Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying the effects of fire on frogs in Booderee National Park

Fire is a common form of recurrent disturbance in many ecosystems, but ecological theory has a poor record of predicting animal responses to fire, at both species and assemblage levels. As a consequence, there is limited information to guide fire regime management for biodiversity conservation. We investigated a key research gap in the fire ecology literature; that is, the response of an anuran assemblage to variation in the fire return interval. We tested two hypotheses using a spatially-explicit fire database collected over a 40 year period: (1) Species richness would peak at intermediate levels of disturbance. (2) Species with traits which enabled them to escape fire burrowing or canopy dwelling would be better able to survive fires, resulting in higher levels of occurrence in frequently burned sites. We found no evidence for either a reduction in species richness at locations with sh01i fire reh1m intervals , or a peak in species richness at intermediate levels of disturbance. Although we found some support for individual species responses to fire return intervals, these were inconsistent with th_e interpretation of burrowing or climbing being :functional traits for fire-avoidance. Instead burrowing and climbing species may be more likely to be disadvantaged by frequent fire than surface dwelling frogs. Nlore generally, our results show that many species in our sh1dy system have persisted despite a range of fire frequencies , and therefore that active management of fire regin1es for anuran persistence 1nay be unnecessary. The responses of anurans to fire in this location are unlikely to be predictable using simple life-history traits. Future work should focus on understanding the mechanistic underpinnings of fire responses , by integrating information on ani1nal behavior and species' ecological require1nents.
Volume 10, SeaWiFS Postlaunch Calibration and Validation Analyses, Part 2

The effort to resolve data quality issues and improve on the initial data evaluation methodologies of the SeaWiFS Project was an extensive one. These evaluations have resulted, to date, in three major reprocessings of the entire data set where each reprocessing addressed the data quality issues that could be identified up to the time of the reprocessing. Three volumes of the SeaWiFS Postlaunch Technical Report Series (Volumes 9, 10, and 11) are needed to document the improvements implemented since launch. Volume 10 continues the sequential presentation of postlaunch data analysis and algorithm descriptions begun in Volume 9. Chapter 1 of Volume 10 describes an absorbing aerosol index, similar to that produced by the Total Ozone Mapping Spectrometer (TOMS) Project, which is used to flag pixels contaminated by absorbing aerosols, such as, dust and smoke. Chapter 2 discusses the algorithm being used to remove SeaWiFS out-of-band radiance from the water-leaving radiances. Chapter 3 provides an itemization of all significant changes in the processing algorithms for each of the first three reprocessings. Chapter 4 shows the time series of global clear water and deep-water (depths greater than 1,000 m) bio-optical and atmospheric properties (normalized water-leaving radiances, chlorophyll, atmospheric optical depth, etc.) based on the eight-day composites as a check on the sensor calibration stability. Chapter 5 examines the variation in the derived products with scan angle using high resolution data around Hawaii to test for residual scan modulation effects and atmospheric correction biases. Chapter 6 provides a methodology for evaluating the atmospheric correction algorithm and atmospheric derived products using ground-based observations. Similarly, Chapter 7 presents match-up comparisons of coincident satellite and in situ data to determine the accuracy of the water-leaving radiances, chlorophyll a, and K(490) products.
Evidence of the Role of Inflammation and the Hormonal Environment in the Pathogenesis of Adrenal Myelolipomas in Congenital Adrenal Hyperplasia

Adrenal myelolipomas (AML) are composed of mature adipose and hematopoietic components. They represent approximately 3 percent of adrenal tumors and are commonly found in patients with congenital adrenal hyperplasia (CAH). CAH provides a unique environment to explore AML pathogenesis. We aimed to evaluate the role of the immune system and hormones that accumulate in poorly controlled CAH in the development of AML. When compared to normal adrenal tissue, CAH-affected adrenal tissue and myelolipomas showed an increased expression of inflammatory cells (CD68, IL2Rbeta), stem cells (CD117) B cells (IRF4), and adipogenic markers (aP2/FABP4, AdipoQ, PPARγ, Leptin, CideA), and immunostaining showed nodular lymphocytic accumulation. Immunohistochemistry staining revealed a higher density of inflammatory cells (CD20, CD3, CD68) in CAH compared to non-CAH myelolipomas. In vitro RNA-sequencing studies using NCI-H295R adrenocortical cells with exogenous exposure to ACTH, testosterone, and 17-hydroxyprogesterone hormones, showed the differential expression of genes involved in cell cycle progression, phosphorylation, and tumorigenesis. Migration of B-lymphocytes was initiated after the hormonal treatment of adrenocortical cells using the Boyden chamber chemotaxis assay, indicating a possible hormonal influence on triggering inflammation and the development of myelolipomas. These findings demonstrate the important role of inflammation and the hormonal milieu in the development of AML in CAH.
A cross-sectional observational study for ethno-geographical disparities in sleep quality, brain morphometry and cognition (a SOLACE study) in Indians residing in India, and South Asians and Europeans residing in the UK – a study protocol

Introduction As individuals age, their sleep patterns change, and sleep disturbances can increase the risk of dementia. Poor sleep quality can be a risk factor for mild cognitive impairment (MCI) and dementia. Epidemiological studies show a connection between sleep quality and cognitive changes, with brain imaging revealing grey matter volume reduction and amyloid beta accumulation in Alzheimer’s disease. However, most research has focused on Europeans, with little attention to other ethnic groups. Methods This is a cross sectional study comparing effects across countries and ethnicities. Group 1 (n = 193) will be Indians residing in India (new participant recruitment), Group 2 will be South Asians residing in UK and group 3 will be Europeans residing in the UK. For group 2 and 3 (n = 193), data already collected by UK-based Southall and Brent REvisited (SABRE) tri-ethnic study will be used. For group 1, Pittsburgh Sleep Quality Index questionnaire (PSQI) will be used for assessment of sleep quality, Indian Council of Medical Research (Neurocognitive ToolBox) (ICMR-NCTB) for cognition testing and a 3 T MRI cerebral scan for brain morphometry. The data will be compared to sleep, cognitive function and brain MRI parameters from SABRE. Discussion Racial and ethnic differences can impact the relationships of cognitive function, sleep quality and brain structure in older adults. Earlier studies have highlighted higher prevalence of poor sleep among black individuals compared to white individuals. Genetic or epigenetic mechanisms may contribute to these variations. Socio-cultural and environmental factors, such as neighbourhood, migration, lifestyle, stress and perceived discrimination may influence sleep patterns. The aim of the study is to examine the ethnogeographic variations in sleep quality, cognitive performance and brain morphometry among Indians living in India, and South Asians and Europeans residing in the UK.
Enhancing Bug Report Summaries Through Knowledge-Specific and Contrastive Learning Pre-Training

Bug reports are crucial in software maintenance, with concise summaries significantly enhancing the efficiency of bug triagers and ultimately contributing to the development of high-quality software products. Contemporary methods for automatic bug report summarization primarily utilize neural networks’ robust learning capabilities. However, these approaches often produce suboptimal summaries due to two primary limitations: 1) the difficulty in assimilating the domain-specific knowledge inherent in bug reports, and 2) the limitations of purely supervised learning in comprehending the comprehensive context of bug reports. To address the above two problems, in this paper, we propose a new approach for bug report summarization, namely KSCLP, which leverages large language models and domain-specific pre-training strategies, i.e., Knowledge-Specific and Contrastive Learning Pre-training. Specifically, the Knowledge-Specific strategy allows to pre-train KSCLP on project-specific bug reports corpus, by which the model can fully learn internal knowledge of bug reports, learning bug report-aware representation. As for the Contrastive Learning strategy, it performs a sequence-level pre-training for KSCLP, helping it capture the semantic information of bug reports on a global level. Upon completion of the pre-training phase, KSCLP undergoes further refinement through a Sequence-to-Sequence framework specifically tailored for bug report summarization. The efficacy of KSCLP is rigorously evaluated against five baseline models using a publicly available dataset. The empirical results demonstrate that KSCLP outperforms all baselines, achieving remarkable improvements by up to 23.73, 13.97, and 20.89 points in ROUGE-1, ROUGE-2, and ROUGE-L metrics, thereby setting new benchmarks in the field of bug report summarization.
Practical Jsc Limits for SHJ Devices: Insights From Modelling

Modern industrial silicon heterojunction (SHJ) solar cells are increasingly limited by the short-circuit current density (Jsc) and there is a strong interest in understanding how much novel approaches such as window layers, novel transparent conductive oxides (TCOs) and anti-reflection coatings (ARCs) could improve the Jsc of SHJ solar cells. In this work, the practical Jsc limits of SHJ solar cells are determined using a carefully calibrated ray-tracing model, validated using empirical data from in-house solar cells as well as recently published high-efficiency front-and-back contacted (FAB) SHJ solar cells. The model is then further refined to obtain a detailed Jsc loss breakdown of the latest record efficiency FAB SHJ solar cells, for which there are no published Jsc loss breakdowns. Notable advances made in these advanced solar cells with regards to window layers, TCOs and ARCs at the cell level are analysed. Based on the magnitude of impact on the solar cell Jsc, the most critical factors for achieving high-Jsc SHJ solar cells are identified and ranked. Allowing for additional improvements and combining the best approaches identified, an estimate of the practical upper limit of Jsc for FAB SHJ solar cells is determined to be 41.81 mA/cm2. This work serves as a useful reference for the current state of play for Jsc improvements in SHJ solar cells, and highlights practical pathways and issues for improving commercial SHJ solar cells.
Risks and financial performance of Indian banks: a cursory look at the COVID-19 period

PurposeThe novel coronavirus (COVID-19) has caused financial stress and limited their lending agility, resulting in more non-performing loans (NPLs) and lower performance during the II wave of the coronavirus crisis. Therefore, it is essential to identify the risky factors influencing the financial performance of Indian banks spanning 2018–2022.Design/methodology/approachOur sample consists of a balanced panel dataset of 75 scheduled commercial banks from three different ownership groups, including public, private and foreign banks, that were actively engaged in their operations during 2018–2022. Factor identification is performed via a fixed-effects model (FEM) that solves the issue of heterogeneity across different with banks over time. Additionally, to ensure the robustness of our findings, we also identify the risky drivers of the financial performance of Indian banks using an alternative measure, the pooled ordinary least squares (OLS) model.FindingsEmpirical evidence indicates that default risk, solvency risk and COVAR reduce financial performance in India. However, high liquidity, Z-score and the COVID-19 crisis enhance the financial performance of Indian banks. Unsystematic risk and systemic risk factors play an important role in determining the prognosis of COVID-19. The study supports the “bad-management,” “moral hazard” and “tail risk spillover of a single bank to the system” hypotheses. Public sector banks (PSBs) have considerable potential to achieve financial performance while controlling unsystematic risk and exogenous shocks relative to their peer group. Finally, robustness check estimates confirm the coefficients of the main model.Practical implicationsThis study contributes to the knowledge in the banking literature by identifying risk factors that may affect financial performance during a crisis nexus and providing information about preventive measures. These insights are valuable to bankers, academics, managers and regulators for policy formulation. The findings of this paper provide important insights by considering all the risk factors that may be responsible for reducing the probability of financial performance in the banking system of an emerging market economy.Originality/valueThe empirical analysis has been done with a fresh perspective to consider unsystematic risk, systemic risk and exogenous risk (COVID-19) with the financial performance of Indian banks. Furthermore, none of the existing banking literature explicitly explores the drivers of the I and II waves of COVID-19 while considering COVID-19 as a dependent variable. Therefore, the aim of the present study is to make efforts in this direction.
Trophic relationships of a subtidal fish assemblage in the Francisco Coloane Coastal Marine Protected Area, southern Chilean Patagonia

ABSTRACT A combination of stomach content and nitrogen (δ15N) and carbon (δ13C) stable-isotope analysis was used to assess the trophic interactions and feeding habits of three notothenioid coastal fish (Champsocephalus esox, Patagonotothen tessellata and Patagonotothen cornucola) and one exotic salmon species (Oncorhynchus tschawytscha) with diverse life habits (benthic and benthopelagic) in the Francisco Coloane Coastal Marine Protected Area, southern Chile. The stomach contents of C. esox were mainly fish; those of P. cornucola and O. tschawytscha were crustacean decapods, Munida gregaria. A cluster analysis on isotope data and stable-isotope Bayesian ellipses detected two different predator groups, one with benthopelagic habits (C. esox and O. tshawytscha) and one with benthic habits (P. cornucola and P. tessellata). These results were supported with similar isotopic trophic level of each group. We suggest that the exotic salmon O. tschawytscha is a generalist predator with a broad trophic niche that may compete with the native notothenioid C. esox, as both have equivalent trophic levels with substantial overlap. This preliminary study is the first on trophic relationships of a subtidal fish assemblage within a remote ecosystem of fjords and channels in Chile’s southern Patagonia.
Relationship and Priority of Risks using ISM and Grey Approach

A supply chain should ensure survivability and sustainability. However, a supply chain has been exposed to various risks because of uncertainty, complexity, ambiguity, and etc. These risks expose the vulnerability of a supply chain and threaten the survivability and sustainability of the chain. If a risk occurs in a supply chain, it should be removed or weaken from the supply chain. But, it is not easy to remove or weaken from the chain. Therefore, this study proposes a method to prioritize the risks and to establish a corresponding strategy about them after considering the relationship and fatality of the risks which occur in a supply chain. This study uses Grey approach and Interpretive Structural Modeling (ISM) to propose a method which finds the location, the most vulnerable place, about the risks in a supply chain. Evolutionary Simulation Optimization, and Service Supply
Cognitive Behavioral Group Counseling with Cognitive Restructuring Technique for Improving Senior High School Student's Self-compassion

This study aimed to see the effectiveness of group counseling in improving 10th-grade students’ self-compassion in SMA Bina Ummat Yogyakarta using Cognitive Behavioral Therapy (CBT) with Cognitive restructuring technique. Applying Randomized Pretest-Posttest control group design, fourteen students were recruited and assigned randomly into two groups: experimental and control groups. _ The result of repeated-measures MIX MANOVA showed that cognitive-behavioral group counseling with cognitive restructuring technique improved students’ self-compassion (F(2) =140.856, p <0.05). A significant difference in group effect on self-compassion was noticed (F (10.640) = 14.882, p<0.05). Time interaction with group was also found to affect self-compassion (F (8.741) = 16.886, p < 0.05). This result indicated that Cognitive behavioral group counseling with cognitive restructuring may effectively improve students’ self-compassion. This study's result could be used as one of the alternatives for school counselors when they aim to improve students’ self-compassion using the cognitive restructuring technique.
A Hybrid Method for Ultrasonic Thickness Measurement of Cobalt-Rich Crusts in a Reverberation Environment

Cobalt-rich crusts (CRCs) are an extremely important deep-sea mineral resource. In order to promote the commercial exploitation of CRCs, the thickness measurement of deep-sea CRCs is of great significance. In order to measure the thickness of CRCs in a reverberation environment, a low-power and high-performance underwater thickness measuring system was built. The system has strong penetration ability and measurement resolution. For strong reverberation and low signal-to-noise ratio signals, a wavelet threshold denoising (WTD) evaluation method was proposed by wavelet time–frequency analysis based on the multilayer medium echo characteristics when pure signals cannot be obtained. It is convenient for the selection of optimal parameters of WTD. The WTD removed the high-frequency reverberation noise and improved the echo quality. A hybrid algorithm for transmission time estimation was proposed by combining the advantages of adaptive echo matching (AEM) and envelope peak. We solved the multilayer medium echo interference by intercepting the echo through the envelope peak thresholding. The results show that the algorithm can efficiently and accurately process the echo signals with low noise interference and calculate the transmission time of the echoes. The ultrasonic thickness measuring system and signal processing method in this article is an effective method to measure the thickness of CRCs.
Media Representations and Social Integration: A Study of Deaf Cafes in China

There is a large population of deaf workers in China. These individuals often face challenges in obtaining quality vocational education in their youth, further hampered by societal prejudice that questions their ability to lead normal lives. Their employment, especially in the catering sector, has been less than promising due to these combined factors. This paper explores the potential of social media as a platform to promote deaf-owned businesses and challenge prevailing biases. By interviewing the deaf owner of Sign Cafe, the study highlights how social media can not only serve as an advertising tool but also as a medium to change perceptions about the capabilities of the deaf community.
Brief Mindset Intervention Changes Attitudes but Does Not Improve Working Memory Capacity or Standardized Test Performance

There has been extensive research conducted on mindset and grit, involving both experimental and observational methods. However, the findings in the literature remain mixed. This should give educators and researchers pause from an intervention perspective—if we still do not have a good understanding of how mindset works, then more research is needed. We implemented a mindset intervention with undergraduate women to improve cognitive performance measures relevant to academic performance—working memory capacity and standardized test performance in math. To better understand how mindset interventions work, we also examined self-report measures (e.g., pertaining to academic attitudes and belonging) as well as post-intervention behavior. We expected the growth mindset intervention to significantly improve cognitive performance and to cause more positive academic attitudes and attitudinal change. The mindset intervention did change students’ beliefs about ability and also caused students to report higher grit overall (no condition difference), and to feel less belonging in terms of connection to their university—which was not in line with our hypotheses. We also found that the growth mindset intervention had no significant effects on improving WMC or standardized test performance. We discuss the implications of these findings and make suggestions for future work in this area.
Effect of heterologous expression of FT gene from Medicago truncatula in growth and flowering behavior of olive plants

Olive (Olea europaea L. subsp. europaea) is one of the most important crops of the Mediterranean Basin and temperate areas worldwide. Obtaining new olive varieties adapted to climatic changing conditions and to modern agricultural practices, as well as other traits such as biotic and abiotic stress resistance and increased oil quality, is currently required; however, the long juvenile phase, as in most woody plants, is the bottleneck in olive breeding programs. Overexpression of genes encoding the ‘florigen’ Flowering Locus T (FT), can cause the loss of the juvenile phase in many perennials including olives. In this investigation, further characterization of three transgenic olive lines containing an FT encoding gene from Medicago truncatula, MtFTa1, under the 35S CaMV promoter, was carried out. While all three lines flowered under in vitro conditions, one of the lines stopped flowering after acclimatisation. In soil, all three lines exhibited a modified plant architecture; e.g., a continuous branching behaviour and a dwarfing growth habit. Gene expression and hormone content in shoot tips, containing the meristems from which this phenotype emerged, were examined. Higher levels of OeTFL1, a gene encoding the flowering repressor TERMINAL FLOWER 1, correlated with lack of flowering. The branching phenotype correlated with higher content of salicylic acid, indole-3-acetic acid and isopentenyl adenosine, and lower content of abscisic acid. The results obtained confirm that heterologous expression of MtFTa1 in olive induced continuous flowering independently of environmental factors, but also modified plant architecture. These phenotypical changes could be related to the altered hormonal content in transgenic plants.