Miracle-dz/UniFAR-FTUs huggingface dataset:
Population dynamics linked to glacial cycles in Cercis chuniana F. P. Metcalf (Fabaceae) endemic to the montane regions of subtropical China

The mountains of subtropical China are an excellent system for investigating the processes driving the geographical distribution of biodiversity and radiation of plant populations in response to Pleistocene climate fluctuations. How the major mountain ranges in subtropical China have affected the evolution of plant species in the subtropical evergreen broadleaved forest is an issue with long‐term concern. Here, we focused on Cercis chuniana, a woody species endemic to the southern mountain ranges in subtropical China, to elucidate its population dynamics. We used genotyping by sequencing (GBS) to investigate the spatial pattern of genetic variation among 11 populations. Geographical isolation was detected between the populations located in adjacent mountain ranges, thought to function as geographical barriers due to their complex physiography. Bayesian time estimation revealed that population divergence occurred in the middle Pleistocene, when populations in the Nanling Mts. separated from those to the east. The orientation and physiography of the mountain ranges of subtropical China appear to have contributed to the geographical pattern of genetic variation between the eastern and western populations of C. chuniana. Complex physiography plus long‐term stable ecological conditions across glacial cycles facilitated the demographic expansion in the Nanling Mts. , from which contemporary migration began. The Nanling Mts. are thus considered as a suitable area for preserving population diversity and large population sizes of C. chuniana compared with other regions. As inferred by ecological niche modeling and coalescent simulations, secondary contact occurred during the warm Lushan–Tali Interglacial period, with intensified East Asia summer monsoon and continuous habitat available for occupation. Our data support the strong influence of both climatic history and topographic characteristics on the high regional phytodiversity of the subtropical evergreen broadleaved forest in subtropical China.
Digital Twin for FANUC Robots: Industrial Robot Programming and Simulation Using Virtual Reality

A Digital Twin is the concept of creating a digital replica of physical models (such as a robot). This is similar to establishing a simulation using a robot operating system (ROS) or other industrial-owned platforms to simulate robot operations and sending the details to the robot controller. In this paper, we propose a Digital Twin model that assists in the online/remote programming of a robotic cell by creating a 3D digital environment of a real-world configuration. Our Digital Twin model consists of two components, (1) a physical model: FANUC robot (M-10iA/12), and (2) a digital model: Unity (a gaming platform) that comes with specialized plugins for virtual and augmented reality devices. One of the main challenges in the existing approach of robot programming is writing and modifying code for a robot trajectory that is eased in our framework using a Digital Twin. Using a Digital Twin setup along with Virtual Reality, we observe the trajectory replication between digital and physical robots. The simulation analysis provided a latency of approximately 40 ms with an error range of −0.28 to 0.28∘ across the robot joint movements in a simulation environment and −0.3 to 0.3∘ across the actual robot joint movements. Therefore, we can conclude that our developed model is suitable for industrial applications.
An Economic Analysis of Paddy Cultivation in Cuddalore District

In this paper an attempt was made to analyze economics of paddy cultivation in Cuddalore district. Based on area under paddy, three blocks namely Kurinjipadi, Kumaratchi and Vridhachalam were selected. The total sample size was 120 paddy growers. The study revealed that area and production of paddy crop was declining during the period 1998-2008 while the productivity was growing positively during the same period. During 2009-2019, compound growth rate of area, production and productivity of paddy was depicting an increasing trend due to the role-played by high yielding varieties which created greater affinity towards paddy crop. The cost of production of paddy per hectare was estimated to be Rs. 56,617. The average gross income was found to be Rs. 92,077 per hectare and net income was observed to be Rs. 29,712 per hectare. Excessive usage of nitrogen and phosphorous fertilizers could be reduced to decrease the production cost and increase the efficiency of inputs. Adoption of System of Rice Intensification (SRI) method was suggested to increase the productivity of paddy.
Non-mechanical beam scanner based on VCSEL integrated amplifier with resonant wavelength detuning design

We demonstrate the non-mechanical beam steering and amplifier operation of a vertical cavity surface emitting laser (VCSEL) integrated Bragg reflector waveguide amplifier with a cut-off wavelength detuning design, which enables unidirectional lateral coupling, continuous electrical beam steering, and diffraction-limited divergence angle. We present the modeling of the proposed structure for unidirectional coupling between a seed single-mode VCSEL and slow-light amplifier. We also present the detailed operating characteristics including the near-field and far-field patterns, light/current characteristics, and lasing spectrum. The experimental measurements exhibit a single-mode output of over 8 mW under CW operation, a continuous beam steering range of 16°, and beam divergence below 0.1° as an optical beam scanner. The integrated amplifier length is as small as 0.9 mm, and thus we could expect much higher powers and higher resolution points by increasing the amplifier lengths.
Photocatalytic Dye Degradation and Biological Activities of Cu-Doped ZnSe Nanoparticles and Their Insights

Environmental nanotechnology has received much attention owing to its implications on environmental ecosystem, and thus is promising for the elimination of toxic elements from the aquatic surface. This work focuses on Cu-doped ZnSe nanoparticles using the co-precipitation method. The synthesized Cu-doped ZnSe nanoparticles were examined for structural, optical, and morphological properties with the help of XRD, FTIR, UV/vis diffuse reflection spectroscopy (DRS), FESEM, TEM, and XPS. The synthesized Cu-doped ZnSe nanoparticles revealed the presence of Cu2+ in the ZnSe lattice, which has been shown to take a predominant role for enhanced catalysis in the Cu-doped ZnSe nanoparticles. The synthesized Cu-doped ZnSe nanoparticles were investigated for their catalytic and antibacterial activities. The 0.1 M copper-doped ZnSe nanoparticles exhibited the highest rate of degradation against the methyl orange dye, which was found to be 87%. A pseudo-first-order kinetics was followed by Cu-doped ZnSe nanoparticles with a rate constant of 0.1334 min−1. The gram-positive and gram-negative bacteria were used for investigating the anti-bacterial activity of the Cu-doped ZnSe nanoparticles. The Cu-doped ZnSe nanoparticles exhibited enhanced photocatalytic and antibacterial activity.
Co-processing of Saturated and Unsaturated Triglycerides in Catalytic Cracking Process for Hydrocarbon Fuel Production

With the aim of the efficient use of plant oils as alternative fuels, the deoxygenation of saturated and unsaturated triglyc- erides in a catalytic cracking process was investigated using a fluid catalytic cracking catalyst with enhanced hydrogen-transfer activity. The decomposition and deoxygenation of sunflower oil (unsaturated triglycerides) proceeded rapidly and produced a large amount of aromatic hydrocarbons, which are unsuitable for fuel applications. In contrast, the rate of deoxygenation of coconut oil (saturated triglycerides) was slow and some oxygen-containing species were observed as products. During the co-processing of saturated and unsaturated triglycerides, the deoxygenation of saturated triglycerides was accelerated and complete deoxygenation was achieved. The acceleration of the deoxygenation reaction was attributed to the rapid formation of hydrogen donors, such as olefins and naphthenes, from the decomposition of unsaturated triglycerides. The olefins and naphthenes released hydrogen species by cyclization and aromatization reactions. These hydrogen species then reacted with saturated triglycerides and their derivatives (fatty acids and aldehydes) in hy-drogen-transfer reactions, accelerating the hydrodeoxygenation of saturated triglycerides. The hydrodeoxygenation of saturated triglycerides produced paraffins and olefins rather than aromatics. The increase in the amount of paraffins and olefins produced by the accelerated deoxygenation of saturated triglycerides was larger than the amount of aromatic hydrocarbons derived from unsaturated triglycerides. Thus, co-processing of saturated and unsaturated triglycerides was confirmed to be effective for simultaneously achieving both the acceleration of saturated triglyceride deoxygenation and the suppression of aromatic hydrocarbon formation.
Synthesis, Computational, Antibacterial and Antifungal Investigation of Two Tri-Fluorinated Chalcones of 1-(2,3-Dihydrobenzo[b][1,4]dioxin-6-yl)ethan-1-one

Abstract In the present study, we report the combined experimental and computational study along with antimicrobial screening of two tri-fluorinated chalcones from 1-(2,3-dihydrobenzo[b][1,4]dioxin-6-yl)ethan-1-one. The (E)-1-(2,3-dihydrobenzo[b][1,4]dioxin-6-yl)-3-(4-(trifluoromethyl)phenyl)prop-2-en-1-one (DBTFP-1) and (E)-1-(2,3-dihydrobenzo[b][1,4]dioxin-6-yl)-3-(4-(trifluoromethoxy)phenyl)prop-2-en-1-one (DBTFP-2) were synthesized by the famous Claisen-Schmidt condensation reaction. The computational investigation of optimized molecular structures, bond lengths and bond angles were performed by using density functional theory (DFT) with a B3LYP functional and 6-31G(d,p) basis set. The electronic properties were computed using Time-Dependent density functional theory (TD-DFT) with a B3LYP functional and 6-31G(d,p) basis set for the optimized geometries. The lower band gap in DBTFP-1 demonstrated the inevitable intramolecular charge transfer. The UV-Visible simulations were performed in the gas phase and dichloromethane (DCM) solvent. The experimental UV-Visible analysis was performed in DCM solvent. The first singlet excited state was attributed to the n-π* and second singlet excited state to the π -π* electronic transition. The scaled vibrational bands of titled compounds were compared with experimental observations and correct vibrational assignments were made. Various global reactivity parameters were analyzed and discussed to apprehend the chemical behavior of the synthesized chalcones. MESP and contour surfaces revealed negative potentials near the oxygen atoms and positive potentials over the hydrogen atoms. Mulliken charge study revealed that C17 and C33 are the most negative and positive carbon atoms in DBTFP-1, respectively, whereas C17 and C35 are the most negative and positive carbon atoms in DBTFP-2. The antibacterial activity was performed against P. vulgaris and S. aureus and antifungal activity against A. niger and C. albicans. The antimicrobial activity for these two compounds was correlated with LUMO and band gap energy. The magnificent antimicrobial activity of DBTFP-1 was attributed to its more stabilized LUMO and lower band gap than DBTFP-2. Graphical Abstract
Random Projections of Mel-Spectrograms as Low-Level Features for Automatic Music Genre Classification

In this work, we analyse the random projections of Mel-spectrograms as low-level features for music genre classification. This approach was compared to handcrafted features, features learned using an auto-encoder and features obtained from a transfer learning setting. Tests in five different well-known, publicly available datasets show that random projections leads to results comparable to learned features and outperforms features obtained via transfer learning in a shallow learning scenario. Random projections do not require using extensive specialist knowledge and, simultaneously, requires less computational power for training than other projection-based low-level features. Therefore, they can be are a viable choice for usage in shallow learning content-based music genre classification.
Flotation in Water and Wastewater Treatment

Flotation constitutes a separation process that originated from mineral processing. Nowadays, wider applications have been found and compared to flotation for water and wastewater treatment. Stress in the present review paper was mainly applied to heavy metal ions recovery by flotation and the respective mechanism followed, being either ion, precipitate, or sorptive flotation. In the latter case, the use of adsorbents is included (such as powdered activated carbon, zeolites, and goethite), as well as various biosorbents. The flotation of the following metals was reviewed: copper, zinc, nickel, lead, iron, chromium, arsenic, gold, and others. The bubble generation method could be applied for typical dispersed-air flotation column, electroflotation, or dissolved-air flotation; the latter being the most appropriate established technique in water treatment. The role of particle size (for example, studying flotation of salt-type mineral fines) was also examined.
Potential economic impacts of groundwater conservation in the Mississippi River Alluvial Aquifer (MRAA), Louisiana, USA

Overextraction of groundwater reduces groundwater height, increases the energy cost, and may threaten an aquifer's economic life. Water‐intensive crops, corn, and soybean, dominate the agricultural land in the Mississippi River Alluvial Aquifer (MRAA) region of the United States, thus stressing this confined aquifer. Groundwater conservation policy or the adoption of efficient irrigation technology could save both water and energy. This study aims to estimate the future returns from the irrigated land under the scenarios of 30%, 20%, 10%, 5%, and no groundwater conservation from 2020 to 2022. An accurate model to predict the crop choice decision is important to estimate the impact of groundwater policies. We develop a crop choice model where an individual farmer has a crop planting or land fallowing choice each year. We use the random forest, boosted regression trees, and support vector machine for the crop choice prediction. Boosted regression trees perform the best in our classification problem with 75.5% out of sample accuracy. The prediction model shows that the numbers of corn growers increase in the future. Our results show that the profit of 2572 farmers increased cumulatively by 0.14% when they conserve groundwater by 30% for 3 years. From a policy perspective, providing financial and technical assistant to farmers for making investments to conserve groundwater could save energy costs and sustain the economic life of the MRAA.
The Genome Sequence of Brucella abortus vaccine strain A19 provides insights on its virulence attenuation compared to Brucella abortus strain 9-941.

BACKGROUND Brucellosis is a widespread disease that affects animals and humans. The live attenuated Brucella abortus A19 strain is used for vaccination against brucellosis in China. In addition, the main mechanisms supporting the residual toxicity of A19 have not been elucidated. Here, we performed a comprehensive comparative analysis of the genome-wide sequence of A19 against the whole genome sequences of the published virulent reference strain 9-941. The primary objective of this study was to identify candidate virulence genes by systematically comparing the genomic sequences between the two genomes. RESULTS This analysis revealed two deletion regions in the A19 genome, in which all included large fragments of 63 bp, and one of their gene function is related to ABC transporter permease protein. In addition, we have identified minor mutations in important virulence-related genes that can be used to determine the underlying mechanisms of virulence attenuation. The function of its virulence gene covers LysR family transcriptional regulator, outer membrane, MFS transporter and oxidoreductase etc. At the same time, a PCR differential diagnosis method was constructed, which can distinguish A19, S19 and most other commonly used Brucella viruent strains and vaccine strains. CONCLUSION The data may help to provide resources for further detailed analysis of mechanisms for other Brucella vaccines. It laid the foundation for further distinguishing between vaccine immunity and virulent strains infection.
Spectroscopic QUasar extractor and redshift (z) estimator squeze – II. Universality of the results

In this paper we study the universality of the results of SQUEzE, a software package to classify quasar spectra and estimate their redshifts. The code is presented in \cite{Perez-Rafols+2019}. We test the results against changes on signal-to-noise, spectral resolution, wavelength coverage, and quasar brightness. We find that SQUEzE levels of performance (quantified with purity and completeness) are stable to spectra that have a noise dispersion 4 times that of our standard test sample, BOSS. We also find that the performance remains unchanged if pixels of width 25Aare considered, and decreases by $\sim2\%$ for pixels of width 100A. We see no effect when analyzing subsets of different quasar brightness, and we establish that the blue part (up to 7000A) of the spectra is sufficient for the classification. Finally, we compare our suite of tests with samples of spectra expected from WEAVE-QSO and DESI, and narrow-band imaging from J-PAS. We conclude that SQUEzE will perform similarly when confronted with the demands of these future surveys as when applied to current BOSS (and eBOSS) data. {\it Keywords: cosmology: observations - quasar: emission lines - quasar: absorption lines}
Routine dynamics in virtual teams: the role of technological artifacts

PurposeIn this paper, the authors extend their understanding of the internal dynamics of routines in contexts characterized by increased levels of virtuality. In particular, the authors focus on the role of routine artifacts in the internal dynamics of routines to answer the question: How does extensive reliance on information and communication technologies (ICTs) due to physical distance influence the internal dynamics of the new product development (NPD) routine (i.e. interactions between performative, ostensive and artifacts of routines) enacted by a virtual team? Design/methodology/approachThis paper is based on an 18-month ethnographic study of the NPD routine performed by a virtual team. The authors relied predominantly on qualitative, ethnographic data collection and analysis methods, using semi-structured interviews, non-participant observation, and the collection of archival data and company documents (formal procedures, guidelines, application designs etc). Qualitative research offers a valuable means to investigate dynamic processes in organizations due to its sensitivity to the organizational context and potential to focus on activities as they unfold.FindingsThe findings highlight the central role of routine artifacts (ICTs) in the routine dynamics of the NPD routine performed by virtual team. In particular, the authors show that the use of the particular types of ICTs enabled team members to confidently and meaningfully relate to the overall routine activity and coordinate their actions in a context characterized by physical distance and extensive reliance on communication and collaboration technologies.Originality/valueThe paper sheds light into role of routine artifacts in the routine dynamics in a context characterized by a high degree of virtuality. This work contributes to the literature on routine dynamics by theorizing about the processes through which routine artifacts (ICTs) afforded routine participants the ability to act confidently and meaningfully to the present and dynamically coordinate their actions with their fellow routine participants.
A Comprehensive Analysis of Demand Response Pricing Strategies in a Smart Grid Environment Using Particle Swarm Optimization and the Strawberry Optimization Algorithm

In the modern world, the systems getting smarter leads to a rapid increase in the usage of electricity, thereby increasing the load on the grids. The utilities are forced to meet the demand and are under stress during the peak hours due to the shortfall in power generation. The abovesaid deficit signifies the explicit need for a strategy that reduces the peak demand by rescheduling the load pattern, as well as reduces the stress on grids. Demand-side management (DSM) uses several algorithms for proper reallocation of loads, collectively known as demand response (DR). DR strategies effectively culminate in monetary benefits for customers and the utilities using dynamic pricing (DP) and incentive-based procedures. This study attempts to analyze the DP schemes of DR such as time-of-use (TOU) and real-time pricing (RTP) for different load scenarios in a smart grid (SG). Centralized and distributed algorithms are used to analyze the price-based DR problem using RTP. A techno-economic analysis was performed by using particle swarm optimization (PSO) and the strawberry (SBY) optimization algorithms used in handling the DP strategies with 109, 1992, and 7807 controllable industrial, commercial, and residential loads. A better optimization algorithm to go along with the pricing scheme to reduce the peak-to-average ratio (PAR) was identified. The results demonstrate that centralized RTP using the SBY optimization algorithm helped to achieve 14.80%, 21.7%, and 21.84% in cost reduction and outperformed the PSO.
DATA INQUIRY: METHODOLOGICAL CONSIDERATIONS ON DATAFICATION IN SOCIAL
 RESEARCH

Datafication is widely acknowledged as a process “transforming all things under the sun into a data format” (van Dijck, 2017, p. 11). As data become both objects and instruments of social science, many scholars call for attention to the ways datafication reconfigures scholarly knowledge production, its methodological opportunities, and challenges (Lomborg et al., 2020). This contribution offers a reflection on the interdependence between methodological approaches taken to study datafication and concepts about it, that these approaches provide within the domains of critical data studies and media studies. Expanding on the concept of methods' performativity (Barad, 2007), I apply the notion of methods assemblages: “a continuing process of crafting and enacting necessary boundaries [and relations]" between researchers and all relevant matters (Law, 2004: 144). The key question in the presented study is what kinds of methods assemblages are being applied in current datafication research and what concepts of datafication they produce. 32 expert interviews were conducted with scholars who published empirical work on dataficaiton between 2015 and 2020. Three methods assemblages were developed. Central to distinguishing between methods assemblages are the ways of associating of the involved actors and things. In my analysis the questions of (1) what we are talking about when talking about datafication and (2) kinds of knowledges that researchers were interested in producing can be understood as such ways of associating. The methods assemblages contribute to critical data studies by producing accounts about datafication processes that are in concert with the methods assemblages applied to study these.