bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sustainability transition for Indian agriculture
Authors: Paul Bino , Murari Kamal Kumar , Patnaik Unmesh , Bahinipati Chandra Sekhar , Sasidharan Subash 
Published: May 2023

AbstractFarming in India faces a sustainability challenge due to its overreliance on chemical inputs. For every US$ 1,000 investment in sustainable farming, a US$ 100,000 subsidy is allocated for chemical fertilizers. Indian farming system is far off the optimal nitrogen efficiency, calling for substantial reforms in policy towards the transition to sustainable inputs. We examine the propensity of Indian farmers to adopt biofertilizers and other sustainable inputs. While small farmers are inclined towards chemical inputs, sustainable inputs are costly. Here we show that less than 5 per cent of the farming population contributes to the 95 per cent usage of the bio-fertilizer in India. However, small and marginal farmers contribute substantially to food security. Shifting from chemical to sustainable inputs calls for autonomous investment by the state to augment the capacity and improve affordability. We illustrate the transition to sustainability through a framework that includes scale, affordability, and sustainable inputs.
Evaluating COVID-19 vaccination intentions and vaccine hesitancy among parents of children with autism spectrum disorder
Authors: Khoodoruth Mohamed Adil Shah , Khoodoruth Widaad Nuzhah Chut-kai , Ramadan Abd Alrhem Mohamad , Johnson Beena , Gulistan Shaima , Deluvio Raf Bernard Corvera , Alamri Mohammed Nasser , Al-Abdulla Majid , Ouanes Sami , Khan Yasser Saeed 
Published: May 2023

AbstractAs the global vaccination mass campaign against COVID-19 extended to children aged 5 to 11 years, some parents remained hesitant about their children being administered the vaccine despite data supporting its safety. Parent vaccine hesitancy (PVH) may have predisposed certain groups of children, particularly those with autism spectrum disorder (ASD), to COVID-19 when other neurotypical children would have been vaccinated. We investigated the current PVH in 243 parents of children with ASD and 245 controls using the Parent Attitudes about Childhood Vaccines (PACV) scale. The study was conducted in Qatar from May to October 2022. Overall, 15.0% [95% CI 11.7%; 18.3%] of parents were vaccine-hesitant, with no difference (p = 0.054) between groups (ASD children [18.2%] vs. controls [11.7%]). The only sociodemographic factor associated with higher vaccine hesitancy was being a mother (as compared to being a father). The COVID-19 vaccine receipt rate at the time of the study did not differ between ASD (24.3%) and non-ASD groups (27.8%). Around two-thirds of parents of children with ASD refused or were unsure about vaccinating their children against COVID-19. We found that the intent to vaccinate against COVID-19 was higher in parents who were married and in those with a lower PACV total score. Continued public health efforts are needed to address vaccine hesitancy among parents.
Programming nonreciprocity and harmonic beam steering via a digitally space-time-coded metamaterial antenna
Authors: Vosoughitabar Shaghayegh , Wu Chung-Tse Michael 
Published: May 2023

AbstractRecent advancement in digital coding metasurfaces incorporating spatial and temporal modulation has enabled simultaneous control of electromagnetic (EM) waves in both space and frequency domains by manipulating incident EM waves in a transmissive or reflective fashion, resulting in time-reversal asymmetry. Here we show in theory and experiment that a digitally space-time-coded metamaterial (MTM) antenna with spatiotemporal modulation at its unit cell level can be regarded as a radiating counterpart of such digital metasurface, which will enable nonreciprocal EM wave transmission and reception via surface-to-leaky-wave transformation and harmonic frequency generation. Operating in the fast wave (radiation) region, the space-time-coded MTM antenna is tailored in a way such that the propagation constant of each programmable unit cell embedded with varactor diodes can toggle between positive and negative phases, which is done through providing digital sequences by using a field-programmable gate array (FPGA). Owing to the time-varying coding sequence, harmonic frequencies are generated with different main beam directions. Furthermore, the space time modulation of the digitally coded MTM antenna allows for nonreciprocal transmission and reception of EM waves by breaking the time-reversal symmetry, which may enable many applications, such as simultaneous transmitting and receiving, unidirectional transmission, radar sensing, and multiple-input and multiple-output (MIMO) beamformer.
Large scale sequence alignment via efficient inference in generative models
Authors: Mongia Mihir , Shen Chengze , Davoodi Arash Gholami , Marçais Guillaume , Mohimani Hosein 
Published: May 2023

AbstractFinding alignments between millions of reads and genome sequences is crucial in computational biology. Since the standard alignment algorithm has a large computational cost, heuristics have been developed to speed up this task. Though orders of magnitude faster, these methods lack theoretical guarantees and often have low sensitivity especially when reads have many insertions, deletions, and mismatches relative to the genome. Here we develop a theoretically principled and efficient algorithm that has high sensitivity across a wide range of insertion, deletion, and mutation rates. We frame sequence alignment as an inference problem in a probabilistic model. Given a reference database of reads and a query read, we find the match that maximizes a log-likelihood ratio of a reference read and query read being generated jointly from a probabilistic model versus independent models. The brute force solution to this problem computes joint and independent probabilities between each query and reference pair, and its complexity grows linearly with database size. We introduce a bucketing strategy where reads with higher log-likelihood ratio are mapped to the same bucket with high probability. Experimental results show that our method is more accurate than the state-of-the-art approaches in aligning long-reads from Pacific Bioscience sequencers to genome sequences.
Performance aware shared memory hierarchy model for multicore processors
Authors: Mohamed Ahmed M. , Mubark Nada , Zagloul Saad 
Published: May 2023

AbstractDespite the fact that multicore processors have a better instruction execution speed and lower power consumption, they also encounter a set of design challenges. The appearance of multicore and many core architectures has raised the problem of managing shared hierarchical memory systems. The main focus of this paper is to evaluate the behavior of shared hierarchical memory systems by modeling their response time analytically. Since the gap between the memory and processor speed increases rapidly, it gets more crucial to find an analytical model that includes the significant factors that affect the performance of hierarchical memory systems. The proposed model considers the interdependence between different memory layers and differentiates between the memory response time and memory system time. Moreover, the model evaluates the effect of memory hierarchy on the variance of the memory access time. The existence of a large variance can lead to extremely long wait queues which can dramatically affect the performance of multicore processors
Broadband subwavelength imaging of flexural elastic waves in flat phononic crystal lenses
Authors: Danawe Hrishikesh , Tol Serife 
Published: May 2023

AbstractSubwavelength imaging of elastic/acoustic waves using phononic crystals (PCs) is limited to a narrow frequency range via the two existing mechanisms that utilize either the intense Bragg scattering in the first phonon band or negative effective properties (left-handed material) in the second (or higher) phonon band. In the first phonon band, the imaging phenomenon can only exist at frequencies closer to the first Bragg band gap where the equal frequency contours (EFCs) are convex. Whereas, for the left-handed materials, the subwavelength imaging is restricted to a narrow frequency region where wave vectors in PC and background material are close to each other, which is essential for single-point image formation. In this work, we propose a PC lens for broadband subwavelength imaging of flexural waves in plates exploiting the second phonon band and the anisotropy of a PC lattice for the first time. Using a square lattice design with square-shaped EFCs, we enable the group velocity vector to always be perpendicular to the lens interface irrespective of the frequency and incidence angle; thus, resulting in a broadband imaging capability. We numerically and experimentally demonstrate subwavelength imaging using this concept over a significantly broadband frequency range.
Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes
Authors: Beegum Sahila , Timlin Dennis , Reddy Kambham Raja , Reddy Vangimalla , Sun Wenguang , Wang Zhuangji , Fleisher David , Ray Chittaranjan 
Published: May 2023

AbstractGOSSYM, a mechanistic, process-level cotton crop simulation model, has a two-dimensional (2D) gridded soil model called Rhizos that simulates the below-ground processes daily. Water movement is based on gradients of water content and not hydraulic heads. In GOSSYM, photosynthesis is calculated using a daily empirical light response function that requires calibration for response to elevated carbon dioxide (CO2). This report discusses improvements made to the GOSSYM model for soil, photosynthesis, and transpiration processes. GOSSYM’s predictions of below-ground processes using Rhizos are improved by replacing it with 2DSOIL, a mechanistic 2D finite element soil process model. The photosynthesis and transpiration model in GOSSYM is replaced with a Farquhar biochemical model and Ball-Berry leaf energy balance model. The newly developed model (modified GOSSYM) is evaluated using field-scale and experimental data from SPAR (soil–plant–atmosphere-research) chambers. Modified GOSSYM better predicted net photosynthesis (root mean square error (RMSE) 25.5 versus 45.2 g CO2 m−2 day−1; index of agreement (IA) 0.89 versus 0.76) and transpiration (RMSE 3.3 versus 13.7 L m−2 day−1; IA 0.92 versus 0.14) and improved the yield prediction by 6.0%. Modified GOSSYM improved the simulation of soil, photosynthesis, and transpiration processes, thereby improving the predictive ability of cotton crop growth and development.
Deep learning applied to EEG source-data reveals both ventral and dorsal visual stream involvement in holistic processing of social stimuli
Authors: Borra Davide , Bossi Francesco , Rivolta Davide , Magosso Elisa 
Published: May 2023

AbstractPerception of social stimuli (faces and bodies) relies on “holistic” (i.e., global) mechanisms, as supported by picture-plane inversion: perceiving inverted faces/bodies is harder than perceiving their upright counterpart. Albeit neuroimaging evidence suggested involvement of face-specific brain areas in holistic processing, their spatiotemporal dynamics and selectivity for social stimuli is still debated. Here, we investigate the spatiotemporal dynamics of holistic processing for faces, bodies and houses (adopted as control non-social category), by applying deep learning to high-density electroencephalographic signals (EEG) at source-level. Convolutional neural networks were trained to classify cortical EEG responses to stimulus orientation (upright/inverted), separately for each stimulus type (faces, bodies, houses), resulting to perform well above chance for faces and bodies, and close to chance for houses. By explaining network decision, the 150–200 ms time interval and few visual ventral-stream regions were identified as mostly relevant for discriminating face and body orientation (lateral occipital cortex, and for face only, precuneus cortex, fusiform and lingual gyri), together with two additional dorsal-stream areas (superior and inferior parietal cortices). Overall, the proposed approach is sensitive in detecting cortical activity underlying perceptual phenomena, and by maximally exploiting discriminant information contained in data, may reveal spatiotemporal features previously undisclosed, stimulating novel investigations.
Evaluating the complete (44-item), short (20-item) and ultra-short (10-item) versions of the Big Five Inventory (BFI) in the Brazilian population
Authors: Costa Mastrascusa Raul , de Oliveira Fenili Antunes Matheus Loli , de Albuquerque Nathalia Saraiva , Virissimo Sara Luísa , Foletto Moura Marcela , Vieira Marques Motta Bibiana , de Lara Machado Wagner , Moret-Tatay Carmen , Quarti Irigaray Tatiana 
Published: May 2023

AbstractThe Big Five Inventory (BFI) is an instrument designed to assess the personality of individuals aged 18 and above. The original version consists of 44 items divided into five sub-scales representing each of the five personality factors: agreeableness, neuroticism, conscientiousness, openness, and extraversion. The main purpose of this study was to assess the factorial structure of the 44-item BFI and the reliability of two shorter versions with 20 and 10 items. The study also aimed to present normative data for interpreting scores from the short and ultrashort versions of the BFI for the Brazilian population. A total of 3565 individuals with a mean age of 33.3 years (SD = 13.0) from all Brazilian states participated in the study, with 44.2% from the State of Rio Grande do Sul. Participants completed a sociodemographic questionnaire and the BFI. Confirmatory factor analysis showed poor adaptation of the original 44-item model, but the short and ultrashort versions with 20 and 10 items respectively had good adaptation indexes and reliability, with Omega coefficients above 0.70. Normative data for the shorter versions were presented using mean, standard deviation, and percentiles (lower, medium, and higher). The study concluded that the short and ultrashort versions of the BFI have good reliability and can be used in surveys requiring a brief personality assessment.
Double-negative metamaterial square enclosed Q.S.S.R For microwave sensing application in S-band with high sensitivity and Q-factor
Authors: Khalil Muhammad Amir , Yong Wong Hin , Islam Mohammad Tariqul , Hoque Ahasanul , Islam Md. Shabiul , leei Cham Chin , Soliman Mohamed S. 
Published: May 2023

AbstractMetamaterials have gained much attention due to their exciting characteristics and potential uses in constructing valuable technologies. This paper presents a double negative square resonator shape metamaterial sensor to detect the material and its thickness. An innovative double-negative metamaterial sensor for microwave sensing applications is described in this paper. It has a highly sensitive Q-factor and has good absorption characteristics approximately equal to one. For the metamaterial sensor, the recommended measurement is 20 by 20 mm. Computer simulation technology (C.S.T.) microwave studios are used to design the metamaterial structure and figure out its reflection coefficient. Various parametric analyses have been performed to optimize the design and size of the structure. The experimental and theoretical results are shown for a metamaterial sensor that is attached to five different materials such as, Polyimide, Rogers RO3010, Rogers RO4350, Rogers RT5880, and FR-4. A sensor’s performance is evaluated using three different thicknesses of FR-4. There is a remarkable similarity between the measured and simulated outcomes. The sensitivity values for 2.88 GHz and 3.5 GHz are 0.66% and 0.19%, respectively, the absorption values for both frequencies are 99.9% and 98.9%, respectively, and the q-factor values are 1413.29 and 1140.16, respectively. In addition, the figure of merit (FOM) is analyzed, and its value is 934.18. Furthermore, the proposed structure has been tested against absorption sensor applications for the purpose of verifying the sensor's performance. With a high sense of sensitivity, absorption, and Q-factor, the recommended sensor can distinguish between thicknesses and materials in various applications.
Zero-shot transfer learned generic AI models for prediction of optimally ripe climacteric fruits
Authors: Dutta Jayita , Patwardhan Manasi , Deshpande Parijat , Karande Shirish , Rai Beena 
Published: May 2023

AbstractIdeally, ripe fruits offer appropriate nutritional content and best quality in terms of taste and flavour. Prediction of ripe climacteric fruits acts as the main marketing indicator for quality from the consumer perspective and thus renders it a genuine industrial concern for all the stakeholders of the fruit supply chain. However, the building of fruit-specific individual model for the prediction of ripeness level remains an existing challenge due to the scarcity of sufficient labeled experimental data for each fruit. This paper describes the development of generic AI models based on the similarity in physico-chemical degradation phenomena of climacteric fruits for prediction of ‘unripe’ and ‘ripe’ levels using ‘zero-shot’ transfer learning techniques. Experiments were performed on a variety of climacteric and non-climacteric fruits, and it was observed that transfer learning works better for fruits within a cluster (climacteric fruits) as compared to across clusters (climacteric to non-climacteric fruits). The main contributions of this work are two-fold (i) Using domain knowledge of food chemistry to label the data in terms of age of the fruit, (ii) We hypothesize and prove that the zero-shot transfer learning works better within a set of fruits, sharing similar degradation chemistry depicted by their visual properties like black spot formations, wrinkles, discoloration, etc. The best models trained on banana, papaya and mango dataset resulted in s zero-shot transfer learned accuracies in the range of 70 to 82 for unknown climacteric fruits. To the best of our knowledge, this is the first study to demonstrate the same.
RNA-seq analysis and reconstruction of gene networks involved in response to salinity stress in quinoa (cv. Titicaca)
Authors: Hosseini Sahar Sadat , Ramezanpour Seyedeh Sanaz , Soltanloo Hassan , Seifati Seyed Ebrahim 
Published: May 2023

AbstractTo better understand the mechanisms involved in salinity stress, the adaptability of quinoa cv. Titicaca—a halophytic plant—was investigated at the transcriptome level under saline and non-saline conditions. RNA-sequencing analysis of leaf tissue at the four-leaf stage by Illumina paired—end method was used to compare salt stress treatment (four days after stress at 13.8 dsm−1) and control. Among the obtained 30,846,354 transcripts sequenced, 30,303 differentially expressed genes from the control and stress treatment samples were identified, with 3363 genes expressed ≥ 2 and false discovery rate (FDR) of < 0.001. Six differential expression genes were then selected and qRT-PCR was used to confirm the RNA-seq results. Some of the genes (Include; CML39, CBSX5, TRX1, GRXC9, SnRKγ1 and BAG6) and signaling pathways discussed in this paper not been previously studied in quinoa. Genes with ≥ 2 were used to design the gene interaction network using Cytoscape software, and AgriGO software and STRING database were used for gene ontology. The results led to the identification of 14 key genes involved in salt stress. The most effective hub genes involved in salt tolerance were the heat shock protein gene family. The transcription factors that showed a significant increase in expression under stress conditions mainly belonged to the WRKY, bZIP and MYB families. Ontology analysis of salt stress-responsive genes and hub genes revealed that metabolic pathways, binding, cellular processes and cellular anatomical entity are among the most effective processes involved in salt stress.
The cytoplasmic N-terminal tail of Zika virus NS4A protein forms oligomers in the absence of detergent or lipids
Authors: Surya Wahyu , Liu Yiting , Torres Jaume 
Published: May 2023

AbstractThe non-structural (NS) NS4A protein in flaviviruses has three predicted transmembrane domains, is critical for virulence and participates in membrane morphogenesis. In Dengue virus (DENV), both hydrophylic N-terminal tail and its first transmembrane domain participate in the formation of oligomers which are important for pathogenicity. However, the relative importance of the N-terminal domain in oligomerization has been under debate. In particular, since in the absence of detergent or lipids, this domain (residues 1–48) in both DENV and Zika virus (ZIKV) NS4A, was found to be disordered. Recently, however, we reported preliminary data that showed that peptide ZIKV NS4A 4–58 adopts a defined secondary structure in aqueous solution and forms oligomers, signaling its importance for full length NS4A oligomerization. Herein we have performed detailed analytical ultracentrifugation experiments to further characterize the oligomerization of this peptide and also a shorter variant (residues 4–44). In both cases, sedimentation velocity produced a single species with concentration-dependent sedimentation coefficient, consistent with a fast equilibrium between at least two species. Combining sedimentation velocity and equilibrium experiments, data is best fitted to a monomer–dimer–trimer equilibrium. Possible models of NS4A oligomers obtained with AlphaFold-2 predict the stabilizing role for residues in this N-terminal domain, such as Arg20, Asn27, Ala44 and Glu50, all at highly conserved positions in flavivirus NS4A proteins. Our results are thus consistent with N-terminal domain interactions acting as one of the driving forces for NS4A homo-oligomerization.