Miracle-dz/UniFAR-FTUs huggingface dataset:
Toxicity and residual effects of toxic baits with spinosyns on the South American fruit fly.

The objective of this work was to assess the lethal concentration and lethal time (LC and LT) of spinosad and spinetoram, combined with different food lures, and their residual effects on South American fruit fly ( Anastrepha fraterculus ). The toxic baits were offered in eight concentrations (2, 6, 14, 35, 84, 204, 495, and 1,200 mg L -1 ), combined with the following food lures: 7% sugarcane molasses, 3% Biofruit, 1.5% CeraTrap, 1.25% Flyral, 3% Samarita Bait, and 3% Samarita Tradicional; diluted food lures in water were used as controls. The residual effect of the formulations at 96 mg L -1 concentration were evaluated for 21 days and were compared with that of the commercial bait Success 0.02 CB. Both insecticides were toxic to adults of A. fraterculus , and mortality varied with the food lure used. The LC 50 and LT 50 ranged from 15.19 to 318.86 mg L -1 and from 11.43 to 85.93 hours, respectively. Spinosad was 2 to 36 times as toxic as spinetoram when combined with different hydrolyzed proteins. Toxic baits formulated with spinosad and spinetoram (96 mg L -1 ) caused mortality equivalent to the one by Success 0.02 CB (90.2%), when assessed on the day of application. Toxic baits formulated with 3% Biofruit + spinosad and 3% Samarita Bait + spinetoram are effective for managing A. fraterculus and provide up to seven days of residual effect in the absence of rain; however, only Success 0.02 CB caused more than 80% mortality for up to 21 days. Normal 0 21 false false false PT-BR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabela normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-fareast-language:EN-US;}
The taxonomic significance of seed morphology in the Passiflora subgenus Astrophea (Passifloraceae)

The center of diversity for Passiflora subg. Astrophea is in low altitude areas of northern South America. The majority of species of this group are difficult to find in nature. Seed morphology was described in detail for 25 species of Passiflora subgenus Astrophea, a subgenus that until now did not exist. For morphological analysis, 20 seeds per species were measured for length, width and thickness, and the arithmetic means calculated. The seeds varied in length, width and thickness. Eight types of ornamentation were found. The margins varied among crestate, dentate, parted, entire and parted-crestate. The seed apex can be distinguished by the shape and position of the apical appendage. Seed shape varied among obovate, lanceolate, cordiform, and oblong to elliptical. An identification key was developed and a PCA was performed both using the principal morphological characters. Morphological characters of seeds are a new source of data for delimiting taxa with quite conflicting morphological boundaries, such as seen here with the Passiflora subgenus Astrophea. Furthermore, seed morphology is especially useful for the identification of specimens with only fruits and, consequently, seeds available.
Analytical modelling and verification of potential profile of DG JLFET with and without stack oxide

ABSTRACT In this paper, a physically based two-dimensional analytical model of potential profile is proposed for both symmetric and asymmetric p-type-doped Double Gate Junctionless Field Effect Transistors (DG JLFETs). The proposed model keeps its validity in the subthreshold region. In order to establish the model, 2-D Poisson’s equation is solved in the channel region while assuming cubic potential distribution along the channel region. We also propose a 2-D analytical model of symmetric Double Gate Stack-Oxide Junctionless Field Effect Transistors (DGS JLFETs). In order to check out the validity of our proposed model, we have used SILVACO ATLAS simulator. Comparison of potential distribution is made between different structures. Between symmetric and asymmetric structures, symmetric structure shows better potential profile as they have shown higher potential distribution in channel region. But when DG JLFET is compared with DGS JLFET, we find better potential profile distribution in DGS JLFET. Important performance parameters like Ion/Ioff ratio, SS, DIBL, Threshold Voltage, I–V characteristics for different structures are found out and compared among them. Asymmetric structure with same electrode materials in both gates but having lower bottom gate oxide thickness showed better performances like higher Ion/Ioff ratio, lower SS, less DIBL compared to other DG JLFETs with and without stack oxide.
Female copulation calls vary with male ejaculation in captive olive baboons

Copulation calls are mating-associated vocalizations that are common in primates, with females vocalizing after copulation in several Old World monkeys and apes. Baboon females typically produce copulation calls that correlate with fertile phase. Calls are, thus, regarded as an upshot of cycle physiology and sexually selected calls. Here, we describe three captive troops of olive baboons wherein, against expectation, females suppressed vocalizing during copulations. Vaginal cytology, together with sexual swelling observations, confirmed that females experienced full receptive cycles. Ovulation did not affect vocal probability during sex, while copulation calls were predicted by male ejaculation just as in other Old World primate species. Results cast doubt on the existence of physiological triggers for baboon copulation calls. Social factors may instead play a larger role. Alterations in social structure (as typically observed in the wild) may be implemented strategically as captive enrichment in order to reveal how females in highly social primates change sexual strategies and, therefore, the use of their copulation calls.
Macrofracturing of Oceanic Lithosphere in Complex Large Earthquake Sequences

Major earthquakes in oceanic lithosphere seaward of the subduction zone outer trench slope are relatively uncommon, but several recent occurrences have involved very complex sequences rupturing multiple nonaligned faults and/or having high aftershock productivity with diffuse distribution. This includes the 21 December 2010 MW 7.4 Ogasawara (Bonin), 11 April 2012 MW 8.6 Indo‐Australia, 23 January 2018 MW 7.9 Off‐Kodiak Island, and 20 December 2018 MW 7.3 Nikol'skoye (northwest Pacific) earthquakes. Major oceanic intraplate event sequences farther from plate boundaries do not tend to be as complex in faulting or aftershocks. Outer trench slope extensional faulting can involve complex distributed sequences, particularly when activated by great megathrust ruptures such as 11 March 2011 MW 9.1 Tohoku and 15 November 2006 MW 8.3 Kuril Islands. Intense faulting sequences also occur near subduction zone corners, with many fault geometries being activated, including some in nearby oceanic lithosphere, as for the 29 September 2009 MW 8.1 Samoa, 6 February 2013 MW 8.0 Santa Cruz Islands, and 16 November 2000 MW 8.0 New Ireland earthquakes. The laterally varying plate boundary stresses from heterogeneous locking, recent earthquakes, or boundary geometry influence the specific faulting geometries activated in nearby major intraplate ruptures in oceanic lithosphere. Preexisting lithospheric structures and fabrics exert secondary influences on the faulting. Intraplate stress release in oceanic lithosphere near subduction zones favors distributed macrofracturing of near‐critical fault systems rather than localized, single‐fault failures, both under transient loading induced by plate boundary ruptures and under slow loading by tectonic motions and slab pull.
Spin Injection and Relaxation in 
p
-Doped 
(In,Ga)As/GaAs
 Quantum-Dot Spin Light-Emitting Diodes at Zero Magnetic Field

We report on efficient spin injection in p-doped $(\mathrm{In},\mathrm{Ga})\mathrm{As}/\mathrm{Ga}\mathrm{As}$ quantum-dot (QD) spin light-emitting diodes (spin LEDs) under zero applied magnetic field. A high degree of electroluminescence circular polarization (${P}_{c}$) \ensuremath{\sim}19% is measured in remanence up to 100 K. This result is obtained thanks to the combination of a perpendicularly magnetized $\mathrm{Co}\text{\ensuremath{-}}\mathrm{Fe}\text{\ensuremath{-}}\mathrm{B}/\mathrm{Mg}\mathrm{O}$ spin injector allowing efficient spin injection and an appropriate p-doped $(\mathrm{In},\mathrm{Ga})\mathrm{As}/\mathrm{Ga}\mathrm{As}$ QD layer in the active region. By analyzing the bias and temperature dependence of the electroluminescence circular polarization, we evidence a two-step spin-relaxation process. The first step occurs when electrons tunnel through the $\mathrm{Mg}\mathrm{O}$ barrier and travel across the $\mathrm{Ga}\mathrm{As}$ depletion layer. The spin relaxation is dominated by the Dyakonov-Perel mechanism related to the kinetic energy of electrons, which is characterized by a bias-dependent ${P}_{c}$. The second step occurs when electrons are captured into QDs prior to their radiative recombination with holes. The temperature dependence of ${P}_{c}$ reflects the temperature-induced modification of the QD doping, together with the variation of the ratio between the charge-carrier lifetime and the spin-relaxation time inside the QDs. The understanding of these spin-relaxation mechanisms is essential to improve the performance of spin LEDs for future spin optoelectronic applications at room temperature under zero applied magnetic field.
Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases

Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of networks remains poorly understood. We launched the "Disease Module Identification DREAM Challenge", an open competition to comprehensively assess module identification methods across diverse gene, protein and signaling networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). While a number of approaches were successful in terms of discovering complementary trait-associated modules, consensus predictions derived from the challenge submissions performed best. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge).
Predicted Changes in Climatic Niche of Alburnus Species -Teleostei:Cyprinidae- in Iran Until 2050

Distribution ranges of many organisms are changing in response to global climate change and human activities. To test the impact of climatic change on distribution range of cyprinid fish species, Species Distribution Modeling (SDM) was used to predict the current climatically suitable habitats and to identify key variables shaping the potential distribution for the genus Alburnus in Iran, an excellent example of high diversity and endemism in the western Palearctic region. Then, future changes in potential suitable areas of the genus Alburnus were evaluated with one future global climatic model (GCM) based on 2050 climatic projection. Results show as a general pattern, basins along the Elburz and Zagros Mountains had highest climatic suitability for the genus in Iran. According to the results of jackknife test and percent contribution of each variable to construct the models, precipitation plays the important role on the distribution of Alburnus species in Iran than temperature. Model outputs show all species likely to be negatively affected by the climate change in future and the currently potential suitable areas were predicted to decrease in the coming decades, suggesting a comprehensive management plan for conservation of this cyprinid fish need to be conducted in the country.
Proximate Composition, Fatty Acid Profile and Mycotoxin Contamination in Several Varieties of Mexican Maize

In Mexico maize (Zea mays L.) is an important cereal due to excellent taste and nutritional value. Nutritional content and fatty acid profile has been reported in white maize, however, there are several genotypes natives (red, yellow, black, blue, pinto), and many improved hybrids maize of which little is known. Fumonisins and aflatoxins are mycotoxins present in 25% of the world’s cereals, mainly in tropical and subtropical regions around the world. This study presents the analysis of proximate composition (ash, protein, lipids), as well as mycotoxins (fumonisins and aflatoxins) and five different fatty acids, two of saturated fatty acids (palmitic and stearic) and three of polyunsaturated fatty acids (oleic, linoleic and linolenic), evaluated by Gas Chromatography and Flame Detector (GC-DF). Thirty varieties of maize (native and hybrid maize) were collected in states of central region. The total fumonisins were determined using the QuickTox TM extraction and quantificated by QuickScan fumonisins; the aflatoxins were analyzed by commercial ELISA kit. The highest protein level was 10.43 g/100g, 5.63 g/100g for fat, 1.62 g/100g for ash in hybrid maize. In native maize, the highest levels of protein and ash were 10.94 g/100g and 1.45 g/100g for pinto maize. The higher value for fat was 5.45 g/100g in yellow maize. The palmitic and stearic acids, in native maize were higher that hybrid maize, for linoleic acid and linoleinic fatty with a significant difference between native corn. Fumonisins and aflatoxins were contaminated in all genotypes of maize, in allow levels. This information obtained may be considered in maize breeding programs, industrialization processes and healthy diets.
Resource Partitioning and Application Scheduling with Module Merging on Dynamically and Partially Reconfigurable FPGAs

Dynamically partially reconfigurable (DPR) technology based on FPGA is applied extensively in the field of high-performance computing (HPC) because of its advantages in processing efficiency and power consumption. To make full use of the advantages of DPR in execution efficiency, we build a DPR system model that meets to the actual application requirements and the objective constraints. According to the consistency of reconfiguration order and dependencies, we propose two algorithms based on simulated annealing (SA). The algorithms partition FPGA resource to several regions and schedule tasks to the regions. In order to improve the performance of the algorithms, we exploit the module merging technology to improve the parallelism of task execution and design a new solution generation method to speed up the convergence speed. Experimental results show that the proposed algorithms have a lower time complexity than mixed-integer linear programming (MILP), iterative scheduler (IS) and Ant Colony Optimization (ACO). For applications with more tasks, the proposed algorithms show performance advantages in producing better partitioning and scheduling results in a shorter time.
Clustering Millimeter Wave Propagation Channels with Watershed Transformation

A clustering method based on image processing is proposed in this paper. It is used to identify clusters in 2D representations of propagation channels. The approach uses operations such as watershed segmentation and is particularly well suited for clustering directional channels obtained by beam-steering at millimeter-wave. This situation occurs for instance with electronic beam-steering using analog antenna arrays during beam training process or during channel modeling measurements using either electronic or mechanical beam-steering. In particular, the proposed technique is used here to cluster two-dimensional power angular spectrum maps. The proposed clustering is unsupervised and is well suited to preserve the shape of clusters, which is useful to obtain more accurate descriptions of channel spatial properties. The approach is found to outperform approaches based on K-Power-Means in terms of accuracy as well as computational resources. The technique is assessed in simulation using IEEE 802.11ad channel model and in measurement using experiments conducted at 60 GHz in an indoor environment.
Trap colour and aggregation pheromone dose affect the catch of western flower thrips in blackberry crops

Frankliniella occidentalis causes significant damage to berry crops in Mexico. Traps may be used for monitoring or mass‐trapping thrips populations. Generally, colour traps are used for monitoring thrips, but sometimes a chemical stimulus can be added to the traps. However, there is conflicting information about what colour is the most attractive and efficient for capturing F. occidentalis. In this study, we first evaluated six colours of adhesive traps for catching F. occidentalis in blackberries grown in tunnels or in an open field. Subsequently, using the most attractive trap colour, we assessed the biological activity of neryl (S)‐2‐methylbutanoate and (R)‐lavandulyl acetate, components of the pheromone aggregation of F. occidentalis. Finally, we examined the effect of neryl (S)‐2‐methylbutanoate dosage rates on the number of captured thrips. We found that blue (tunnel) and yellow (open field) followed by violet traps captured a significantly greater number of F. occidentalis compared with the white, black and green traps. Our results confirm that neryl (S)‐2‐methylbutanoate is the only component necessary for enhancing the performance of coloured traps. Blue and yellow traps baited with 200–400 µg of neryl (S)‐2‐methylbutanoate increased the capture 2.5–3 times compared to unbaited traps. In all experiments, traps captured more females than males in blackberries grown in tunnels, whereas the opposite was found in blackberries cultivated in the open field. These results constitute the first step in the development of a monitoring system for F. occidentalis in soft fruit crops in Mexico.
Lipid-polymer hybrid nanoparticles as a targeted drug delivery system for melanoma treatment

Abstract Aiming to target vitamin D receptors (VDR) expressed in melanoma cells, vitamin D3 functionalized hybrid lipid-polymer nanoparticles (HNP-VDs) comprising a poly(lactic-co-glycolic acid) (PLGA) core and a lipid shell composed of hydrogenated soy phosphatidylcholine (HSPC), cholesterol (CHOL) and 1,2-disteroyl-sn-glycero-3-phosphaethanolamine-N[succinyl(polyethyleneglycol)-2000 (DSPE-PEG2000) were synthesized. The nanocarriers were optimized to a lipid surface area coverage of 97%. In vitro drug release studies showed an initial burst release in the first 24 h followed by diffusive transport. Finally, cellular uptake experiments demonstrated that the HNP-VDs efficiently targeted B16 melanoma cells, thus resulting in a promising vehicle to deliver therapeutics for the melanoma treatment. Graphical Abstract
Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI

Machine learning techniques have been widely used for condition-based monitoring of wind turbines using Supervisory Control & Acquisition (SCADA) data. However, many machine learning models, including neural networks, operate as black boxes: despite performing suitably well as predictive models, they are not able to identify causal associations within the data. For data-driven system to approach human-level intelligence in generating effective maintenance strategies, it is integral to discover hidden knowledge in the operational data. In this paper, we apply deep learning to discover causal relationships between multiple features (confounders) in SCADA data for faults in various sub-components from an operational turbine using convolutional neural networks (CNNs) with attention. Our technique overcomes the black box nature of conventional deep learners and identifies hidden confounders in the data through the use of temporal causal graphs. We demonstrate the effects of SCADA features on a wind turbine’s operational status, and show that our technique contributes to explainable AI for wind energy applications by providing transparent and interpretable decision support.
Evaluation of Intelligent Speech Technology in Epidemic Prevention: Take Iflytek Input Software in Chinese and Japanese Recognition as an Example

This study aims to investigate public’s understanding of intelligent speech technology and to evaluate the word accuracy rate of speech recognition technology in Japanese and Chinese recognition and translation, using the simulating corpus of doctor-patient communication. It is concluded from the questionnaire that currently the public has a high awareness and demand of intelligent speech products. The results of speech recognition experiments show that the word accuracy rates are 99.4% in Mandarin, 96.1% in Japanese, 94.2% in Japanese translation of Chinese, and 82.7% in Chinese translation of Japanese, respectively. In the recognition of Mandarin and Japanese, the errors mainly include missing words and word errors caused by the same or similar pronunciation. In the translation between Japanese and Chinese recognition, the whole sentence omission, sentence patterns, tenses and so on are more common.
Changes in bulk and surface properties of two biochar types during 12 months of field ageing in two West-African soils

The study investigated the changes in properties of rice husk and corn cob biochars applied in urban agricultural field soils in Tamale (northern Ghana) and Ouagadougou (Burkina Faso), respectively. The biochars were both pyrolyzed at 500 °C with a batch reactor. Fine polyethylene mesh (litter bags) filled with 10 g of each type of biochar were buried at 20 cm depth in urban fields trials with a 3 x 2 factorial layout replicated 4 times. Factor 1 involved soil management practices at 3 levels: (1) farmers’ practice (FP), (2) 20 t biochar ha-1 and (3) control (no biochar). The second factor was time (duration) at two levels (6 and 12 months). Aged and fresh biochars were analyzed for volatile matter (VM), ash and fixed carbon (FC) contents, pH, effective cation exchange capacity (ECEC), and total surface acidity (Sa) and basicity (Sb). Dissolved organic carbon contents were determined sequentially by cold (cDOC) and hot water extractions (hDOC), respectively and aromaticities of cold water DOC (cSUVA) and hot water DOC (hSUVA) were determined. There was no significant interaction effect of soil management practices and time on measured ageing biochar properties. Time significantly affected most biochar ageing properties except Sa and Sb in rice husk biochar and ECEC in corn cob biochars at 6 months of exposure. In both biochars, Ash content, Fixed carbon (FC), cDOC, hDOC, cSUVA and hSUVA increased whilst pH and volatile matter contents decreased significantly. The hDOC was 2-3 times higher than cDOC contents for both biochars. Aromaticity of DOC contents of aged rice husk biochar exposed to soil management practices and time in the experimental site in Tamale showed persistence with time compared to corn cob biochar exposed in Ouagadougou experimental site. The results imply that rainfall, soil organic matter contents with interplay of soil minerals are key drivers to ageing and sequestration of these biochars and that these forces act at different scales but driven by time.