic. Therefore, having the required information such as the time series of variables, this hybrid model can efficiently suggest the best planning production.
Research of Gas/Solid Two-Phase Flow Capacitance Cross-Correlation Measurement System

The paper takes gas/solid two-phase flow cross-correlation measurement system as the research object, adopts the method of computer simulation to research the measuring mechanism of cross-correlation velocity. By using Monte-Carlo method, the gas/solid two-phase flow model is established; and it is used to study the multiple factors affecting the system measurement performance such as sensor geometry, the distance of two sensors along the pipeline axis, the particle size and velocity, solidification flow pattern, non-solidification flow pattern, etc.
An interactive Landscape for Creativity and Innovation

We describe the i-LAND environment which constitutes an example of our vision of the workspaces of the future, in this case supporting cooperative work of dynamic teams with changing needs. i-LAND requires and provides new forms of human-computer interaction and new forms of computer-supported cooperative work. Its design is based on an integration of information and architectural spaces, implications of new work practices and an empirical requirements study informing our design. i-LAND consists of several ‘roomware’ components, i.e. computer-augmented objects integrating room elements with information technology. We present the current realization of i-LAND in terms of an interactive electronic wall, an interactive table, two computer-enhanced chairs, and two “bridges” for the Passage-mechanism. This is complemented by the description of the creativity support application and the technological infrastructure. The paper is accompanied by a video figure in the CHI’99 video program.
Progress of plated metallization for industrial bifacial TOPCon silicon solar cells

Industrial tunnel oxide and passivated contact (i‐TOPCon) solar cells were metallized at Fraunhofer ISE using ultrashort pulse laser ablation of the passivation layers for the subsequent Ni/Cu/Ag plating process. The solar cells feature a tunnel SiOx and n‐type doped polysilicon layer covered by a SiNx at the rear side, whereas the front side is made of a boron emitter passivated with a AlOx/SiNx stack. The reference i‐TOPCon solar cells screen‐printed at the supplier reach an efficiency of 23.46% measured by Fraunhofer ISE CalLab. The impact of the laser process on the implied open circuit voltage (iVoc) is characterized showing minor impact on the TOPCon side, while the emitter side reveals an increased iVoc loss due to laser damage. Loss analysis by simulating the plated solar cells points out the benefit of reducing the laser contact opening (LCO) area in terms of shading and contact recombination. Optimization of laser ablation and hydrofluoric acid (HF) pretreatment process result in Voc > 700 mV and FF > 82% leading to a mean efficiency 23.6% measured in‐house and a champion efficiency of 23.84% measured at Fraunhofer ISE CalLab thus outperforming the references by 0.4%abs.
Project ASPIRE

The U.S. Marine Corps’ OSCAR program teaches resilience skills to warfighters. This paper describes the design and development process of Project ASPIRE, a light-weight, Flash-based game that serves as a practice environment for the skills learned in OSCAR. Rapid, iterative development/usability cycles were used to identify the ways in which the game could be improved. The results of these usability evaluations are discussed, and general recommendations for the design of training games are provided.
Double Deep Recurrent Reinforcement Learning for Centralized Dynamic Multichannel Access

We consider the problem of dynamic multichannel access for transmission maximization in multiuser wireless communication networks. The objective is to find a multiuser strategy that maximizes global channel utilization with a low collision in a centralized manner without any prior knowledge. Obtaining an optimal solution for centralized dynamic multichannel access is an extremely difficult problem due to the large-state and large-action space. To tackle this problem, we develop a centralized dynamic multichannel access framework based on double deep recurrent Q-network. The centralized node first maps current state directly to channel assignment actions, which can overcome prohibitive computation compared with reinforcement learning. Then, the centralized node can be easy to select multiple channels by maximizing the sum of value functions based on a trained neural network. Finally, the proposed method avoids collisions between secondary users through centralized allocation policy.
A low profile wideband pattern reconfigurable metasurface antenna

A low profile electrically controlled pattern reconfigurable antenna with wide bandwidth is proposed in this article. The antenna is designed on two closely stacked substrates with a very low profile of 0. 04λ0. On the top layer of the design is a periodic metasurface and two parasitic strips, and on the bottom layer is a metallic ground etched with rectangle slot. The feed line is designed on the middle layer to excite the metasurface patch antenna. Eight pin diodes are mounted between the parasitic metallic strips and the adjacent metallic metasurface patch cells for pattern reconfiguration. Two DC biasing voltages are employed to control the pin diodes. By changing the DC voltages, antenna can work at three different modes, and the main beam could be steered among 0°, +25°, and −25° directions. The prototype of the antenna is fabricated and the performance of the prototype is measured. The measured S parameters and radiation pattern show good agreement with the simulated results. The measured overlapped impedance matching bandwidth of the proposed antenna at all working modes is 18.3%. The proposed antenna has the advantages of low profile, high gain, wideband and adjustable main beam.
q
 -Rung Orthopair Fuzzy Matroids with Application to Human Trafficking

The theory of q -rung orthopair fuzzy sets ( q -ROFSs) is emerging for the provision of more comprehensive and useful information in comparison to their counterparts like intuitionistic and Pythagorean fuzzy sets, especially when responding to the models of vague data with membership and non-membership grades of elements. In this study, a significant generalized model q -ROFS is used to introduce the concept of q -rung orthopair fuzzy vector spaces ( q -ROFVSs) and illustrated by an example. We further elaborate the q -rung orthopair fuzzy linearly independent vectors. The study also involves the results regarding q -rung orthopair fuzzy basis and dimensions of q -ROFVSs. The main focus of this study is to define the concepts of q -rung orthopair fuzzy matroids ( q -ROFMs) and apply them to explore the characteristics of their basis, dimensions, and rank function. Ultimately, to show the significance of our proposed work, we combine these ideas and offer an application. We provide an algorithm to solve the numerical problems related to human flow between particular regions to ensure the increased government response action against frequently used path (heavy path) for the countries involved via directed q -rung orthopair fuzzy graph ( q -ROFG). At last, a comparative study of the proposed work with the existing theory of Pythagorean fuzzy matroids is also presented.
Genome-wide identification and expression profiling of duplicated flavonoid 3'-hydroxylase gene family in Carthamus tinctorius L.

Flavonoid 3′-hydroxylase (F3’H) enzyme is essential in determining the flavonoids B-ring hydroxylation pattern. It is mainly implicated in the biosynthetic pathway of cyaniding-based anthocyanins, flavonols, and flavan-3-ols. However, the evolution and regulatory mechanism of these important flavonoid hydroxylases have not been systematically investigated in safflower (Carthamus tinctorius L.). In this study, we identified 22 duplicatedCtF3'H-encoding genes from safflower through genome-wide prediction and conservation analysis. Phylogenetic analysis revealed the pattern of conservation and divergence of CtF3'Hs encoding proteins and their homologs from different plant species. The distribution of conserved protein motifs and cis-regulatory units suggested several structural components that could be crucial in deciphering the final function of CtF3'H proteins. Furthermore, the results of RNA-seq and qRT-PCR assay in different flowering tissues suggested differential expression level of CtF3’H genes during flower development. Based on the unique homology of CtF3’H5 with flavonoid 3’ hydroxylases from other plant species, further validation of CtF3’H5 was carried out. The transient expression of CtF3’H5 in onion epidermal cells implied that the subcellular localization of the fusion construct containing CtF3’H5 and GFP was predominantly detected in the plasma membrane. Similarly, the prokaryotic expression and western blot hybridization of CtF3’H5 demonstrated the detection of a stable 50.3kD target protein. However, more efforts are needed to further extend the functional validation of CtF3’H5 in safflower. This study provides a fundamental gateway for future functional studies and understanding the genetic evolution of F3'Hs in plants.
AdaptBit-HD: Adaptive Model Bitwidth for Hyperdimensional Computing

Brain-inspired Hyperdimensional (HD) computing is a novel computing paradigm emulating the neuron’s activity in high-dimensional space. The first step in HD computing is to map each data point into high-dimensional space (e.g., 10,000). This poses several problems. For instance, the size of the data can explode and all subsequent operations need to be performed in parallel in D = 10,000 dimensions. Prior work alleviated this issue with model quantization. The HVs could then be stored in less space than the original data and lower bitwidth operations can be used to save energy. However, prior work quantized all samples to the same bitwidth. We propose, AdaptBit-HD, an Adaptive Model Bitwidth Architecture for accelerating HD Computing. AdaptBit-HD operates on the bits of the quantized model one bit at a time to save energy when fewer bits can be used to find the correct class. With AdaptBit-HD, we can achieve both high accuracy by utilizing all the bits when necessary and high energy efficiency by terminating execution at lower bits when our design is confident in the output. We additionally design an endto-end FPGA accelerator for AdaptBit-HD. Compared to 16-bit models, AdaptBit-HD is 14× more energy efficient and compared to binary models, AdaptBit-HD is 1.1% more accurate, which is comparable in accuracy to 16-bit models. This demonstrates that AdaptBit-HD is able to achieve the accuracy of full precision models, with the energy efficiency of binary models.
A heater plate assisted integrated bake/chill system for photoresist processing

A thermal processing module, which consists of a dense distribution of multivariate controlled heat/chill elements, is developed to achieve temperature uniformity of a silicon wafer throughout the processing temperature cycle of ramp, hold and quench in microlithography. In the proposed unit, the bake and chill steps are conducted sequentially within the same module without any substrate movement. The unit includes two heating sources. The first is a mica heater which serves as the dominant means for heat transfer. The second is a set of thermoelectric devices (TEDs) which are used to provide a distributed amount of heat to the substrate for uniformity and transient temperature control. The TEDs also provide active cooling for chilling the substrate to a temperature suitable for subsequent processing steps. The feasibility of a practical system is demonstrated via detailed modeling and simulations based on first principle heat transfer analysis.
Biomarker-based deep learning for personalized nutrition

In the digital era, disease diagnosis and patient management is taking a decisive leap forward to dynamically link personalized medical decision making, disease recognition and management with the massive individuality and uniqueness of the human body. Individual needs are recognised and associated with unique individual demands and tastes via automated processes and the pre-processing power of complex and accurate recom-mender systems. The gigantic pool of biometrics and biomarkers are used to predict outcomes and identify patterns in patients in an individualized manner. In this paper, we continue and improve upon recent previous work of ours [1] and develop software systems for personalized nutrition based on biomarkers and deep learning algorithms. Evaluation on real data demonstrates the high performance of our approach.
Can Post-Vaccine ‘Vaxication’ Rejuvenate Global Tourism? Nexus between COVID-19 Branded Destination Safety, Travel Shaming, Incentives and the Rise of Vaxication Travel

Vaxication (i.e., post-vaccination travel) and branding destinations for COVID-19 safety have emerged as the cornerstones to fully rebound global tourism. Numerous destination brands are now stimulating tourism demand through realigned travel incentives specifically for fully vaccinated travelers. However, there is growing fear and incidents of travel shaming across destinations, especially due to the recent outbreaks of the highly contagious COVID-19 ‘delta and omicron’ variants. Addressing this critical research gap, the present study makes pioneering efforts to empirically examine the effects of COVID-19 branded destination safety (CBDS) on vaxication intentions, under the moderating influence of travel shaming and travel incentives. Drawing on study data from 560 fully-vaccinated residents from Hawaii, United States and structural equation modeling (SEM) with Mplus, the evidence suggests that the positive impact of CBDS on vaxication intention can be further strengthened by travel incentives, or weakened when travel shaming picks up more momentum. Besides the validation of newly developed scales, the study offers strategic insights based on dominant theories (e.g., theory of planned behavior and protection motivation theory) to interpret the changing tourism demand, and to transform the emerging challenges into opportunities through and beyond the pandemic.
Racial Differences in Time at Work Not Working

Racial differences in effort at work, if they exist, can potentially explain race-based wage/earnings disparities in the labor market. The authors estimate specifications of time spent on non-work activities at work by Black and White males and females with data from the American Time Use Survey. Estimates reveal that trivially small differences occur between non-Hispanic Black and non-Hispanic White males in time spent not working while on the job that disappear entirely when correcting for non-response errors. The findings imply that Black–White male differences in the fraction of the workday spent not working are either not large enough to partially explain the Black–White wage gap, or simply do not exist at all.
New Transition Method of a Ducted-Fan Unmanned Aerial Vehicle

In this research, a winged version of the ISTAR (from “intelligence, surveillance, target acquisition, and reconnaissance”) unmanned aerial vehicle is modeled first, and then a new transition method is proposed, which enables the vehicle to fly sideways at low speed for drag reduction. A nonlinear trajectory-following logic is adopted to correct altitude loss and horizontal drift during the transition. By simulation, the proposed transition method shows better acceleration performance. The comparison of the induced drag shows that the vehicle should roll to resume fixed-wing lift as soon as its minimum level-flight speed is achieved to optimize its acceleration performance.
Definition of artificially soft and hard surfaces for electromagnetic waves

The widely used transversely corrugated surfaces and other alternative surfaces having the same anisotropic surface impedance deserve a common name. Here it is proposed to call them soft surfaces by analogy with the soft surfaces in acoustics. In the same way artificially hard surfaces are defined. Cylindrical hard waveguides of any cross-sectional shape can support TEM waves.
Recent experiences in the industrial exploitation of principal component based fault detection methods

Summary form only given. There has been a plethora of research and many industrial studies involving the application of multivariate statistical techniques for the detection and isolation of faults on process plants. Despite all this work and reported success of the studies, there remain very few online applications of the technology. To address this issue and to determine the capabilities and limitations of the multivariate statistical techniques, the Control Technology Centre Ltd. has undertaken a comprehensive study aimed specifically at the development of online multivariate solutions for process plants. This paper provides details of several of these investigations. These investigations highlight a number of factors which should be considered when conducting multivariate analysis. For example, there appears to be a need for consideration of cause and effect relationships, which is often ignored in other application studies. In addition the integration of the multivariate statistical routines into a hierarchical system is demonstrated to provide the potential for robust and self-diagnosing control systems.