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  • The three-dimensional (3-D) image-based TPS (RT-RSI, Beijing Atom and High Technique Industries Inc, Beijing, China) was applied to delineate the shape and calculate the maximum cross-section (axial section) and volume of preoperative tumor and postoperative ablation range (a medical physicist, designed and corrected the calculation). We used TPS to sketch the 3-D shape of the tumor and ablation range, as shown in Fig. 5. Preoperative maximum tumor area (PreMTA) and preoperative tumor volume (PreTV) were the largest cross-sectional area and the volume of CT image of the tumor before ablation, respectively. Postoperative maximum ablation area (PostMAA) and postoperative ablation volume (PostAV) were the largest cross-sectional area and the volume of CT image of ablation necrosis after the procedure, respectively. Two of the authors (Dr. Zhenkang Qiu and Dr. Guobao Wang) were in charge of delineating work, and the TPS calculated PreMTA, PreTV, PostMAA and PostAV automatically. Volume ratio was calculated as the volume in a cubic centimetre PostAV divided by PreTV. Area ratio was calculated as the area in square centimetre PostMAA divided by PreMTA. Contrast-enhanced CT or MR scans were performed in all patients one month after treatment for evaluating tumor response to thermal ablation. Based on the follow-up CT or MR results, the technique effectiveness was determined as described elsewhere. The ablation was considered a success when all of the following findings were observed at follow-up CT or MR scans. We were in charge of collecting follow-up data, including the level of tumor sizes, the existence of a residual tumor, tumor recurrence, progression of the primary tumor and the overall condition of each patient. The data were acquired using CT or MR scans, direct patient contact, or review of medical records stored in the Department of Medical Records of Sun Yat-sen University Cancer Center.
    Data Types:
    • Tabular Data
    • Dataset
  • Supplement Table 1. Frequency of sensitization to allergens from the patch test in allergic contact dermatitis patients. Supplement Table 2. Correlations of total eosinophil count, total IgE, and disease duration with serum ECP in ACD and non-ACD groups. Supplement Table 3. Comparison of serum allergy markers between ACD and AD-ACD groups. Supplement Figure 1. (A) ROC curve testing whether serum ECP differentiates ACD from non-ACD patients (B) ROC curve testing of total IgE. ROC, Receiver operating characteristic; AUC, Area under curve Supplement Figure 2. Dermal eosinophil density from skin biopsy specimens of ACD patients was not correlated with their serum ECP levels (r = 0.21, p = 0.82). Among the study patients, 15 patients underwent a skin biopsy of lesional skin. Two board-certified dermatologists (J.H.K and Y.I.L) independently reviewed the hematoxylin and eosin sections. The presence of eosinophilic spongiosis and dermal eosinophil density were scored in a semi-quantitative manner. HPFs, High power fields.
    Data Types:
    • Dataset
    • Document
  • Modification of nighttime light levels by artificial illumination (artificial light at night; ALAN) is a rapidly increasing form of human disturbance that affects natural environments worldwide. Light in natural environments influences a variety of physiological and ecological processes directly and indirectly and, as a result, the effects of light pollution on species, communities and ecosystems are emerging as significant. Small prey species may be particularly susceptible to ALAN as it makes them more conspicuous and thus more vulnerable to predation by visually oriented predators. Understanding the effects of disturbance like ALAN is especially important for threatened or endangered species as impacts have the potential to impede recovery, but due to low population numbers inherent to at-risk species, disturbance is rarely studied. The endangered Stephens’ kangaroo rat (SKR), Dipodomys stephensi, is a nocturnal rodent threatened by habitat destruction from urban expansion. The degree to which ALAN impacts their recovery is unknown. In this study, we examined the effects of ALAN on SKR foraging decisions across a gradient of light intensity for two types of ALAN, flood and bug lights (756 vs 300 lumen, respectfully) during full and new moon conditions. We found that ALAN decreased probability of resource patch depletion compared to controls. Moreover, lunar illumination, distance from the light source and light type interacted to alter SKR foraging. Under the new moon, SKR were consistently more likely to deplete patches under control conditions, but there was an increasing probability of patch depletion with distance from the source of artificial light. The full moon dampened SKR foraging activity and the effect of artificial lights. Our study underscores that ALAN reduces habitat suitability, and raises the possibility that ALAN may impede the recovery of at-risk nocturnal rodents. Main conclusion: Artificial light source, moon phase and distance to light interact to negatively impact foraging energetics of endangered kangaroo rats, which has implications for management and recovery of nocturnal prey species.
    Data Types:
    • Tabular Data
    • Dataset
  • From CloudResearch, collected in exchange for 3 dollars
    Data Types:
    • Tabular Data
    • Dataset
  • Today the sector has emerged as the first degree, and we are shifting ahead with the common motive of shielding the surroundings and attaining sustainable improvement. The new marketing philosophy is getting stronger some of the hundreds, and this mindset of the clients has forced the enterprise fraternity to rethink and plan their techniques to do their businesses in a more revolutionary and environmentally pleasant way. This paper targeted some critiques of green marketing and advertising, idea, new green projects in India and unique advertising blend. This paper moreover highlighted the destiny prospects of Green marketing in India. Keywords: Green Marketing- Practices- Marketing Mix.
    Data Types:
    • Dataset
    • Document
  • Data from Busack et al., 2020, Journal of Neurogenetics
    Data Types:
    • Tabular Data
    • Dataset
  • Dataset accompanying the paper "Presence of CD3+ and CD79a+ lymphocytes in the pituitary gland of dogs at post mortem examination". The dataset consists of a comma-separated values (CSV) file with data from 20 dogs recruited at routine necropsy to investigate presence and distribution of lymphocytes in pituitary glands in dogs with no suspicion of pituitary disease. The pituitary glands were collected at the Section of Pathology, Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, from November 2013 to February 2014, and April 2017 to September 2017. Formalin-fixed paraffin-embedded pituitary sections were stained with haematoxylin and eosin (H&E) or subjected to immunohistochemistry (IHC) using primary antibodies specific for the T-cell marker CD3 and B-cell marker CD79a. The number of CD3+ and CD79a+ cells per area unit (CPA, cells/mm²) was determined for different pituitary regions: pars tuberalis (PT), pars distalis (PD), pars intermedia (PI), infundibulum (In), and lobus nervosus (LN). The dataset contains information about: • Identification and signalement — fields: ID, Breed, Age (years of age at necropsy), Sex, Neutering status • Concurrent pathological findings — field: Necropsy diagnosis (multiple diagnoses are separated by semicolon) • Morphologic changes in the pituitary gland — fields: Pituitary lesion, Pituitary lesion group (No, Limited or Extensive lesion) • Number of CD3+ CPA (cells/mm²) in each pituitary region* — fields: PT CD3 CPA, PD CD3 CPA, PI CD3 CPA, In CD3 CPA, LN CD3 CPA • Number of CD79a+ CPA (cells/mm²) in each pituitary region* — fields: PT CD79a CPA, PD CD79a CPA, PI CD79a CPA, In CD79a CPA, LN CD79a CPA ____________ *PT, pars tuberalis; PD, pars distalis; PI, pars intermedia; In, infundibulum; LN, lobus nervosus
    Data Types:
    • Tabular Data
    • Dataset
  • The data consist of Agro-meteorological factors influencing a crop growth for major crops of Indian state Tamilnadu. The data also host the various crops grown in 37 districts of the state in binary format.This data is a part of the data used for a crop recommendation system by forecasting various climatic factors.The data are stocked from various journals and government websites.citers can get information about the optimum range of agro-meteorlogical factors for individual crops. This dataset contains information about 107 crops, citers can develop it by adding crops and various other agro-meteorlogical factors.
    Data Types:
    • Tabular Data
    • Dataset
  • Purpose: The aim of this study was to assess the reliability of singleshot 2-dimensional multislice late gadolinium enhancement (2DMSLGE) compared with gold standard single-slice 2D inversion recovery segmented gradient echo (2D-SSLGE). Materials and Methods: Sixty-seven patients prospectively underwent clinically indicated cardiac magnetic resonance (CMR) imaging and were enrolled. The image quality was assessed using a 4-point scale. Segments positive for LGE were classified as ischemic or nonischemic for 2D-MSLGE and 2D-SSLGE. Interobserver and intraobserver variability was assessed for both sequences by 2 readers. The endpoints were as follows: (a) detection of myocardial segments involved by LGE and (b) classification of LGE as ischemic and nonischemic pattern. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy value were calculated for the 2 endpoints. Results: 2D-MSLGE and 2D-SSLGE were successfully performed in all patients with comparable image quality (1.56±0.59 vs. 1.54±0.58, P=0.84). For the overall population, 2D-MSLGE correctly identified 1093 of 1139 myocardial segments positive for LGE (96%; 95% confidence interval [CI]: 95%-97%), as compared with 2D-SSLGE. Similarly, 2D-MSLGE correctly identified 1128 of 1139 (99%; 95% CI: 98%-99%) and 1108 of 1139 (97%; 95% CI: 96%- 98%) of nonischemic and ischemic LGE patterns. Interobserver and intraobserver variability for quantification of LGE using 2DMSLGE was 0.98 and 0.99, respectively. The acquisition time was shorter for 2D-MSLGE as compared with 2D-SSLGE (2.0±0.5 vs. 6.0 ±2.0 min, P: 0.01). Conclusions: As compared with 2D-SSLGE, 2D-MSLGE is a reliable tool in both ischemic and nonischemic cardiac disease; it is associated with shorter scan times without the need for prolonged breath holding and may be beneficial for those with dysrhythmia.
    Data Types:
    • Tabular Data
    • Dataset
  • The data were collected as described in (https://doi.org/10.1016/j.scitotenv.2019.134195 and http://dx.doi.org/10.17632/p64dtjx7rj.1). The raw MID-IR (MID-Infra-red) data (http://dx.doi.org/10.17632/p64dtjx7rj.1) was used to determine total C in biosolids using two approaches - full spectral and selected wavelengths methods. For the full spectral method, the raw data was mean-centred and PCA analysis was carried out to remove abnormal samples. After the removal of abnormal samples, the full spectral data (located in the full spectral folder) was divided into two data set, the training set (approximately 2/3) and test set (approximately 2/3). The full spectra training set and test set data were saved in files named ‘Full spectra training set.xlsx’ and ‘Full spectra test set.xlsx’, respectively. For the selected wavelength method, wavenumbers that had a correlation coefficient > 0.5 with total C were selected. The remainder of the spectral data was deleted. The data was then analysed by PCA to remove any abnormal samples and divided into training and test set, similar to the full spectral method. The data containing both total C and MID IR data was stored in the selected wavelength folder and given the filenames ‘Selected wavelength training set.xlsx’ and ‘Selected wavelengths test set.xlsx’. A full description of how the data was used is provided in (https://doi.org/10.1016/j.scitotenv.2019.134195).
    Data Types:
    • Tabular Data
    • Dataset
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