bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the pump-turbine cavitation with small guide vane opening on pump mode
Authors: Tian Q H , Min H P , Xiao Y X , Liu J , Wang X D , Tang D D , Zhan D , Lu Z X
Published: December 2024

Cavitation is the main factor affecting the secure and stable operation of pump-turbine units. In this paper, a prototype of pump-turbine with splitter blade was chosen for analysis. The three-dimensional numerical calculation of the entire flow passage is carried out for the pump model under different cavitation number with small guide vane opening, and analysis the flow behaviour and cavitation phenomena. The calculated critical cavitation number is consistent with the experimental results. It is found that the cavitation mainly occurs at the runner long blade low-pressure edge, and large vortices are generated between the pressure surface of the long blade and the suction surface of the splitter blade flow channel. The combined effect of cavitation and vortex hinder the flow in the runner blade to blade channels, which makes the flow pattern in the runner and it’s downstream become more complex, which further leads to large hydraulic energy losses in the vanes and spiral case domain.
CFD – Tool for Choosing a Suitable Flow Measurement Methods
Authors: Souček J. , Nowak P.
Published: December 2024

Verifying guaranteed turbine parameters, especially flow rate, is essential after turbine or pump-turbine rehabilitation. Extensive changes in the hydraulic circuit are realized in the case of the transformation of an existing hydropower plant (HPP) to a pumped storage power plant (PSP), replacing vertical Kaplan with a new reversible Francis turbine. The article introduces a methodology for choosing a suitable flow measurement method. Computational fluid dynamics (CFD) supported by standards (IEC, ASME, ISO) and scientific literature serves as a tool for choosing a suitable flow measurement method, its optimal position in the penstock, and quantifying the value of uncertainty. Two main flow measurement methods – the current meter and the ultrasonic method - were considered in this article. A “virtual flow measurement” was performed based on the velocity field obtained from the CFD model. The reconstructed flow rates obtained from the virtual measurement by both methods were compared with exact flow rate values from CFD. The flow deviation’s sensitivity to the current meter position or the ultrasonic paths rotation was performed for the selected profiles. The profiles with small deviations and low sensitivity to rotation correspond to the recommended profiles according to the standards.
Analysis of the Water Quality Index (WQI) of the Kupang River to Achieve Sustainable Development Goals (SDGs)
Authors: Setyawan A , Muhammad F , Hermawan F
Published: December 2024

Human impacts include farming activities, settlements, and industrial waste, all of which degrade the quality of the water in the Kupang River in Central Java. Based on Sustainable Development Goal (SDGs) 6, Clean Water and Sanitation, the Indonesian government targeted a value of 55.5 for the WQI. Descriptive quantitative research was conducted by studying water quality data in the rainy and dry seasons from 2021 to 2023. The results showed that, in general, the Kupang River was in good condition in its upstream parts, and its downstream areas had degraded further into light and heavy pollution. WQI scores were 48 in 2021, 50 in 2022, and 44 in 2023, indicating that the SDG target has yet to be achieved. The significant polluters are high levels of fecal coliform from domestic waste, coupled with low DO and high levels of BOD, COD, and total phosphate. Textile and batik industry wastes increase the level of pollution further downstream. Improvement in wastewater management and public education on environmental conservation is urgently needed for the restoration of the water quality in the river and to support the achievement of SDGs.
Utilization Of Animal Manure For Biogas Production: Renewable Energy Solutions For Livestock Houses
Authors: Awan F N , Mawaddah N , Munandar A , Taher T , Fajar M
Published: December 2024

Utilizing livestock manure for biogas production offers an efficient and sustainable renewable energy solution for farming households. This research aims to disseminate the potential of livestock manure as raw material for biogas production, identify the benefits and challenges faced, and provide recommendations for wider implementation. The methods used include literature analysis, case studies on farmer households, as well as economic and environmental evaluation of biogas production. The research results show that livestock manure has great potential to be processed into biogas, which can be used as an energy source for domestic purposes such as cooking, lighting and heating. Apart from that, the residue resulting from the fermentation process can be used to make high-quality organic fertilizer, which can increase soil fertility and agricultural productivity. The application of biogas technology also contributes to better waste management and reduced greenhouse gas emissions, especially methane. However, several challenges still need to be overcome, including farmers’ limited knowledge of biogas technology, relatively high initial investment costs, and the need for strong policy support from the government. This study suggests improving extension programs, providing financial incentives, and developing supportive policies to encourage the adoption of biogas technology among livestock farmers. Overall, the use of livestock manure for biogas production not only produces a sustainable renewable energy solution but also contributes to improving the welfare of farmers and preserving the environment. Effective implementation of this technology can provide significant long-term benefits to the economy and ecology of farmer households.
Green synthesis of halogenated flavonoids and their pharmacological properties: a mini-review
Authors: Danova A , Hermawati E , Mujahidin D
Published: December 2024

Halogenated flavonoids have attracted much attention due to their diverse biological activities and potential therapeutic applications. These organic molecules are modified by introducing halogen atoms, such as fluorine, chlorine, bromine, and iodine, which can significantly change their physicochemical properties, affecting biological activity and environmental behavior. As environmental sustainability becomes an increasing concern, eco-synthesis, which involves the design and development of environmentally friendly synthetic pathways, has emerged as a major area of focus in the synthesis of halogenated flavonoids. This approach aims to minimize the use of hazardous reagents and solvents, reduce waste generation and improve overall sustainability. Therefore, this study aims to discuss green halogenation methods and the pharmacological properties of halogenated flavonoids.
Predictive soil nutrient modeling with spectral data and machine learning in four major Indonesian Provinces located on the island of java
Authors: Ramdhani T I , Adnan  , Suryana Y , Rochmadi T , Aziz A , Kamaruddin A , Ghazali N , Hadi A , Oktaviani W , Budiwati S V , Hakim A R , Fahrodji  , Nuraini L
Published: December 2024

This study provides a detailed analysis of predicting soil nutrient content using spectral data and machine learning techniques in four Indonesian provinces: West Java, Central Java, Yogyakarta (DIY), and East Java. The research collected 145 soil samples to predict various key soil nutrients, such as N Total, NH4, NO3, P Total, P Available, K Total, K Available, C Organic, and pH. The study used linear regression (LR) and deep neural networks (DNN) with a deep cross-network (DCN) architecture to model the relationships between soil spectral data and nutrient content. LR was used as a baseline model to understand linear relationships between spectral features and soil properties and identify the most influential spectral frequencies in predicting soil nutrient levels. On the other hand, the DNN model captured complex, non-linear patterns within the data. Results showed that while the DNN model displayed advanced capabilities, the LR model generally outperformed it in predictive accuracy, particularly for nutrients like N-Total, P-Total, and K-Total. The findings highlight the potential of combining spectral data with advanced machine-learning techniques for precise soil nutrient estimation, which could significantly enhance agricultural productivity and soil management practices in Indonesia.
Implementation of greenship rating tools at Kubah Timah Mosque Pangkalpinang
Authors: Felly R , Syafrina A , Rahmadyani H , Fahimah R , Dirda A U , Adari E S
Published: December 2024

Global warming is a common issue today. Previous research has shown that green building is capable of reducing environmental damage, lowering carbon emissions, and mitigating harmful ecological impacts by implementing renewable energy. Greenship is the standard for evaluating green building criteria, developed by the Green Building Council Indonesia (GBCI). Through Greenship assessments, buildings can be assessed for their sustainability performance. Currently Bangka Belitung Province, especially Pangkalpinang as capital city, does not have any buildings that are certified as green buildings. This study aims to assess the green building points of the Kubah Timah Mosque Pangkalpinang. The method used is assessing the implementation of green building by Greenships Rating Tools verse 1.2. This research found that this building got 20 points, which does not qualify for any Green Building ranking. However, the building has significant potential to achieve a Bronze rank from GBCI with a minimum score of 35 points. This research gives some recommendations to increase the criteria point by implementing some categories in Appropriate Site Development (ASD), Energy Efficiency & Conservation (EEC), Water Conservation (WAC), and Indoor Health and Comfort (IHC).
Green treatment solutions: Decolorization of textile wastewater by Chlorella vulgaris
Authors: Duong D V , Trung L D , Tuong L Q , My L V H , Tuyet L T H , Tran T
Published: December 2024

The textile dyeing industry is continually evolving, presenting the ongoing challenge of treating wastewater generated during the production process. Effective wastewater treatment in the dyeing industry requires a combination of methods to ensure the effluent quality and reduce costs, thereby aligning with the sustainable development goals of businesses. A promising solution lies in the use of the microalgae Chlorella vulgaris, which has the capability to absorb and degrade pollutants. This study aims to optimize the initial factors affecting the decolorization efficiency of Chlorella vulgaris, investigating the impact of pH on the decolorization rate and growth rate of the microalgae. The decolorization process was monitored over several consecutive days to evaluate the daily decolorization capacity of the microalgae. The survey of pH influence on decolorization efficiency revealed that the dye removal efficiency of wastewater exceeded 95% after 10 days when wastewater with a color intensity of 400 Pt-Co was introduced into a Chlorella vulgaris solution of the same volume. The results indicated that a pH of 8 is the most suitable environment for the decolorization process and the growth of Chlorella vulgaris. The decolorization rate at pH 8 achieved 62% efficiency after 5 days. Based on these findings, it can be concluded that Chlorella vulgaris presents an effective and sustainable solution for treating industrial dyeing wastewater, contributing to green processing in the industry.
Design of a nodemcu-based system for monitoring and controlling the water quality of catfish tarp pond
Authors: Anggraini E , Putra G B , Kurniawan R
Published: December 2024

Patin fish is known as a type of fish that is widely consumed by the public, which makes its selling price high. This is what makes catfish a type of fish that is widely cultivated. Catfish are cultivated from small fry to fish that are ready to be sold. Catfish farmers often use tarpaulin or earthen ponds as media. Many catfish farmers often or rarely even know that one of the important factors in the success of catfish cultivation is well-maintained water quality. According to the National Standardization Agency (SNI, 2016) there are several water quality parameters including, Temperature, pH, DO, Ammonia, Turbidity and Salinity. This research is creating a system that combines the concept of the Internet of Things (IoT) with cultivating catfish in tarpaulin ponds which aims to facilitate monitoring and maintenance of fish pond water by farmers. The system that will be created is capable of monitoring and controlling fish pond water quality remotely using a Telegram bot on Android which can be accessed continuously remotely without having to go directly to the location. The overall process starts from the fish pond water which is used as research material where temperature sensors, pH sensors, TDS sensors and ultrasonic sensors are inserted into the fish pond water to measure the quality of the fish pond water, then the ESP32 which receives signals from all sensors, carries out the processing data, and controlling relays based on sensor measurement results or commands from the Telegram bot, for example when to open or close a solenoid valve based on water level or other water quality parameters.
Analysis of shallot growth with boron and benzyl amino purine (BAP) application in Central Bangka Regency
Authors: Wahyuni W , Kartika  , Sari E
Published: December 2024

The cultivation of shallots in Bangka Island has been regularly carried out by farmers in Central Bangka Regency in recent years. However, the amount of production and productivity achieved has not met the demand for shallots in the area. The Bangka Islands region is generally surrounded by critical land due to mining activities that have a significant impact on soil fertility. The addition of cytokinins as growth regulators in the form of Benzyl amino purine (BAP) and the micronutrient boron has been reported to enhance the production and productivity of shallots. The aim of this research is to determine the appropriate concentration of BAP and the required dosage of boron to enhance the yield and productivity of shallot in Bangka Island, specifically the bima brebes and bauji varieties. The research results indicate that there is an interaction in the treatment combinations regarding plant height parameters in both varieties. The addition of BAP at 100 ppm affects the height of the Bima Brebes variety. The application of boron at various doses does not influence the vegetative growth of the shallot plants of the Bima Brebes and Bauji varieties.
Study of the potential of microhydro electric power plant in Universitas Bangka Belitung’s Embung
Authors: Hisyam E S , Arkan F , Oktarianty H , Aldila H
Published: December 2024

In today’s world, electrical energy has become a fundamental need for people to perform various activities. The search for energy sources that are ecofriendly, zero waste, cost-effective, and sustainable is a major focus for researchers developing new power generation technologies. Among these, the microhydro power plant stands out as a promising technology with these desired attributes for generating electricity. This study aims to assess the water flow rate and the head of the water in UBB’s Embung from July to August 2024 as part of its potential analysis. The results indicate that UBB’s Embung has the potential to support a microhydro power plant, with a maximum estimated output of 98.45 kW.
Literacy rate of environmental protection policy on compliance and community participation in conservation programs: a comparative
Authors: Ardyawin I , Syaharuddin  , Iswanto D , Septyanun N
Published: December 2024

This study aims to examine differences in environmental policy literacy on community compliance and participation in conservation programs, as well as examine differences based on gender. This study used a quantitative approach with research subjects consisting of 24 men and 63 women spread across 10 districts/cities in West Nusa Tenggara (NTB) Province. The research instrument used was a questionnaire. The results of the analysis showed a t-test value of 3.018 with Sig. (2-tailed) of 0.003<0.05, which indicated a significant difference between the level of compliance and community participation in maintaining environmental conservation. In addition, testing the level of community participation based on gender shows a t-test value of 2.456 with Sig.(2-tailed) of 0.016<0.05, which also indicates a significant difference. These findings indicate that environmental policy literacy has a significant effect on community compliance and participation, and there are differences in the level of participation based on gender in environmental conservation programs.
Supply chain model for improving material & environment sustainability: an analysis from green supply chain implementation in automobile industry
Authors: Huda M , Rahayu A , Furqon C , Sultan M A , Hartati N , Bahri K N , Achmad L I
Published: December 2024

Prevention of environmental damage must be considered by all stakeholders in order to reduce the negative effects. As a result, the objective of this inquire about is to set up how a few organizations utilize green supply chain administration and the affect it has on corporate execution. This study uses observation methods to obtain primary data and also uses secondary data from various relevant research sources. According to the findings, 1) Automotive industry has effectively executed green supply chain administration hones. Its application is to employ ecologically friendly raw materials, maximize raw materials, make goods easier to recycle, reduce waste, and encourage environmental activities, 2) Green supply chain management can increase firm performance by increasing efficiency and lowering expenses
The ethnic diversity of farmer groups in environmental management of lowland rice farming in Rias Village, Toboali District, South Bangka Regency
Authors: Sitorus R , Zulkarnain I , Wahyuni W
Published: December 2024

An increase in population quantity and community cultural diversity drives the need for the Bangka Belitung Islands Province to increase the productivity of the agricultural sector, especially rice as the main source of staple food. Not only is increasing the quantity of lowland rice production a measure of guaranteeing food security, but managing a healthy agricultural environment is also very important in achieving the sustainability target of national food security. What is unique is that the group of farmers in the rice production center of Bangka Belitung, namely Rias Village, Toboali District, South Bangka Regency, has a variety of cultures whose domicile is grouped based on ethnicity. This research was carried out to map the locus of lowland rice farmer groups based on ethnicity and describe the character of environmental management of lowland rice farming in the context of sustainable food security. The research method used was a survey of 60 rice farmers, mapping farmer group loci, and quantitative descriptive methods. The research results are depicted in a locus map of farmer groups of Bangka ethnic, Javanese, Bugis, and Sundanese ethnic groups. It was found that differences in the environmental management characteristics of lowland rice farming include: the selection of rice varieties, different agricultural practices, such as the use of organic fertilizer, traditional-based irrigation, crop rotation, cooperation patterns, and land ownership systems.
Ecotourism for sustainability: an in-depth perception and evaluation analysis of community-based “Belitong Geopark” in Belitung Island
Authors: Zukhri N , Rosalina E
Published: December 2024

Belitong Geopark covers an area of approximately 125,000 hectares. A community-based ecotourism area that seeks to balance tourism development by integrating ecology and socio-economic welfare. This study aims to explore perceptions and evaluations. Perception and evaluation of community-based tourism management in the Belitong Geopark Area. Tourism management must achieve sustainable development goals. This research method used a combination of qualitative and quantitative. This approaches community perceptions and evaluations of the Belitong Geopark ecotourism initiative. Questionnaires, surveys, and interviews were conducted to capture various perspectives from the community, tourists, and stakeholders involved in the management of Belitong Geopark. Data analysis techniques introduces the innovative use of the Community-Based Ecotourism (CBE) model combined with SWOT analysis, providing a robust analytical framework to assess the strengths, weaknesses, opportunities, and threats of Belitong Geopark. The findings of this study are that the community and stakeholders have a positive perception of the management of community-based ecotourism areas in Belitong Geopark. Another finding is the importance of integrating community perspectives into ecotourism planning and management strategies. It can ensure long-term sustainability and mutual benefit for all stakeholders involved. By fostering collaboration between residents, government agencies, NGOs, and private sector entities, community-based ecotourism management and development initiatives will generate economic opportunities. We need attention to the preservation of nature and the socio-cultural life of the community.
Smith homomorphisms and 𝑠𝑝𝑖𝑛^{ℎ} structures
Authors: Debray Arun , Krulewski Cameron
Published: December 2024

In this article, we answer two questions of Buchanan–McKean [KSp-characteristic classes determine Spinh cobordism, https://arxiv.org/ abs/2312.08209, 2023] about bordism for manifolds with

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. Our proofs use the general theory of twisted spin structures and Smith homomorphisms that we developed joint with Devalapurkar, Liu, Pacheco-Tallaj, and Thorngren [The Smith fiber sequence and invertible field theories, https://arxiv.org/abs/2405.04649, 2024], specifically that the Smith homomorphism participates in a long exact sequence with explicit, computable terms.
GUI-Equipped Waveform Simulator
Authors: Essick John
Published: December 2024

Readers write a digitized waveform simulation program with advanced graphical user interface (GUI) features, including numeric input controls, a pull-down menu, and an embedded waveform plot. The completed program creates waveforms with sine, cosine, DC level, square, sawtooth, triangle, and user-defined shapes. In writing this program, three Python “utility” modules are created to carry out the following tasks: creation of waveform data with a desired shape, creation of a GUI with interactive controls, and creation of a GUI-embedded plot to display waveform data. These three modules are used in programs created throughout the remainder of the book. The GUI-equipped program created as a Do It Yourself project allows for interactive study of arbitrary-shape waveform generation via the summation of sine waves, while a Use It! example demonstrates the need for multithread execution in programs that carry out simultaneous GUI and time-intensive data-acquisition processes.
Data Analysis: Fast Fourier Transform
Authors: Essick John
Published: December 2024

Using SciPy functions, readers write Python programs to investigate the proper use of the fast Fourier transform (FFT). After a quick introduction to FFT properties, the theory of the discrete Fourier transform and discrete inverse Fourier transform is presented, including the mathematics behind how these quantities are used to produce discrete complex-amplitude and frequency spectra from a given input waveform. Then, readers write a program in which SciPy’s complex Fourier transform function is applied to various sinusoidal inputs, demonstrating that this function produces the expected complex-amplitude spectra. Finally, a program is written that simply plots the magnitude of the complex-amplitude as a function of frequency, and the effects of spectral leakage, windowing, and aliasing for input frequencies above the Nyquist frequency are explored. By applying this understanding of the FFT, along with the use of a DAQ device, readers construct a computer-based spectrum analyzer as a Do It Yourself project. A Use It! example investigates another of SciPy’s frequency-related signal-processing capabilities—digital filtering.
Formatting Text
Authors: Panchekha Pavel , Harrelson Chris
Published: December 2024

In the last chapter, our browser created a graphical window and drew a grid of characters to it. That’s OK for Chinese, but English text features characters of different widths grouped into words that you can’t break across lines. In this chapter, we’ll add those capabilities. You’ll even be able to read this page [1]!
Applying Author Styles
Authors: Panchekha Pavel , Harrelson Chris
Published: December 2024

In the previous chapter we gave each pre element a gray background. It looks OK, and it is good to have defaults, but sites want a say in how they look. Websites do that with Cascading Style Sheets (CSS), which allow web authors (and, as we’ll see, browser developers) to define how a web page ought to look.
Handling Buttons and Links
Authors: Panchekha Pavel , Harrelson Chris
Published: December 2024

Our browser is still missing the key insight of hypertext: documents linked together by hyperlinks. It lets us watch the waves, but not surf the web. So in this chapter, we’ll implement hyperlinks, an address bar, and the rest of the browser interface—the part of the browser that decides which page we are looking at.
Sending Information to Servers
Authors: Panchekha Pavel , Harrelson Chris
Published: December 2024

So far, our browser has seen the web as read only—but when you post on Facebook, fill out a survey, or search Google, you’re sending information to servers as well as receiving information from them. In this chapter, we’ll start to transform our browser into a platform for web applications by building out support for HTML forms, the simplest way for a browser to send information to a server.
Animating and Compositing
Authors: Panchekha Pavel , Harrelson Chris
Published: December 2024

Complex web applications use animations when transitioning between states. These animations help users understand the change and improve visual polish by replacing sudden jumps with gradual changes. But to execute these animations smoothly, the browser must minimize time in each animation frame, using GPU acceleration to speed up visual effects and compositing to minimize rendering work.
Making Content Accessible
Authors: Panchekha Pavel , Harrelson Chris
Published: December 2024

So far, we’ve focused on making the browser an effective platform for developing web applications. But ultimately, the browser is a user agent. That means it should assist the user in whatever way it can to access and use web applications. Browsers therefore offer a range of accessibility [1] features that take advantage of declarative UI and the flexibility of HTML and CSS to make it possible to interact with web pages by touch, keyboard, or voice.
A Changing Landscape
Authors: Panchekha Pavel , Harrelson Chris
Published: December 2024

The web is a dynamic, ever-changing place. The first web browser, in 1989, did not support colors, images, styling, or scripting. Three decades of market forces, implementation quirks, and the ever-expanding reach of the web then made browsers what they are today. Those forces are as strong as ever. Browsers continue to evolve!
Cell-specific priors rescue differential gene expression in spatial spot-based technologies
Authors: Nahman Ornit , Few-Cooper Timothy J , Shen-Orr Shai S
Published: December 2024

Spatial transcriptomics (ST), a breakthrough technology, captures the complex structure and state of tissues through the spatial profiling of gene expression. A variety of ST technologies have now emerged, most prominently spot-based platforms such as Visium. Despite the widespread use of ST and its distinct data characteristics, the vast majority of studies continue to analyze ST data using algorithms originally designed for older technologies such as single-cell (SC) and bulk RNA-seq—particularly when identifying differentially expressed genes (DEGs). However, it remains unclear whether these algorithms are still valid or appropriate for ST data. Therefore, here, we sought to characterize the performance of these methods by constructing an in silico simulator of ST data with a controllable and known DEG ground truth. Surprisingly, our findings reveal little variation in the performance of classic DEG algorithms—all of which fail to accurately recapture known DEGs to significant levels. We further demonstrate that cellular heterogeneity within spots is a primary cause of this poor performance and propose a simple gene-selection scheme, based on prior knowledge of cell-type specificity, to overcome this. Notably, our approach outperforms existing data-driven methods designed specifically for ST data and offers improved DEG recovery and reliability rates. In summary, our work details a conceptual framework that can be used upstream, agnostically, of any DEG algorithm to improve the accuracy of ST analysis and any downstream findings.
A self-attention-driven deep learning framework for inference of transcriptional gene regulatory networks
Authors: Liu Yong , Zhong Le , Yan Bin , Chen Zhuobin , Yu Yanjia , Yu Dan , Qin Jing , Wang Junwen
Published: December 2024

The interactions between transcription factors (TFs) and the target genes could provide a basis for constructing gene regulatory networks (GRNs) for mechanistic understanding of various biological complex processes. From gene expression data, particularly single-cell transcriptomic data containing rich cell-to-cell variations, it is highly desirable to infer TF–gene interactions (TGIs) using deep learning technologies. Numerous models or software including deep learning–based algorithms have been designed to identify transcriptional regulatory relationships between TFs and the downstream genes. However, these methods do not significantly improve predictions of TGIs due to some limitations regarding constructing underlying interactive structures linking regulatory components. In this study, we introduce a deep learning framework, DeepTGI, that encodes gene expression profiles from single-cell and/or bulk transcriptomic data and predicts TGIs with high accuracy. Our approach could fuse the features extracted from Auto-encoder with self-attention mechanism and other networks and could transform multihead attention modules to define representative features. By comparing it with other models or methods, DeepTGI exhibits its superiority to identify more potential TGIs and to reconstruct the GRNs and, therefore, could provide broader perspectives for discovery of more biological meaningful TGIs and for understanding transcriptional gene regulatory mechanisms.
Breaking free from references: a consensus-based approach for community profiling with long amplicon nanopore data
Authors: Stock Willem , Rousseau Coralie , Dierickx Glen , D'hondt Sofie , Amadei Martínez Luz , Dittami Simon M , van der Loos Luna M , De Clerck Olivier
Published: December 2024

Third-generation sequencing platforms, such as Oxford Nanopore Technology (ONT), have made it possible to characterize communities through the sequencing of long amplicons. While this theoretically allows for an increased taxonomic resolution compared to short-read sequencing platforms such as Illumina, the high error rate remains problematic for accurately identifying the community members present within a sample. Here, we present and validate CONCOMPRA, a tool that allows the detection of closely related strains within a community by drafting and mapping to consensus sequences. We show that CONCOMPRA outperforms several other tools for profiling bacterial communities using full-length 16S rRNA gene sequencing. Since CONCOMPRA does not rely on a sequence database for profiling communities, it is applicable to systems and amplicons for which little to no reference data exists. Our validation test shows that the amplification of long PCR products is likely to produce chimeric byproducts that inflate alpha diversity and skew community structure, stressing the importance of chimera detection. CONCOMPRA is available on GitHub (https://github.com/willem-stock/CONCOMPRA).
GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering
Authors: Cui Lubin , Guo Guiliang , Ng Michael K , Zou Quan , Qiu Yushan
Published: December 2024

Single-cell multi-omics refers to the various types of biological data at the single-cell level. These data have enabled insight and resolution to cellular phenotypes, biological processes, and developmental stages. Current advances hold high potential for breakthroughs by integrating multiple different omics layers. However, singlecell multi-omics data usually have different feature dimensions and direct or indirect relationships. How to keep the data structure of these different data and extract hidden relationships is a major challenge for omics data integration, and effective integration models are urgently needed. In this paper, we propose an irregular tensor decomposition model (GSTRPCA) based on tensor robust principal component analysis (TRPCA). We developed a weighted threshold model for the decomposition of irregular tensor data by combining low-rank and sparsity constraints, which requires that the low-dimensional embeddings of the data remain lowrank and sparse. The major advantage of the GSTRPCA algorithm is its ability to keep the original data structure and explore hidden related features among omics data. For GSTRPCA, we also designed an effective algorithm that theoretically guarantees global convergence for the tensor decomposition. The computational experiments on irregular tensor datasets demonstrate that GSTRPCA significantly outperformed the state-of-the-art methods and hence confirm the superiority of GSTRPCA in clustering single-cell multiomics data. To our knowledge, this is the first tensor decomposition method for irregular tensor data to keep the data structure and hence improve the clustering performance for single-cell multi-omics data. GSTRPCA is a Matlabbased algorithm, and the code is available from https://github.com/GGL-B/GSTRPCA.
scPAS: single-cell phenotype-associated subpopulation identifier
Authors: Xie Aimin , Wang Hao , Zhao Jiaxu , Wang Zhaoyang , Xu Jinyuan , Xu Yan
Published: December 2024

Despite significant advancements in single-cell sequencing analysis for characterizing tissue sample heterogeneity, identifying the associations between cell subpopulations and disease phenotypes remains a challenging task. Here, we introduce scPAS, a new bioinformatics tool designed to integrate bulk data to identify phenotype-associated cell subpopulations within single-cell data. scPAS employs a network-regularized sparse regression model to quantify the association between each cell in single-cell data and a phenotype. Additionally, it estimates the significance of these associations through a permutation test, thereby identifying phenotype-associated cell subpopulations. Utilizing simulated data and various single-cell datasets from breast carcinoma, ovarian cancer, and atherosclerosis, as well as spatial transcriptomics data from multiple cancers, we demonstrated the accuracy, flexibility, and broad applicability of scPAS. Evaluations on large datasets revealed that scPAS exhibits superior operational efficiency compared to other methods. The open-source scPAS R package is available at GitHub website: https://github.com/aiminXie/scPAS.
A likelihood approach to incorporating self-report data in HIV recency classification
Authors: Yang Wenlong , Liu Danping , Bao Le , Li Runze
Published: December 2024

Estimating new HIV infections is significant yet challenging due to the difficulty in distinguishing between recent and long-term infections. We demonstrate that HIV recency status (recent versus long-term) could be determined from self-report testing history and biomarkers, which are increasingly available in bio-behavioral surveys. HIV recency status is partially observed, given the self-report testing history. For example, people who tested positive for HIV over 1 year ago should have a long-term infection. Based on the nationally representative samples collected by the Population-based HIV Impact Assessment (PHIA) Project, we propose a likelihood-based probabilistic model for HIV recency classification. The model incorporates individuals with known recency status based on testing histories and individuals whose recency status could not be determined and integrates the mechanism of how HIV recency status depends on biomarkers and the mechanism of how HIV recency status, together with the self-report time of the most recent HIV test, impacts the test results. We compare our method to logistic regression and the binary classification tree (current practice) on Malawi PHIA data, as well as on simulated data. Our model obtains more efficient and less biased parameter estimates and is relatively robust to potential reporting error and model misspecification.
Graphical model inference with external network data
Authors: Jewson Jack , Li Li , Battaglia Laura , Hansen Stephen , Rossell David , Zwiernik Piotr
Published: December 2024

A frequent challenge when using graphical models in practice is that the sample size is limited relative to the number of parameters. They also become hard to interpret when the number of variables p gets large. We consider applications where one has external data, in the form of networks between variables, that can improve inference and help interpret the fitted model. An example of interest regards the interplay between social media and the co-evolution of the COVID-19 pandemic across USA counties. We develop a spike-and-slab prior framework that depicts how partial correlations depend on the networks, by regressing the edge probabilities, average partial correlations, and their variance on the networks. The goal is to detect when the network data relates to the graphical model and, if so, explain how. We develop computational schemes and software in R and probabilistic programming languages. Our applications show that incorporating network data can improve interpretation, statistical accuracy, and out-of-sample prediction.
Misidentified Victim-Survivors as Domestic and Family Violence Perpetrators: Plea Negotiations as a Tool for Justice?
Authors: Moffa Monique , Flynn Asher , Burns Kate Hutton
Published: December 2024

The misidentification of primary perpetrators in domestic and family violence (DFV) incidents has received increased attention in academic, practitioner and policy contexts. Yet limited research has explored the implications of misidentification for women in criminal proceedings, specifically how misidentification and subsequent criminalisation of women are linked to both erroneous or forced guilty pleas, and a reliance on plea negotiations to correct misidentification errors. Drawing on interviews with 21 legal defence practitioners, we document the strategies practitioners use in the plea negotiation process to advocate for women defendants who have been misidentified in DFV contexts. We also explore the barriers that women defendants face in accessing justice in a discretionary and managerialist criminal justice system.
Deglobalization: three scenarios
Authors: van Bergeijk Peter A G
Published: December 2024

The trade developments of the first quarter of the 21st century prompt speculation on how future generations will perceive them. Will they interpret this era as one where deglobalization took root and flourished, marked by a slowdown in world trade? Or will they view it as a mere pause in globalization’s upward trajectory? The literature explores these possibilities, noting the impact of events like the Financial Crisis, COVID-19 lockdowns and the Ukraine and Gaza wars on world trade. There is disagreement over whether globalization is receding or evolving. Three scenarios offer varied perspectives, from a bleak outlook of disintegrating international relations to a more optimistic view where deglobalization is seen as a temporary setback. These scenarios highlight the complexity and uncertainty surrounding (de)globalization, emphasizing the need for interdisciplinary analysis and a nuanced understanding of global trends.
Measuring and quantifying the effects of pyloric dilatation in patients with delayed emptying of the gastric conduit after Ivor-Lewis esophagectomy using EndoFlip™
Authors: Brunner Stefanie , Lorenz Florian , Dratsch Thomas , Krauss Dolores T , Eckhoff Jennifer A , Schröder Lorenz , Allo Gabriel , Jung Jin-On , Kasper Philipp , Fuchs Hans F , Schroeder Wolfgang , Bruns Christiane J , Goeser Tobias , Chon Seung-Hun
Published: December 2024

The most common functional challenge after Ivor-Lewis esophagectomy is delayed emptying of the gastric conduit. One of the primary endoscopic treatment strategies is performing a pyloric dilatation. However, the effects of dilation have never been scientifically proven. A novel method to detect pyloric distensibility (DI) is the endoluminal functional lumen imaging probe (EndoFlip™). The purpose of this study is to analyze the effects of pyloric dilatation using an EndoFlip™ measurement. Forty-nine patients after Ivor-Lewis esophagectomy were included retrospectively from June 2021 to August 2023 at University Hospital Cologne, Germany. All patients suffered from early delayed emptying of the gastric conduit (DGCE). DI was measured before and after endoscopic dilatation using EndoFlip™ at 40, 45, and 50 mL balloon filling. The Student’s t-test and Chi-Squared test were used. All tests were two-sided, with statistical significance set at P ≤ 0.05. EndoFlip™ measurement and pyloric dilatation were feasible in all patients and no adverse events were recorded. DI proved to be smaller in patients before dilatation compared to patients after dilatation. For 40, 45, and 50 mL balloon filling, the mean DI was 5.0 versus 10.0, 4.5 versus 9.1, and 4.0 and 7.5 mm2/mmHg before versus after dilatation. The differences were significant in all balloon fillings. Endoscopic dilatation of the pylorus is the primary endoscopic treatment strategy in patients suffering from DGCE. Currently, the success of dilatation can only be measured with clinical data. This study could demonstrate that EndoFlip™ can be used as an additional diagnostic tool to rate the success of pyloric dilatation.
Ventricular septal defect characteristics influence presence of septal anatomical isthmuses in patients with repaired tetralogy of Fallot
Authors: Wallet Justin , Kimura Yoshitaka , Blom Nico A , Hazekamp Mark G , Bartelings Margot M , Jongbloed Monique R M , Zeppenfeld Katja
Published: December 2024

Aims

In repaired tetralogy of Fallot (rTOF), the septal anatomical isthmuses (AI), AI 3, between the ventricular septal defect (VSD) and pulmonary annulus, and AI 4, between the VSD and tricuspid annulus, are important ventricular tachycardia (VT) substrates when slow conducting. Our aim was to assess the influence of VSD characteristics, specifically the presence of muscular or fibrous tissue at its border, on the presence or absence of septal AIs, potentially related to VT.

Methods and results

All consecutive rTOF patients who underwent electroanatomical mapping between January 2005 and March 2023 with an available surgical report providing VSD details (n = 91) were included. The majority of patients had an outlet perimembranous VSD (n = 76, 84%), 6 (7%) an outlet muscular VSD, and 7 (8%) a doubly committed juxta-arterial VSD. In patients with an outlet perimembranous VSD, AI 3 was present in almost all (97%), whereas no AI 4 was observed. In patients with an outlet muscular VSD, AI 3 and AI 4 were present in 83% and 33%, respectively. In all patients with a doubly committed VSD, where the outlet septum is hypoplastic/fibrous, AI 3 was absent. Among patients with a doubly committed VSD with a muscular postero-inferior rim, 50% had AI 4, whereas none of those with a fibrous postero-inferior rim had AI 4.

Conclusion

Ventricular septal defect characteristics aid in determining the presence of septal AIs potentially related to VT. In patients with doubly committed VSDs, septal VT substrates are unlikely. Detailed knowledge of anatomical VSD characteristics is desirable for understanding VT in rTOF.
Post-Acute Care Admissions Among Medicare Beneficiaries with Disabilities During Payment Reform and the COVID-19 Pandemic
Authors: Prusynski Rachel , Leland Natalie E , Humbert Andrew , Amaravadi Harsha , Brown Cait , Dahal Arati , Saliba Debra , Mroz Tracy M
Published: December 2024

Background and Objectives

Recent Medicare payment reforms aimed to improve post-acute access to skilled nursing facilities (SNFs) and home health agencies (HHAs) for patients with complex care needs, including beneficiaries with disabilities. Soon after reforms were implemented, the COVID-19 pandemic began, which disproportionately impacted older adults and people with disabilities. Leveraging Medicare administrative data to identify two distinct cohorts of beneficiaries with disabilities, this study explored changes in their SNF and HHA admission patterns during payment reform and COVID-19.

Research Design and Methods

Secondary analysis of 2018-2021 Medicare administrative data for two cohorts of fee-for-service beneficiaries with disabilities: 1) enrollees with disability as the reason for original entitlement (OE) and 2) enrollees qualifying based on age who have disabling conditions and/or mobility impairments (C&I). Adjusted linear mixed effects models with interaction terms for disability cohort estimated whether differences in SNF and HHA admissions following hospitalization varied over time by disability cohort.

Results

For 7,732,989 hospitalizations in the OE cohort and 7,028,195 hospitalizations in the C&I cohort, SNF admissions decreased over time while HHA admissions increased. Compared to the C&I cohort, the OE cohort experienced lower SNF admissions throughout the study and smaller changes in SNF and HHA admissions.

Discussion and Implications

Both disability cohorts experienced decreased SNF and increased HHA admissions following payment reform and COVID-19. The magnitudes of changes differed between the disability cohorts. These results highlight the heterogeneity in healthcare experiences across disability cohorts and the importance of including multiple definitions of disability in research using administrative datasets.
Quantitative Stability of Sobolev Inequalities on Compact Riemannian Manifolds
Authors: Nobili Francesco , Parise Davide
Published: December 2024

We study quantitative stability results for different classes of Sobolev inequalities on general compact Riemannian manifolds. We prove that, up to constants depending on the manifold, a function that nearly saturates a critical Sobolev inequality is quantitatively $W^{1,2}$-close to a non-empty set of extremal functions, provided that the corresponding optimal Sobolev constant satisfies a suitable strict bound. The case of sub-critical Sobolev inequalities is also covered. Finally, we discuss degenerate phenomena in our quantitative controls.