Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphologic and Molecular Heterogeneity of High-grade Serous Carcinoma Precursor Lesions

Serous tubal intraepithelial carcinoma (STIC) is the fallopian tube precursor lesion for most cases of pelvic high-grade serous carcinoma (HGSC). To date, the morphologic, molecular, and clinical heterogeneity of STIC and a less atypical putative precursor lesion, termed serous tubal intraepithelial lesion, has not been well characterized. Better understanding of precursor heterogeneity could impact the clinical management of women with incidental STICs (without concurrent carcinoma) identified in cases of prophylactic or opportunistic salpingectomy. This study analyzed morphologic and molecular features of 171 STICs and 21 serous tubal intraepithelial lesions. We assessed their histologic features, Ki-67 and p53 staining patterns, and genome-wide DNA copy number alterations. We classified all precursor lesions into 2 morphologic subtypes, one with a flat surface (Flat) and the other characterized by budding, loosely adherent, or detached (BLAD) morphology. On the basis of pathology review by a panel of 8 gynecologic pathologists, we found 87 BLAD, 96 Flat, and 9 indeterminate lesions. As compared with Flat lesions, BLAD lesions were more frequently diagnostic of STIC (P<0.0001) and were found concurrently with HGSC (P<0.0001). BLAD morphology was also characterized by higher Ki-67 proliferation index (P<0.0001), presence of epithelial stratification (P<0.0001), and increased lymphocyte density (P<0.0001). BLAD lesions also exhibited more frequent DNA copy number gain/amplification at the CCNE1 or CMYC loci canonical to HGSCs (P<0.0001). Both BLAD morphology and STIC diagnoses are independent risk factors for an elevated Ki-67 proliferation index. No correlation was observed between BLAD and Flat lesions with respect to patient age, presence of germline BRCA1/2 mutation, or p53 staining pattern. These findings suggest that tubal precursor lesions are morphologically and molecularly heterogeneous, laying the foundation for further studies on the pathogenesis of HGSC initiation and identifying histologic features predictive of poor patient outcomes.
Management Of Shoreline Morphological Changes Consequent To Breakwater Construction

The coastal stretch from Veli to Varkala along Thiruvananthapuram coast, which was in dynamic equilibrium, has two identifiable sediment cells separated by the Muthalapozhi inlet with harbour breakwaters on either side of the inlet. Construction of breakwaters to develop a fishing harbour at Muthalapozhi has caused erosion immediately north of the inlet and beach build up south of the inlet. In addition, the harbour mouth gets blocked due to deposition of sand, virtually making the harbour unusable. In the present study, the processes of shoreline morphological changes along the high energy coast are analyzed using numerical models to propose management options to tackle morphological modifications. Shoreline changes, nearshore processes and beach characteristics along this sector are studied through extensive field observations. The data is used to calibrate and validate sediment transport and shoreline change models for this coast. Sediment transport and shoreline changes are simulated using different modules of LITPACK model. The LITDRIFT module is used to calculate annual sediment transport. The LITLINE module is used for shoreline evolution during fair season and the behaviour of coast during monsoon is simulated using the module LITPROF. The calibration of the model is done with field observations. It is found that beach sediments get deposited on southern side of the breakwater and bypassed sediment gets deposited at the inlet mouth. The model after validation is used to simulate the processes with different designs and a groin field of smaller transitional lengths comparable with the surf zone width. The groins having lengths 40, 30 and 20 m at 120, 220 and 300 m south of breakwater, has been found best suited to control the chocking of harbour mouth due to sediment deposition during beach building period.
Cultivation of recombinant Aspergillus niger strains on dairy whey as a carbohydrate source

Abstract Agricultural waste valorisation provides a sustainable solution to waste management, and combining waste utilisation with commodity production allows for responsible production processes. Recombinant Aspergillus niger D15 strains expressing fungal endoglucanases (Trichoderma reesei eg1 and eg2 and Aspergillus carneus aceg) were evaluated for their ability to utilise lactose as a carbon source to determine whether dairy waste could be used as a feedstock for enzyme production. The recombinant A. niger D15[eg1]PyrG, D15[eg2]PyrG, and D15[aceg]PyrG strains produced maximum endoglucanase activities of 34, 54, and 34 U/mL, respectively, on lactose and 23, 27, and 22 U/mL, respectively, on whey. The A. niger D15[eg2]PyrG strain was used to optimise the whey medium. Maximum endoglucanase activity of 46 U/mL was produced on 10% whey medium containing 0.6% NaNO3. The results obtained indicate that dairy whey can be utilised as a feedstock for recombinant enzyme production. However, variations in enzyme activities were observed and require further investigation.
Environmental Toxicology and Chemistry

A hybrid model was used to characterize potential ecological risks posed by atrazine to the endangered Topeka shiner. The model linked a Topeka shiner individual‐based bioenergetics population model (TS‐IBM) to a comprehensive aquatic system model (CASMTS) to simulate Topeka shiner population and food web dynamics for an Iowa (USA) headwater pool. Risks were estimated for monitored concentrations in Iowa, Missouri, and Nebraska (USA), and for monitored concentrations multiplied by 2, 4, and 5. Constant daily atrazine concentrations of 10, 50, 100, and 250 μg/L were assessed. Exposure–response functions were developed from published atrazine toxicity data (median effect concentrations [EC50s] and no‐observed‐effect concentrations). Two toxicity scenarios were developed: the first included sensitive and insensitive species of algae, and the second reduced algal EC50 values to increase atrazine sensitivity. Direct and indirect effects of atrazine on Topeka shiner prey were modeled; direct effects on Topeka shiner were not assessed. Risks were characterized as differences between population biomass values of 365‐d baseline and exposure simulations. The results indicated no discernable food web effects for monitored atrazine concentrations or constant exposures of 10 μg/L on Topeka shiner populations for either toxicity scenario. Magnified monitored concentrations and higher constant concentrations produced greater modeled indirect effects on Topeka shiners. The hybrid model transparently combines species‐specific and surrogate species data to estimate food web responses to environmental stressors. The model is readily updated by new data and is adaptable to other species and ecosystems. Environ Toxicol Chem 2019;38:2243–2258. © 2019 SETAC
Comparative genomics of Japanese encephalitis virus shows low rates of recombination and a small subset of codon positions under episodic diversifying selection

Orthoflavivirus japonicum (JEV) is the dominant cause of viral encephalitis in the Asian region with 100,000 cases and 25,000 deaths reported annually. The genome is comprised of a single polyprotein that encodes three structural and seven non-structural proteins. We collated a dataset of 349 complete genomes from a number of public databases, and analysed the data for recombination, evolutionary selection and phylogenetic structure. There are low rates of recombination in JEV, subsequently recombination is not a major evolutionary force shaping JEV. We found a strong overall signal of purifying selection in the genome, which is the main force affecting the evolutionary dynamics in JEV. There are also a small number of genomic sites under episodic diversifying selection, especially in the envelope protein and non-structural proteins 3 and 5. Overall, these results support previous analyses of JEV evolutionary genomics and provide additional insight into the evolutionary processes shaping the distribution and adaptation of this important pathogenic arbovirus.
Proteomics of the Heart.

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein expression, isoform conformations, dynamic turnover information, and data on direct protein-protein interactions. Cardiac proteomics offers researchers and clinicians a deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed for researchers to study proteomes at a single cell level, employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic post-translational modifications (PTMs). Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction (HFpEF), have provided the tools to study a challenging organ in the laboratory. Further technological development will pave way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.
Schistosoma mansoni Infection in Holochilus sciureus Shows Sex-Related Differences in Parasitological Patterns

Due to the different parasitological patterns found between sexes in human populations and in different biological models during Schistosoma mansoni infection, we proposed to investigate such differences using Holochilus sciureus rodent, besides confirming whether this rodent is suitable for experimental infections. In this sense, males and females of H. sciureus were infected with 200 cercariae from a human strain of S. mansoni. The number of eggs per gram of feces (epg) and the worms were quantified, besides histopathological analysis. Thus, it was shown that females have fewer epg, as well as a longer prepatent period. On the other hand, males had a lower recovery rate of adult worms. The histopathological analysis did not show differences between the sexes. Thus, we suggest that infection in H. sciureus females provides a favorable environment for the development of adult worms, despite impairing the parasite fecundity. In addition, H. sciureus may be an excellent biological model for S. mansoni experimental infections.
A review of solutions and challenges to addressing human population growth and global climate change

The world’s population recently surpassed 7 billion and is predicted to reach 9.2 billion by 2050. Continued population growth will result in increased resource consumption and greenhouse gas emissions, enhancing the effects of climate change. Synergisms between population growth and climate change will therefore have substantial negative impacts on the environment. However, solutions to population growth are often absent within the context of climate change. To address this absence, we conducted a review of the primary scientific literature published between 1980 and 2011 using ISI Web of Knowledge to determine the major topics that have been discussed, the geographic scale at which these topics were addressed, what types of solutions were proposed, and whether or not these solutions were tractable. In particular, we quantified the portion of the literature that addressed population growth and climate change as synergistic issues. Of 1,438 papers addressing population growth and climate change, only 139 (~10%) included solutions. Among these 139 papers, the most frequent topics and solutions addressed the societal aspects of population growth and climate change. Land use/land cover change and greenhouse gas emissions were also frequently discussed, while changes in policy, economics, and science and technology were the most frequently offered solutions to population growth and climate change. Education, energy, and health, were the least discussed topics and the least mentioned as solutions. In addition, while topics were discussed on a global scale, actionable solutions were often regionally dependent and tailored to address either population growth or climate change as separate, unrelated topics. Importantly, the number of papers offering solutions increased significantly over time, with 46% published since 2008. These results suggest that while solutions to human population growth have seldom been discussed in the context of climate change, they are beginning to be considered in the literature, perhaps indicating an increased awareness of the interrelatedness of these issues.
Gamified exercise for the distal upper extremity in people with post-stroke hemiparesis: feasibility study on subjective perspectives during daily continuous training

Abstract Introduction Dose (number of repetitions) has been suggested as a key element in the effectiveness of rehabilitation exercises to promote motor recovery of the hemiparetic upper limb. However, rehabilitation exercises tend to be monotonous and require significant motivation to continue, making it difficult to increase the exercise dose. To address this issue, gamification technology has been implemented in exercises to promote self-engagement for people with hemiparesis in continuing monotonous repetitive movements. This study aimed to investigate how subjective perspectives, specifically enjoyability, motivation to continue, and expectancy of effectiveness, change through continuous daily exercise using a developed gamified exercise system. Materials and Method Ten people with stroke suffering upper limb dysfunction underwent daily gamified exercise for seven days. The gamified exercise consisted of an electromyography (EMG)-controlled operating system that enabled users to play virtual games using repetitive finger movements. The participants performed conventional self-exercise on the same day as the control exercise, and rated their subjective perspectives on both exercises on a numerical rating scale on each exercise day. Results Ratings for enjoyability and motivation to continue consistently showed significantly higher scores for the gamified exercise than for conventional self-exercise on all exercise days. A similar trend was observed in the ratings for the expectancy of effectiveness. No changes over time were found in any of the ratings throughout the exercise period. Conclusions Exercise using the developed EMG-controlled gamified system may have the potential to maintain motivation and enjoyment in people with stroke to continue monotonous repetitive finger movements.
Reimagining TaxiVis through an Immersive Space-Time Cube metaphor and reflecting on potential benefits of Immersive Analytics for urban data exploration

Current visualization research has identified the potential of more immersive settings for data exploration, leveraging VR and AR technologies. To explore how a traditional visualization system could be adapted into an immersive framework, and how it could benefit from this, we decided to revisit a landmark paper presented ten years ago at IEEE VIS. TaxiVis, by Ferreira et al., enabled interactive spatio-temporal querying of a large dataset of taxi trips in New York City. Here, we reimagine how TaxiVis' functionalities could be implemented and extended in a 3D immersive environment. Among the unique features we identify as being enabled by the Immersive TaxiVis prototype are alternative uses of the additional visual dimension, a fully visual 3D spatio-temporal query framework, and the opportunity to explore the data at different scales and frames of reference. By revisiting the case studies from the original paper, we demonstrate workflows that can benefit from this immersive perspective. Through reporting on our experience, and on the vision and reasoning behind our design decisions, we hope to contribute to the debate on how conventional and immersive visualization paradigms can complement each other and on how the exploration of urban datasets can be facilitated in the coming years.
Using Multi-Temporal Sentinel-1 and Sentinel-2 data for water bodies mapping

Climate change is intensifying extreme weather events, causing both water scarcity and severe rainfall unpredictability, and posing threats to sustainable development, biodiversity, and access to water and sanitation. This paper aims to provide valuable insights for comprehensive water resource monitoring under diverse meteorological conditions. An extension of the SEN2DWATER dataset is proposed to enhance its capabilities for water basin segmentation. Through the integration of temporally and spatially aligned radar information from Sentinel-1 data with the existing multispectral Sentinel-2 data, a novel multisource and multitemporal dataset is generated. Benchmarking the enhanced dataset involves the application of indices such as the Soil Water Index (SWI) and Normalized Difference Water Index (NDWI), along with an unsupervised Machine Learning (ML) classifier (k-means clustering). Promising results are obtained and potential future developments and applications arising from this research are also explored.
D-Nikud: Enhancing Hebrew Diacritization with LSTM and Pretrained Models

D-Nikud, a novel approach to Hebrew diacritization that integrates the strengths of LSTM networks and BERT-based (transformer) pre-trained model. Inspired by the methodologies employed in Nakdimon, we integrate it with the TavBERT pre-trained model, our system incorporates advanced architectural choices and diverse training data. Our experiments showcase state-of-the-art results on several benchmark datasets, with a particular emphasis on modern texts and more specified diacritization like gender.
Data Management Challenges in Agile Software Projects: A Systematic Literature Review

Agile software development follows an adaptive and iterative approach. However, the management of data (e.g., development data or product data) can pose significant challenges for projects and agile teams. We aim to identify and characterize key challenges faced in data management within agile projects and to examine potential solutions proposed in the literature. We used a Systematic Literature Review (SLR) to collect and analyse relevant studies. We identified 45 studies related to data management in agile software development. We then manually analysed and mapped data from these studies to categorise different data management aspects and identify challenges and solutions as identified in those studies. Our findings reveal major challenges such as data integration and quality assurance. We found implications of challenges on team members and the product delivery process. We found that teams frequently struggle to integrate heterogeneous data sources, ensuring data reliability and real-time analytics. Additionally, fragmented data collection and a lack of standardized practices can impede team collaboration and project transparency. The studies have also proposed various solutions to address those challenges, including the use of ontologies, diverse data management strategies, automated tools, and the adoption of quality-focused development methods. Solutions also include training to enhance data quality and analysis. This SLR provides in-depth insights and recommendations for practitioners, emphasizing the importance of robust data management strategies. It suggests integrating advanced data management techniques into agile frameworks to enhance decision-making and improve software project outcomes. The study highlights the need for a more focused approach to data management in agile environments, advocating tailored solutions to meet the unique demands of agile software development.
Seismic Traveltime Tomography with Label-free Learning

Deep learning techniques have been used to build velocity models (VMs) for seismic traveltime tomography and have shown encouraging performance in recent years. However, they need to generate labeled samples (i.e., pairs of input and label) to train the deep neural network (NN) with end-to-end learning, and the real labels for field data inversion are usually missing or very expensive. Some traditional tomographic methods can be implemented quickly, but their effectiveness is often limited by prior assumptions. To avoid generating labeled samples, we propose a novel method by integrating deep learning and dictionary learning to enhance the VMs with low resolution by using the traditional tomography-least square method (LSQR). We first design a type of shallow and simple NN to reduce computational cost followed by proposing a two-step strategy to enhance the VMs with low resolution: (1) Warming up. An initial dictionary is trained from the estimation by LSQR through dictionary learning method; (2) Dictionary optimization. The initial dictionary obtained in the warming-up step will be optimized by the NN, and then it will be used to reconstruct high-resolution VMs with the reference slowness and the estimation by LSQR. Furthermore, we design a loss function to minimize traveltime misfit to ensure that NN training is label-free, and the optimized dictionary can be obtained after each epoch of NN training. We demonstrate the effectiveness of the proposed method through numerical tests.
Chiral and directional optical emission from a dipole source coupled to a helical plasmonic antenna

Plasmonic antennas with helical geometry are capable transducers between linearly polarized dipole emission and purely circular polarized far-fields. Besides large Purcell enhancements they possess a wide tunability due to the geometry dependence of their resonant modes. Here, the coupling of a dipole emitter embedded in a thin film to plasmonic single and double helices is numerically studied. Using a higher-order finite element method (FEM) the wavelength dependent Purcell enhancement of a dipole with different positions and orientations is calculated and the far-fields with respect to their chirality and radiation patterns are analyzed. Both single and double helices demonstrate highly directional and circularly polarized far-fields for resonant excitation but with significantly improved directional radiation for the case of double helices.
Research Methods for Urban Planning in the Digital Age

The chapter provides an overview of online research methods for urban and planning research. In examining different digital technologies and Web-based research methods, applied in different stages of the research process, in particular during data acquisition and data analysis, the chapter discusses critical differences and similarities between conventional paper-and-pencil research settings and online research environments. In this outline, the chapter addresses methodological procedures and ethical concerns in research conducted online with respondents or human participants
A technical note for the 91-clauses SAT resolution with Indirect QAOA based approach

This paper addresses the resolution of the 3-SAT problem using a QAOA-like approach. The chosen principle involves modeling the solution ranks of the 3-SAT problem, which, in this particular case, directly represent a solution. This results in a highly compact circuit with few gates, enabling the modeling of large-sized 3-SAT problems. Numerical experimentation demonstrates that the approach can solve instances composed of 91 clauses and 20 variables with an implementation based on Qiskit.