bluuebunny/crossref_metadata_2025 huggingface dataset:
Agroforestry mapping using multi temporal hybrid CNN+LSTM framework with landsat 8 satellite imagery and google earth engine
Authors: Vincent M Jenila , Varalakshmi P
Published: June 2024

Agroforestry is indeed a traditional practice followed in tropical countries like India. About 28.43 million hectare area is used for agroforest cultivation. By 2050 India has the mission of increasing the area under agroforestry to 53 million hectares. In this study, we have made an effort to map the agroforest areas using the geospatial tools and hybrid deep learning techniques. The land utilized for cultivation and various agroforestry activities such as rubber, tea, coconut, and banana plantation were classified as forest canopy by the existing classifiers taking the tree canopy density as a parameter. In light of proposing a solution to the issue, we have put forth a multi temporal hybrid deep learning framework which is a fusion of convolutional neural network, a deep neural net and long short term memory network to classify agroforestry distinguishing it from the forest canopy using remote sensing data. The experimentation was carried out in the southern districts of India, and Landsat 8 imagery was used to classify the agroforestry of the study area that includes tea, banana, rubber, coconut, and crop lands. An efficient multi temporal hybrid deep learning framework was designed to classify the agroforest plantation distinguishing it from crop lands and forest clusters. The experimental results of multi temporal hybrid CNN+LSTM outperformed CNN, LSTM, BiLSTM model reducing the error rate with respective accuracy and kappa score of 98.23% and 0.88. The proposed method provides a benchmark to accurately classify and estimate the LULC, particularly mapping the agroforest plantation for other regions across the country.
Identification and prioritization of context-specific climate smart agricultural (CSA) practices in Ethiopia: a framework approach
Authors: Adimassu Zenebe , Tamene Lulseged , Tibebe Degefie , Ebrahim Mohammed , Abera Wuletawu
Published: June 2024

Ethiopia’s diverse agroecological zones showcase a variety of Climate Smart Agricultural (CSA) Practices, yet the documentation and prioritization of best-bet practices have been lacking. To address this gap, this study utilized the Climate Change, Agriculture, and Food Security (CCAFS)-CSA Prioritization framework. This approach was deployed across nine key agro-ecologies in Ethiopia to identify and prioritize CSA practices based on the three pillars of CSA and gender-equity considerations. By employing this participatory framework, this study successfully identified and prioritized over 200 Climate Smart Agricultural (CSA) practices within Ethiopia’s nine major agroecological zones. These practices were segmented into four main systems: crop management (40 practices), livestock management (41 practices), soil fertility management (40 practices), erosion control and water management (41 practices), and forest and agroforestry (40 practices). Notably, the results highlighted the significance of CSA practices linked to agroforestry/forestry management, rangeland/forage enhancement, exclosure strategies, and water management in addressing the goals associated with the three pillars (productivity, adaptation, mitigation) of CSA practices simultaneously. The findings also revealed that the majority of Climate Smart Agricultural (CSA) practices focused on improving productivity and enhancing adaptation to climate change. Additionally, the results demonstrated that trade-offs exist among the three pillars of CSA, emphasizing the need for integration with other practices to enhance complementarity and achieve all pillars simultaneously. Overall, this study underscores the importance of combining CSA practices of various categories to maximize their effectiveness and impact in sustainable agriculture.
An overview of additively manufactured metal matrix composites: preparation, performance, and challenge
Authors: Chen Liang-Yu , Qin Peng , Zhang Lina , Zhang Lai-Chang
Published: June 2024

Metal matrix composites (MMCs) are frequently employed in various advanced industries due to their high modulus and strength, favorable wear and corrosion resistance, and other good properties at elevated temperatures. In recent decades, additive manufacturing (AM) technology has garnered attention as a potential way for fabricating MMCs. This article provides a comprehensive review of recent endeavors and progress in AM of MMCs, encompassing available AM technologies, types of reinforcements, feedstock preparation, synthesis principles during the AM process, typical AM-produced MMCs, strengthening mechanisms, challenges, and future interests. Compared to conventionally manufactured MMCs, AM-produced MMCs exhibit more uniformly distributed reinforcements and refined microstructure, resulting in comparable or even better mechanical properties. In addition, AM technology can produce bulk MMCs with significantly low porosity and fabricate geometrically complex MMC components and MMC lattice structures. As reviewed, many AM-produced MMCs, such as Al matrix composites, Ti matrix composites, nickel matrix composites, Fe matrix composites, etc, have been successfully produced. The types and contents of reinforcements strongly influence the properties of AM-produced MMCs, the choice of AM technology, and the applied processing parameters. In these MMCs, four primary strengthening mechanisms have been identified: Hall–Petch strengthening, dislocation strengthening, load transfer strengthening, and Orowan strengthening. AM technologies offer advantages that enhance the properties of MMCs when compared with traditional fabrication methods. Despite the advantages above, further challenges of AM-produced MMCs are still faced, such as new methods and new technologies for investigating AM-produced MMCs, the intrinsic nature of MMCs coupled with AM technologies, and challenges in the AM processes. Therefore, the article concludes by discussing the challenges and future interests of AM of MMCs.
Fracturing pump head body failure analysis and improvement measures
Authors: Du Zhe , Xue Jijun
Published: June 2024

The head body of fracturing pump is one of the most easily damaged parts in fracturing equipment. Due to its own structure and working environment, it is easy to cause stress concentration, fatigue cracking and other problems. The working time of a batch of fracturing pump head body used in an oilfield is more than 300 h, and the pump head body is designed by the manufacturer for the oilfield.In this paper, the five-cylinder fracturing pump head body of this batch of cracking occurred as the research object. Firstly, the macro fracture analysis, physical and chemical properties analysis and micro fracture analysis were carried out at the cracking place. Secondly, the finite element analysis and fatigue life analysis were carried out by using ANSYS Workbench software and nCode software to explore the cause of pump head cracking failure. The results show that the crack originates from the sharp corner of the outer corner and spreads to the inner cavity. The chemical composition and mechanical properties of the pump head meet the requirements of the technical agreement. The grain size of the material does not meet the requirements of the technical agreement. The primary fracture morphology observed is indicative of fatigue streaking, while stress concentration can be identified at the location of this crack. There are two reasons for the cracking. First, the structure design is unreasonable and there is a large stress concentration at the cracking location. Second, the grain size of the material is large, resulting in a significant reduction in fatigue life, which is mainly related to the chemical composition of the material, forging process and heat treatment process, and ultimately lead to the pump head body cracking at the outside right Angle shoulder, expanding to the inner cavity, and cracking. According to the analysis results, the improvement measures of pump head body can improve the stress distribution and relieve fatigue. The results can provide a reference for the structural design and optimization of the pump head body.
Thermal modeling, simulation, and experimental validation of micro electric discharge machining of tungsten carbide (WC)
Authors: Ali Sohail , Ali Khan Wajid , Ali Hasnain
Published: June 2024

Tungsten carbide is a material that is widely used in tools and dies applications due to its high hardness, excellent toughness, and wear resistance. However, machining this material using conventional methods can be very challenging due to its exceptional properties. In such cases, electrical discharge machining can be used as an alternative method for machining this material. The aim of this study is to examine the thermal properties of EDM of tungsten carbide, both through finite element modeling and experimental conditions. The study aims to evaluate the temperature distribution in tungsten carbide during EDM die sinking. This is accomplished by drilling 0.5 mm diameter and 1 mm deep micro holes using micro-drilling processes. Seven experiments were performed using an EDM die-sinking machine, and a 3D axis symmetrical model was created and simulated using the COMSOL Multiphysics heat transfer module. The temperature profile of tungsten carbide material during a single spark machining was obtained by considering only 30% of energy in the form of Gaussian distribution that gets transferred to the workpiece. The temperature profile of this model was then used to estimate the material removal rate. By comparing the numerical and experimental results, it was found that there was only a 4.8% average percentage error, indicating very close agreement between the numerical and experimental results. The findings suggest that the finite element method of the COMSOL Multiphysics heat transfer module can accurately predict and simulate the real-time results of EDM machining. These results could be useful for EDM machine operators for pre-estimating MRR and maximum temperatures before proceeding with the actual machining.
Modelling and optimization of fabrication parameters for multi-walled carbon nanotubes-filled GFRP composites using RSM and Rao-1 algorithm
Authors: Ch Rajeswari , Punna Eshwaraiah
Published: June 2024

This study presents an optimized approach for fabricating multi-walled carbon nanotubes (MWCNTs) filled glass fibre reinforced polymers (GFRP) composites using hybrid optimization approach. The experimental runs performed as per Box-Behnken design of response surface methodology (RSM) by considering three fabrication parameters: MWCNT loading, sonication time (ST), and oven curing temperature (OCT), and the output response, ultimate tensile strength (UTS) is noted. Analysis of variance (ANOVA) is employed to ascertain the significance of the effects that each factor has on UTS and found fabrication variables, OCT, and combined effects of ST and OCT are most significant. Other variables, direct effects of MWCNT loading, interaction effects of all three combinations have influence on UTS. Mathematical modeling is postulated using RSM from which contour plots are drawn to illustrate both direct and interactive effects and reveal fabrication parameters have detrimental effects on UTS. The mathematical equation of UTS is then solved by Rao-1 optimization algorithm and obtained condition is: 1.0% of MWCNT loading, 97.5 min of sonication time, and 76 °C of oven curing temperature and corresponding UTS of 624 MPa. SEM analysis has also been performed to verify the distribution of MWCNTs in the GFRP and observed uniform dispersion of MWCNTs in the developed composite. A confirmatory test validates the predicted optimal fabrication condition derived from the RSM combined with Rao-1 algorithm, ensuring that the methodology has ability to enhance the UTS of MWCNTs-embedded GFRP composites.
Design of high-K dielectric HSS-DMG Junctionless FinFET using hetero GOS for nanoscale application
Authors: Kumar Appikatla Phani , Lorenzo Rohit
Published: June 2024

This article presents a detailed investigation of the High-K dielectric horizontal stack spacer (HSS) dual material gate junction-less FinFET device for analog and RF application using the gate oxide stack (GOS) approach. At first, the impact of the horizontal stack spacer (HSS) with different high-K spacer materials are investigated by placing different dielectric material like HfO2, SiO2, Si3N4, and TiO2 on the horizontal spacer. The simulation results of the device indicate that the High-K dielectric HSS makes the device high stability toward the leakage current and static power dissipation at the sub-nano scale regime. The DC characteristics of the device are also investigated alongside the AC/RF characteristics. The proposed device predominantly improves performance in terms of parameters like subthreshold swing, Ion/Ioff, and DIBL. The proposed device shows a high ON current of 8.56 × 10−5 A μm−1, which is about 15% higher than the existing literature, and the device also makes a notable impact on the leakage current by restricting it to 9.635 × 10−12 A/μm. The simulation of the device is carried out with optimization of the doping to investigate and improve the device’s performance. The device shows an excellent improvement in performance which is highly suitable for future-ready device applications.
Mapping construction sector greenhouse gas emissions: a crucial step in sustainably meeting increasing housing demands
Authors: Yoffe Hatzav , Rankin Keagan H , Bachmann Chris , Posen I Daniel , Saxe Shoshanna
Published: June 2024

This paper examines the tension between needing to build more infrastructure and housing and simultaneously reduce greenhouse gas emissions (GHG) to avoid the most catastrophic impacts of climate change. This study uses an Environmentally Extended Input-Output approach to conduct a high-resolution top-down analysis of Canada’s national construction GHG emissions. Our findings highlight that Canada’s current construction practices cannot accommodate the construction required to restore housing affordability by 2030 without substantial environmental consequences. On a consumption life cycle basis, the construction sector was responsible for approximately 90 Mt CO2e in 2018, equivalent to over 8% of Canada’s total GHG emissions, while delivering less than a third of Canada’s annual housing needs. Residential construction was responsible for the largest share (42%) of total construction emissions. Overall, 84% of emissions are from material manufacturing and 35% of construction emissions are imported, underscoring the need for a comprehensive regulatory framework addressing both domestic and imported emissions. Under current construction practices (i.e. current material use patterns and emissions intensities), meeting Canada’s 2030 housing affordability and climate commitments requires an 83% reduction in GHG emissions per construction product (i.e. per home) compared to the 40% economy-wide reduction promised in Canada’s international reduction commitments. Mitigating the GHG gap between emission caps and housing demand calls for changes in the ratio of housing to other infrastructure (e.g. fewer roads, less fossil fuel infrastructure), new construction approaches (e.g. increasing material efficiency) and/or disproportionally allocating climate budget to construction. The implications of our study extend beyond Canada, offering valuable insights for other growing countries with climate goals. The results emphasize the urgency in considering and establishing sectoral GHG budgets for construction and for transformative changes in the construction sector to meet national GHG emission reduction commitments.
Expanding renewable electricity use in global corporate supply chains
Authors: Sievert Katrin , Song Yi , Chen Yuang , Karplus Valerie J
Published: June 2024

Expanding renewable electricity (RE) use in global corporate supply chains can help to achieve global net-zero greenhouse gas emissions targets by mid-century, but efforts face several challenges. First, corporations and their suppliers may be subject to varying climate policy stringency, leading to a misalignment of incentives to act. Second, measuring true progress is difficult, because counterfactuals are unobserved, and measures of effort vary under policy. Third, relevant policy and broader stakeholder audiences differ in the standards of measurement they recognize. Transparent and broadly accepted, or at least interoperable, standards for assessing effort would help corporations and nations strengthen confidence in corporate claims that RE procurement efforts support international climate goals.
Drivers of agrivoltaic perception in California and North Carolina
Authors: Cuppari Rosa Isabella , Fernandez-Bou Angel Santiago , Characklis Gregory W , Ramirez Marielena , Nocco Mallika A , Abou-Najm Majdi
Published: June 2024

The last decade has seen dramatic growth in solar power. In some regions, the most favorable land for solar panels is farmland, which is often flat and exposed to high levels of irradiance. At the same time, the agricultural sector is faced with growing challenges, notably changing water availability and increasingly frequent extreme weather events. The combination of these trends presents an opportunity for a synergistic relationship between the agriculture and solar sectors: agrivoltaic systems (AVS). In AVS, solar panels are placed above and between crops, such that the same land produces both food and energy. This system has beneficial microclimate impacts, such as reduced evapotranspiration. Yet, despite these benefits there has been limited uptake of AVS. One reason may be hesitation on the part of farmers, whose perceptions of AVS have been explored little. This analysis seeks to address part of this gap by exploring the relationship between farmer perceptions and interest in AVS. A Likert scale survey was designed and distributed to farmers across two large, agriculturally productive states, North Carolina and California. Responses from the 41 participants who fully completed the survey suggest that farmers who perceive AVS as diversifying their income or whose goals include reducing water use are the most interested in installing AVS. Respondents also identified financial viability as a major concern, agreeing that upfront cost is a major barrier to AVS, and markets as the most influential driver of crop decisions. These findings provide insights for policymakers interested in expanding AVS, particularly in response to environmental stressors, such as water scarcity and extreme weather events. They also suggest the aspects of AVS that may be most important to farmers, and most effective in encouraging AVS uptake. This information can support efforts to promote AVS, contributing to sustainable agriculture.
Electricity and electromagnetism
Authors: Kragh Helge
Published: June 2024

From their beginning in the eighteenth century, the electrical sciences have given rise to many new words such as electromagnetism, ion, electron, superconductivity, and transistor. The many-sided history of electricity is followed with an emphasis on neologisms and other linguistic aspects. Moreover, a number of related terms and concepts are investigated from a linguistic point of view, including the theory of relativity and the so-called Weber–Fechner law as manifested in various units and scales (decibel, the pH scale, and the Richter scale). One of the sections is devoted to the terminology of solid-state physics.
An assessment of beliefs about mental health care among community-based adults with severe, untreated alcohol use disorder
Authors: Hutchison Morica , Szafranski Sarah , Titus Caitlin , Abar Beau , Conner Kenneth R , Maisto Stephen , Stecker Tracy
Published: June 2024

Objective

Alcohol use disorder (AUD) is among the most prevalent substance use disorders in the USA. Despite availability of effective interventions, treatment initiation and engagement remain low. Existing interventions target motivation and practical barriers to accessing treatment among individuals established within treatment systems. In contrast, Cognitive Behavioral Therapy for Treatment-Seeking (CBT-TS) aims to elicit and modify treatment-seeking beliefs to increase treatment-seeking behaviors among treatment-naïve samples. We aim to understand which beliefs were endorsed by those who did/did not initiate treatment, including changes in number of drinking days.

Method

We examined treatment seeking beliefs elicited during CBT-TS among community-based adults with moderate–severe AUD with no treatment history. In this study, we discuss which beliefs were modifiable (i.e. those discussed during the intervention among individuals who subsequently attended treatment and may be associated with treatment-seeking behaviors).

Results

Of the 194 participants who received the intervention, 16 categories of beliefs were endorsed. Of the 38 participants (19.6%) who attended treatment, the most frequently endorsed belief was ‘Not wanting specific types of substance use treatment or supports’ (50%), a belief that may inhibit treatment seeking. The idea ‘Treatment is positive’ (47%) was also frequently cited, a belief that may facilitate treatment seeking.

Conclusions

This study describes the beliefs that were more frequently endorsed among adults with moderate–severe, but untreated AUD who reported attending treatment following CBT-TS. Findings point to the potential of discussing and modifying treatment-seeking beliefs among treatment-naïve adults with severe AUD to increase treatment-seeking behaviors.
On the agent-relativity of ‘ought’
Authors: Lee Junhyo
Published: June 2024

In the standard theory of deontic modals, ‘ought’ is understood as expressing a propositional operator. However, this view has been called into question by Almotahari and Rabern’s puzzle about deontic ‘ought’, according to which the ethical principle that one ought to be wronged by another person rather than wrong them is intuitively coherent but the standard theory makes it incoherent. In this paper, I take up Almotahari and Rabern’s challenge and offer a refinement of the standard theory to handle the puzzle. I propose that ‘ought’ is evaluated relative to contextual parameters (e.g. Kratzer’s conversational backgrounds, Finlay and Snedegar’s alternative sets) and those contextual parameters are sensitive to agents as well as possible worlds.
Development of a crosswalk to convert French PCS2003 into international ISCO88 occupational classifications. Application to the Occupational Asthma-specific Job-Exposure Matrix (OAsJEM)
Authors: Pilorget Corinne , Dananché Brigitte , Garras Loïc , Orsi Florence , Sit Guillaume , Ribet Céline , Houot Marie-Tülin , Goldberg Marcel , Dumas Orianne , Le Moual Nicole
Published: June 2024

Introduction

The problem of transcoding is recurrent when researchers wish to link occupational data from cohorts to Job-Exposure Matrices (JEMs) which were not set up in the same classifications. The Occupational Asthma-specific JEM (OAsJEM) is a JEM developed for assessing exposure to agents known at risk for asthma for jobs coded with ISCO88 occupation classification. To apply the OAsJEM in the CONSTANCES cohort, in which jobs and industries were coded with French PCS2003 and NAF2008 classifications respectively, we developed a crosswalk to convert jobs from PCS2003 into ISCO88 classification.

Methods

This work was carried out by 2 skilled coders and 1 novice coder who have worked independently by using different tools and transcoding strategies defined a priori. Consensus meetings were organized with skilled coders to define the final crosswalk. This work was elaborated in 2 steps: (i) for 38 ISCO88 codes classified as potentially exposed to cleaning and disinfection products by the OAsJEM, and (ii) for all jobs from the ISCO88 classification. A comparison between the 3 initial coder’s crosswalk proposals and the final crosswalk was made for the 38 ISCO codes in step (i).

Results

The final crosswalk provided 998 matches between the 482 4-digit PCS2003 codes, 308 4-digit ISCO88 codes, and 31 3-digit ISCO88 codes. Information regarding the NAF2008 industry classification was also used in some cases to improve the final crosswalk. For the selected 38 ISCO88 codes, the final crosswalk provided 110 combinations, but the number of proposed ISCO88–PCS2003 couples by each of the 3 coders varied greatly from 68 to 153. In addition, an important variability between the 3 coders were observed among the number of common combinations between the initial coder’s proposals and the final crosswalk (from 47% to 78%).

Discussion

We have developed a crosswalk specifically for an application of the OAsJEM in population-based surveys using the PCS2003 occupation classification. The development of this crosswalk is of great interest for the use of OAsJEM on the data of the CONSTANCES cohort and on any other survey with occupational data coded according to the French classifications. This OAsJEM crosswalk could be used by other teams to evaluate occupational exposures known to be at risk of asthma from occupational calendars coded with French classifications.
Prediction of disease-free survival for precision medicine using cooperative learning on multi-omic data
Authors: Hahn Georg , Prokopenko Dmitry , Hecker Julian , Lutz Sharon M , Mullin Kristina , Sejour Leinal , Hide Winston , Vlachos Ioannis , DeSantis Stacia , Tanzi Rudolph E , Lange Christoph
Published: June 2024

In precision medicine, both predicting the disease susceptibility of an individual and forecasting its disease-free survival are areas of key research. Besides the classical epidemiological predictor variables, data from multiple (omic) platforms are increasingly available. To integrate this wealth of information, we propose new methodology to combine both cooperative learning, a recent approach to leverage the predictive power of several datasets, and polygenic hazard score models. Polygenic hazard score models provide a practitioner with a more differentiated view of the predicted disease-free survival than the one given by merely a point estimate, for instance computed with a polygenic risk score. Our aim is to leverage the advantages of cooperative learning for the computation of polygenic hazard score models via Cox’s proportional hazard model, thereby improving the prediction of the disease-free survival. In our experimental study, we apply our methodology to forecast the disease-free survival for Alzheimer’s disease (AD) using three layers of data. One layer contains epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status and 10 leading principal components. Another layer contains selected genomic loci, and the last layer contains methylation data for selected CpG sites. We demonstrate that the survival curves computed via cooperative learning yield an AUC of around $0.7$, above the state-of-the-art performance of its competitors. Importantly, the proposed methodology returns (1) a linear score that can be easily interpreted (in contrast to machine learning approaches), and (2) a weighting of the predictive power of the involved data layers, allowing for an assessment of the importance of each omic (or other) platform. Similarly to polygenic hazard score models, our methodology also allows one to compute individual survival curves for each patient.
CLEAPA: a framework for exploring the conformational landscape of cryo-EM using energy-aware pathfinding algorithm
Authors: Lin Teng-Yu , Chung Szu-Chi
Published: June 2024

Motivation

Cryo-electron microscopy (cryo-EM) is a powerful technique for studying macromolecules and holds the potential for identifying kinetically preferred transition sequences between conformational states. Typically, these sequences are explored within two-dimensional energy landscapes. However, due to the complexity of biomolecules, representing conformational changes in two dimensions can be challenging. Recent advancements in reconstruction models have successfully extracted structural heterogeneity from cryo-EM images using higher-dimension latent space. Nonetheless, creating high-dimensional conformational landscapes in the latent space and then searching for preferred paths continues to be a formidable task.

Results

This study introduces an innovative framework for identifying preferred trajectories within high-dimensional conformational landscapes. Our method encompasses the search for the minimum energy path in the graph, where edge weights are determined based on the energy estimation at each node using local density. The effectiveness of this approach is demonstrated by identifying accurate transition states in both synthetic and real-world datasets featuring continuous conformational changes.

Availability and implementation

The CLEAPA package is available at https://github.com/tengyulin/energy_aware_pathfinding/.
Drug–target interaction predictions with multi-view similarity network fusion strategy and deep interactive attention mechanism
Authors: Song Wei , Xu Lewen , Han Chenguang , Tian Zhen , Zou Quan
Published: June 2024

Motivation

Accurately identifying the drug–target interactions (DTIs) is one of the crucial steps in the drug discovery and drug repositioning process. Currently, many computational-based models have already been proposed for DTI prediction and achieved some significant improvement. However, these approaches pay little attention to fuse the multi-view similarity networks related to drugs and targets in an appropriate way. Besides, how to fully incorporate the known interaction relationships to accurately represent drugs and targets is not well investigated. Therefore, there is still a need to improve the accuracy of DTI prediction models.

Results

In this study, we propose a novel approach that employs Multi-view similarity network fusion strategy and deep Interactive attention mechanism to predict Drug–Target Interactions (MIDTI). First, MIDTI constructs multi-view similarity networks of drugs and targets with their diverse information and integrates these similarity networks effectively in an unsupervised manner. Then, MIDTI obtains the embeddings of drugs and targets from multi-type networks simultaneously. After that, MIDTI adopts the deep interactive attention mechanism to further learn their discriminative embeddings comprehensively with the known DTI relationships. Finally, we feed the learned representations of drugs and targets to the multilayer perceptron model and predict the underlying interactions. Extensive results indicate that MIDTI significantly outperforms other baseline methods on the DTI prediction task. The results of the ablation experiments also confirm the effectiveness of the attention mechanism in the multi-view similarity network fusion strategy and the deep interactive attention mechanism.

Availability and implementation

https://github.com/XuLew/MIDTI.
Bigtools: a high-performance BigWig and BigBed library in Rust
Authors: Huey Jack D , Abdennur Nezar
Published: June 2024

Motivation

The BigWig and BigBed file formats were originally designed for the visualization of next-generation sequencing data through a genome browser. Due to their versatility, these formats have long since become ubiquitous for the storage of processed sequencing data and regularly serve as the basis for downstream data analysis. As the number and size of sequencing experiments continues to accelerate, there is an increasing demand to efficiently generate and query BigWig and BigBed files in a scalable and robust manner, and to efficiently integrate these functionalities into data analysis environments and third-party applications.

Results

Here, we present Bigtools, a feature-complete, high-performance, and integrable software library for generating and querying both BigWig and BigBed files. Bigtools is written in the Rust programming language and includes a flexible suite of command line tools as well as bindings to Python.

Availability and implementation

Bigtools is cross-platform and released under the MIT license. It is distributed on Crates.io, Bioconda, and the Python Package Index, and the source code is available at https://github.com/jackh726/bigtools.
Evidence for metabolism of creatine by the conceptus, placenta, and uterus for production of adenosine triphosphate during conceptus development in pigs
Authors: Lefevre Carli M , Cain Joe W , Kramer Avery C , Seo Heewon , Lopez Arianna N , Sah Nirvay , Wu Guoyao , Bazer Fuller W , Johnson Gregory A
Published: June 2024

In pigs, the majority of embryonic mortality occurs when free-floating conceptuses (embryos/fetuses and associated placental membranes) elongate, and the uterine–placental interface undergoes folding and develops areolae. Both periods involve proliferation, migration, and changes in morphology of cells that require adenosine triphosphate (ATP). We hypothesize that insufficient ATP in conceptus and uterine tissues contributes to conceptus loss in pigs. Creatine is stored in cells as phosphocreatine for ATP regeneration through the creatine–creatine kinase– phosphocreatine pathway. However, the expression of components of this pathway in pigs has not been examined throughout gestation. Results of qPCR analyses indicated increases in AGAT, GAMT, CKM, CKB, and SLC6A8 mRNAs in elongating porcine conceptuses, and immunofluorescence microscopy localized guanidinoacetate N-methyltransferase, creatine kinase M, and creatine kinase B proteins to the trophectoderm of elongating conceptuses, to the columnar chorionic epithelial cells at the bottom of chorioallantoic troughs, and to endometrial luminal epithelium at the tops of the endometrial ridges of uterine–placental folds on Days 40, 60, and 90 of gestation. Guanidinoacetate N-methyltransferase protein is expressed in endometrial luminal epithelium at the uterine–placental interface, but immunostaining is more intense in luminal epithelium at the bottoms of the endometrial ridges. Results of this study indicate that key elements of the pathway for creatine metabolism are expressed in cells of the conceptus, placenta, and uterus for potential production of ATP during two timepoints in pregnancy with a high demand for energy; elongation of the conceptus for implantation and development of uterine–placental folding during placentation.
Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes
Authors: Liu Xueqing , Qian Tianchen , Bell Lauren , Chakraborty Bibhas
Published: June 2024

In mobile health, tailoring interventions for real-time delivery is of paramount importance. Micro-randomized trials have emerged as the “gold-standard” methodology for developing such interventions. Analyzing data from these trials provides insights into the efficacy of interventions and the potential moderation by specific covariates. The “causal excursion effect,” a novel class of causal estimand, addresses these inquiries. Yet, existing research mainly focuses on continuous or binary data, leaving count data largely unexplored. The current work is motivated by the Drink Less micro-randomized trial from the UK, which focuses on a zero-inflated proximal outcome, i.e., the number of screen views in the subsequent hour following the intervention decision point. To be specific, we revisit the concept of causal excursion effect, specifically for zero-inflated count outcomes, and introduce novel estimation approaches that incorporate nonparametric techniques. Bidirectional asymptotics are established for the proposed estimators. Simulation studies are conducted to evaluate the performance of the proposed methods. As an illustration, we also implement these methods to the Drink Less trial data.
A phase II multicentre study of plasminogen activator inhibitor-1 inhibitor (TM5614) plus nivolumab for treating anti-programmed cell death 1 antibody-refractory malignant melanoma: TM5614-MM trial
Authors: Fujimura Taku , Yoshino Koji , Kato Hiroshi , Fukushima Satoshi , Ishizuki Shoichiro , Otsuka Atsushi , Matsushita Shigeto , Amagai Ryo , Muto Yusuke , Yamazaki Emi , Kambayashi Yumi , Yahata Takashi , Miyata Toshio , Fujisawa Yasuhiro , Asano Yoshihide
Published: June 2024

Background

Anti-programmed cell death 1 antibodies (PD-1 Abs) are widely used for advanced melanoma, but information on the efficacy of anti-PD-1 Abs is limited in the Asian population. There remains an unmet need to improve the therapeutic effects of anti-PD-1 Ab-treatment, particularly in patients with melanoma who are refractory to anti-PD-1 Abs. The aim of this study was to evaluate anti-PD-1 Ab-treatment in combination with TM5614 (a plasminogen activator inhibitor-1 inhibitor) in patients with unresectable melanoma.

Methods

The TM5614-MM study was a multicentre, open-label, single-arm, phase II clinical trial to evaluate the efficacy and safety of nivolumab in combination with TM5614 in patients with advanced, unresectable malignant melanoma recruited at seven Japanese institutes between 13 September 2021 and 31 March 2023. Patients with metastatic or unresectable melanoma previously treated with anti-PD-1 Abs were enrolled. Nivolumab 480 mg was administered intravenously every 4 weeks for 8 weeks, while TM5614 was administered orally at a dose of 120 mg (0–4 weeks) and 180 mg once daily (5–8 weeks). The primary endpoint was the overall response rate after 8 weeks of concomitant use of TM5614.

Results

Thirty-nine patients were enrolled, and 34 patients were included in the anti-PD-1 Ab-refractory cohort. The overall response rate at 8 weeks was 25.9% (95% confidence interval 12.9–44.9%, P = 0.027) in 27 patients who were anti-PD-1 Ab-refractory based on investigator assessment in the protocol per set cohort. Seven patients discontinued treatment owing to progressive disease or adverse events. Treatment-related grade 3 or higher adverse events occurred in 3 of 39 patients (7.7%) in the intention-to-treat cohort.

Conclusions

TM5614 in combination with nivolumab is well tolerated and effective in anti-PD-1 Ab-refractory unresectable melanoma.
Brain lesions causing parkinsonism versus seizures map to opposite brain networks
Authors: Schaper Frederic L W V J , Morton-Dutton Mae , Pacheco-Barrios Niels , Turner Joseph I , Drew William , Khosravani Sanaz , Joutsa Juho , Fox Michael D
Published: June 2024

Recent epidemiological studies propose an association between parkinsonism and seizures, but the direction of this association is unclear. Focal brain lesions causing new-onset parkinsonism versus seizures may provide a unique perspective on the causal relationship between the two symptoms and involved brain networks. We studied lesions causing parkinsonism versus lesions causing seizures and used the human connectome to identify their connected brain networks. Brain networks for parkinsonism and seizures were compared using spatial correlations on a group and individual lesion level. Lesions not associated with either symptom were used as controls. Lesion locations from 29 patients with parkinsonism were connected to a brain network with the opposite spatial topography (spatial r = −0.85) compared to 347 patients with lesions causing seizures. A similar inverse relationship was found when comparing the connections that were most specific on a group level (spatial r = −0.51) and on an individual lesion level (average spatial r = −0.042; P < 0.001). The substantia nigra was found to be most positively correlated to the parkinsonism network but most negatively correlated to the seizure network (spatial r > 0.8). Brain lesions causing parkinsonism versus seizures map to opposite brain networks, providing neuroanatomical insight into conflicting epidemiological evidence.
Population dynamics is a cancer driver
Authors: dos Santos Oliveira Mariana , de C Griebeler Marcelo , Henz Bernardo , dos Santos Filipe Ferreira , Guardia Gabriela D A , Conceição Helena B , Galante Pedro A F , Minussi Darlan C , Oliveira Manuel M , Lenz Guido
Published: June 2024

Most tissues are continuously renovated through the division of stem cells and the death of old or damaged cells, which is known as the cell turnover rate (CTOR). Despite being in a steady state, tissues have different population dynamics thus producing diverse clonality levels. Here, we propose and test that cell population dynamics can be a cancer driver. We employed the evolutionary software esiCancer to show that CTOR, within a range comparable to what is observed in human tissues, can amplify the risk of a mutation due to ancestral selection (ANSEL). In a high CTOR tissue, a mutated ancestral cell is likely to be selected and persist over generations, which leads to a scenario of elevated ANSEL profile, characterized by few niches of large clones, which does not occur in low CTOR. We found that CTOR is significantly associated with the risk of developing cancer, even when correcting for mutation load, indicating that population dynamics per se is a cancer driver. This concept is central to understanding cancer risk and for the design of new therapeutic interventions that minimizes the contribution of ANSEL in cancer growth.
The role of teledermatology for the long-term management of stable psoriasis treated with biologics: a survey-based study
Authors: Portarapillo Antonio , Esposito Valeria , Megna Matteo , Potestio Luca , Comune Rosita , Martora Fabrizio , Ruggiero Angelo
Published: June 2024

Teledermatology may be a useful tool for the management of moderate-to-severe psoriasis. Our result confirmed the efficacy of teledermatology to save patients’ time and to ensure the continuity of care. Teledermatology should be improved with laws and guidelines specifically dedicated to this service.
Are people more concerned about photoaging than skin cancer when raising awareness about risks of skin exposure?
Authors: Dreno Brigitte , Passeron Thierry , Puig Susana , Lim Henry W , Goh Chee Leok , Kang Hee Young , Ly Fatimata , Morita Akimichi , Ocampo-Candiani Jorge , Schalka Sergio , Wei Liu , Demessant Anne Laure , Le Floc’h Caroline , Kerob Delphine , Krutmann Jean
Published: June 2024

This study conducted a comprehensive online survey across 17 countries to assess the influence of fear of skin cancer versus fear of photoaging on photoprotection practices. Revealing significant differences in sun protection behaviors, the research found that individuals concerned about photoaging are more likely to adopt comprehensive sun protection measures compared to those fearful of skin cancer. The findings highlight the potential for integrating concerns about photoaging into skin cancer awareness campaigns to enhance public health strategies for sun protection.
Meta-regression of sulcal patterns, clinical and environmental factors on neurodevelopmental outcomes in participants with multiple CHD types
Authors: Maleyeff Lara , Park Hannah J , Khazal Zahra S H , Wypij David , Rollins Caitlin K , Yun Hyuk Jin , Bellinger David C , Watson Christopher G , Roberts Amy E , Newburger Jane W , Grant P Ellen , Im Kiho , Morton Sarah U
Published: June 2024

Congenital heart disease affects 1% of infants and is associated with impaired neurodevelopment. Right- or left-sided sulcal features correlate with executive function among people with Tetralogy of Fallot or single ventricle congenital heart disease. Studies of multiple congenital heart disease types are needed to understand regional differences. Further, sulcal pattern has not been studied in people with d-transposition of the great arteries. Therefore, we assessed the relationship between sulcal pattern and executive function, general memory, and processing speed in a meta-regression of 247 participants with three congenital heart disease types (114 single ventricle, 92 d-transposition of the great arteries, and 41 Tetralogy of Fallot) and 94 participants without congenital heart disease. Higher right hemisphere sulcal pattern similarity was associated with improved executive function (Pearson r = 0.19, false discovery rate-adjusted P = 0.005), general memory (r = 0.15, false discovery rate P = 0.02), and processing speed (r = 0.17, false discovery rate P = 0.01) scores. These positive associations remained significant in for the d-transposition of the great arteries and Tetralogy of Fallot cohorts only in multivariable linear regression (estimated change β = 0.7, false discovery rate P = 0.004; β = 4.1, false discovery rate P = 0.03; and β = 5.4, false discovery rate P = 0.003, respectively). Duration of deep hypothermic circulatory arrest was also associated with outcomes in the multivariate model and regression tree analysis. This suggests that sulcal pattern may provide an early biomarker for prediction of later neurocognitive challenges among people with congenital heart disease.
The cytoarchitectonic landscape revealed by deep learning method facilitated precise positioning in mouse neocortex
Authors: Liu Zhixiang , Li Anan , Gong Hui , Yang Xiaoquan , Luo Qingming , Feng Zhao , Li Xiangning
Published: June 2024

Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, we developed a cytoarchitectonic landmark identification pipeline. The fluorescence micro-optical sectioning tomography method was employed to image the whole mouse brain stained by general fluorescent nucleotide dye. A fast 3D convolution network was subsequently utilized to segment neuronal somas in entire neocortex. By approach, the cortical cytoarchitectonic profile and the neuronal morphology were analyzed in 3D, eliminating the influence of section angle. And the distribution maps were generated that visualized the number of neurons across diverse morphological types, revealing the cytoarchitectonic landscape which characterizes the landmarks of cortical regions, especially the typical signal pattern of barrel cortex. Furthermore, the cortical regions of various ages were aligned using the generated cytoarchitectonic landmarks suggesting the structural changes of barrel cortex during the aging process. Moreover, we observed the spatiotemporally gradient distributions of spindly neurons, concentrated in the deep layer of primary visual area, with their proportion decreased over time. These findings could improve structural understanding of neocortex, paving the way for further exploration with this method.
The integrated care model: facilitating initiation of or transition to home dialysis
Authors: Poinen Krishna , Mitra Sandip , Quinn Robert R
Published: June 2024

A proportion of end-stage kidney disease (ESKD) patients require kidney replacement therapy to maintain clinical stability. Home dialysis therapies offer convenience, autonomy and potential quality of life improvements, all of which were heightened during the COVID-19 pandemic. While the superiority of specific modalities remains uncertain, patient choice and informed decision-making remain crucial. Missed opportunities for home therapies arise from systemic, programmatic and patient-level barriers. This paper introduces the integrated care model which prioritizes the safe and effective uptake of home therapies while also emphasizing patient-centered care, informed decision-making, and comprehensive support. The integrated care framework addresses challenges in patient identification, assessment, eligibility determination, education and modality transitions. Special considerations for urgent dialysis starts are discussed, acknowledging the unique barriers faced by this population. Continuous quality improvement is emphasized, with the understanding that local challenges may require tailored solutions. Overall, the integrated care model aims to create a seamless and beneficial transition to home dialysis therapies, promoting flexibility and improved quality of life for ESKD patients globally.