Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulated reflectance above snow constrained by airborne measurements of solar radiation: implications for the snow grain morphology in the Arctic

Abstract. Accurate knowledge of the reflectance from snow/ice-covered surfaces is of fundamental importance for the retrieval of snow parameters and atmospheric constituents from space-based and airborne observations. In this paper, we simulate the reflectance in a snow–atmosphere system, using the phenomenological radiative transfer model SCIATRAN, and compare the results with that of airborne measurements. To minimize the differences between measurements and simulation, we determine and employ the key atmospheric and surface parameters, such as snow grain morphologies (or habits). First, we report on a sensitivity study. This addresses the requirement for adequate a priori knowledge about snow models and ancillary information about the atmosphere. For this aim, we use the well-validated phenomenological radiative transfer model, SCIATRAN. Second, we present and apply a two-stage snow grain morphology (i.e., size and shape of ice crystals in the snow) retrieval algorithm. We then describe the use of this new retrieval for estimating the most representative snow model, using different types of snow morphologies, for the airborne observation conditions performed by NASA's Cloud Absorption Radiometer (CAR). Third, we present a comprehensive comparison of the simulated reflectance (using retrieved snow grain size and shape and independent atmospheric data) with that from airborne CAR measurements in the visible (0.670 µm ) and near infrared (NIR; 0.870 and 1.6 µm ) wavelength range. The results of this comparison are used to assess the quality and accuracy of the radiative transfer model in the simulation of the reflectance in a coupled snow–atmosphere system. Assuming that the snow layer consists of ice crystals with aggregates of eight column ice habit and having an effective radius of ∼99 µm , we find that, for a surface covered by old snow, the Pearson correlation coefficient, R , between measurements and simulations is 0.98 ( R2∼0.96 ). For freshly fallen snow, assuming that the snow layer consists of the aggregate of five plates ice habit with an effective radius of ∼83 µm and having surface inhomogeneity, the correlation is ∼0.97 ( R2∼0.94 ) in the infrared and 0.88 ( R2∼0.77 ) in the visible wavelengths. The largest differences between simulated and measured values are observed in the glint area (i.e., in the angular regions of specular and near-specular reflection), with relative azimuth angles ± 40 ∘ in the forward-scattering direction. The absolute difference between the modeled results and measurements in off-glint regions, with a viewing zenith angle of less than 50 ∘ , is generally small ∼ ± 0.025 and does not exceed ±0.05 . These results will help to improve the calculation of snow surface reflectance and relevant assumptions in the snow–atmosphere system algorithms (e.g., aerosol optical thickness retrieval algorithms in the polar regions).
Efficiency assessment of ANFIS in surface topology prediction in diamond turning of RSA443 optical aluminum using Small Datasets

This paper presents an assessment of the efficiency of the ANFIS model in surface topology prediction of RSA 443 optical aluminium using small datasets. The experiments are designed and conducted based on the Taguchi L9 orthogonal array. The single point diamond turning procedure has been carried out on Nanoform 250 Precision CNC machine. Cutting speed, feed rate and depth of cut together with acoustic emission signal root mean square, dominant frequency and peak rate are the ANFIS model input parameters. The function that gave the best results was the sigmoidal membership function, hence it is used in this paper. To evaluate model performance, the measured surface roughness results are compared to ANFIS predicted results based on the Mean Absolute Percentage Error (MAPE) and prediction accuracy. The MAPE values show that the ANFIS prediction accuracy of surface topology is 79.42%. This value is within the upper quartile range, indicating the high predicting accuracy of ANFIS even in the absence of enough training data. The model can be reliably utilized in surface roughness prediction using small datasets while its prediction accuracy can however be improved by using larger datasets.
Nanohydroxyapatite-doped polycaprolactone-based nanoscaffolds as a viable drug delivery agent in bone tissue engineering

In bone tissue engineering research, nanohydroxyapatite (n-HAp) has been recently gaining a lot of interest because of its excellent functional properties such as improvement in the formation of neo-tissue. In this study, the composite nanoscaffolds of n-HAp (0.1–0.5%)-doped polycaprolactone (PCL) (10%) were engineered by electrospinning as a drug delivery system and bone tissue growth. The cell proliferation activities of the prepared composite nanoscaffolds were examined in vitro using osteoblast cells like (MG-63) (Passage 10) cell line. The electrospun PCL/n-HAp nanoscaffolds were subjected to the drug delivery studies using a bone infection antibiotic cephalexin drug and the antibacterial study of the composite was carried out using Escherichia coli bacteria. These results revealed that the mechanical strength (13.25 ± 0.3536) increased and the fiber diameter decreased (100 nm) at the optimized n-HAp (0.4%) concentration, the maximum drug (68%) loading capacity of the electrospun nanofiber PCL/n-HAp takes place at 48 h and the maximum drug release was found to be 78% at 48 h. These novel nanohydroxyapatite-doped polycaprolactone (PCL/n-HAp) scaffolds show promising applications as a drug delivery system using cephalexin and this would also be a potential biomaterial for enhancing bone tissue growth.
A Multi-Timescale Bilinear Model for Optimization and Control of HVAC Systems with Consistency

Reducing the energy consumption of the heating, ventilation, and air conditioning (HVAC) systems while ensuring users’ comfort is of both academic and practical significance. However, the-state-of-the-art of the optimization model of the HVAC system is that either the thermal dynamic model is simplified as a linear model, or the optimization model of the HVAC system is single-timescale, which leads to heavy computation burden. To balance the practicality and the overhead of computation, in this paper, a multi-timescale bilinear model of HVAC systems is proposed. To guarantee the consistency of models in different timescales, the fast timescale model is built first with a bilinear form, and then the slow timescale model is induced from the fast one, specifically, with a bilinear-like form. After a simplified replacement made for the bilinear-like part, this problem can be solved by a convexification method. Extensive numerical experiments have been conducted to validate the effectiveness of this model.
A Channel Phase Error Estimation Method for Multichannel TOPS and Multichannel Sliding Spotlight SAR Imaging

In an azimuth multichannel synthetic aperture radar (SAR) system operating in sliding spotlight mode or Terrain Observation by Progressive Scans (TOPS) mode, due to the varying Doppler centroid and the greater processed Doppler bandwidth, the conventional channel phase error estimation algorithms that tailored to stripmap mode will fail and unable to be directly employed. To address these issues, a deramping-based method is proposed in this letter, which extends the conventional methods to sliding spotlight and TOPS cases. By multiplying the signals of each channel with the corresponding deramp phase, the problem of varying Doppler centroid is solved, and its resulting greater Doppler bandwidth is reduced. Therefore, the spectral properties of the signals are the same as those in the stripmap case, and the conventional channel phase error estimation methods can be applied subsequently. Estimation and imaging results of the simulation data and the real data of GaoFen-3 (GF-3) operating in dual-channel sliding spotlight mode demonstrate the effectiveness of the proposed method.
Demonstrating a Flexible Electricity Consumer: Keeping Sight of Sites in a Real-world Experiment

ABSTRACT Real-world experiments have become a common method for testing and developing new technologies to decarbonize the energy system. The significance of the site of such experiments is evident yet elusive. A case in point is the Danish island Bornholm, test site for a smart grid experiment involving more than 800 private households. The object of intervention of this experiment is the so-called flexible electricity consumer; a means for countering radical increases in fluctuating, renewable energy that challenges the stability of the electricity system. A flexible consumer adjusts consumption to production rather than the other way. Accordingly, the experiment seeks to knit together the electricity system infrastructure and its users in new ways. The island provides the boundaries for this experiment, all the while it is endowed with multiple politics by its various participants. To the scientists running the experiment, Bornholm is their living laboratory: it provides a partly controllable electricity system upon which to test their reorganized energy system. To local participants, however, the experiment is above all a demonstration of their commitment to the island and its role in a green transition. Finally, during the experiment, the local energy supplier begins to frame the island’s energy system and its users as assets; a test island for future participatory experiments. Eventually, the site of this real-world experiment makes a flexible consumer possible as object of intervention, yet at the same time, it transforms the scientific results produced and the identity of the island.
Insights from Circular Economy Literature: A Review of Extant Definitions and Unravelling Paths to Future Research

The circular economy (CE) has become one of the prominent topics in both natural science and management literature over the last few decades. CE is a dual-loop regenerative system that focuses on the effective and efficient utilization of resources in the ecosystem, which is beneficial to environmental and economic performance optimization. Dual CE initiatives allow firms to increased resource eco-efficiency, as well as resource effectiveness. CE has profound consequences for economic and operational advantage. This reinforces the need for reflection on the definition that may provide guidelines to assess and advance the depth and diversity of the field. We aim to provide a definitional analysis of the CE and suggest future research streams to advance the existing literature. For this purpose, we employed a systematic literature review to collect related publications in the CE. As a result of this, a total of 91 papers were selected, studied, and analyzed. We proposed a sound definition of a circular economy that includes the main identified elements, organizational planning processes, customers and society, utilization of the ecosystem, and economic resource flows. Moreover, future direction agenda, in CE research, is suggested considering three research streams: (1) circular design as value creation and capture, (2) antecedents of key activities, and (3) consequences of key processes. There is limited empirical research conducted on CE, and much of the existing research focuses on theoretical, conceptual, and normative. A few empirical research studies are mainly cross-sectional in their focus and are confined to developing and emerging economies. We hope this study’s findings will extend the field of CE, in which some of the most influential information regarding CE literature is provided. This study suggests that the development of CE initiatives plays an important role in the growing digital transformation in the value chain. There have been limited research studies in the interface of circular economy and Industry 4.0. Future research studies may investigate the extent to which digital transformation can increase the implementation of CE, and their influence on digital performance management.
Evolutionary Deep Belief Network for Cyber-Attack Detection in Industrial Automation and Control System

Industrial automation and control systems (IACS) are tremendously employing supervisory control and data acquisition (SCADA) network. However, their integration into IACS is vulnerable to various cyber-attacks. In this article, we first present population extremal optimization (PEO)-based deep belief network detection method (PEO-DBN) to detect the cyber-attacks of SCADA-based IACS. In PEO-DBN method, PEO algorithm is employed to determine the DBN's parameters, including number of hidden units and the size of mini-batch and learning rate, as there is no clear knowledge to set these parameters. Then, to enhance the performance of single method for cyber-attacks detection, the ensemble learning scheme is introduced for aggregation of the proposed PEO-DBN method, called EnPEO-DBN. The proposed detection methods are evaluated on gas pipeline system dataset and water storage tank system dataset from SCADA network traffic by comparing with some existing methods. Through performance analysis, simulation results show the superiority of PEO-DBN and EnPEO-DBN.
A user-driven process for INSPIRE-compliant land use database: example from Wallonia, Belgium

ABSTRACT Regional land use monitoring at high spatial, temporal, and thematic resolution is an important expectation of Walloon stakeholders. Over the last decade, increased data-processing capacities and the annual acquisition of remotely sensed data have resulted in the production of a large amount of relevant geodata. The INSPIRE directive and its obligations for 2020 serve as a path for the development of a new user-driven and open-source hierarchical land use classification system mapping scheme, as presented in this paper. The process includes intensive user consultation, the development of an entire automatic processing chain, and efforts to address challenges such as big data handling, the variability of input data properties, and reproducibility. The thematically detailed land use map, with its 69 classes, is already widely used by Walloon stakeholders, and new demands for updating have already emerged. Based on a European classification system that is compulsory for all member states, INSPIRE-compliant land use maps will make it possible to carry out cross-border studies and compare spatial planning strategies between states.
Professional Development for Working with Students with Autism Spectrum Disorders and Teacher Self-Efficacy

The purpose of this pilot study was to determine the effect of teacher professional development for working with students with Autism Spectrum Disorders and teacher (N = 56) self-efficacy in the general education classroom. A pretest/posttest quasi-experimental research design was implemented. Teachers in one randomly assigned school received professional development training on research-based practices in working with students with autism to determine if the training had any effect on their perceived selfefficacy ratings and teachers in the other school were randomly assigned to serve as the control (i.e., no additional professional development training was provided during the research phase). Results showed that the training had a large positive effect on teacher self-efficacy ratings regarding working with students with autism in the inclusion classroom. Findings tentatively show the need and importance for the provision of more professional development training to general education teachers for working with students with autism to improve teacher self-efficacy and to provide the most effective and inclusive educational experience possible.
Photocatalytic Degradation of Dyes by ZnIn2S4 Microspheres under Visible Light Irradiation

ZnIn2S4 microspheres were successfully synthesized by a hydrothermal method. A series of synthesis temperatures from 80 to 200 °C was investigated. The samples were characterized by X-ray diffraction, UV−vis spectroscopy, nitrogen sorption analysis, X-ray photoelectron spectroscopy, transmission electron microscopy, and scanning electron microscopy (SEM). The results indicated that the crystalloid structure and optical property of temperature series products were almost the same. The specific surface area (SBET) of ZnIn2S4 products declined with increasing synthesis temperature. The 80 °C sample had the largest SBET (85.53 m2 g−1). SEM images demonstrated that the morphology of ZnIn2S4 was marigold-like microspheres, and the 80 °C sample had a well-proportioned morphology. Several dyes (methyl orange, congo red, and rhodamine B) were applied in the ZnIn2S4 photocatalytic reactivity investigation. It showed efficient visible light photocatalytic degradation of dyes. A liquid chromatogram−mass spectrometer .
Electrostatically Sprayed Nanostructured Electrodes for Energy Conversion and Storage Devices

The electrostatic spray method is a promising nonvacuum technique for efficient deposition of thin films from solutions or dispersions. The multitude of electrostatic spray process parameters, including surface tension, viscosity, and conductivity of the liquid, applied voltage, nozzle size, and flow rate, make electrostatic spray deposition very versatile for the morphological engineering of nanostructured films. The current state‐of‐the‐art in electrostatic spraying can produce exceptional morphologies. Such tailoring of morphologies is notably useful in electrochemical applications where high electrolyte‐accessible surface area often improves performance. Interesting morphologies of metal oxides and their composites are highlighted, including nanopillars, nanoferns, and porous microspheres produced by electrostatic spraying to enhance energy conversion and storage performance. The physics associated with the electrostatic spray process and morphology control using it are also presented. The manuscript highlights the potential of electrospray processing for producing thin films of controlled microstructure, from ultrasmooth layers in organic photovoltaics and perovskite photovoltaics to hierarchical nanostructured films for anodes and photoanodes. It aims to help researchers appreciate essential aspects of electrostatic spray deposition efficiency, process control, and morphology engineering for energy conversion (e.g., solar cell, fuel cell, and photoelectrochemical cell) and energy storage (e.g., lithium‐ion battery and supercapacitor) electrodes.
Annual survival probabilities of anadromous Arctic Char remain high and stable despite interannual differences in sea ice melt date

Throughout their range, anadromous Arctic Char (Salvelinus alpinus (Linnaeus, 1758)) support commercial, recreational, and subsistence fisheries that are important economically, socially, and culturally. However, drivers of interannual variation in survival in this species remain poorly understood. Here, we aimed to quantify the impact of environmental and biological parameters on the survival probability of anadromous Arctic Char near the community of Cambridge Bay, Nunavut, Canada. To do so, we tracked 183 Arctic Char tagged with acoustic transmitters and used capture–mark–recapture methods to estimate survival probabilities over six years. Annual survival probabilities for individuals was high, varying between 0.79 and 0.88, whereas recapture probabilities varied between 0.64 and 0.90. Interannual variation in survival probability was low and neither the environmental (air temperature and sea ice cover) nor biological (sex) variables influenced survival probability. These estimates suggest that annual survival probability is high for anadromous adult Arctic Char in the Cambridge Bay area, despite clear differences in the ice cover melt date among years. These results further our understanding of the demographic parameters of Arctic Char in the region, which will be important for future assessments of the sustainability of commercial fisheries as well as for predicting population responses to a rapidly changing Arctic.
Synthesis and properties of isothiocyanate liquid crystals containing cyclohexene unit

ABSTRACT Isothiocyanate liquid crystals containing cyclohexene core unit were designed and synthesised through a practical synthetic route. The structures of the designed mesogens and intermediate products were confirmed by 1H NMR, 13C NMR and GC/EI-MS. The effect of this core unit on the mesomorphic and physical properties were investigated by comparing with four reference compounds based on trans-cyclohexane and phenyl. The results illustrated that the function of this unit on the melting points and nematic phase range fell in between classical cores trans-cyclohexane and benzene. When compared with phenyl, this core structure can depress the presence of smectic phase. The birefringence and dielectric anisotropy values of the cyclohexene-based liquid crystals were higher than the trans-cyclohexane-based references, respectively, illustrating that this core could be used as an enhanced version of trans-cyclohexane. Density Functional Theory (DFT) calculations of energy minimum structures, polarisability anisotropy (Δα) and dipole moment (µ) were carried out at last to clarify the structure–property relationship of the mesogens. Graphical abstract
Xenon-129 NMR investigation of coal micropores

The microporous structures of three Argonne Premium coals, and a weathered sample and three oxidized samples of Illinois No 6 coal (APCS No. 3), have been investigated by 129 Xe NMR spectroscopy. An analytical model has been developed which approximates the average pore sizes and pore swelling characteristics for the coals according to changes in 129 Xe chemical shifts as a function of xenon pressure. Pore regions can be described which differ in size (∼6 and ∼10 A in diameter) or chemical composition. The effects of weathering and oxidation at elevated temperatures on the pore size and swelling of Illinois No. 6 coal have also been examined
Catalytic removal of organic colorants from water using some transition metal oxide nanoparticles synthesized under sunlight

Transition metal oxides (TMO) constitute a most amazing class of materials with a wide range of properties and applications; therefore, their synthesis using a green approach is a necessity. As such, sunlight irradiation was employed to synthesize various TMO nanostructures (ZnO, CuO, Co3O4, NiO and Cr2O3) using water as a solvent. Nanoparticles obtained with distinct morphologies, such as nanotubes (ZnO; 86.86% (CuO) > 85.89% (NiO) > 80.35% (Co3O4), depending on the sizes of the respective TMO nanoparticles. This is also supported by the finding of small and non-toxic by-products such as but-2-enal, sulfur trioxide and benzoquinone. With high potential observed in the removal of dyes, TMO nanoparticles have a bright future with respect to their use as important adsorbents in waste water treatment. The advantage of the present work lies in the green synthesis of nanoparticles and their application in helping to make our environment green.
The Virtues and Limitations of Dynamic Capabilities

Dynamic capabilities have been identified as a key determinant of competitive advantage. This paper explores the foundations of dynamic capabilities, and the limits to their effectiveness, first theoretically and then through the case of Danaher, the most successful US conglomerate for over three decades. Limitations of dynamic capabilities include that they (a) can be substitutable and (b) embody strategic choices themselves. The Danaher case, an exemplar of dynamic capabilities, illustrates how dynamic capabilities require long-term commitments in order to be effective, involve a set of choices that are closely tied to others made by the firm, and embody tradeoffs that imply that investments in any particular dynamic capability may be inconsistent with acquiring new ones.