Distribution Map Research Articles

Description of a new Psalmopoeus Pocock, 1895 species (Araneae, Theraphosidae, Psalmopoeinae) from the Chocó region of Ecuador

A new species of Theraphosidae, genus Psalmopoeus Pocock, 1895 is described from the Chocó region of Ecuador, Psalmopoeus pristirana n. sp. (male and female). The identity of the female of the recently described Psalmopoeus satanas Peñaherrera-R. & León-E., 2023 is discussed. Images of Psalmopoeus ecclesiasticus Pocock, 1903 are given for comparison and a distribution map of all Ecuadorian Psalmopoeus species is presented.

Artemisia Frigida Distribution Mapping in Grassland with Unmanned Aerial Vehicle Imagery and Deep Learning

Artemisia frigida, as an important indicator species of grassland degradation, holds significant guidance significance for understanding grassland degradation status and conducting grassland restoration. Therefore, conducting rapid surveys and monitoring it is crucial. In this study, to address the issue of insufficient identification accuracy due to the large density and small size of Artemisia frigida in UAV images, we improved the YOLOv7 object detection algorithm to enhance the performance of the YOLOv7 model in Artemisia frigida detection. We applied the improved model to the detection of Artemisia frigida across the entire experimental area, achieving spatial mapping of Artemisia frigida distribution. The results indicate: In comparison across different models, the improved YOLOv7 + Biformer + wise-iou model exhibited the most notable enhancement in precision metrics compared to the original YOLOv7, showing a 6% increase. The mean average precision at intersection over union (IoU) threshold of 0.5 (mAP@.5) also increased by 3%. In terms of inference speed, it ranked second among the four models, only trailing behind YOLOv7 + biformer. The YOLOv7 + biformer + wise-iou model achieved an overall detection precision of 96% and a recall of 94% across 10 plots. The model demonstrated superior overall detection performance. The enhanced YOLOv7 exhibited superior performance in Artemisia frigida detection, meeting the need for rapid mapping of Artemisia frigida distribution based on UAV images. This improvement is expected to contribute to enhancing the efficiency of UAV-based surveys and monitoring of grassland degradation. These findings emphasize the effectiveness of the improved YOLOv7 + Biformer + wise-iou model in enhancing precision metrics, overall detection performance, and its applicability to efficiently map the distribution of Artemisia frigida in UAV imagery for grassland degradation surveys and monitoring.

Temperature imaging inside fluid devices using a ratiometric near infrared (NIR-II/III) fluorescent Y2O3: Nd3+, Yb3+, Er3+ nanothermometer.

Luminescence thermometry is a non-contact method that can measure surface temperatures and the temperature of the area where the fluorescent probe is located, allowing temperature distribution visualizations with a camera. Ratiometric fluorescence thermometry, which uses the intensity ratio of fluorescence peaks at two wavelengths with different fluorescence intensity dependencies, is an excellent method for visualizing temperature distributions independent of the fluorophore spatial concentration, excitation light intensity and absolute fluorescence intensity. Herein, Nd3+/Yb3+/Er3+-doped Y2O3 nanomaterials with a diameter of 200nm were prepared as phosphors for temperature distribution measurement of fluids at different temperatures. The advantages of this designed fluorescent material include non-aggregation in water and the fact that its near-infrared (NIR) fluorescence excitation (808nm) is not absorbed by water, thereby minimizing sample heating upon irradiation. Under optical excitation at 808nm, the ratio of the fluorescence intensities of Yb3+ (IYb; 975nm) and Er3+ (IEr; 1550nm), which exhibited different temperature responses, indicated the temperature distribution inside the fluid device. Thus, this technique using Nd3+/Yb3+/Er3+-doped Y2O3 is expected to be applied for temperature distribution mapping analysis inside fluidic devices as a ratiometric NIR fluorescence thermometer, which is unaffected by laser-induced heating.

Moorish Viper, Daboia mauritanica (Gray, 1849) (Squamata, Viperidae), in Algeria: new provincial records, range extension, and an update on its distribution

 Daboia mauritanica (Gray, 1849), Moorish Viper, is native to North Africa. We update the distribution map for this species in Algeria, providing 19 new locality records, filling distribution gaps and significantly expanding the species’ known range. Our updated distribution map reveals a widespread presence of the species in northern Algeria, extending south into the northern Sahara. We note that some historical records in certain provinces remain unconfirmed and/or questionable, indicating the need for further investigation. Our findings underscore the importance of collaboration between researchers and citizen scientists in Algeria.

In Situ Nondestructive Detection of Nitrogen Content in Soybean Leaves Based on Hyperspectral Imaging Technology

In this paper, hyperspectral imaging technology, combined with chemometrics methods, was used to detect the nitrogen content of soybean leaves, and to achieve the rapid, non-destructive and in situ detection of the nitrogen content in soybean leaves. Soybean leaves under different fertilization treatments were used as the research object, and the hyperspectral imaging data and the corresponding nitrogen content data of soybean leaves at different growth stages were obtained. Seven spectral preprocessing methods, such as Savitzky–Golay smoothing (SG), first derivative (1-Der), and direct orthogonal signal correction (DOSC), were used to establish the quantitative prediction models for soybean leaf nitrogen content, and the quantitative prediction models of different spectral preprocessing methods for soybean leaf nitrogen content were analyzed and compared. On this basis, successive projections algorithm (SPA), genetic algorithm (GA) and random frog (RF) were employed to select the characteristic wavelengths and compress the spectral data. The results showed the following: (1) The full-spectrum prediction model of soybean leaf nitrogen content based on DOSC pretreatment was the best. (2) The PLS model of soybean leaf nitrogen content based on the five characteristic wavelengths had the best prediction performance. (3) The spatial distribution map of soybean leaf nitrogen content was generated in a pixel manner using the extracted five characteristic wavelengths and the DOSC-RF-PLS model. The nitrogen content level of soybean leaves can be quantified in a simple way; this provides a foundation for rapid in situ non-destructive detection and the spatial distribution difference detection of soybean leaf nitrogen. (4) The overall results illustrated that hyperspectral imaging technology was a powerful tool for the spatial prediction of the nitrogen content in soybean leaves, which provided a new method for the spatial distribution of the soybean nutrient status and the dynamic monitoring of the growth status.

Hegnera obcordata (Fabaceae: Desmodieae), a newly recorded genus and species for the flora of China

Hegnera obcordata (Miq.) Schindl., is reported here as a newly recorded genus and species for the flora of China. It was collected from Xishuangbanna, Yunnan Province and Changjiang, Hainan Province. As a member of the tribe Desmodieae, H. obcordata can be easily distinguished from other genera by its climbing habit, depressed obovate terminal leaflet with an obcordate apex, and pods with U-shaped articles and deeply indented upper sutures. This study provides a detailed morphological description, phenology, distribution map and colored photographs of H. obcordata. Additionally, an updated dichotomous key to the Chinese Desmodieae genera is provided.

Taxonomic revision of the Neotropical skipper genus Incisus Grishin, 2019 (Lepidoptera, Hesperiidae, Pyrginae), with the description of a new species

The taxonomy of the genus Incisus Grishin, 2019 is reviewed, including redescriptions of known species, the description of a new species, Incisus mineirus sp. nov., identification keys, and an updated distribution map. Images of the genitalia for each species are included, with the female genitalia being illustrated for the first time. A lectotype and paralectotype for Antigonus incisus Mabille, 1878, and neotypes for Staphylus ordinarius Hayward, 1933 and Nisoniades aterea Plötz, 1884, are designated. Staphylus ordinarius Hayward, 1933 is a syn. nov. of Incisus fasciatus (Hayward, 1933). Antigonus variegatus Mabille, 1878 is a syn. nov. of Nisoniades macarius Herrich-Schäffer, 1870, and Staphylus dentivittata Hayward, 1933 is a syn. nov. of Staphylus musculus (Burmeister, 1875). Additionally, the subgeneric name Stolla Grishin, 2023 is a syn. nov. of Uniphylus Lemes, Siewert, Mielke, Casagrande & Warren, 2023.

An enigmatic Anthophorine bee from the south of France revealed as a new species: Anthophora (Paramegilla) ahlamae n. sp. (Hymenoptera: Apidae)

Summary A bee specimen identified as Anthophora planca Pérez, 1895, from France, was discovered in collections of Museum für Naturkunde, Berlin. This male specimen presents a morphology that does not conform to any of the Anthophora Latreille, 1803 species known from France, or indeed from Europe. After careful examination, it cannot be identified as Anthophora planca Pérez which is considered to be a nomen dubium (type lost), but furthermore it does not belong to any currently described species. Additional specimens of this species were collected in Morocco, Spain (Melilla) and Algeria. The new species is named Anthophora (Paramegilla) ahlamae Rasmont & Wood, n. sp. The new species is documented by numerous high-resolution photographs. Its diagnosis is compared with the near species Anthophora (Paramegilla) gallica (Dalla Torre & Friese, 1895) and A. (Paramegilla) podagra Lepeletier, 1841. DNA barcodes data are presented, allowing for confirmation of placement within the subgenus Paramegilla Friese, 1897. A detailed distribution map is provided along with ecological observations. Anthophora ahlamae n. sp. may be specialised on flowers of the genus Ballota L. (Lamiaceae).

Neea bradeana (Nyctaginaceae: Pisonieae), a new species with whorled leaf arrangement from the Atlantic Forest of Southeastern Brazil

Neea bradeana is here described for the Atlantic Rainforest of Southeastern Brazil. This new species had been confused for decades with N. verticillata, the type species of the genus which is described for Peru. N. bradeana is characterized by its unbranched shrubs with whorled sessile or short-petiolate leaves and erect-congested inflorescences. This species is here described and illustrated; remarks on taxonomic and morphologic affinities, distribution map, and conservation assessment are also provided.

[Analysis of changes in intrinsic neural timescales in male smoking addicts based on whole brain resting-state functional magnetic resonance imaging].

Objective: To investigate the abnormal changes of intrinsic neural time scale (INT) in male smoking addicts based on whole brain resting state functional magnetic resonance imaging (rs-fMRI). Methods: A case-control study. The clinical data and whole brain rs-fMRI data of 139 male subjects, aged (34.1±8.8) years, recruited through the online platform from January 2019 to December 2021 were retrospectively analyzed. According to the existence of smoking addiction, they were divided into smoking addiction group (n=83) and healthy control group (n=56).INT was calculated to reflect the brain neural activity dynamics. Single sample t test was used to obtain the whole brain spatial distribution maps of INT in smoking addiction group and the control group. Then two-sample t test was conducted to explore the difference of INT between the smoking addition group and the healthy control group, with age and years of education as covariates. Finally, Spearman correlation analysis was used to explore the relationship between INT and nicotine dependence scale score and smoking index. Results: Subjects with smoking addiction and healthy control group showed a similar pattern of hierarchical neural timescales, namely shorter INT in sensorimotor areas and longer INT in parietal lobe, posterior cingulate cortex. In addition, in the smoking addiction group, the left medial occipital gyrus (peak t=-3.18), left suproccipital gyrus (peak t=-3.66), bilateral pericalar cleft cortex (left: peak t=-3.02, right: peak t=-3.22), bilateral lingual gyrus (left: peak t=-3.10, right: t peak=-3.04), left cuneus (peak t=-2.97), default network associated brain region [left anterior cuneus(peak t=-3.23), left angular gyrus (peak t=-3.07), and left posterior cingulate cortex (peak t=-3.54) were significantly lower than those of healthy controls (gaussian random field correction, voxel level all P<0.005, mass level all P<0.05). However, there was no significant correlation between INT and nicotine dependence scale score and smoking index (both P>0.05 after Bonferroni correction). Conclusion: Compared with healthy controls, smoking addicts showed abnormal changes in the dynamics of neural activity in the visual cortex and the default network.

PECT Composite Defect Detection Algorithm Based on DualGAN

To address the problems of insufficient accuracy and slow reconstruction speed of Planar Electrical Capacitance Tomography (PECT) detection of damaged specimens, a Dual Generative Adversarial Networks (DualGAN)-based PECT image defect detection method is proposed in this paper. The improved particle swarm algorithm with adaptive particle number and L2-norm is used to optimize the sensitivity field, combined with the parallel Landweber algorithm to solve the PECT inverse problem to obtain the dielectric constant distribution map. In the DualGAN network, the Unet generator utilizes an Adam-based local attention mechanism to adjust module weights, facilitating feature extraction and the generation of high-quality transformation images of the Landweber dielectric constant distribution. A PatchGAN discriminator is employed to distinguish between transformation images and real images, using the generated transformation images as target images. Experimental results demonstrate that the sensitivity field, enhanced by the improved particle swarm algorithm and L2-norm normalization, achieves better balance. Furthermore, the addition of a network transformation using the Adam-based local attention weight mechanism on the DualGAN network reduces artifacts in the reconstructed images, resulting in more accurate PECT reconstructions. The PECT image defect detection method, integrating DualGAN, an improved particle swarm optimization algorithm, and a local attention mechanism, has made significant strides in addressing challenges related to image reconstruction accuracy and speed. This technological advancement has enhanced the precision and efficiency of defect detection in carbon fiber composite materials, thereby fostering the broader utilization of planar capacitance tomography technology in industrial damage detection and material defect analysis.

Diffusion calculations on reconstructed bentonite microstructures with anion exclusion effects.

Due to their prevalence in the lithosphere and their high capability of sorbing pollutants, smectite clays play a foreground role in environmental pollution studies, waste management, and soil science. In complementarity with existing approaches at the molecular or macroscopic scales, real microstructures have been employed to investigate ionic transport by diffusion through montmorillonite and water-saturated Wyoming bentonite at intermediate scales ranging between the nanometer and the micrometer. The coupled solute transport and electrostatic phenomena investigated at the nanopore scale are upscaled using the homogenization of porous media approach. Homogenization computations rely on a hierarchical description of bentonite that acknowledges the existence of pores networks at different scales. At the scale of montmorillonite layers, digitized TEM images have been employed to simulate the diffusion of ionic solutes by considering electrostatic interactions in the vicinity of the negatively charged clay platelets' surface. Finite element microstructures are created after extraction of the contours of the layers using dedicated image processing algorithms. Local electric potential distribution, anion exclusion, and cation inclusion are displayed by ion distribution maps. The effective diffusion tensor and the transport equation obtained through volume averaging are then used to simulate diffusion at the scale of a Wyoming bentonite sample composed of clay gels of variable density, solid grains, and micropores. Qualitative comparisons were made with existing diffusion data, and a particular attention is given to the anisotropy of the diffusion tensors at both the mesoscopic and macroscopic scales.

A novel framework for urban flood risk assessment: Multiple perspectives and causal analysis

Risk assessment and adaptation have become key focuses in the examination of urban flooding risk. In recent decades, global climate change has resulted in a high incidence of extreme weather events, notably flooding. This study introduces a spatial multi-indicator model developed for assessing flood risk at the urban agglomeration scale. A crucial addition to the model is the incorporation of an adaptive capacity within the IPCC risk framework. The model systematically considers various flood risk indicators related to the economic, social, and geographic environments of the central and southern Liaoning urban agglomeration (CSLN). It generates a spatial distribution map of integrated flood risk for multiple scenario combinations. Furthermore, the intricate relationship between different risk indicators and flood risk was analyzed using correlation analysis and the Light Gradient Boosting Machine model (Light GBM). The findings reveal notable variations in flood risk under different scenarios. The inclusion of vulnerability indicators increased flood risk by 33 %, while the subsequent inclusion of adaptive indicators decreased flood risk by 45 %. Dense populations and assets contribute to high flood risk, while adaptive capacity significantly mitigates urban flood risk. The framework adopted in this paper can be applied to other areas where urban agglomeration-scale flood risk assessment is needed, and can contribute to advancing scientific research on flood forecasting and mitigation.

Lesion Frequency Distribution Maps of Traumatic Axonal Injury on Early Magnetic Resonance Imaging after Moderate and Severe Traumatic Brain Injury and Associations to 12 Months Outcome.

Traumatic axonal injury (TAI) is a common finding on MRI in patients with moderate - severe traumatic brain injury (TBI), and the burden of TAI is associated with outcome in this patient group. Lesion mapping offers a way to combine imaging findings from numerous individual patients into common lesion maps where the findings from a whole patient cohort can be assessed. The aim of this study was to evaluate the spatial distribution of traumatic axonal injury (TAI) lesions on different MRI sequences and its associations to outcome with use of lesion mapping. 269 patients (8-70 years) with moderate or severe TBI traumatic brain injury and magnetic resonance imaging (MRI) within six weeks after injury were prospectively included. TAI lesions were evaluated and manually segmented on fluid-attenuated inversed recovery (FLAIR), diffusion weighted imaging (DWI) and either T2* gradient echo (T2*GRE) or susceptibility weighted imaging (SWI). The segmentations were registered to the Montreal Neurological Institute space and combined to lesion frequency distribution maps. Outcome was assessed with Glasgow Outcome Scale Extended (GOSE) score at 12 months. The frequency and distribution of TAI was assessed qualitatively by evaluated visually reading. Univariable associations to outcome was assessed qualitatively by visual reading evaluated visually and also quantitatively with use of voxel-based lesion-symptom mapping (VLSM). The highest frequency of TAI was found in the posterior half of corpus callosum. The frequency of TAI was higher in the frontal- and temporal lobes than in the parietal- and occipital lobes, and in the upper parts of the brainstem than in the lower. On At the group level, all the voxels in mesencephalon had TAI on FLAIR. The patients with poorest outcome (GOSE scores ≤ 4) had higher frequencies of TAI. On VLSM, poor outcome was associated with TAI lesions univariable associations to outcome was found bilaterally in the splenium, and in the right side of tectum, tegmental mesencephalon and pons. With this study, we present lesion frequency distribution maps of TAI in a large cohort of patients with moderate and severe TBI. In conclusion, we found the highest higher frequency of TAI in posterior corpus callosum, and TAI in splenium, mesencephalon and pons were associated to with poor outcome. In the future, integration into picture archiving systems would enable comparison of individual patient maps with If lesion frequency distribution maps containing outcome information based on imaging findings from numerous patients in the future can be compared to the imaging findings from individual patients, it would offer a new tool in the clinical work-up and outcome prediction of TBI patient. Key Words: Brain injuries, traumatic; Diffuse axonal injury; Neuroimaging; Brain mapping; Artificial intelligence.

THREE NEW SPECIES OF DIXELLA DYAR &amp; SHANNON (DIPTERA: DIXIDAE) FROM SANTA CATARINA, BRAZIL

We describe three new species of Dixella Dyar &amp; Shannon: Dixella moultoni sp. nov., Dixella jailtoi sp. nov., and Dixella spinosa sp. nov., and record Dixella limai (Santos, 1940) and Dixella trinitensis (Lane, 1943) from the state of Santa Catarina, Brazil. The new species can be distinguished by coloration of the thorax and morphology of the male and female terminalia (except Dixella jailtoi, the female of which is unknown). This represents the first record of Dixidae for Santa Catarina, as well as for the Southern Region of Brazil. An identification key as well as distribution map for these species are provided.

Residual stress distribution of silicon wafers machined by rotational grinding based on molecular dynamics

Wafer rotational grinding is widely used to thin silicon wafers and the grinding-induced residual stress distribution is desired to be known. However, it is difficult to obtain it directly by measurement since the variation of residual stress values of different locations tends to be submerged in the fluctuations of measured values. In this study, molecular dynamics was employed to obtain the residual stress states of ground monocrystalline silicon of different crystal directions. The actual cutting directions of the abrasive grains were obtained as the tangential directions of the abrasive grain's traces on the silicon wafer surface relative to the crystal coordinate system. It was found that the actual cutting direction of an abrasive grain along a single grinding trace would change from the center to the edge of the silicon wafer since the grinding traces are curved lines. The residual stress state at a specific point on the wafer surface was obtained by mapping the residual stress values obtained by molecular dynamics to the actual cutting direction. The residual stress distribution map was obtained successfully and any point of the ground silicon wafer could be known. The location of maximum residual stress was found to deviate from the [1 1 0] crystalline direction on the ground wafer due to the change in the actual cutting direction relative to it.

Winter Wheat Yield Estimation with Color Index Fusion Texture Feature

The rapid and accurate estimation of crop yield is of great importance for large-scale agricultural production and national food security. Using winter wheat as the research object, the effects of color indexes, texture feature and fusion index on yield estimation were investigated based on unmanned aerial vehicle (UAV) high-definition digital images, which can provide a reliable technical means for the high-precision yield estimation of winter wheat. In total, 22 visible color indexes were extracted using UAV high-resolution digital images, and a total of 24 texture features in red, green, and blue bands extracted by ENVI 5.3 were correlated with yield, while color indexes and texture features with high correlation and fusion indexes were selected to establish yield estimation models for flagging, flowering and filling stages using partial least squares regression (PLSR) and random forest (RF). The yield estimation model constructed with color indexes at the flagging and flowering stages, along with texture characteristics and fusion indexes at the filling stage, had the best accuracy, with R2 values of 0.70, 0.71 and 0.76 and RMSE values of 808.95 kg/hm2, 794.77 kg/hm2 and 728.85 kg/hm2, respectively. The accuracy of winter wheat yield estimation using PLSR at the flagging, flowering, and filling stages was better than that of RF winter wheat estimation, and the accuracy of winter wheat yield estimation using the fusion feature index was better than that of color and texture feature indexes; the distribution maps of yield results are in good agreement with those of the actual test fields. Thus, this study can provide a scientific reference for estimating winter wheat yield based on UAV digital images and provide a reference for agricultural farm management.

Xiphinema bricolense Ebsary, Vrain &amp; Graham

Abstract A new distribution map is provided for Xiphinema bricolense Ebsary, Vrain &amp; Graham Enoplea: Dorylaimida: Longidoridae Host: Undetermined but probably polyphagous.

Raspberry leaf mottle virus

Abstract A new distribution map is provided for Raspberry leaf mottle virus Closteroviridae: Closterovirus Host: Rubus spp.

Between the lines: Life cycle impact assessment models of collision and electrocution impacts of power lines on bird diversity in Norway

AbstractThe expansion of the electric grid is inevitable. Renewable energy is on the rise, and new transmission lines must be built to link new electricity production facilities with the local network. In addition, higher electricity demand due to electrification will lead to the growth of the distribution grid. However, further construction of power lines will affect the local biodiversity. Birds are especially vulnerable: every year, power lines cause the deaths of hundreds of millions of birds by collision and electrocution. Yet the environmental impacts of the electric grid in life cycle assessment (LCA) are limited to a few impact categories, failing to cover the area of protection for damages to ecosystem quality. We developed the first methodology to quantify power lines' collision and electrocution impacts on bird richness within LCA. We calculated the potentially disappeared fraction of species (PDF) by developing species–area relationships using high‐resolution species distribution maps, species‐specific characteristics, and the location of power lines and pylons. We applied our models to Norway, a country that aims to become a low‐emission nation by 2050. The characterization factors ranged between 8.48 × 10−16 and 5.6 × 10−15 PDF*yr/kWh for collision and 3.27 × 10−18 and 1.66 × 10−16 PDF*yr/kWh for electrocution. Integrating power lines’ impacts on biodiversity in LCA is essential, as harmonized models can estimate the effects of electricity production alongside the impacts of electricity distribution. This brings us a step further in promoting a holistic assessment of energy systems.