Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical, Histopathological and Molecular Spectrum of Cutaneous Lesions in Myelodysplastic Syndrome and Myeloproliferative Neoplasms (MDS/MPN): An Integrative Review

Simple Summary Skin lesions in the context of MDS/MPN are frequent and poorly understood in the current literature. This paper thoroughly reviews the dermatoses reported so far in these patients based on their relationship with prognosis and its main clinical, histopathological and genetical features. Different histological patterns and mutations have been described in the literature. However, the true nature of the cells in these cutaneous infiltrates as well as their mutational background and the link with the underlying hematological neoplasm have to be further investigate in order to clarify their biological significance and the main therapeutic implications. A classification proposal is developed with the aim of helping dermatologists, hematologists and pathologists to recognize them when present in these complex patients. The figures and tables included in the text and in the supplemental material facilitate the understanding of each of the proposed categories. In addition, the main publications in which these dermatoses have been previously treated are indicated. Abstract Myeloid neoplasms and acute leukemias include different entities that have been recently re-classified taking into account molecular and clinicopathological features. The myelodysplastic syndrome/myeloproliferative neoplasm (MDS/MPN) category comprises a heterogeneous group of hybrid neoplastic myeloid diseases characterized by the co-occurrence of clinical and pathological features of both myelodysplastic and myeloproliferative neoplasms. The most frequent entity in this category is chronic myelomonocytic leukemia (CMML) which is, after acute myeloid leukemia (AML), the main myeloid disorder prone to develop cutaneous manifestations. Skin lesions associated with myelodysplastic and myeloproliferative neoplasms include a broad clinical, histopathological and molecular spectrum of lesions, poorly understood and without a clear-cut classification in the current medical literature. The aim of this review is to describe and classify the main clinical, histopathological and molecular patterns of cutaneous lesions in the setting of MDS/MPN in order to improve the diagnostic skills of the dermatologists, hematologists and pathologists who deal with these patients.
Association between lactate metabolism‑related molecules and venous thromboembolism: A study based on bioinformatics and an in vitro model

Venous thromboembolism (VTE) is characterized by a high recurrence rate and adverse consequences, including high mortality. Damage to vascular endothelial cells (VECs) serves a key role in VTE and lactate (LA) metabolism is associated with VEC damage. However, the pathogenesis of VTE and the role of lactate metabolism-related molecules (LMRMs) remain unclear. Based on the GSE48000 dataset, the present study identified differentially expressed (DE-)LMRMs between healthy individuals and those with VTE. Thereafter, LMRMs were used to establish four machine learning models, namely, the random forest, support vector machine and generalized linear model (GLM) and eXtreme gradient boosting. To verify disease prediction efficiency of the models, nomograms, calibration curves, decision curve analyses and external datasets were used. The optimal machine learning model was used to predict genes involved in disease and an in vitro oxygen-glucose deprivation (OGD) model was used to detect the survival rate, LA levels and LMRM expression levels of VECs. A total of four DE-LMRMs, solute carrier family 16 member 1 (SLC16A1), SLC16A7, SLC16A8 and SLC5A12 were obtained and GLM was identified as the best performing model based on its ability to predict differential expression of the embigin, lactate dehydrogenase B, SLC16A1, SLC5A12 and SLC16A8 genes. Additionally, SLC16A1, SLC16A7 and SLC16A8 served key roles in VTE and the OGD model demonstrated a significant decrease in VEC survival rate as well as a significant increase and decrease in intracellular LA and SLC16A1 expression levels in VECs, respectively. Thus, LMRMs may be involved in VTE pathogenesis and be used to build accurate VTE prediction models. Further, it was hypothesized that the observed increase in intracellular LA levels in VECS was associated with the decrease in SLC16A1 expression. Therefore, SLC16A1 expression may be an essential target for VTE treatment.
Cloud Computing in Smart Cities: Privacy, Ethical and Social Issues

The rapid development of cloud computing technologies has revolutionized various sectors, and smart cities are no exception. Smart cities leverage cloud computing to optimize urban services, enhance resource management, and improve the overall quality of life for their inhabitants. However, as these technological advancements proliferate, concerns about privacy, ethical considerations, and social implications have emerged. This research paper critically examines the multifaceted challenges associated with the integration of cloud computing in smart cities, shedding light on the potential risks and highlighting the need for comprehensive solutions. The research employs a mixed-methods approach, combining quantitative data analysis and qualitative case studies to offer a comprehensive perspective on the identified issues. The primary focus lies in identifying privacy risks, ethical dilemmas, and social disparities that arise due to the extensive use of cloud-based systems and data in smart cities. Furthermore, the study investigates the role of key stakeholders, including governments, technology providers, and citizens, in mitigating or exacerbating these challenges. Key findings reveal that while cloud computing empowers smart cities with unparalleled capabilities, it also exposes residents' personal information to potential breaches and misuse. Ethical concerns arise from the handling of sensitive data, data ownership, and algorithmic biases that could perpetuate discrimination. Moreover, social issues like the digital divide and access disparities may further exacerbate existing inequalities in smart city implementation. This research paper concludes by proposing a comprehensive framework of guidelines and best practices to address the identified issues effectively. These recommendations encompass enhanced data privacy measures, transparent and accountable data governance, the promotion of ethical data usage, and inclusive strategies to bridge social disparities. By adopting these measures, smart cities can harness the full potential of cloud computing while safeguarding individual rights and fostering a more equitable and inclusive urban environment. Overall, this study underscores the critical importance of addressing privacy, ethical, and social challenges in the context of cloud computing in smart cities. By adopting a holistic and proactive approach, city planners, policymakers, and technology providers can build sustainable and responsible smart cities that ensure the well-being and dignity of their residents in the digital era.
Demonstration of a Transportable Fabry–Pérot Refractometer by a Ring-Type Comparison of Dead-Weight Pressure Balances at Four European National Metrology Institutes

Fabry–Pérot-based refractometry has demonstrated the ability to assess gas pressure with high accuracy and has been prophesized to be able to realize the SI unit for pressure, the pascal, based on quantum calculations of the molar polarizabilities of gases. So far, the technology has mostly been limited to well-controlled laboratories. However, recently, an easy-to-use transportable refractometer has been constructed. Although its performance has previously been assessed under well-controlled laboratory conditions, to assess its ability to serve as an actually transportable system, a ring-type comparison addressing various well-characterized pressure balances in the 10–90 kPa range at several European national metrology institutes is presented in this work. It was found that the transportable refractometer is capable of being transported and swiftly set up to be operational with retained performance in a variety of environments. The system could also verify that the pressure balances used within the ring-type comparison agree with each other. These results constitute an important step toward broadening the application areas of FP-based refractometry technology and bringing it within reach of various types of stakeholders, not least within industry.
Sweetcane (Erianthus arundinaceus) as a native bioenergy crop with environmental remediation potential in southern China: A review

Sweetcane (Erianthus arundinaceus [Retzius] Jeswiet) is an ecologically dominant warm‐season perennial grass native to southern China. It traditionally plays an important role in sugarcane breeding due to its excellent biological traits and genetic relatedness to sugarcane. Recent studies have shown that sweetcane has a great potential in bioenergy and environmental remediation. The objective of this paper is to review the current research on sweetcane biology, phenology, biogeography, agronomy, and conversion technology, in order to explore its development as a bioenergy crop with environmental remediation potential. Sweetcane is resistant to a variety of stressors and can adapt to different growth environments. It can be used for ecological restoration, soil and water conservation, contaminated land repairing, nonpoint source pollutants barriers in buffer strips along surface waters, and as an ornamental and remediation plant on roadsides and in wetlands. Sweetcane exhibits higher biomass yield, calorific value and cellulose content than other bioenergy crops under the same growth conditions, thereby indicating its superior potential in second‐generation biofuel production. However, research on sweetcane as a bioenergy plant is still in its infancy. More works need be conducted on breeding, cultivation, genetic transformation, and energy conversion technologies.
Ascidies littorales de Guadeloupe VIII. Questions de systématique évolutive posées par les Didemnidae

Description de 4 especes nouvelles: Trididemnum palmae, Didemnum calliginosum, Polysyncration louminae et Diplosoma tritestis et d'une forme nouvelle de Didemnidae. La systematique de cette famille est rendue difficile par la proche parente de certaines especes, une variabilite intraspecifique, l'absence de valeur phylogenetique de certains genres. La presence d'algues symbiotes complique encore les problemes poses
ADP-glucose pyrophosphorylase genes are differentially regulated in sugar-dependent or -independent manners in tomato (Solanum lycopersicum L.) fruit

In early developing tomato (Solanum lycopersicum L.) fruit, starch accumulates at high levels and is used by various primary metabolites in ripening fruits. ADP-glucose pyrophosphorylase is responsible for the first key step of starch biosynthesis. Although it has been reported that AgpL1 and AgpS1 isoforms are mainly expressed in early developing fruit, their regulatory mechanism has not been elucidated. The present study investigated the transcriptional response of AgpL1 and AgpS1 to various metabolizable sugars, nonmetabolizable sugar analogues, hexokinase inhibitors and proline by an experimental system using half-cut fruits. AgpL1 was upregulated in response to sucrose and constituted hexoses such glucose, whereas the AgpS1 gene almost did not exhibit a prominent sugar response. Further analyses revealed that other disaccharides such maltose and trehalose did not show a remarkable effect on both AgpL1 and AgpS1 expressions. These results indicate that there are two distinct regulatory mechanisms, namely, sugar metabolism-dependent and -independent, for the regulation of AGPase gene expression. Interestingly, the ADP treatment, a hexokinase inhibitors, cancelled the sugar response of AgpL1, indicating that hexokinase-mediated sugar signaling should be involved in the sugar response of AgpL1. These results suggest that sugar-dependent (AgpL1) and sugar-independent (AgpS1) pathways coordinatively regulate starch biosynthesis in immature tomato fruit.
Sources and contamination routes of seafood with human pathogenic Vibrio spp.: A Farm-to-Fork approach.

Vibrio spp. , known human foodborne pathogens, thrive in freshwater, estuaries, and marine settings, causing vibriosis upon ingestion. The rising global vibriosis cases due to climate change necessitate a deeper understanding of Vibrio epidemiology and human transmission. This review delves into Vibrio contamination in seafood, scrutinizing its sources and pathways. We comprehensively assess the contamination of human-pathogenic Vibrio in the seafood chain, covering raw materials to processed products. A "Farm-to-Fork" approach, aligned with the One Health concept, is essential for grasping the complex nature of Vibrio contamination. Vibrio's widespread presence in natural and farmed aquatic environments establishes them as potential entry points into the seafood chain. Environmental factors, including climate, human activities, and wildlife, influence contamination sources and routes, underscoring the need to understand the origin and transmission of pathogens in raw seafood. Once within the seafood chain, the formation of protective biofilms on various surfaces in production and processing poses significant food safety risks, necessitating proper cleaning and disinfection to prevent microbial residue. In addition, inadequate seafood handling, from inappropriate processing procedures to cross-contamination via pests or seafood handlers, significantly contributes to Vibrio food contamination, thus warranting attention to reduce risks. Information presented here support the imperative for proactive measures, robust research, and interdisciplinary collaboration in order to effectively mitigate the risks posed by human pathogenic Vibrio contamination, safeguarding public health and global food security. This review serves as a crucial resource for researchers, industrials, and policymakers, equipping them with the knowledge to develop biosecurity measures associated with Vibrio-contaminated seafood.
An Incremental Knowledge Learning Framework for Continuous Defect Detection

Defect detection is one of the most essential processes for industrial quality inspection. However, in continuous defect detection (CDD), where defect categories and samples continually increase, the challenge of incremental few-shot defect detection remains unexplored. Current defect detection models fail to generalize to novel categories and suffer from catastrophic forgetting. To address these problems, this article proposes an incremental knowledge learning framework (IKLF) for CDD. The proposed framework follows the pretrain-finetuning paradigm. To realize end-to-end fine-tuning for novel categories, an incremental Region-based Convolutional Neural Network (RCNN) module is proposed to calculate cosine-similarity features of defects and decouple classwise representations. What is more, two incremental knowledge align losses are proposed to deal with catastrophic problems. The feature knowledge align (FKA) loss is designed for class-agnostic feature maps, while the logit knowledge align (LKA) loss is proposed for class-specific output logits. The combination of two align losses mitigates the catastrophic forgetting problem effectively. Experiments have been conducted on two real-world industrial inspection datasets (NEU-DET and DeepPCB). Results show that IKLF outperforms other methods on various incremental few-shot scenes, which proves the effectiveness of the proposed method.
Application of trichoderma and aspergillus as biofertilizers in eco-friendly ratoon rice cultivation

The study’s goal is to find the best native fungus from rice husk waste so that a solid biofertilizer can be made with high-husk flour as a carrier material and an inert agent. This study was conducted on agricultural land in Seloliman Village, Trawas District, and Mojokerto Regency. Biofertilization and biological agent formulation activities carried out at Muhammadiyah University of Sidoarjo’s Microbiology Laboratory aided the research. The experiment was conducted using a factorial randomized block design. The first factor consisted of three treatments: no fungi, Trichoderma sp. , and Aspergillus sp. The second factor consists of soil treatment and apical treatment. The six treatment combinations were repeated four times (24 samples). The variables measured comprised plant height, number of panicles, weight of grain per plant, weight of 100 grams of grain, and the efficacy of biological agents in improving plant growth and productivity. All data underwent analysis of variety and then an HSD test at the 5% significance level to identify disparities among treatments. The study reveals that isolates Tc-013 and As-022 were identified as Trichoderma esperellum and Aspergillus flavus or A. oryzae, respectively. The application of Trichoderma and Aspergillus caused a decrease in the intensity of disease symptoms, reaching 64.7% and 37.3%, an increase in plant height and number of panicles, and an increase in the weight of 100 grains of 59.89 and 49.35%, respectively, as compared to the control treatment where the fungus was not applied.
Geogebra as a Scaffolding Tool for Exploring Analytic Geometry Structure and Developing Mathematical Thinking of Diverse Achievers

One of the reasons to use technology in education is to visualize and explore the insight of mathematics with optimum possibilities. Geogebra gives visual meaning to symbolic ideas along with optimum dynamic possibilities. The purpose of this experimental study was to know about the potential effect of dynamic geometry software on diverse students’ mathematical thinking behavior. For which a sample of forty students (grade-12) of F.G Inter College for Boys Mardan Cantt was selected. On the of their previous grade-11 standardized exams two groups along with their nested factors higher and lower achievers students were constructed. To investigate students’ mathematical thinking basis in the subject of analytic geometry, a model behavior of thinking with its six aspects was constructed on the basis of this model a well-design criterion test was developed for data collection. The six dependent variables were combined together to form the total mathematical thinking in this research study. Further, six week experiments of 22 lessons were prepared and two teaching methods traditional vs DGS (Dynamic Geometry Software) aided instructions were tested for two groups with almost equal statistical background and with the same compatibility in the biological age. Two hypotheses were carried out i.e. Treatment does not significantly affect the higher and low achievers of the two groups in mathematical thinking mean scores. To check the significant effect of the treatment on the students’ overall mathematical thinking variable across the groups, the two-way (ANOVA) was used and analyzed through as statistical tool SPSS. The study findings showed that treatment did significantly affect the higher and lower achievers of the two groups in mathematical thinking mean scores.
Correcting False Information: Journalistic Coverage During the 2016 and 2020 US Elections

ABSTRACT This study examines journalistic coverage of false information through a qualitative textual analysis of news about four popular false information cases during the 2016 and 2020 US presidential elections: The false claims that (1) the Pope endorsed Donald Trump; (2) Hillary Clinton and her campaign manager ran a pedophilia ring in a pizza shop; (3) the 2020 election was fraudulent and stolen; and (4) liberal politicians and celebrities were Satan worshippers and pedophiles. The analysis identified three dimensions of correction of false information in news coverage. The first dimension examined emphasis on the correct rather than false information. This nuanced past research by considering different practices, such as elaborating on correct information and avoiding the inclusion of incorrect information. The second dimension referred to the tone used to correct false information. The adoption of an assertive tone demonstrated journalists’ use of their voice to authoritatively correct false information. The third dimension entailed the inclusion of sources, which were used to frame correct information consistently with a diversity of audiences’ worldviews. These findings offer a framework to assess journalistic reporting on false information and illuminate strategies to stem its spread.
Evaluation of Chemical and Morphological Properties of Spruce Wood Stored in the Natural Environment

This paper focuses on the changes in chemical structure and fiber morphological properties of spruce wood during 15 months of its storage in an open forest woodshed. From the chemical composition, the extractives, cellulose, holocellulose, and lignin content were determined. The pH value was measured on the wood surface using a contact electrode. Acetic and formic acid, saccharides (glucose, xylose, galactose, arabinose and mannose), and polymerization degree (PD) of cellulose were analyzed using the HPLC method. Fiber length and width were determined using a fiber tester analyzer. After 15 months of storage the content of both cellulose (determined by the Seifert method) and lignin did not change; the quantity of hemicelluloses decreased by 13.2%, due to its easier degradation and less stability compared to cellulose; and the pH value dropped by one degree. HPLC analyses showed a total decrease in the cellulose DP of 9.2% and in saccharides of 40.2%, while the largest decreases were recorded in the quantity of arabinose, by 72%, in the quantity of galactose, by 61%, and in the quantity of xylose, by 43%. Organic acids were not detected due to their high volatility during wood storage. The total decrease in average fiber length was 38.2% and in width was 4.8%. An increase in the proportion of shorter fibers, and a decrease in the proportion of longer fibers, was recorded. It can be concluded that fundamental changes occurred in the wood, which could affect the quality of further products (e.g., chips, pulp, paper, particleboards).