bluuebunny/crossref_metadata_2025 huggingface dataset:
A Graph-Based Meta-Data Model for DevOps: Extensions to SSP and SysML2 and a Review on the DCP standard
Authors: Reiterer Stefan H. , Schiffer Clemens , Schwaiger Mario
Published: March 2024

Computer simulation has become a vital tool for modeling complex systems. However, the development and deployment of simulation models often involve multiple stages, tools, and teams, which can lead to significant challenges in maintaining quality, reliability, and efficiency. DevOps, a set of practices that combines software development and IT operations, has emerged as a promising approach to streamline the simulation development. However, most system engineers are not DevOps specialists and there are a lot of manual steps involved when writing build pipelines and configurations of simulations. For this purpose, an abstract graph-based meta-data model was presented in previous work to provide an automation framework for DevOps with simulations. In this work we want to continue our investigations by expanding and harmonizing this approach to better work with established standards like SSP, SysML2 and DCP and demonstrating it's application on real-life use cases.
Testing the verification and validation capability of a DCP based interface for distributed real-time applications
Authors: Segura Mikel , Calderón Alejandro J. , Poggi Tomaso , Barcena Rafael
Published: March 2024

Cyber-physical systems are composed of a variety of elements developed by different vendors that are often geographically distributed. Therefore, its development process presents a double challenge: each element has to be developed individually and, at the same time, a correct interaction with the rest of the elements has to be ensured. In a previous work, we proposed and developed an interface, based on the non-proprietary Distributed Co-simulation Protocol standard, to ease the interaction between these elements. In this paper, we improve it to be applicable in a variety of hardware platforms and we test its applicability for the verification and validation process. To do so, firstly, we prove that our interface is hardware agnostic, demonstrating its easy implementation on different platforms. Secondly, we test its applicability in different X-in-the-Loop simulations. Finally, we also test its behaviour in distributed real-time executions, a necessary requirement for linking elements from different suppliers and helping to preserve their Intellectual Property.
On the Characteristics of One-Dimensional Compressible Flow
Authors: Qiao Hongtao , Kobayashi Takashi , Laughman Christopher , Bortoff Scott
Published: March 2024

Eigen decomposition of the governing equations that describe one-dimensional compressible flow has been presented. Analytical solution of the characteristics of the flow was derived. Simulation studies were conducted to support the theoretical analyses and wave propagation results were discussed in detail. It was found that acoustic effect due to the dynamic momentum led to a significant slowdown in the simulation and could be neglected in models without significant loss in accuracy for applications where energy transfer is of greater interest.
Heat Consumer Model for Robust and Fast Simulations of District Heating Networks
Authors: Zipplies Johannes , Orozaliev Janybek , Vajen Klaus
Published: March 2024

Dynamic thermo-hydraulic simulations of district heating networks are an essential tool to investigate concepts for their sustainable design and operation. The way the numerous heat consumers are modeled has crucial impact on the simulation performance. The proposed model for heat consumers is designed to require low computational effort by using a simplified modeling approach, avoiding state events and limiting its dynamics, while still reproducing their main characteristics. It is tested for a demonstration network, showing its ability to yield realistic results throughout the whole range of operational states including undersupply situations. The results show that the heat consumer model itself requires little time to simulate but still significantly influences the simulation time. Fast dynamics and including a bypass in the model increase the simulation time, so that users should sensibly choose how to use these options. Furthermore, heat consumer models triggering unnecessary state events result in the highest computational effort.
Supporting Infinitely Fast Processes in Continuous System Modeling
Authors: Tinnerholm John Kristofer , Casella Francesco , Pop Adrian
Published: March 2024

In this article, we examine the consequences of introducing a new construct into an equation-based language to model infinitely fast processes. We do this by extending the equation-based language Modelica with a special time constant, Θ. Θ provides modelers with an additional language construct that they can utilize both to improve performance of numerical integration for existing models as well as formulating and simulating models that existing tools struggle with. We present two cases where clear net benefits of introducing this new operator are illustrated. The first being an artificial DAE-System using a monotonic function, the second being an electrical circuit with and without a parasitic capacitance Based on or observations we believe that by enabling modelers to express common idealizations using Θwe can improve both performance and maintainability, since idealizations made by the modeler are encoded explicitly in the model.
Dropwise CondensationWater Drainage Model
Authors: Richardson Marcus Karel , Kunz Robert Francis
Published: March 2024

Modeling of condensation is important to estimating the residual water in small channels. The residual water that forms becomes a water source for permeable materials such as wooden structure or insulation. A model has been implemented in Modelica that will predict the amount of residual moisture after a period of water build up. This model includes parameters to relate droplet physics to a control volume. The parameters provide an macroscopic means of varying droplet adhesion force, droplet velocity, and drainage dynamics. Using CFD data as an example of real world data, this model has been correlated to demonstrate the effects of the parameters.
Modeling and Control Design of an Educational Magnetic Levitation System
Authors: Haumer Anton
Published: March 2024

A magnetic levitation system is a perfect educational example of a nonlinear unstable system. Only with suitable control, a small permanent magnet can be held floating stable below a coil. After modeling and simulation of the system, control of the system can be developed. At the end, the control algorithm can be coded on a microcontroller, connected to a pilot plant.
Automatic Optimization of Energy Supply Systems in Buildings and City Quarters based on Modelica Models
Authors: Schwan Torsten , Feige David , Wenzel Leonhard , Voelckner Charlotte , Leuschke Martin
Published: March 2024

The evaluation and analysis of complex energy supply systems with Modelica models is more and more an integral part of the building design processes. Dynamic system modeling became there especially important regarding analyses of the use of storage and the integration of volatile renewable resources as well as intelligent control. However, this still requires extensive engineering work and time-consuming modeling efforts, although the basic work steps are largely comparable and based on the same fundamentals. Therefore, the open interfaces to and from Modelica offer extensive possibilities for automation and generalization of these processes. This paper describes such a new integrative and automated optimization framework for energy systems of buildings and districts, which uses Modelica models and FMUs iteratively for the identification of optimal system configurations.
Active transfer learning for audiogram estimation
Authors: Twinomurinzi Hossana , Myburgh Herman , Barbour Dennis L.
Published: March 2024

Computational audiology (CA) has grown over the last few years with the improvement of computing power and the growth of machine learning (ML) models. There are today several audiogram databases which have been used to improve the accuracy of CA models as well as reduce testing time and diagnostic complexity. However, these CA models have mainly been trained on single populations. This study integrated contextual and prior knowledge from audiogram databases of multiple populations as informative priors to estimate audiograms more precisely using two mechanisms: (1) a mapping function drawn from feature-based homogeneous Transfer Learning (TL) also known as Domain Adaptation (DA) and (2) Active Learning (Uncertainty Sampling) using a stream-based query mechanism. Simulations of the Active Transfer Learning (ATL) model were tested against a traditional adaptive staircase method akin to the Hughson-Westlake (HW) method for the left ear at frequencies ω=0.25,0.5,1,2,4,8 kHz, resulting in accuracy and reliability improvements. ATL improved HW tests from a mean of 41.3 sound stimuli presentations and reliability of ±9.02 dB down to 25.3±1.04 dB. Integrating multiple databases also resulted in classifying the audiograms into 18 phenotypes, which means that with increasing data-driven CA, higher precision is achievable, and a possible re-conceptualisation of the notion of phenotype classifications might be required. The study contributes to CA in identifying an ATL mechanism to leverage existing audiogram databases and CA models across different population groups. Further studies can be done for other psychophysical phenomena using ATL.
Characterization of reservoir quality in tight sandstones from the Benxi Formation, eastern Ordos Basin, China
Authors: Li Guoyong , Li Cong , Zhang Boming , Zhang Lei , Liang Zhuang , Chen Qi
Published: March 2024

The Benxi Formation in the eastern Ordos Basin harbors abundant natural gas resources and shows promising exploration and development potential. However, the reservoir characteristics are complex, and the primary controlling factors are unclear, presenting significant challenges for reservoir characterization. In response to these challenges, we conducted a systematic study on the characteristics of tight sandstone reservoirs in the Benxi Formation by integrating thin section analysis, scanning electron microscopy, high-pressure mercury injection, and conventional petrophysical analysis alongside well log data analysis. By applying empirical calculation formulas of a porosity evolution quantitative model, we elucidated the primary controlling factors of reservoir heterogeneity. Our research identified that the reservoirs in the eastern Ordos Basin, Benxi Formation, are predominantly composed of quartz sandstone and lithic quartz sandstone, with pore-filling cementation as the dominant cement type and the main storage spaces being intergranular pores and dissolved pores. The homogenization temperatures of fluid inclusions in authigenic quartz range from 92.8 to 185.7°C, indicating that the target layer is in the mesodiagenesis phase B. The main reasons for the differences in reservoir quality in the Benxi Formation are attributed to both sedimentation and diagenesis. In terms of sedimentation, two distinct sedimentary microfacies control the distribution of reservoir quality differences based on variations in quartz content and soluble components. Regarding diagenesis, the Benxi Formation underwent compaction, cementation, and dissolution, with compaction being the fundamental cause of widespread reservoir compaction.
Exploring the potential of pheophorbide A, a chlorophyll-derived compound in modulating GLUT for maintaining glucose homeostasis
Authors: Paul Saptadipa , Pallavi Anuma , Gandasi Nikhil R.
Published: March 2024

Introduction

Pheophorbide A, a chlorophyll-breakdown product, is primarily investigated for its anti-oxidant and anti-inflammatory activity. Recent reports on pheophorbide A have shown its potential in lowering blood glucose levels, thus leading to the exploration of its use in diabetes management. Literature has also shown its effect on enhanced insulin secretion, whereas its mechanism on glucose stimulated insulin secretion (GSIS) in pancreatic β cells remains unexplored.

Methods

In-silico and in-vitro investigations were used to explore the effect of pheophorbide A on class I glucose transporters (GLUTs). In-silico studies include - Molecular docking studies and stability assessment using GROMACS. In-vitro studies include - MTT assay, Glucose uptake assay, Live-cell imaging and tracking of GLUTs in presence of Pheophorbide A compared to control.

Results

Molecular docking studies revealed better binding affinity of pheophorbide A with GLUT4 (−11.2 Kcal/mol) and GLUT1 (−10.7 Kcal/mol) when compared with metformin (−5.0 Kcal/mol and −4.9 Kcal/mol, respectively). Glucose levels are largely regulated by GLUTs where GLUT1 is one of the transporters that is ubiquitously present in human β cells. Thus, we confirmed the stability of the complex, that is, pheophorbide A-GLUT1 using GROMACS for 100 ns. We further assessed its effect on a pancreatic β cell line (INS-1) for its viability using an MTT assay. Pheophorbide A (0.1–1 µM) showed a dose-dependent response on cell viability and was comparable to standard metformin. To assess how pheophorbide A mechanistically acts on GLUT1 in pancreatic β cell, we transfected INS-1 cells with GLUT1–enhanced green fluorescent protein and checked how the treatment of pheophorbide A (0.50 µM) modulates GLUT1 trafficking using live-cell imaging. We observed a significant increase in GLUT1 density when treated with pheophorbide A (0.442 ± 0.01 µm−2) at 20 mM glucose concentration when compared to GLUT1 control (0.234 ± 0.01 µm−2) and metformin (0.296 ± 0.02 µm−2). The average speed and distance travelled by GLUT1 puncta were observed to decrease when treated with pheophorbide A. The present study also demonstrated the potential of pheophorbide A to enhance glucose uptake in β cells.

Conclusion

The current study’s findings were validated by in-silico and cellular analyses, suggesting that pheophorbide A may regulate GLUT1 and might be regarded as a potential lead for boosting the GSIS pathway, thus maintaining glucose homeostasis.
Safety, tolerability, pharmacokinetics and pharmacokinetic-pharmacodynamic modeling of cetagliptin in patients with type 2 diabetes mellitus
Authors: Zhou Chen , Zhou Sufeng , Wang Jie , Xie Lijun , Lv Zhanhui , Zhao Yuqing , Wang Lu , Luo Huan , Xie Daosheng , Shao Feng
Published: March 2024

Aims

To evaluate the safety, tolerability, pharmacokinetics (PK), and pharmacodynamics (PD) of cetagliptin (CAS number:2243737-33-7) in Chinese patients with type 2 diabetes mellitus (T2DM). A population PK/PD model was developed to quantify the PK and PD characteristics of cetagliptin in patients.

Materials and methods

32 Chinese adults with T2DM were enrolled in this study. The subjects were randomly assigned to receive either cetagliptin (50 mg or 100 mg), placebo, or sitagliptin (100 mg) once daily for 14 days. Blood samples were collected for PK and PD analysis. Effects on glucose, insulin, C-peptide, and glucagon were evaluated following an oral glucose tolerance test (OGTT) (day15). Effects on HbA1c and glycated albumin (GA), and safety assessments were also conducted. Meanwhile, a population PK/PD model was developed by a sequential two-step analysis approach using Phoenix.

Results

Following multiple oral doses, cetagliptin was rapidly absorbed and the mean half-life were 34.9-41.9 h. Steady-state conditions were achieved after 1 week of daily dosing and the accumulation was modest. The intensity and duration of DPP-4 inhibition induced by 50 mg cetagliptin were comparable with those induced by sitagliptin, and 100 mg cetagliptin showed a much longer sustained DPP-4 inhibition (≥80%) than sitagliptin. Compared with placebo group, plasma active GLP-1 AUEC0-24h increased by 2.20- and 3.36-fold in the 50 mg and 100 mg cetagliptin groups. A decrease of plasma glucose and increase of insulin and C-peptide were observed following OGTT in cetagliptin groups. Meanwhile, a tendency of reduced GA was observed, whereas no decreasing trend was observed in HbA1c. All adverse events related to cetagliptin and sitagliptin were assessed as mild. A population PK/PD model was successfully established. The two-compartment model and Sigmoid-Emax model could fit the observed data well. Total bilirubin (TBIL) was a covariate of volume of peripheral compartment distribution (V2), and V2 increased with the increase of TBIL.

Conclusions

Cetagliptin was well tolerated, inhibited plasma DPP-4 activity, increased plasma active GLP-1 levels, and exhibited a certain trend of glucose-lowering effect in patients with T2DM. The established population PK/PD model adequately described the PK and PD characteristics of cetagliptin.
Modelling and optimizing microgrid systems with the utilization of real-time residential data: a case study for Palapye, Botswana
Authors: Seane T. B. , Samikannu Ravi , Oladiran Moses Tunde , Yahya Abid , Makepe Patricia , Gamariel Gladys , Kadarmydeen Maruliya Begam , Ladu Nyagong Santino David , Senthamarai Heeravathi
Published: March 2024

Microgrids are becoming a realistic choice for residential buildings due to the increasing need for affordable and sustainable energy solutions in developing nations. Through modeling and simulation, the main goal is to evaluate the viability and performance of a solar microgrid system. Residential load modeling is used, which is vital to developing an effective Energy Management System (EMS) for the microgrid. A residential household’s load metering data is examined using statistical methods, including time series and regression analysis. For the residential community load in this research, Proportional-Integral-Derivative (PID) controllers and Fuzzy Logic Controllers (FLC) are used to generate the necessary Direct Current (DC) microgrid voltage. The simulation research shows that FLC have benefits over PID controllers. The FLC technique performs better at reducing total harmonic distortion, which improves the microgrid system’s overall power quality. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was found to be the most appropriate and reliable model for the dataset after the performance of the models was evaluated using the metrics. The optimization results also showed that FLC optimization improves the microgrid system’s stability. The exponential Gaussian process regression (GPR) produced the highest R-squared measure of 0.49 and RSME measure of 7.9646, making it the best goodness fit for modeling the total daily energy usage and the peak daily usage.
Monitoring ammonia concentrations in more than 10 stations in the Po Valley for the period 2007–2022 in relation to the evolution of different sources
Authors: Colombi C. , D’Angelo L. , Biffi B. , Cuccia E. , Dal Santo U. , Lanzani G.
Published: March 2024

Regarding secondary aerosols, in addition to the significant contribution of anthropogenic gases such as NOx and SO2, atmospheric ammonia (NH3) plays a crucial role as the primary basic gaseous species capable of neutralizing acidic compounds. This acid–base reaction is responsible for the formation of ammonium nitrate (NH4NO3), constituting up to 60% of PM10 within the Po River basin in Italy. Ion chromatographic analyses performed on offline samples indicate that this secondary inorganic species exhibits minimal concentration variability over the Po Valley because of limited air circulation due to orography and mesoscale air circulation. Therefore, investigating gaseous precursors becomes crucial. From the northern to the southern part of Lombardy—the region at the center of the basin—NH3 emission amounts account for 2.5, 11.1, and 27.7 t/y/km2, mainly due to agriculture and livestock activities (∼97%). To study NH3 temporal and spatial variability, the Environmental Protection Agency of Lombardy Region has been monitoring NH3 concentrations across its territory since 2007, with 10 active monitoring sites. Annual and seasonal cycles are presented, along with a focus on different stations, including urban, low-mountain background, high-impact livestock, and rural background, highlighting the impact of various sources. Measurements indicate that within the Po basin, NH3 concentrations can reach up to 700 µg/m3 (as an hourly average) in proximity to the main gaseous NH3 source. Instrument intercomparisons among online monitors and passive vials, as well as different online monitors, are presented. Therefore, this paper provides crucial data to understand the formation of secondary inorganic aerosols in one of the most important hotspot sites for air pollution.
Modeling future land use and land cover under different scenarios using patch-generating land use simulation model. A case study of Ndola district
Authors: Mutale Bwalya , Qiang Fan
Published: March 2024

Accurate predictions of changes in Land-use and Land-cover (LULC) are crucial in climate modeling, providing valuable insights into the possible effects of land-use alterations on Earth’s intricate system. This study focuses on forecasting and examining future LULC changes in the Ndola district from 2022 to 2042, considering three scenarios: Traditional mode (TM), Ecological protection (EP), and Economic Development (ED). TM reflects past land use changes, EP prioritizes environmental conservation, and ED emphasizes economic growth and urbanization. Using the patch-generating land use simulation (PLUS) model, we achieved precise predictions of LULC changes in Ndola district. The model, which combines LEAS rule-extraction with a CA model using CARS, addresses limitations of previous models like CLUE-S, CA-Markov, and FLUS by accurately simulating scattered LULC patterns and the mutual attraction and evolution of open space and urban land under different policies. Using LULC data from the livingatlas platform for the base period (2017–2022), the model demonstrated a Kappa coefficient of 78% and a FoM value of 0.34. Key findings indicate significant trends, such as reductions in forest and agricultural lands in the TM and ED scenarios, with rangeland expanding consistently across all scenarios, particularly in the ED scenario. The decline in agricultural and forest lands raises concerns about household food security, habitat fragmentation, biodiversity loss, and diminished ecosystem services. Urban sprawl onto other land uses could further strain urban infrastructure and public services. Future research should incorporate uncertainty analysis methods such as fuzzy logic or Bayesian methodologies to quantify and differentiate uncertainties related to modeling simulations.
Exploring type I interferon pathway: virulent vs. attenuated strain of African swine fever virus revealing a novel function carried by MGF505-4R
Authors: Dupré Juliette , Le Dimna Mireille , Hutet Evelyne , Dujardin Pascal , Fablet Aurore , Leroy Aurélien , Fleurot Isabelle , Karadjian Grégory , Roesch Ferdinand , Caballero Ignacio , Bourry Olivier , Vitour Damien , Le Potier Marie-Frédérique , Caignard Grégory
Published: March 2024

African swine fever virus represents a significant reemerging threat to livestock populations, as its incidence and geographic distribution have surged over the past decade in Europe, Asia, and Caribbean, resulting in substantial socio-economic burdens and adverse effects on animal health and welfare. In a previous report, we described the protective properties of our newly thermo-attenuated strain (ASFV-989) in pigs against an experimental infection of its parental Georgia 2007/1 virulent strain. In this new study, our objective was to characterize the molecular mechanisms underlying the attenuation of ASFV-989. We first compared the activation of type I interferon pathway in response to ASFV-989 and Georgia 2007/1 infections, employing both in vivo and in vitro models. Expression of IFN-α was significantly increased in porcine alveolar macrophages infected with ASFV-989 while pigs infected with Georgia 2007/1 showed higher IFN-α than those infected by ASFV-989. We also used a medium-throughput transcriptomic approach to study the expression of viral genes by both strains, and identified several patterns of gene expression. Subsequently, we investigated whether proteins encoded by the eight genes deleted in ASFV-989 contribute to the modulation of the type I interferon signaling pathway. Using different strategies, we showed that MGF505-4R interfered with the induction of IFN-α/β pathway, likely through interaction with TRAF3. Altogether, our data reveal key differences between ASFV-989 and Georgia 2007/1 in their ability to control IFN-α/β signaling and provide molecular mechanisms underlying the role of MGF505-4R as a virulence factor.
Retention rate of biologic and targeted synthetic anti-rheumatic drugs in elderly rheumatoid arthritis patients: data from GISEA registry
Authors: Manfredi Andreina , Fornaro Marco , Bazzani Chiara , Perniola Simone , Cauli Alberto , Rai Alessandra , Favalli Ennio Giulio , Bugatti Serena , Rossini Maurizio , Foti Rosario , Conti Fabrizio , Lopalco Giuseppe , Scalvini Anna , Garufi Cristina , Congia Mattia , Gorla Roberto , Gremese Elisa , Atzeni Fabiola , Caporali Roberto , Iannone Florenzo , Sebastiani Marco
Published: March 2024

Objectives

An increased number of elderly individuals affected by rheumatoid arthritis (RA) has been reported, including both patients with RA onset in advanced age and patients aged with the disease. In this registry-based study, we aimed to analyze the retention rate and cause of discontinuation of biologic (b) and targeted synthetic (ts)-disease-modifying anti-rheumatic drugs (DMARDs) in RA patients over 65 year old.

Methods

RA patients enrolled in the Italian GISEA registry and starting a b- or a ts-DMARD over 65 years of age were included. Demographic, clinical, serologic, and therapeutic features were collected.

Results

A total of 1,221 elderly RA patients were analyzed (mean age 71.6 ± 5.2 years). RA was diagnosed before 65 years in 72.5% of cases, a 60.6% of patients experienced a previous b- or ts-DMARD. In patients older than 65 initiating a new b- or ts-DMARDS, tumor necrosis factor alpha inhibitors (TNFi) were prescribed in 29.6% of patients, abatacept in 24.8%, anti-interleukin 6 receptor antagonists (anti-IL6R) in 16.3%, Janus kinases inhibitors (JAKi) in 24.9%, and rituximab in 4.4%. The main causes of discontinuation were primary or secondary inadequate responses (66.1%). The median retention rate for all treatments was 181.3 weeks. A statistically higher retention rate was observed for abatacept when compared to TNFi (p = 0.02), JAKi (p < 0.001), and anti-IL6R (p < 0.001), and for TNFi vs. JAKi (p = 0.013).

Conclusion

We described, in a real-life setting, elderly RA patients treated with a biologic or a ts-DMARD in Italy. Loss of efficacy was the main cause of discontinuation, and the DMARD safety profile suggests that age does not contraindicate their use. Our study reinforced that the control of disease activity is mandatory.
Advancements in autologous peripheral nerve transplantation care: a review of strategies and practices to facilitate recovery
Authors: Xu Guoying , Zou Xiaodi , Dong Yanzhao , Alhaskawi Ahmad , Zhou Haiying , Ezzi Sohaib Hasan Abdullah , Kota Vishnu Goutham , Abdulla Mohamed Hasan Abdulla Hasan , Alenikova Olga , Abdalbary Sahar Ahmed , Lu Hui
Published: March 2024

Autologous peripheral nerve transplantation, a pioneering technique in nerve injury treatment, has demonstrated remarkable progress. We examine recent nursing strategies and methodologies tailored to various anatomical sites, highlighting their role in postoperative recovery enhancement. Encompassing brachial plexus, upper limb, and lower limb nerve transplantation care, this discussion underscores the importance of personalized rehabilitation plans, interdisciplinary collaboration, and innovative approaches like nerve electrical stimulation and nerve growth factor therapy. Moreover, the exploration extends to effective complication management and prevention strategies, encompassing infection control and pain management. Ultimately, the review concludes by emphasizing the advances achieved in autologous peripheral nerve transplantation care, showcasing the potential to optimize postoperative recovery through tailored and advanced practices.
Phybers: a package for brain tractography analysis
Authors: González Rodríguez Lazara Liset , Osorio Ignacio , Cofre G. Alejandro , Hernandez Larzabal Hernan , Román Claudio , Poupon Cyril , Mangin Jean-François , Hernández Cecilia , Guevara Pamela
Published: March 2024

We present a Python library (Phybers) for analyzing brain tractography data. Tractography datasets contain streamlines (also called fibers) composed of 3D points representing the main white matter pathways. Several algorithms have been proposed to analyze this data, including clustering, segmentation, and visualization methods. The manipulation of tractography data is not straightforward due to the geometrical complexity of the streamlines, the file format, and the size of the datasets, which may contain millions of fibers. Hence, we collected and structured state-of-the-art methods for the analysis of tractography and packed them into a Python library, to integrate and share tools for tractography analysis. Due to the high computational requirements, the most demanding modules were implemented in C/C++. Available functions include brain Bundle Segmentation (FiberSeg), Hierarchical Fiber Clustering (HClust), Fast Fiber Clustering (FFClust), normalization to a reference coordinate system, fiber sampling, calculation of intersection between sets of brain fibers, tools for cluster filtering, calculation of measures from clusters, and fiber visualization. The library tools were structured into four principal modules: Segmentation, Clustering, Utils, and Visualization (Fibervis). Phybers is freely available on a GitHub repository under the GNU public license for non-commercial use and open-source development, which provides sample data and extensive documentation. In addition, the library can be easily installed on both Windows and Ubuntu operating systems through the pip library.
Incorporating a-priori information in deep learning models for quantitative susceptibility mapping via adaptive convolution
Authors: Graf Simon , Wohlgemuth Walter A. , Deistung Andreas
Published: March 2024

Quantitative susceptibility mapping (QSM) has attracted considerable interest for tissue characterization (e.g., iron and calcium accumulation, myelination, venous vasculature) in the human brain and relies on extensive data processing of gradient-echo MRI phase images. While deep learning-based field-to-susceptibility inversion has shown great potential, the acquisition parameters applied in clinical settings such as image resolution or image orientation with respect to the magnetic field have not been fully accounted for. Furthermore, the lack of comprehensive training data covering a wide range of acquisition parameters further limits the current QSM deep learning approaches. Here, we propose the integration of a priori information of imaging parameters into convolutional neural networks with our approach, adaptive convolution, that learns the mapping between the additional presented information (acquisition parameters) and the changes in the phase images associated with these varying acquisition parameters. By associating a-priori information with the network parameters itself, the optimal set of convolution weights is selected based on data-specific attributes, leading to generalizability towards changes in acquisition parameters. Moreover, we demonstrate the feasibility of pre-training on synthetic data and transfer learning to clinical brain data to achieve substantial improvements in the computation of susceptibility maps. The adaptive convolution 3D U-Net demonstrated generalizability in acquisition parameters on synthetic and in-vivo data and outperformed models lacking adaptive convolution or transfer learning. Further experiments demonstrate the impact of the side information on the adaptive model and assessed susceptibility map computation on simulated pathologic data sets and measured phase data.
Diagnosis of benign and malignant peripheral lung lesions based on a feature model constructed by the random forest algorithm for grayscale and contrast-enhanced ultrasound
Authors: Wei Hong , Wang Yichun , Li Jinyao , Wang Yanyan , Lu Longdi , Sun Jiawei , Wang Xiaolei
Published: March 2024

Rationale and objectives

To construct a predictive model for benign and malignant peripheral pulmonary lesions (PPLs) using a random forest algorithm based on grayscale ultrasound and ultrasound contrast, and to evaluate its diagnostic value.

Materials and methods

We selected 254 patients with PPLs detected using chest lung computed tomography between October 2021 and July 2023, including 161 malignant and 93 benign lesions. Relevant variables for judging benign and malignant PPLs were screened using logistic regression analysis. A model was constructed using the random forest algorithm, and the test set was verified. Correlations between these relevant variables and the diagnosis of benign and malignant PPLs were evaluated.

Results

Age, lesion shape, size, angle between the lesion border and chest wall, boundary clarity, edge regularity, air bronchogram, vascular signs, enhancement patterns, enhancement intensity, homogeneity of enhancement, number of non-enhancing regions, non-enhancing region type, arrival time (AT) of the lesion, lesion-lung AT difference, AT difference ratio, and time to peak were the relevant variables for judging benign and malignant PPLs. Consequently, a model and receiver operating characteristic curve were constructed with an AUC of 0.92 and an accuracy of 88.2%. The test set results showed that the model had good predictive ability. The index with the highest correlation for judging benign and malignant PPLs was the AT difference ratio. Other important factors were lesion size, patient age, and lesion morphology.

Conclusion

The random forest algorithm model constructed based on clinical data and ultrasound imaging features has clinical application value for predicting benign and malignant PPLs.
RAAWC-UNet: an apple leaf and disease segmentation method based on residual attention and atrous spatial pyramid pooling improved UNet with weight compression loss
Authors: Wang Jianlong , Jia Junhao , Zhang Yake , Wang Haotian , Zhu Shisong
Published: March 2024

Introduction

Early detection of leaf diseases is necessary to control the spread of plant diseases, and one of the important steps is the segmentation of leaf and disease images. The uneven light and leaf overlap in complex situations make segmentation of leaves and diseases quite difficult. Moreover, the significant differences in ratios of leaf and disease pixels results in a challenge in identifying diseases.

Methods

To solve the above issues, the residual attention mechanism combined with atrous spatial pyramid pooling and weight compression loss of UNet is proposed, which is named RAAWC-UNet. Firstly, weights compression loss is a method that introduces a modulation factor in front of the cross-entropy loss, aiming at solving the problem of the imbalance between foreground and background pixels. Secondly, the residual network and the convolutional block attention module are combined to form Res_CBAM. It can accurately localize pixels at the edge of the disease and alleviate the vanishing of gradient and semantic information from downsampling. Finally, in the last layer of downsampling, the atrous spatial pyramid pooling is used instead of two convolutions to solve the problem of insufficient spatial context information.

Results

The experimental results show that the proposed RAAWC-UNet increases the intersection over union in leaf and disease segmentation by 1.91% and 5.61%, and the pixel accuracy of disease by 4.65% compared with UNet.

Discussion

The effectiveness of the proposed method was further verified by the better results in comparison with deep learning methods with similar network architectures.
Identification of leaf diseases in field crops based on improved ShuffleNetV2
Authors: Zhou Hanmi , Chen Jiageng , Niu Xiaoli , Dai Zhiguang , Qin Long , Ma Linshuang , Li Jichen , Su Yumin , Wu Qi
Published: March 2024

Rapid and accurate identification and timely protection of crop disease is of great importance for ensuring crop yields. Aiming at the problems of large model parameters of existing crop disease recognition methods and low recognition accuracy in the complex background of the field, we propose a lightweight crop leaf disease recognition model based on improved ShuffleNetV2. First, the repetition number and the number of output channels of the basic module of the ShuffleNetV2 model are redesigned to reduce the model parameters to make the model more lightweight while ensuring the accuracy of the model. Second, the residual structure is introduced in the basic feature extraction module to solve the gradient vanishing problem and enable the model to learn more complex feature representations. Then, parallel paths were added to the mechanism of the efficient channel attention (ECA) module, and the weights of different paths were adaptively updated by learnable parameters, and then the efficient dual channel attention (EDCA) module was proposed, which was embedded into the ShuffleNetV2 to improve the cross-channel interaction capability of the model. Finally, a multi-scale shallow feature extraction module and a multi-scale deep feature extraction module were introduced to improve the model’s ability to extract lesions at different scales. Based on the above improvements, a lightweight crop leaf disease recognition model REM-ShuffleNetV2 was proposed. Experiments results show that the accuracy and F1 score of the REM-ShuffleNetV2 model on the self-constructed field crop leaf disease dataset are 96.72% and 96.62%, which are 3.88% and 4.37% higher than that of the ShuffleNetV2 model; and the number of model parameters is 4.40M, which is 9.65% less than that of the original model. Compared with classic networks such as DenseNet121, EfficientNet, and MobileNetV3, the REM-ShuffleNetV2 model not only has higher recognition accuracy but also has fewer model parameters. The REM-ShuffleNetV2 model proposed in this study can achieve accurate identification of crop leaf disease in complex field backgrounds, and the model is small, which is convenient to deploy to the mobile end, and provides a reference for intelligent diagnosis of crop leaf disease.
Transcriptome and co-expression network revealed molecular mechanism underlying selenium response of foxtail millet (Setaria italica)
Authors: Wen Yinyuan , Cheng Liuna , Zhao Zeya , An Mengyao , Zhou Shixue , Zhao Juan , Dong Shuqi , Yuan Xiangyang , Yin Meiqiang
Published: March 2024

Introduction

Selenium-enriched foxtail millet (Setaria italica) represents a functional cereal with significant health benefits for humans. This study endeavors to examine the impact of foliar application of sodium selenite (Na2SeO4) on foxtail millet, specifically focusing on selenium (Se) accumulation and transportation within various plant tissues.

Methods

To unravel the molecular mechanisms governing selenium accumulation and transportation in foxtail millet, we conducted a comprehensive analysis of selenium content and transcriptome responses in foxtail millet spikelets across different days (3, 5, 7, and 12) under Na2SeO4 treatment (200 μmol/L).

Results

Foxtail millet subjected to selenium fertilizer exhibited significantly elevated selenium levels in each tissue compared to the untreated control. Selenate was observed to be transported and accumulated sequentially in the leaf, stem, and spikes. Transcriptome analysis unveiled a substantial upregulation in the transcription levels of genes associated with selenium metabolism and transport, including sulfate, phosphate, and nitrate transporters, ABC transporters, antioxidants, phytohormone signaling, and transcription factors. These genes demonstrated intricate interactions, both synergistic and antagonistic, forming a complex network that regulated selenate transport mechanisms. Gene co-expression network analysis highlighted three transcription factors in the tan module and three transporters in the turquoise module that significantly correlated with selenium accumulation and transportation. Expression of sulfate transporters (SiSULTR1.2b and SiSULTR3.1a), phosphate transporter (PHT1.3), nitrate transporter 1 (NRT1.1B), glutathione S-transferase genes (GSTs), and ABC transporter (ABCC13) increased with SeO42- accumulation. Transcription factors MYB, WRKY, and bHLH were also identified as players in selenium accumulation.

Conclusion

This study provides preliminary insights into the mechanisms of selenium accumulation and transportation in foxtail millet. The findings hold theoretical significance for the cultivation of selenium-enriched foxtail millet.
Visual vertical neglect in acquired brain injury: a systematic review
Authors: Moretta Pasquale , Cavallo Nicola Davide , Fonzo Eleonora , Maiorino Antonio , Ferrante Cesario , Ambrosino Pasquale , Femiano Cinzia , Santangelo Gabriella , Marcuccio Laura
Published: March 2024

Vertical neglect represents a visuospatial deficit occurring as a possible consequence of acquired brain injury (ABI). Differently from unilateral spatial neglect on horizontal space, vertical neglect is poorly studied in the literature and rarely assessed in clinical practice. In the available studies, the terms “radial,” “vertical,” and “altitudinal” neglect are often used interchangeably, although they do not describe the same spatial dimension. “Altitudinal” and “vertical” refer to the sagittal plane, whereas “radial” refers to the transverse plane. The term “vertical” is sometimes used interchangeably with respect to both axes. The aim of this systematic review was to identify the main characteristics of vertical neglect after ABI, the diagnostic tools used, and the treatment options. We also proposed a clarification of the manifestations and characteristics of vertical and radial neglect. The 23 articles reviewed, showed that the vertical neglect occurred more frequently on the lower space than on the upper space, that its presence was associated with horizontal neglect, and that it could also occur with compromise of the radial space, with the near radial being more common. The most frequent etiology associated with vertical neglect is vascular, particularly ischaemic. The lesions side are very heterogeneous and include both cortical and subcortical areas and all lobes, although the temporal lobe is most affected. With regard to the assessment tools, paper and pencil tasks are the most commonly used diagnostic tools to identify vertical neglect, although in recent years the use of computer-based tasks increased. Taken together, our results suggest that vertical neglect may be underestimated in patients with right hemisphere lesions and should always be assessed, especially in cases where the patient shows signs of horizontal neglect. The clinical assessment of vertical neglect is very important since it can lead to important functional limitations in everyday life, such as poor wheelchair handling, stumbling over unnoticed obstacles located below (or above), walking down stairs, taking off shoes.
Personal dispositions explain differences in physical health benefits of nature exposure: the role of restorativeness and affect
Authors: Russo Claudia , Romano Luciano , Spano Giuseppina , Theodorou Annalisa , Carrus Giuseppe , Mastandrea Stefano , Angelini Cinzia , Sanesi Giovanni , Panno Angelo
Published: March 2024

Introduction

Urbanization processes are constantly increasing, and most of the European population currently live in urban areas. Nevertheless, evidence is consistent in highlighting the positive association between nature exposure and human wellbeing, although individual differences might affect this association.

Methods

The present study aimed to investigate the association among nature connectedness, conceptualized as Love and Care for Nature, place identity, and physical wellbeing, via restorativeness and positive and negative affect. A total of 312 visitors of an urban green area (i.e., Milan’s Parco Nord) participated in the study. They completed an anonymous questionnaire.

Results

Findings showed that nature connectedness and place identity positively affect physical wellbeing, via restorativeness and positive affect, but not through the negative ones.

Discussion

Results highlight the importance of the joint role of exposure to nature and individual differences in promoting wellbeing. This study offers implications for interventions aimed at enhancing individuals’ health through exposure to nature. Limitations of the study and future research developments are discussed.
World addiction medicine reports: formation of the International Society of Addiction Medicine Global Expert Network (ISAM-GEN) and its global surveys
Authors: Ekhtiari Hamed , Khojasteh Zonoozi Arash , Rafei Parnian , Abolghasemi Fateme Sadat , Pemstein Dan , Abdelgawad Tarek , Achab Sophia , Ghafri Hamad Al , Al’Absi Mustafa , Bisch Michaël , Conti Aldo Alberto , Ambekar Atul , Arunogiri Shalini , Bhad Roshan , Bilici Rabia , Brady Kathleen , Bunt Gregory , Busse Anja , Butner Jenna L. , Danesh Ahmad , El-Khoury Joseph , Omari Fatima El , Jokūbonis Darius , Jong Cor de , Dom Geert , Ebrahimi Mohsen , Fathi Jouzdani Ali , Ferri Marica , Galea-Singer Susanna , Parker Dario Gigena , Higuchi Susumu , Kathiresan Preethy , Khelifa Emira , Kouimtsidis Christos , Krupitsky Evgeny M. , Long Jiang , Maremmani Icro , McGovern Garrett , Mohaddes Ardabili Hossein , Rahimi-Movaghar Afarin , Rataemane Solomon Tshimong , Sangchooli Arshiya , Sibeko Goodman , Vella Anna Maria , Vista Salvador Benjamin D. , Zare-Bidoky Mehran , Zhao Min , Javed Afzal , Potenza Marc N. , Baldacchino Alexander Mario
Published: March 2024

Addiction medicine is a dynamic field that encompasses clinical practice and research in the context of societal, economic, and cultural factors at the local, national, regional, and global levels. This field has evolved profoundly during the past decades in terms of scopes and activities with the contribution of addiction medicine scientists and professionals globally. The dynamic nature of drug addiction at the global level has resulted in a crucial need for developing an international collaborative network of addiction societies, treatment programs and experts to monitor emerging national, regional, and global concerns. This protocol paper presents methodological details of running longitudinal surveys at national, regional, and global levels through the Global Expert Network of the International Society of Addiction Medicine (ISAM-GEN). The initial formation of the network with a recruitment phase and a round of snowball sampling provided 354 experts from 78 countries across the globe. In addition, 43 national/regional addiction societies/associations are also included in the database. The surveys will be developed by global experts in addiction medicine on treatment services, service coverage, co-occurring disorders, treatment standards and barriers, emerging addictions and/or dynamic changes in treatment needs worldwide. Survey participants in categories of (1) addiction societies/associations, (2) addiction treatment programs, (3) addiction experts/clinicians and (4) related stakeholders will respond to these global longitudinal surveys. The results will be analyzed and cross-examined with available data and peer-reviewed for publication.