bluuebunny/crossref_metadata_2025_split huggingface dataset:
A preliminary environmental analysis for a sustainable pyrolysis process of Acacia tortilis encroacher bush.
Authors: Charis Gratitude , Muzenda Edison , Danha Gwiranai 
Published: February 2021

Abstract
A shortcut method of environmental assessment was applied procedurally to an Acacia Tortillis pyrolysis project which is in early stages of process development. The method uses mass balance data from the process simulation, which is done in ChemCAD. The ChemCAD model was developed using characterization data for raw biomass and the product bio-oil and data from literature. The shortcut assessment method started off by scoring the impact of inputs and outputs as high (A=1), medium (B= 0.3) and very low (C= 0) under impact categories such as raw material availability, use of critical materials, chronic toxicity, global warming potential, odour and eutrophication potential. An aggregated metric called the general effect index (GEI) was then calculated using this data and mass indices derived from mass balance. The GEI was calculated for inputs, outputs and the overall process. It fell within the scale of 0-1, with values below 0.5 indicating a low environmental impact, while those above that threshold indicated high impact. A GEI of 0 for the inputs reflected on the renewability of biomass and neutral impact of nitrogen and air. A GEI of 0.370 for the outputs showed they do have a significant effect on the environment and organisms, though overall, the process is relatively benign. The impact could be further reduced by utilizing the fuel gas waste stream which has a high methane content. The results obtained generally tally with other literary findings on biomass pyrolysis.
MS-AFF: A Novel Semantic Segmentation Approach for Buried Object Based on Multi-scale Attentional Feature Fusion
Authors: Lu Chao , Chen Fansheng , Su Xiaofeng , Zeng Dan 
Published: February 2021

Abstract
Infrared technology is a widely used in precision guidance and mine detection since it can capture the heat radiated outward from the target object. We use infrared (IR) thermography to get the infrared image of the buried obje cts. Compared to the visible images, infrared images present poor resolution, low contrast, and fuzzy visual effect, which make it difficult to segment the target object, specifically in the complex backgrounds. In this condition, traditional segmentation methods cannot perform well in infrared images since they are easily disturbed by the noise and non-target objects in the images. With the advance of deep convolutional neural network (CNN), the deep learning-based methods have made significant improvements in semantic segmentation task. However, few of them research Infrared image semantic segmentation, which is a more challenging scenario compared to visible images. Moreover, the lack of an Infrared image dataset is also a problem for current methods based on deep learning. We raise a multi-scale attentional feature fusion (MS-AFF) module for infrared image semantic segmentation to solve this problem. Precisely, we integrate a series of feature maps from different levels by an atrous spatial pyramid structure. In this way, the model can obtain rich representation ability on the infrared images. Besides, a global spatial information attention module is employed to let the model focus on the target region and reduce disturbance in infrared images' background. In addition, we propose an infrared segmentation dataset based on the infrared thermal imaging system. Extensive experiments conducted in the infrared image segmentation dataset show the superiority of our method.
A Noise Robust Automatic Radiolocation Animal Tracking System
Authors: Wang Liang , Diakogiannis Foivos , Mills Scott , Bajema Nigel , Atkinson Ian , Bishop-Hurley Greg , Charmley Ed 
Published: February 2021

Abstract
Agriculture is becoming increasingly reliant upon accurate data from sensor arrays, with localization an emerging application in the livestock industry. Ground-based Time Difference of Arrival (TDoA) radiolocation methods have the advantage of being lightweight and exhibit higher energy effciency than methods reliant upon Global Navigation Satellite System (GNSS). Such methods can employ small primary cell batteries, rather than rechargeable cells, and still deliver a multi-year deployment. In this paper, we present a novel deep learning algorithm adapted from a one dimensional U-Net like a convolutional neural network (CNN) model, originally developed for the task of semantic segmentation. This model both converts TDoA sequences directly to positions and reduces positional errors introduced by sources such as multipathing. We have evaluated the model by using simulated animal movements in the form of TDoA position sequences in combination with known distributions of TDoA error. When errors with a standard deviation of 50 m and 100 m are added to simulated TDoA transmissions the model is able to reduce this error to 22 m and 27 m (RMSE) respectively. Without correction, the standard deviation of these errors is on the order of 90 and 200 m. Accordingly, the model can reduce the error by greater than 80 m (> 80%), demonstrating the effectiveness of this novel 1D CNN U-Net like encoder/decoder for error correction of TDoA position estimates.
Local Steroid Treatment: An Effective Procedure for Idiopathic Granulomatous Mastitis, Including Complicated Cases
Authors: Ertürk Taha Furkan , Çakır Özgür , Bayrak Büşra Yaprak , Güneş Abdullah , Aydemir Selahattin , Utkan Nihat Zafer 
Published: February 2021

Abstract
Background: This study aimed to evaluate the effectiveness of local steroid treatment (LST) for idiopathic granulomatous mastitis (IGM) and to compare with surgical methods.Methods: Data was retrospectively collected from hospital electronic records. The patients were divided into two groups, the LST group and the surgery group. Intralesional steroid injection and topical steroid administration were applied in LST group. Surgery and LST were compared with regard to: pain before and after the treatment; complication rate; recurrence rate; and treatment cost.Results: Seventy of 72 lesions responded completely to LST. Pre-treatment median maximum diameter was 23.50 (15.25-35.25) mm, which regressed to 16 (12-25) mm after the first LST session. LST was found to be superior to surgery in pain management. No recurrence occurred in any patients in LST group.Conclusion: LST is a treatment for IGM that is cheap, with high efficiency, negligible recurrence, and has good esthetic outcome.
Drought Effects on Growth, Water Content, and Organic Osmoprotectants in Promising Almond Genotypes with Different Drought Tolerance
Authors: Gohari Shabnam , Imani Ali , Talaei AliReza , Abdossi Vahid , Asghari Mohamad Reza 
Published: February 2021

Abstract
Background

Almonds ( Prunus amygdalus Batsch, syn. P. dulcis (Mill.) DA Webb) is a valuable nut crops species that is widely is cultivated in arid and semi-arid regions of Iran, due to drought tolerance and dehydration under drought stress. Almonds show physiological adaptations for survival in drought stress conditions, but the degree Drought adaptation varies between cultivars. However, to date, its morphological and physiological responses to drought, and the underlying mechanisms are not well understood. This study was aimed to investigate the morphological and physiological changes of almond genotypes under drought stress. almond genotypes were planted in pots and subjected to four levels of soil water treatments: above 80% (control), 60% (light stress), and 40% (severe stress) of field capacity.

Results

Within the total stress period (0–30 days), almond genotypes grew rapidly in the light stress, whereas severe stress had a negative impact on growth. So that, in this study, 10 selected almond genotypes using some morphological traits such as: plant height, trunk diameter at the top of the graft, new branch growth length, leaf yellowness and some physiological indicators under drought stress conditions such as Chlorophyll index was evaluated based on SPAD criterion, relative leaf water content, measurement of chlorophyll fluorescence and Organic Osmoprotectants to identify drought-resistant and sensitive genotypes under drought stress conditions. Among the selected genotypes studied, genotype A-7-100 was the most resistant and genotype A-124-1 was the most sensitive to drought stress.

Conclusions

Our results show that almond genotypes adapt to drought mainly by avoidance mechanisms, and its morphological and physiological characteristics are inhibited under severe stress, However, the degree of drought adaptation varies between different cultivars. These findings might help limited water resources to be fully used for increased the percentage of kernel and finally increased the growth and yield of plants under water stress.
Implementation evaluation of staff support and wellbeing programmes at an academic health science centre during COVID-19: study protocol
Authors: Krausova Barbora , Gnanapragasam Sam Nishanth , Demetriou Len , Beck Alison , Pires-Yfantouda Renata , Docherty Mary Jane , Sevdalis Nick 
Published: February 2021

Abstract
Background
Evidence from previous pandemics as well as early evidence from COVID-19 suggest risk of adverse mental health and wellbeing outcomes for healthcare workers. In response to these concerns, healthcare systems and organisations rapidly established staff support and wellbeing programmes. While there is emerging literature related to the effectiveness of such interventions, what is less well understood and evaluated is the evidence base regarding how such programmes are implemented; what supports and hinders their implementation; and how or if they are maintained following the initial acute phase of the pandemic. This study addresses this gap by studying the implementation process of COVID-19-related staff wellbeing programmes in the three UK NHS Trusts that make up one of Europe’s largest academic health sciences centres, King’s Health Partners.
Methods
We will conduct a prospective, cross-sectional descriptive study using qualitative research methods and non-probability purposive sampling to identify a study participant group representative of the population and implementation activity of interest. We will conduct semi-structured interviews of between 30 minutes and one hour. We will identify theory-driven elements in the dataset using the Consolidated Framework for Implementation Research (barriers and drivers), Exploration, Preparation, Implementation, Sustainment Framework (timeline/chronology/evolution of the implementation and different issues at different times) and Expert Recommendations for Implementing Change (implementation strategies). We will then identify indicators of these constructs within the dataset and report them, as well as their inter-relationships.
Discussion
Through this study we hope to better understand what factors hindered and enabled the implementation of three inter-linked staff support and wellbeing programmes, and how/to what extent have these programmes been sustained. We will also explore whether implementation science frameworks are applicable and beneficial in conceptualising and understanding crisis driven and rapidly implemented interventions, and in what ways, if any, they need to be adjusted when used in unprecedented circumstances such as the COVID-19 pandemic.
Interaction Effect of Serum Serotonin Level and Age on the 12-Week Pharmacotherapeutic Response in Patients With Depressive Disorders
Authors: Choi Wonsuk , Kim Ju-Wan , Kang Hee-Ju , Kim Hee Kyung , Kang Ho-Cheol , Lee Ju-Yeon , Kim Sung-Wan , Stewart Robert , Kim Jae-Min 
Published: February 2021

Abstract
Despite the recognized antidepressant role of serotonin (5-hydroxytryptamine [5-HT]) signaling pathways in the central nervous system, the association between baseline peripheral 5-HT level and the antidepressant treatment response in clinical studies remains debatable. We investigated the individual and interaction effects of baseline serum 5-HT level and age on 12-week remission in outpatients with depressive disorders who received stepwise antidepressant treatment. Baseline serum serotonin levels were measured and the age of 1,094 patients recorded. The patients received initial antidepressant monotherapy; then, patients with an insufficient response or who experienced uncomfortable side effects received alternative treatments every 3 weeks (3, 6, and 9 weeks). Subsequently, 12-week remission, defined as a Hamilton Depression Rating Scale (HAMD) score of ≤ 7, was evaluated. Individual and interaction effects of serum 5-HT level (lower vs. higher based on the median value of 72.6 ng/mL) and age (< 60 vs. ≥ 60 years) on 12-week remission were analyzed using logistic regression models after adjusting for relevant covariates. Significant individual effects of serum 5-HT level and age on 12-week remission were not observed. However, a higher 5-HT level and age ≥ 60 years were significantly associated with higher 12-week remission rates. Our study suggests that the combination of baseline serum 5-HT level and age can be a useful predictor of 12-week antidepressant treatment outcomes.
Fe-MOF nanoparticles as efficient adsorbent for removal of heavy metal ions by facile hydrothermally synthesis
Authors: Dafrawy Shady. M. El , Al-Shorifi Fares T. , Ahmed Awad I. 
Published: February 2021

Abstract
Fe-MOFs catalyst was prepared by simple solvothermal synthesis. The Fe-MOF was characterized by XRD, TEM, SEM and FT-IR which confirmed metal organic framework nanoparticles with Nano size reached nearly 29.4-129.9 nm. The adsorption capacities / percentages of Fe-MOF adsorbent for heavy metals as toxic pollutants from aqueous solutions were high, which indicate that Fe-MOFs nanoparticles can be used as a good adsorbent.
Comparison of the oncological outcomes of abiraterone acetate and enzalutamide in metastatic castration-resistant prostate cancer: A multicenter real-life data
Authors: Demirci Ayşe , Bilir Cemil , Gülbağcı Burcu , Hacibekiroğlu İlhan , V.Bayoğlu İbrahim , Bilgetekin İrem , Koca Sinan , Y.Çınkır Havva , Akdeniz Nadiye , Gül Deniz , Varım Ceyhun , Demirci Umut , Öksüzoğlu Berna 
Published: February 2021

Abstract
Background: To compare enzalutamide (E) and abiraterone acetate (AA) in terms of efficacy, survival and prognostic factors affecting survival in metastatic castration-resistant prostate cancer (mCRPC) patients. Methods: A total of 250 patients treated with E or AA in 5 centers were included.Results: The number of patients with no prostate specific antigen (PSA) decline was higher in the AA group than that in the E group, and the proportion of patients with a PSA decline of ≥50% was higher in the E group (p = 0.020). The rate of progression in the AA group (82.2%) was significantly higher than that in the E group (p <0.001). Radiological progression free survival (rPFS) and overall survival (OS) were significantly longer in the E group when compared to that in the AA group (p <0.001 and p = 0.027, respectively). In the E group, rPFS was significantly longer than that in the AA group in both pre- and post-docetaxel settings (p=0.010 and p=0.003, respectively). OS was similar in the pre-docetaxel setting; but in the post-docetaxel setting, E group had a significantly longer OS than the AA group(p=0.021). In the multivariate analysis performed in the whole patient group, we found that good prognostic factors for rPFS were E treatment, being ≥75 years and a PSA decline of ≥50% while there was no factor affecting OS. Conclusion: With longer OS and PFS, E seems to be more suitable for mCRPC patients in the post-docetaxel setting than AA.
Tumor size as a prognostic factor improves the accuracy of the prognostic prediction of T4 stage colon cancer: a propensity score analysis
Authors: Liang Yuexiang , Li Qiang , He Donglei , Chen Yong , Li Jingquan 
Published: February 2021

Abstract
The aim of this study was to evaluate the potential impact of tumor size on the long-term outcome of CC patients after curative surgery. A total of 782 curatively resected T4 stage CC patients without distant metastasis were enrolled. Patients were categorized into 2 groups according to the best threshold of tumor size: larger group (LG) and smaller group (SG). Propensity score matching was used to adjust for the differences in baseline characteristics. The ideal cutoff points for tumor size was 5 cm. In the multivariate analysis for the whole study series, tumor size was an independent prognostic factors. Patients in the LG had a significant lower 5-year OS rate, but higher distant metastatic rate than those in the SG (37.1% versus 25.2%, P < 0.001). After matching, patients in the LG still demonstrated a significant lower 5-year OS rate than those in the SG (63.5% versus 74.2%, P < 0.001). Patients in the LG benefited more from postoperative adjuvant chemotherapy than patients in the SG. The modified stage including tumor size was found to be more appropriate for predicting the OS of T4 stage CC than TNM stage. In conclusion, tumor size was an independent prognostic factor and could correlate with higher distant metastasis rate and better response of adjuvant chemotherapy. We maintain that tumor size should be incorporated into the staging system to enhance the accuracy of the prognostic prediction of T4 stage CC patients.
Local Recurrence in Young Women with Breast Cancer: Breast Conserving Therapy vs. Mastectomy Alone
Authors: Nguyen Dang Van , Kim Sang-Won , Oh Young-Taek , Noh O Kyu , Jung Yongsik , Yoon Dae Sung , Chun Mison 
Published: February 2021

Abstract

We compared cumulative incidence of local recurrence in young patients (≤ 40 years) with breast cancer between breast conserving therapy (BCT) and mastectomy alone. Among 428 women with early-stage breast cancer treated between 2001 and 2012, 311 underwent BCT and 117 underwent mastectomy alone. Adjuvant systemic treatments were administered to 409 patients (95.6%). We compared the cumulative incidence of LR and survival rates between two groups. During a median follow-up period of 91 months, the 10-year cumulative incidence of LR was 9.3% (median interval of 36.5 months from surgery). Patients treated with BCT tended to have a higher risk for local recurrence (11.1% for BCT vs. 4.1% for mastectomy alone, p = 0.078). All patients with isolated LR after BCT (n = 23) underwent salvage mastectomy followed by systemic treatments. The 5-year distant metastasis-free survival and overall survival of patients with isolated LR after BCT were 44.2% and 82.2%, respectively. The BCT group exhibited approximately a 2.5-fold higher risk of LR than mastectomy alone group. Patients with isolated LR after BCT showed poor prognosis despite undergoing aggressive salvage treatments. More effective long-term follow-up strategies should be established to reduce LR for improving prognosis and preserving cosmetic outcomes in young women.
Re-Evaluate of DNA Index Among the Childhood Acute Lymphoblastic Leukemia
Authors: Qiu Kun-yin , Liao Xiong-yu , Zhou Dun-hua , Fang Jian-pei 
Published: February 2021

Abstract
Background This study was aimed to re-evaluate the value of DNA index(DI) among pediatric acute lymphoblastic leukemia (ALL) with the recent chemotherapy protocols.Methods Retrospective study were analysis among pediatric ALL patients from the TAGET dataset.Result Totally, 1,668 eligible pediatric patients were enrolled in this study. Of them, 993 are male and 675 are female with a median age of 7.6 years old. The median follow-up for those patients was 7.7 years (range 0.1-15.7 years). The probability of 10-year EFS and OS were reported to be 68.3±2% and 79.6±2%, respectively. Multivariate analysis showed that DI was significantly associated with better EFS and OS. The threshold effect of DI on poor outcome was significant after adjusting for potential confounders. The adjusted regression coefficient (Log RR) was 0.7 (95%CI 0.1-3.2, P=0.597) for DI <1.1 while 8.8 (95%CI 1.4-56.0, P=0.021) for DI≥1.2 and 0.0 (95%CI 0.0-0.8, P=0.041) for 1.1≤DI<1.2. Generalized additive models revealed that the lowest rates of the adverse outcomes estimated to occur among DI between 1.1 and 1.2. Conclusion For those childhood ALL treated with recent chemotherapy protocols, the DI between 1.1 and 1.2 can serve as a significant cut-point discriminating the risk group, which indicated an independent prognostic factor.
PI3Kδ Inhibition Prevents IL33, ILC2s and Inflammatory Eosinophils in Persistent Airway Inflammation
Authors: Uddin Sorif , Amour Augustin , Lewis David J , Edwards Chris D , Williamson Matthew G , Hall Simon , Lione Lisa A. , Hessel Edith M 
Published: February 2021

Abstract
Background: Phosphoinositide-3-kinase-delta (PI3Kδ) inhibition is a promising therapeutic approach for inflammatory conditions due to its role in leucocyte proliferation, migration and activation. However, the effect of PI3Kδ inhibition on group-2-innate lymphoid cells (ILC2s) and inflammatory eosinophils remains unknown. Using a murine model exhibiting persistent airway inflammation we sought to understand the effect of PI3Kδ inhibition, montelukast and anti-IL5 antibody treatment on IL33 expression, group-2-innate lymphoid cells, inflammatory eosinophils, and goblet cell metaplasia. Results: Mice were sensitised to house dust mite and after allowing inflammation to resolve, were re-challenged with house dust mite to re-initiate airway inflammation. ILC2s were found to persist in the airways following house dust mite sensitisation and after re-challenge their numbers increased further along with accumulation of inflammatory eosinophils. In contrast to montelukast or anti-IL5 antibody treatment, PI3Kδ inhibition ablated IL33 expression and prevented group-2-innate lymphoid cell accumulation. Only PI3Kδ inhibition and IL5 neutralization reduced the infiltration of inflammatory eosinophils. Moreover, PI3Kδ inhibition reduced goblet cell metaplasia. Conclusions: Hence, we show that PI3Kδ inhibition dampens allergic inflammatory responses by ablating key cell types and cytokines involved in T-helper-2-driven inflammatory responses.
Fire Susceptibility Mapping in the Northeast Forests and Rangelands of Iran using New and Ensemble Data Mining Models
Authors: Eskandari Saeedeh , Pourghasemi Hamid Reza , Tiefenbacher John P. 
Published: February 2021

Abstract
Fires have increased in the northeastern Iran as its semiarid climate landscape is being desiccated by human activities. To combat fire outbreaks in any region, one must map fire susceptibility with accurate and efficient models. This research mapped fire susceptibility in the forests and rangelands of northeastern Iran’s Golestan Province using new data mining models. Fire effective factors data describing elevation, slope angle, annual mean rainfall, annual mean temperature, wind effect, topographic wetness index (TWI), plan curvature, distance from river, distance to road, and distance to village were obtained from several sources. The relative importance of each variable was determined with a random forest algorithm. Fire susceptibility maps were produced in R 3.3.3 software using GAM, MARS, SVM algorithms and a new ens­emble of the three models: GAM-MARS-SVM. Validation of the four fire susceptibility maps was performed with the area under the curve. Results show that distance from village, annual mean rainfall and elevation were of greatest importance in predicting fire susceptibility. The new GAM-MARS-SVM ensemble model achieved the highest fire susceptibility mapping precision. The fire susceptibility map produced using the GAM-MARS-SVM ensemble model best detected the high fire risk areas in Golestan Province.