Miracle-dz/UniFAR-FTUs huggingface dataset:
The synthesis of HgS nanoparticles in polystyrene matrix

A composite of nanodimensional HgS and polystyrene has been prepared by reacting a solution of the copolymer formed from mercury acrylamide and styrene in chloroform solution with H2S. The product shows different colours depending on the amount of H2S used. The composite material has been characterised by UV, PL, TEM, and XRD techniques. The TEM images show particle sizes of less than 12 nm. The band gaps calculated from the optical spectra are higher than that for bulk material as expected for quantum confined materials.
Position Location for Futuristic Cellular Communications: 5G and Beyond

With vast mmWave spectrum and narrow beam antenna technology, precise position location is now possible in 5G and future mobile communication systems. In this article, we describe how centimeter-level localization accuracy can be achieved, particularly through the use of map-based techniques. We show how data fusion of parallel information streams, machine learning, and cooperative localization techniques further improve positioning accuracy.
Synthesis, spectral, 3D molecular modeling and antibacterial studies of dibutyltin (IV) Schiff base complexes derived from substituted isatin and amino acids

New dibutyltin(IV) complexes of Schiff base derived from 5-chloroindoline-2,3-dione, indoline- 2,3-dione with amino acids (tryptophan, alanine and valine) were synthesized and characterized by elemental analysis, IR, electronic spectra, conductance measurements, and biological activity. The analytical data showed that the Schiff base ligand acts as bidentate towards metal ions via the azomethine nitrogen and carboxylate oxygen by a stoichiometric reaction of M:L (1:2) to form metal complexes. NMR (1H, 13C and 119Sn) spectral data of the ligands and metal complex agree with proposed structures. The conductivity values between 14 - 27 ohm-1cm2mol-1 in DMF imply the presence of non-electrolyte species. 3D molecular modeling and analysis of bond lengths and bond angles have also been conducted for a representative compound, [Bu2Sn(L2)2], to substantiate the proposed structures. Antibacterial results indicate that the metal complexes are more active than the free ligands.
Global Semantic Land Use/Land Cover Based on High Resolution Satellite Imagery Using Ensemble Networks

This paper describes an architecture for and the results of global Land Use/Land Cover semantic segmentation. It is based on Vricon 3D Surface Models and high resolution, better than 0.5m resolution, multispectral satellite images. Vri-con uses deep learning to automatically classify the content of the 3D Surface Models. Ortho-rectified 2D-images combined with a rasterized DSM are used as the input. To create a state-of-the-art semantic segmentation with 0.5 meters per pixel, Vricon uses a network ensemble containing multiple Fully Convolutional Networks (FCNs), each with different inputs, outputs, or training data. This ensemble of FCNs produces results with a global scale and excellent accuracy. The use of an ensemble architecture enables usage of different annotated data, preventing overfitting to certain geographic areas.
Characterization of the three lowest-lying singlet electronic states of AlOH

Two linear (1Σ+ and 1Π) and three bent (1 1A′, 2 1A′, and 1 1A″) lowest-lying electronic singlet states of AlOH have been systematically investigated employing ab initio self-consistent-field, configuration interaction with single and double excitations, coupled cluster with single and double excitations (CCSD), CCSD with perturbative triple excitations [CCSD(T)], and CCSD with iterative partial triple excitations (CCSDT-3 and CC3) quantum mechanical methods with basis sets up to augmented correlation consistent polarized valence quadruple zeta (aug-cc-pVQZ). The linear 1Σ+ state is found to be a remarkably low-energy transition state between the two equivalent bent 1 1A′ structures, while the linear 1Π state is a second-order saddle point, which leads to the bent 2 1A′ and 1 1A″ states. The bent ground (X 1A′) state of AlOH is predicted to have a bond angle of 157° at the aug-cc-pVQZ CC3 level of theory and is classified as a quasilinear molecule, confirming previous studies. Employing the equation-of-m.
A Word Embedding-Based Method for Unsupervised Adaptation of Cooking Recipes

Studying food recipes is indispensable to understand the science of cooking. An essential problem in food computing is the adaptation of recipes to user needs and preferences. The main difficulty when adapting recipes is in determining ingredients relations, which are compound and hard to interpret. Word embedding models can catch the semantics of food items in a recipe, helping to understand how ingredients are combined and substituted. In this work, we propose an unsupervised method for adapting ingredient recipes to user preferences. To learn food representations and relations, we create and apply a specific-domain word embedding model. In contrast to previous works, we not only use the list of ingredients to train the model but also the cooking instructions. We enrich the ingredient data by mapping them to a nutrition database to guide the adaptation and find ingredient substitutes. We performed three different kinds of recipe adaptation based on nutrition preferences, adapting to similar ingredients, and vegetarian and vegan diet restrictions. With a 95% of confidence, our method can obtain quality adapted recipes without a previous knowledge extraction on the recipe adaptation domain. Our results confirm the potential of using a specific-domain semantic model to tackle the recipe adaptation task.
On the Complexity Requirements of a Panel-Based Large Intelligent Surface

A Large Intelligent Surface (LIS) is a recently proposed concept, especially suitable for high speed indoor communications and industrial internet of things (IoT) applications. Basing the LIS on smaller panels has clear advantages in terms of flexibility and mass production of its elements. In this paper we consider a panel-based LIS and we study the interplay of the panel size, the number of baseband outputs per square meter of deployed surface, the total activated surface area, the number of baseband outputs per panel, the terminal density and the ensuing minimum terminal rate. Our performance results show that it is desirable to employ smaller panels when the terminal density increases, but this means more outputs per m2, and higher overall LIS implementation complexity. It was observed that we can surpass such increase by working with higher fractions of the LIS area. Furthermore, we present an empirical equation stating the number of outputs per panel needed to ensure that all terminals are reasonably served. These results are useful for the LIS design in practical scenarios.
Tungstate Sulfuric Acid: A Novel and Efficient Solid Acidic Reagent for the Oxidation of Thiols to Disulfides and the Oxidative Demasking of 1,3-Dithianes

Tungstate sulfuric acid in combination with various oxidants was found to be an efficient reagent for the conversion of thiols to disulfides at r.t. in good to excellent yields. The selective oxidative deprotection of 1,3-dithianes to their parent carbonyl compounds at r.t. was also observed with this reagent.
Comparison Study of RF Beamforming Schemes in Hybrid Precoding for Cell-Free MmWave Massive MIMO UDN System

Cell-free Massive MIMO (multiple-input multiple output), where all the access nodes (ANs) cooperate to coherently serve all the user equipments (UEs) and to overcome the inter-cell interference limitation in ultra-dense network environments, has attracted significant attention from both academia and industry as a promising technology for 5G and future wireless communication. In this paper, we investigate the impacts of RF beamforming schemes to be combined with zero-forcing baseband precoding on cell-free mmWave massive MIMO UDN systems.
A one‐dimensional model of dissolved organic carbon cycling in the water column incorporating combined biological‐photochemical decomposition

A one‐dimensional model incorporating separate labile, semilabile, and refractory fractions of dissolved organic carbon (DOC) is used to study the vertical distribution of dissolved organics in the ocean and the downward flux of organic carbon into the water column. The modeled vertical gradient of DOC is generated almost entirely by the semilabile fraction, which has predicted lifetimes of 0.4 years at the ocean surface increasing to 6.3 years at 1000 m, owing to diminishing bacterial numbers. Although predicted fluxes of DOC and sinking particles exiting the upper mixed layer are similar, labile and semilabile DOC are mostly degraded by bacteria before being mixed below 250 m. The simple one‐dimensional scheme employed by the modeling may, however, underestimate downward transport of DOC by physical mechanisms because it does not capture three‐dimensional processes such as subduction. The inclusion of a biologically inert refractory pool is a first step to try and incorporate the growing awareness that photochemical processes play an important role in the dynamics of organic carbon in the ocean. However, the predicted rate of change of refractory material in response to altered climatic forcing (e.g., ultraviolet radiation at the ocean surface) is so slow that it may not be necessary to include it dynamically in ocean models used to examine climatic change within the next 200 years.
Magnetic Field Measurements of First Pre-series Full-Length 4.2 m Quadrupole MQXFA03 Using PCB Rotating Coils for the Hi-Lumi LHC Project

The U.S. Hi-Lumi LHC Accelerator Upgrade Project (AUP) and CERN have joined efforts to develop high field quadrupoles for the Hi-Lumi LHC upgrade. The US national laboratories in the AUP project will deliver 10 magnets and each cryostat has two 4.2 m high gradient quadrupoles in it. These magnets are made of Nb3Sn conductors, with large aperture (150 mm) and integrated gradient of 556.9 T. This paper reports on magnetic measurements performed during the vertical test at Brookhaven National Laboratory (BNL) in 2019-2020. A warm measurement Z-Scan (+/−15 A) with 42 Z-positions before cool-down was performed at BNL. The results were directly compared to field data measured at LBNL during magnet assembly. Measured harmonics and magnetic center offsets (ΔX and ΔY) have provided timely and informative diagnostics on the magnet structure's shape at both warm and cold temperatures. A new centering fixture was designed and added to better center the warm bore tube which contains the rotating coil probe. After the quench training to 16.47 kA was achieved, a complete set of cold measurements (Z-Scan at 16.47 kA and I-Scan from 960 A to 16.47 kA and back to 960 A) was made. Periodic axial variation of allowed and nonallowed harmonics was observed which is related to the coil radial and/or mid-plane variations along the magnet axis. Overall, the average harmonics in the straight section are within the required field boundaries.
Microhardness and structural analysis of (Ti,Al)N, (Ti,Cr)N, (Ti,Zr)N and (Ti,V)N films

Ti-based binary nitride and ternary nitride films were deposited on cemented carbide by the arc ion plating method and investigated on microhardness, lattice parameter and morphology. Micro-Vickers hardness of TiN, CrN, and ZrN binary films was 2000, 1400, and 1500 HV, respectively. On the other hand, ternary nitrides such as (Ti,Al)N, (TiCr)N, (Ti,Zr)N, and (Ti,V)N with identical atomic ratio against Ti generally had higher hardness of 3100, 3000, 3000, and 2400 HV, respectively. The lattice parameters of both (Ti,Al)N and (Ti,Cr)N were smaller with 4.18 and 4.19 A. Futhermore, the surface roughness of TiN, CrN, ZrN, (TiAl)N, and (TiZr)N films was all smooth with small number of droplets, while that of (Ti,Cr)N and (Ti,V)N films became rough with large number of droplets.
A Review of Metasurfaces for Microwave Energy Transmission and Harvesting in Wireless Powered Networks

Wireless energy transmission and harvesting techniques have recently emerged as attractive solutions to realize wireless powered networks. By eliminating fundamental power constraints arising from the use of conventionally battery sources, wireless modes of energy transmission provide viable means to power wireless network devices away from the grid. Metasurfaces have emerged as key enablers for the use of microwave energy as a power source. Their unique abilities to tailor electromagnetic waves have motivated significant research interest into their use for power-focused microwave systems. This article provides an overview of progress in the development of metasurface implementations for microwave energy transmitters and energy harvesters. First, the paper provides a basic introduction to metasurfaces, after which it reviews research progress in metasurfaces for microwave energy transmission and harvesting. Also highlighted are key parameters by which the performance of such metasurface designs are characterized. In addition, an overview of studies on metasurfaces as reconfigurable intelligent surfaces in wireless networks supporting the simultaneous transmission of information and energy is presented. Finally, the paper highlights existing challenges, and explores future directions, including opportunities to control radio environments through ambiently energized reconfigurable intelligent surfaces in next-generation wireless networks.
IRS-Aided Wireless Communication with Imperfect CSI: Is Amplitude Control Helpful or Not?

Intelligent reflecting surface (IRS) is a promising new paradigm to achieve high spectral and energy efficiency for future wireless networks by reconfiguring the wireless signal propagation via passive reflection. To reap the potential gains of IRS, channel state information (CSI) is essential, whereas channel estimation errors are inevitable in practice due to limited channel training resources. In this paper, in order to optimize the performance of IRS-aided communications with imperfect CSI, we propose to jointly design the active transmit precoding at the access point (AP) and passive reflection coefficients of IRS, each consisting of not only the conventional phase shift and also the newly exploited amplitude variation. First, the user's achievable rate is derived assuming a practical IRS channel estimation method, which shows that the interference due to CSI errors is intricately related to the AP transmit precoder, the channel training power and the IRS reflection coefficients during both channel training and data transmission. Next, by combining the benefits of the penalty method, Dinkelbach method and block successive upper-bound minimization (BSUM) method, a new penalized Dinkelbach-BSUM algorithm is proposed to optimize the IRS reflection coefficients for maximizing the achievable data transmission rate subjected to CSI errors. Finally, simulation results are presented to validate the effectiveness of our proposed algorithm as compared to benchmark schemes. In particular, useful insights are drawn to characterize the effect of IRS reflection amplitude control (with/without the conventional phase-shift control) on the system performance under imperfect CSI.
On the Theory of the Concentration Dependence of the Self‐Diffusion Coefficient of Micelles

A theory is given for the ratio of initial slope to intercept in a plot of 1/D versus concentration of colloid particles; D is the self‐diffusion coefficient of the charged colloid particles (micelles). The theory starts from the Einstein relation, and the autocorrelation function expression for the friction constant. The main approximation is the use of Brownian motion theory to describe the effect of the solvent on micelle motion. There is good agreement with experiment in salt solutions, but the agreement is poor when there is no added salt. It is concluded that the theory is probably appropriate for solutions of high ionic strength, but the possibility that the data in salt‐free solution have not been interpreted properly, i.e., that the theory has a wider validity, is also discussed.
UV photodissociation dynamics of allyl radical by photofragment translational spectroscopy

Photodissociation of the allyl radical, CH2CHCH2, has been studied using the method of molecular beam photofragment translational spectroscopy following excitation to the C(2 2B1) and A(1 2B1) states by 248 and 351 nm photons. Two different primary channels have been detected following 248 nm excitation: H-atom loss (84%) and CH3 elimination (16%). From the product translational energy distribution and polarization dependence studies, dissociation processes from the ground-state C3H5 potential energy surface are inferred for both wavelengths. At 248 nm there may also be a contribution to the H-atom loss channel from predissociation by a higher electronically excited state. Rice–Ramsperger–Kassel–Marcus (RRKM) calculations show that the formation of cyclopropene is not important, while formation of allene and methylacetylene from dissociation of 1- and 2-propenyl radicals are important reaction pathways at both wavelengths. Translational energy distributions peaking well away from zero provide evidence fo.
Investigation on Statistical Behavior of Radiation Pattern in Analog Beamforming System

In millimeter-wave wireless communications systems, analog beamforming technology is being used to overcome technical drawbacks such as limited service coverage, high atmospheric loss, and insufficient signal-to-noise ratios. However, the errors caused by circuit implementation, quantized control, and imperfect isolation between antenna elements result in radiation pattern distortion and performance deterioration. In this work, we derived the statistical behavior of radiation pattern distortion due to random error, quantization noise, and mutual coupling. The analysis revealed that the radiation pattern distortion follows the Beckmann distribution.
Satellite-Derived Bathymetry Using Deep Convolutional Neural Network

Our goal is to develop technique for assessing bathymetry maps, which show the topography of the floors of water-bodies, using satellite or aerial imagery. The advent of deep neural networks has enabled the use of new techniques in analysing and creating depth maps from high resolution satellite images. In this paper we report a pilot study in exploring the potential use of a deep learning architecture by framing bathymetry problem as a pixel-wise classification task. We took the Sentinel-2 bands as the satellite image and independent depth measurements from Humminbird™data. The data for the supervised training was carefully prepared and processed to facilitate the use of a powerful deep learning segmentation models. The efficiency of the model was quantified by the average F1-score (Dice score) on the held out dataset on quantized depth bands.
Multi-band sub-GHz technology recognition on NVIDIA’s Jetson Nano

Low power wide area networks support the success of long range Internet of things applications such as agriculture, security, smart cities and homes. This enormous popularity, however, breeds new challenging problems as the wireless spectrum gets saturated which increases the probability of collisions and performance degradation. To this end, smart spectrum decisions are needed and will be supported by wireless technology recognition to allow the networks to dynamically adapt to the ever changing environment where fair co-existence with other wireless technologies becomes essential. In contrast to existing research that assesses technology recognition using machine learning on powerful graphics processing units, this work aims to propose a deep learning solution using convolutional neural networks, cheap software defined radios and efficient embedded platforms such as NVIDIA’s Jetson Nano. More specifically, this paper presents low complexity near-real time multi-band sub-GHz technology recognition and supports a wide variety of technologies using multiple settings. Results show accuracies around 99%, which are comparable with state of the art solutions, while the classification time on a NVIDIA Jetson Nano remains small and offers real-time execution. These results will enable smart spectrum management without the need of expensive and high power consuming hardware.
Monolithic 3D-Based SRAM/MRAM Hybrid Memory for an Energy-Efficient Unified L2 TLB-Cache Architecture

Monolithic 3D (M3D) integration has been emerged as a promising technology for fine-grained 3D stacking. As the M3D integration offers extremely small dimension of via in a nanometer-scale, it is beneficial for small microarchitectural blocks such as caches, register files, translation look-aside buffers (TLBs), etc. However, since the M3D integration requires low-temperature process for stacked layers, it causes lower performance for stacked transistors compared to the conventional 2D process. In contrast, non-volatile memory (NVM) such as magnetic RAM (MRAM) is originally fabricated at a low temperature, which enables the M3D integration without performance degradation. In this paper, we propose an energy-efficient unified L2 TLB-cache architecture exploiting M3D-based SRAM/MRAM hybrid memory. Since the M3D-based SRAM/MRAM hybrid memory consumes much smaller energy than the conventional 2D SRAM-only memory and 2D SRAM/MRAM hybrid memory, while providing comparable performance, our proposed architecture improves energy efficiency significantly. Especially, as our proposed architecture changes the memory partitioning of the unified L2 TLB-cache depending on the L2 cache miss rate, it maximizes the energy efficiency for parallel workloads suffering extremely high L2 cache miss rate. According to our analysis using PARSEC benchmark applications, our proposed architecture reduces the energy consumption of L2 TLB + L2 cache by up to 97.7% (53.6% on average), compared to the baseline with the 2D SRAM-only memory, with negligible impact on performance. Furthermore, our proposed technique reduces the memory access energy consumption by up to 32.8% (10.9% on average), by reducing memory accesses due to TLB misses.
Nutrient and pH stratification with conventional and no‐till management

Abstract This study investigated changes in soil test results associated with sampling depths in fields managed with conventional tillage, no‐till for less than 3 years, no‐till for 3 to 6 years, and no‐till for more than 6 years. Soil samples from depths of 0–5, 0–10, 0–20, and 10–20 cm were collected from 59 fields with different tillage histories from several geologic regions, and analyzed by the North Carolina Department of Agriculture soil test laboratory. Some nutrient stratification was noted in all tillage categories. Soil test phosphorus (P), potassium (K), and zinc (Zn) concentrations were significantly higher in the 0–10 cm depth than in the 10–20 cm depth. Stratification probably results from the prevalence of tillage with disks, chisel plows or subsoilers, which do not mix the soil thoroughly. With the adoption of no‐till methods, stratification becomes even more pronounced. Our data suggest that stratification in pH, calcium (Ca), manganese (Mn), and sulfur (S) is more likely for fields in t.
Automatic Mapping of Tropical Cyclone-Induced Coastal Inundation in SAR Imagery Based on Clustering of Deep Features

Researchers have already verified that the deep learning (DL) technology can realize accurate and robust mapping of tropical cyclone-induced coastal inundation in synthetic aperture radar imagery. In order to liberate the DL-based inundation mapping from human supervision, we propose to use the clustering of deep convolutional autoencoder-generated features. The mapping results of Lekima 2019-induced inundation demonstrate the advantages and availability of the proposed method.