bluuebunny/crossref_metadata_2025 huggingface dataset:
The effect of model uncertainties in the reinforcement learning based regulation problem: An experimental case study with inverted pendulum
Authors: Pal Amit Kumar , Oveisi Atta , Nestorović Tamara
Published: October 2023

This work aims to improve the classical white‐box model of an inverted pendulum in order to reach a more accurate representation of an actual pendulum on a cart system. The purpose of the model is to train different controllers based on machine learning algorithms. In the context of this paper, the inverted pendulum system is driven by a belt drive that is controlled by a stepper motor. Due to the nature of the controller, the input to the stepper motor is in the form of a non‐smooth bang‐bang‐like signal that moves the cart to the left, right, or terminates its movement. One of the main challenges, in this case, is to find a proper function to model the stepper motor as its dynamics cannot be captured with a constant gain. It has been shown that the transient behavior of the stepper motor when changing direction or stopping is not negligible in the closed‐loop control performance. Accordingly, a grey‐box scheme, which accounts for the uncertainties that are not included in the vanilla white‐box model, is utilized to achieve a lower model mismatch compared to the actual pendulum. Initially, the equation of motion was derived using the Euler‐Lagrange equation with force on the cart as the control input. But in the real‐time experiment, the interface is realized by the stepper motor's frequency modulator, hence a transfer function representing the relationship between the frequency and the force applied on the cart (in the model) is calculated as a black‐box model. To improve the accuracy of the transfer function, an experimental data‐driven design of this function is performed based on modern schemes in system identification. For this purpose, the applied frequency to the stepper motor and the states from the actual system are recorded. Then, the applied force on the cart is calculated using the equation of motion and the recorded states. It is also shown that the frequency‐force transfer function uncertainty due to exogenous disturbances is non‐negligible and with the aim of having a more accurate model, an artificial neural network is introduced. Finally, the effectiveness of this grey‐box model is shown by training and implementing a deep Q‐network based controller to swing up and balance the inverted pendulum.
Hemispheric asymmetry of auditory oddball detection: An MEG study
Authors: Zhao Chen , Bao Yan
Published: October 2023

The capacity of the human brain to detect unattended deviant information from frequent information in our environment shows a hemispheric asymmetry, with stronger brain activation in the right temporal area. This lateralization is distinct from the functional left‐ward asymmetry of auditory information processing.
Influence of humidity on the plasma‐assisted CO2 conversion
Authors: Attri Pankaj , Okumura Takamasa , Takeuchi Nozomi , Kamataki Kunihiro , Koga Kazunori , Shiratani Masaharu
Published: October 2023

The current research focuses on carbon dioxide (CO2) conversion at ambient conditions using streamer plasma. In this study, treatment time and humidity have been found to influence CO2 conversion. Our findings reveal a maximum CO2 conversion rate of 35.2%, achieved with a remarkably high energy efficiency of CO2 conversion at 135% and a low energy cost of 2.17 eV/molecule. We employed optical emission and fourier‐transform infrared spectroscopy spectroscopy to analyze the different dissociation products of CO2 and determine the percentage of CO2 conversion. Furthermore, we utilized a two‐dimensional (2D) fluid dynamics model and a zero‐dimensional (0D) chemistry model to gain insights into the reactor mechanism.
On the regulation of human D‐aspartate oxidase
Authors: Rabattoni Valentina , Motta Zoraide , Miceli Matteo , Molla Gianluca , Fissore Alex , Adinolfi Salvatore , Pollegioni Loredano , Sacchi Silvia
Published: October 2023

The human flavoenzyme D‐aspartate oxidase (hDASPO) controls the level of D‐aspartate in the brain, a molecule acting as an agonist of NMDA receptors and modulator of AMPA and mGlu5 receptors. hDASPO‐induced D‐aspartate degradation prevents age‐dependent deterioration of brain functions and is related to psychiatric disorders such as schizophrenia and autism. Notwithstanding this crucial role, less is known about hDASPO regulation. Here, we report that hDASPO is nitrosylated in vitro, while no evidence of sulfhydration and phosphorylation is apparent: nitrosylation affects the activity of the human flavoenzyme to a limited extent. Furthermore, hDASPO interacts with the primate‐specific protein pLG72 (a well‐known negative chaperone of D‐amino acid oxidase, the enzyme deputed to D‐serine degradation in the human brain), yielding a ~114 kDa complex, with a micromolar dissociation constant, promoting the flavoenzyme inactivation. At the cellular level, pLG72 and hDASPO generate a cytosolic complex: the expression of pLG72 negatively affects the hDASPO level by reducing its half‐life. We propose that pLG72 binding may represent a protective mechanism aimed at avoiding cytotoxicity due to H2O2 produced by the hDASPO enzymatic degradation of D‐aspartate, especially before the final targeting to peroxisomes.
Bio‐electrospraying 3‐D Organotypic Human Skin Cultures
Authors: Jayarajan Vignesh , Auguste Jensen O. , Gene Kenilson A. , Auguste Libny , Nunez Camilo , Marcinowski Bartlomiej , Jayasinghe Suwan N.
Published: October 2023

Organotypic 3D tissue models have greatly contributed to understand a wide range of molecular and cellular characteristics within a functional or diseased tissue. Human skin reconstructs which act as models are most useful for a wide range of investigations, ranging from tissue engineering and regenerative medicine, drug development, screening, and discovery to name a few. There are many approaches for reconstructing 3D skin tissue models, however, to date there have been very few that are able to generate organotypic 3D constructs with a single technology having minimal processing steps to finally scalability. The many manifestations of 3D bioprinting have contributed to this endeavor, having said that, the technology's limitations have tempered those reconstructed models, as they are known to contain low cell numbers/concentrations to those having damaged/dead molecules/cells within the reconstructed tissue, which are not desirable, for exploring as tissues models. Contrary to 3D bioprinting approaches, bio‐electrosprays have been demonstrated to possess the ability to handle large concentrations of cells and molecules to whole fertilized embryos without damaging them from a molecular level upwards. Consequently, this article demonstrates, for the first time, bio‐electrospray's capacity to reconstruct skin‐like structures in vitro and its potential in reconstructing full‐thickness 3D organotypic human skin tissues.
An Artificial Intelligence‐Based Framework to Accelerate Data‐Driven Policies to Promote Solar Photovoltaics in Lisbon
Authors: Freitas Sara , Silva Miguel , Silva Eduardo , Marceddu Alessandro , Miccoli Massimo , Gnatyuk Petro , Marangoni Luca , Amicone Alessandro
Published: October 2023

Due to the unavailability of up‐to‐date and georeferenced information about Lisbon's existing solar energy systems, tracking the progress of solar energy in relation to the city's Climate Action Plans 2030 is a complex task, thus hindering the potential of data‐driven decision‐making for a targeted implementation of photovoltaics (PV) in buildings and urban infrastructure. To overcome the challenges posed, an integrated approach to accelerate policy‐making based on artificial intelligence (AI) resources and local citizens' and stakeholders' participation is developed and piloted in Lisbon. Recurring to a two‐step AI model setup to identify and geolocate PV systems, key policy indicators are calculated to inform policy‐makers about the evolution of PV deployment in the city and contribute to tailor future incentives to more depressed or energy poor districts. The AI model based on open data orthophotos from 2016 allowed estimates for the installed peak power at the city level, in that year, to be delivered in a few minutes, whereas manual inspection of aerial images will have taken several months. Although the PV capacity determined is 30% lower than the historical official numbers, the proof of concept for the proposed framework is achieved and validated by local stakeholders.
Energy Band Alignment at p–n Heterojunction Interface in CZTSSe Solar Cells with Novel ZnMgO Buffer Layer
Authors: Wang Yafei , Tong Hao , Tao Shengye , Dong Liangzheng , Gong Qianming , Han Junsu , Wang Hanpeng , Jia Mengyao , Wu Zhihao , Zhuang Daming , Zhao Ming
Published: October 2023

By substituting Zn1−xMgxO (ZMO) for the conventional CdS buffer layer, the CZTSSe solar cells with the efficiency of 11.2% are obtained herein, which can be attributed to the conduction band regulation in the heterojunction. An appropriate conduction band offset (CBO) value can effectively reduce nonradiative recombination loss of charge carriers at the interface, thereby improving the open‐circuit voltage (Voc). Herein, ZMO buffer layer with the optical bandgap ranging from 3.34 to 3.90 eV is applied to enhance the CBO in the heterojunction from 0.14 to 0.72 eV. The ZMO‐buffered solar cells exhibit higher Voc and short‐current density (Jsc) compared to CdS‐buffered cells. The optimal efficiency of 11.2% is obtained in CZTSSe solar cell with the CBO of 0.27 eV, Jsc of 39.0 mA cm−2, fill factor of 69.6%, and Voc of 412 mV.
Optimization of Wire Arc Additive Manufacturing Process Parameters for Low‐Carbon Steel and Properties Prediction by Support Vector Regression Model
Authors: Barik Sougata , Bhandari Rahul , Mondal Manas Kumar
Published: October 2023

This study aims to optimize the process parameters of wire arc additive manufacturing for ER70S6 steel and to build a machine‐learning (ML) model to predict the properties of deposited specimens. Process parameters such as current, voltage, and travel speed are optimized considering other process parameters constant (gas flow rate, contact tip to the work distance, and preheat). The optimization is made using the response surface method and validated the properties by experimentation, including tensile testing and metallography. A support vector regression (SVR) ML model is implemented to predict the material's properties to substantiate the outcomes’ values in every possible combination for the given parameters. In the study's findings, a significant enhancement is revealed in specimen quality, marked by reduced irregularities and porosity, and a remarkable increase in ultimate tensile strength up to 40%, validated through the SVR model. In this study, a valuable path that can be extended to predict properties of other material systems is sketched.
Electromagnetic Characteristics Analysis of a Novel Differential Dual‐Rotor Contra‐Rotating Axial‐Flux PM Motor with Equidirectional Toroidal Winding
Authors: Liao Xiaohui , Li Shihao , Nie Rui , Wang Peixin , Si Jikai
Published: October 2023

In this paper, a novel differential dual‐rotor contra‐rotating axial‐flux PM (DDC‐AFPM) motor with equidirectional toroidal winding (EDTW) applied to electric propulsion of ships is proposed. Different from the conventional AFPM motor with contra‐rotating rotors (CR), the rotors of the proposed motor on both sides of the stator rotate oppositely at different speeds. The structure of the proposed motor is introduced and the operation principle is clarified. Initial parameters of the proposed motor are given, and the correctness of the simulation results is indirectly verified through the prototype of the AFPM motor with dual‐rotor and EDTW. In order to further improve the electromagnetic performance of the proposed motor, parameters of the motor are preliminarily improved. Finally, the electromagnetic characteristics including armature field, no‐load and on‐load characteristics of the proposed motor are analyzed based on three‐dimensional finite element method (3D‐FEM). The simulation results show that the proposed motor has good electromagnetic characteristics and is suitable for ship propulsion. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
Hair corticosterone concentration as a potential stress marker in pet rabbits
Authors: Hube Dana , van Meegen Carmen , Herbrandt Swetlana , Kemper Nicole , Fels Michaela
Published: October 2023

Background

As a prey species, rabbits tend to hide their illnesses and injuries. Consequently, pet rabbit owners often do not notice that their pet may be suffering.

Methods

Data on the housing and health of 34 dwarf rabbits were collected from a total of 22 rabbit owners. A score from 0 (not stressed) to 3 (highly stressed) was assigned to each rabbit based on the owners’ reports. Afterwards, the hair corticosterone concentration (HCC) of the rabbits was analysed as an indicator of long‐term stress.

Results

The mean HCC of all rabbits was 1.54 ± 0.64 pg/mg. Animals with a stress score of 3 had a higher HCC (2.17 pg/mg) than those with a score of 0 (1.09 pg/mg) or 1 (1.44 pg/mg) (p < 0.05). HCC was not significantly affected by sex or age (p > 0.05).

Limitation

Only a small number of rabbits were included in the study. Therefore, the findings need to be confirmed in a larger cohort of animals.

Conclusion

HCC seems to be a promising stress marker in pet rabbits.
Surgical outcomes for cutaneous squamous cell carcinoma of the auricle
Authors: Manole Constantin , Skinner Liam J. , Donnelly Martin J.
Published: October 2023

Background

Cutaneous squamous cell carcinoma (CSCC) on the auricle is believed to carry a higher risk of metastatic spread. The rates of lymphatic metastasis reported in the literature have varied widely. There are no established prognostic criteria to determine which of these tumors are higher risk and warrant prophylactic treatment of the associated lymphatic basins.

Objective

To retrospectively evaluate outcomes after surgical treatment of auricular CSCC in our department, examining excision completeness, tumor recurrence, and lymphatic metastasis. Secondarily, to identify factors associated with lymphatic metastasis.

Methods

One hundred and thirty‐eight consecutive cases of auricular SCC were excised from 126 patients in our department over a 7‐year period (January 2012–December 2018). Data were retrospectively collected on patient characteristics, tumor histology, surgical procedures, and follow‐up.

Results

Incomplete initial excision occurred in 17 cases (12.32%). Six patients (4.76%) had a local recurrence. Lymphatic metastasis occurred in eight patients (6.35%), on average within 10.25 months after primary excision. Six patients with metastasis died during follow‐up, with a mean survival of 10.2 months. Older age was associated with lymphatic metastasis (P = 0.0267). Other factors, including tumor recurrence, size, grade, cartilage invasion, and positive margins, were evaluated and not significantly associated with metastasis.

Conclusion

In this study, the metastatic rate of auricular SCC was 6.35%, which is within the previously reported ranges. No histological prognostic factors were identified in this study, which may be due to our limited sample size. In the absence of established prognostic criteria, decisions regarding prophylactic treatment should be made on an individual basis with multidisciplinary support.
AI and Sensitive Personal Data Under the Law Enforcement Directive: Between Operational Efficiency and Legal Necessity
Authors: Naarttijärvi Markus
Published: October 2023

In constitutional theory, the requirement of necessity is an integral part of a wider proportionality assessment in the limitation of constitutional rights. It fulfils a function of sorting out measures that restrict rights beyond what is required to fulfil the intended purpose. Within data protection, the requirement varies in strictness and interpretation—from ‘ordinary’ necessity to ‘strict necessity’. Recently, the European Court of Justice (ECJ) has introduced what appears to be an even stricter requirement of ‘absolute necessity’ relating to the processing of biometric information under the EU Law Enforcement Directive (LED). In practice, however, the implications of those respective levels of strictness tends to vary, from a strict ‘least restrictive means’ test, to an analysis of whether a measure is necessary for a more effective or a more efficient fulfilment of the intended purpose. In this contribution the principle of necessity as applied by the ECJ is analysed as it pertains to the LED and the Charter, more specifically in the context of implementing AI supported analysis of biometric data. The gradual development of the interpretation of necessity is traced in the data protection case law of the ECJ. The study shows the increased emphasis placed on proportionality over time, highlighting both strengths and potential weaknesses of the requirement in relation to the use of AI supported decision-making in the law enforcement context.
Varying Viewpoints on Sex Differences
Authors: Thomas Hoben
Published: October 2023

Conceptual deficiencies, the surprising claim of no math test score sex differences, and other efforts to understand or explain math and other sex differences in task performance are of concern here
Summaries and Model Extensions
Authors: Thomas Hoben
Published: October 2023

Further model applications, analytical extensions, and clarifications are detailed in 12 sections after the first section which summarizes results and implications of the Chap. 5 analyses.
A parallel geometric multigrid method for adaptive topology optimization
Authors: Herrero-Pérez David , Picó-Vicente Sebastián Ginés
Published: October 2023

This work presents an efficient parallel geometric multigrid (GMG) implementation for preconditioning Krylov subspace methods solving differential equations using non-conforming meshes for discretization. The approach does not constrain such meshes to the typical multiscale grids used by Cartesian hierarchical grid methods, such as octree-based approaches. It calculates the restriction and interpolation operators for grid transferring between the non-conforming hierarchical meshes of the cycle scheme. Using non-Cartesian grids in topology optimization, we reduce the mesh size discretizing only the design domain and keeping the geometry of boundaries in the final design. We validate the GMG method operating on non-conforming meshes using an adaptive density-based topology optimization method, which coarsens the finite elements dynamically following a weak material estimation criterion. The GMG method requires the generation of the hierarchical non-conforming meshes dynamically from the one used by the adaptive topology optimization to analyze to the one coarsening all the mesh elements until the coarsest level of the mesh hierarchy. We evaluate the performance of the adaptive topology optimization using the GMG preconditioner operating on non-conforming meshes using topology optimization on a fine-conforming mesh as the reference. We also test the strong and weak scaling of the parallel GMG preconditioner with two three-dimensional topology optimization problems using adaptivity, showing the computational advantages of the proposed method.
Clinical Application of Computer‐Aided Diagnosis System in Breast Ultrasound: A Prospective Multicenter Study
Authors: He Ping , Chen Wen , Bai Ming‐Yu , Li Jun , Wang Qing‐Qing , Fan Li‐Hong , Zheng Jian , Liu Chun‐Tao , Zhang Xiao‐Rong , Yuan Xi‐Rong , Song Peng‐Jie , Cui Li‐Gang
Published: October 2023

Objectives

Ultrasound tends to present very high sensitivity but relatively low specificity and positive predictive value (PPV), which would result in unnecessary breast biopsies. The purpose of this study is to analyze the diagnostic performance of computer‐aided diagnosis (CAD) (S‐Detect) system in differentiating breast lesions and reducing unnecessary biopsies in non‐university hospitals in less‐developed regions of China.

Methods

The study was a prospective multicenter study from 8 hospitals. The ultrasound images, and cine, CAD analysis, and BI‐RADS were recorded. The accuracy, sensitivity, specificity, PPV, negative predictive value (NPV), and area under the curve (AUC) were analyzed and compared between CAD and radiologists. The Youden Index (YI) was used to determine optimal cut‐off for the number of planes to downgrade.

Results

A total of 491 breast lesions were included in the study. Less‐experienced radiologists combined CAD was superior to less‐experienced radiologists alone in AUC (0.878 vs 0.712, p < 0.001), and specificity (81.3% vs 44.6%, p < 0.001). There was no statistical difference in AUC (0.891 vs 0.878, p = 0.346), and specificity (82.3% vs 81.3%, p = 0.791) between experienced radiologists and less‐experienced radiologists combined CAD. With CAD assistance, the biopsy rate of less‐experienced radiologists was significantly decreased (100.0% vs 25.6%, p < 0.001), and malignant rate of biopsy was significantly increased (15.0% vs 43.9%, p < 0.001).

Conclusions

CAD system can be an effective auxiliary tool in differentiating breast lesions and reducing unnecessary biopsies for radiologists from non‐university hospitals in less‐developed regions of China.
Fitting parameters and therapies of ODE tumor models with senescence and immune system
Authors: Guillén-González F. , Sevillano-Castellano E. , Suárez A.
Published: October 2023

This work is devoted to introduce and study two quasispecies nonlinear ODE systems that model the behavior of tumor cell populations organized in different states. In the first model, replicative, senescent, extended lifespan, immortal and tumor cells are considered, while the second also includes immune cells. We fit the parameters regulating the transmission between states in order to approximate the outcomes of the models to a real progressive tumor invasion. After that, we study the identifiability of the fitted parameters, by using two sensitivity analysis methods. Then, we show that an adequate reduced fitting process (only accounting to the most identifiable parameters) gives similar results but saving computational cost. Three different therapies are introduced in the models to shrink (progressively in time) the tumor, while the replicative and senescent cells invade. Each therapy is identified to a dimensionless parameter. Then, we make a fitting process of the therapies’ parameters, in various scenarios depending on the initial tumor according to the time when the therapies started. We conclude that, although the optimal combination of therapies depends on the size of initial tumor, the most efficient therapy is the reinforcement of the immune system. Finally, an identifiability analysis allows us to detect a limitation in the therapy outcomes. In fact, perturbing the optimal combination of therapies under an appropriate therapeutic vector produces virtually the same results.
Multi-parametric MRI-based machine learning model for prediction of WHO grading in patients with meningiomas
Authors: Zhao Zhen , Nie Chuansheng , Zhao Lei , Xiao Dongdong , Zheng Jianglin , Zhang Hao , Yan Pengfei , Jiang Xiaobing , Zhao Hongyang
Published: October 2023

Objective

The purpose of this study was to develop and validate a nomogram combined multiparametric MRI and clinical indicators for identifying the WHO grade of meningioma.

Materials and methods

Five hundred and sixty-eight patients were included in this study, who were diagnosed pathologically as having meningiomas. Firstly, radiomics features were extracted from CE-T1, T2, and 1-cm-thick tumor-to-brain interface (BTI) images. Then, difference analysis and the least absolute shrinkage and selection operator were orderly used to select the most representative features. Next, the support vector machine algorithm was conducted to predict the WHO grade of meningioma. Furthermore, a nomogram incorporated radiomics features and valuable clinical indicators was constructed by logistic regression. The performance of the nomogram was assessed by calibration and clinical effectiveness, as well as internal validation.

Results

Peritumoral edema volume and gender are independent risk factors for predicting meningioma grade. The multiparametric MRI features incorporating CE-T1, T2, and BTI features showed the higher performance for prediction of meningioma grade with a pooled AUC = 0.885 (95% CI, 0.821–0.946) and 0.860 (95% CI, 0.788–0.923) in the training and test groups, respectively. Then, a nomogram with a pooled AUC = 0.912 (95% CI, 0.876–0.961), combined radiomics score, peritumoral edema volume, and gender improved diagnostic performance compared to radiomics model or clinical model and showed good calibration as the true results. Moreover, decision curve analysis demonstrated satisfactory clinical effectiveness of the proposed nomogram.

Conclusions

A novel nomogram is simple yet effective in differentiating WHO grades of meningioma and thus can be used in patients with meningiomas.

Clinical relevance statement

We proposed a nomogram that included clinical indicators and multi-parameter radiomics features, which can accurately, objectively, and non-invasively differentiate WHO grading of meningioma and thus can be used in clinical work.

Key Points

• The study combined radiomics features and clinical indicators for objectively predicting the meningioma grade.

• The model with CE-T1 + T2 + brain-to-tumor interface features demonstrated the best predictive performance by investigating seven different radiomics models.

• The nomogram potentially has clinical applications in distinguishing high-grade and low-grade meningiomas.
Intrinsic brain functional connectivity predicts treatment-related motor complications in early Parkinson’s disease patients
Authors: De Micco Rosa , Di Nardo Federica , Siciliano Mattia , Silvestro Marcello , Russo Antonio , Cirillo Mario , Tedeschi Gioacchino , Esposito Fabrizio , Tessitore Alessandro
Published: October 2023

Background

Treatment-related motor complications may develop progressively over the course of Parkinson’s disease (PD).

Objective

We investigated intrinsic brain networks functional connectivity (FC) at baseline in a cohort of early PD patients which successively developed treatment-related motor complications over 4 years.

Methods

Baseline MRI images of 88 drug-naïve PD patients and 20 healthy controls were analyzed. After the baseline assessments, all PD patients were prescribed with dopaminergic treatment and yearly clinically re-assessed. At the 4-year follow-up, 36 patients have developed treatment-related motor complications (PD-Compl) whereas 52 had not (PD-no-Compl). Single-subject and group-level independent component analyses were used to investigate FC changes within the major large-scale resting-state networks at baseline. A multivariate Cox regression model was used to explore baseline predictors of treatment-related motor complications at 4-year follow-up.

Results

At baseline, an increased FC in the right middle frontal gyrus within the frontoparietal network as well as a decreased connectivity in the left cuneus within the default-mode network were detected in PD-Compl compared with PD-no-Compl. PD-Compl patients showed a preserved sensorimotor FC compared to controls. FC differences were found to be independent predictors of treatment-related motor complications over time.

Conclusion

Our findings demonstrated that specific FC differences may characterize drug-naïve PD patients more prone to develop treatment-related complications. These findings may reflect the presence of an intrinsic vulnerability across frontal and prefrontal circuits, which may be potentially targeted as a future biomarker in clinical trials.
No evidence that coring affects tree growth or mortality in three common European temperate forest tree species
Authors: Portier Jeanne , Shackleton Ross T. , Klesse Stefan , Ferretti Marco , Flury Roman , Hobi Martina L. , Stillhard Jonas , von Arx Georg , Rohner Brigitte , Thürig Esther
Published: October 2023

Tree cores are a highly valuable scientific resource. Annual growth ring data can, for example, improve our understanding of climate change impacts and effects of environmental pollution, allow for better annual estimations of tree growth patterns and carbon storage, and help quantify dynamics and changes in forest ecosystems. The value of coring trees for research has been weighted against concerns around the potential harm coring might cause to trees. To date, there is indeed limited research accurately quantifying the potential effects of coring on tree growth and only a handful of studies assessing its influence on mortality. Consequently, many European long-term forest inventorying and monitoring programs are concerned that tree coring might bias the repeated tree measurements in permanent plots, which they rely on for assessments of states and changes of forests. In this study, we assessed the effects of tree coring on the growth and mortality of three widespread European tree species approximately 10 years after they were cored. We used repeated tree measurements from permanent research sites in Switzerland and Ukraine. In Switzerland, we assessed 35 cored and 159 uncored Norway spruce (Picea abies) trees as well as 147 cored and 332 uncored silver fir (Abies alba) trees. In Ukraine, we assessed 348 cored and 6′611 uncored European beech (Fagus sylvatica) trees. We found no statistical evidence that coring negatively affected the growth or mortality of the three tree species assessed. Although we cannot rule out subtle effects on tree health and wood quality, our findings do not provide any evidence that coring affects or biases repeated measurements (such as DBH measures and recording of mortality) performed on the investigated tree species. Tree coring could therefore be considered more often for routine incorporation, particularly in long-term forest inventorying and monitoring programs and initiatives.
Nitrogen fixation associated with epiphytes on the seagrass Zostera marina in a temperate lagoon with moderate to high nitrogen loads
Authors: Marino Roxanne , Hayn Melanie , Howarth Robert W. , Giblin Anne E. , McGlathery Karen J. , Berg Peter
Published: October 2023

As part of a long-term study on the effects of nitrogen (N) loading in a shallow temperate lagoon, we measured rates of N2 fixation associated with seagrass (Zostera marina) epiphytes during the summer from 2005 to 2019, at two sites along a gradient from where high N groundwater enters the system (denoted SH) to a more well-flushed outer harbor (OH). The data presented here are the first such long-term N2 fixation estimates for any seagrass system and one of the very few reported for the phyllosphere in a temperate system. Mean daily N2 fixation was estimated from light and dark measurements using the acetylene reduction assay intercalibrated using both incorporation of 15N2 into biomass and a novel application of the N2:Ar method. Surprisingly, despite a large inorganic N input from a N-contaminated groundwater plume, epiphytic N2 fixation rates were moderately to very high for a seagrass system (OH site 14-year mean of 0.94 mmol N m−2 d−1), with the highest rates (2.6 mmol N m−2 d−1) measured at the more N-loaded eutrophic site (SH) where dissolved inorganic N was higher and soluble reactive phosphorus was lower than in the better-flushed OH. Over 95% of the total N2 fixation measured was in the light, suggesting the importance of cyanobacteria in the epiphyte assemblages. We observed large inter-annual variation both within and across the two study sites (range from 0.1 to 2.6 mmol N fixed m−2 d−1), which we suggest is in part related to climatic variation. We estimate that input from phyllosphere N2 fixation over the study period contributes on average an additional 20% to the total daily N load per area within the seagrass meadow.
Adapting E-cigarette prevention programming to reach the latinx community
Authors: Herrmann Alison K. , Ferullo Sylvia Lopez , Hernandez Miriam , Barriga Verónica Arciga , Leggis Bernadett , Ruiz Julissa , Glenn Beth A. , Bastani Roshan
Published: October 2023

Purpose

E-cigarettes are the most commonly used tobacco product among youth in the United States. Yet evidence-based prevention programming is limited due to the rapid onset of this threat. Community-based efforts to address vaping largely target youth in school settings. Although parents can play an important role in youth tobacco control efforts, messages about the dangers of vaping, use among adolescents, and strategies for intervening have not reached many Spanish-speaking parents in low-income Latinx communities. Our community-academic team developed e-cigarette prevention programming for use by promotor/as de salud to address this unmet need.

Methods

During the 1-year project, the team worked closely with a Project Advisory Committee to: review existing evidence-informed materials; conduct focus groups with parents, youth and promotor/as to guide program development; develop a curriculum to prepare promotor/as to educate low-literacy, Spanish-speaking parents about vaping; craft Spanish language resources for promotor/as to use in community education sessions; train 61 promotor/as to deliver the program; and support program delivery to 657 community members.

Results

Focus groups with promotor/as and community members, key-informant interviews, and brief surveys informed program development and assessment. Community member feedback was essential to development of appropriate materials. Promotor/as demonstrated significant pre- to post- training increases in e-cigarette knowledge and confidence in delivering vaping prevention education. Community members demonstrated a mastery of basic e-cigarette concepts and expressed intention to discuss vaping with their children.

Conclusions

Promotor/a-led programming for parents represents a promising approach to vaping prevention and control in the Latinx community.
The irrigated wheat initiative of Ethiopia: a new paradigm emulating Asia’s green revolution in Africa
Authors: Effa Kefena , Fana Daniel Muleta , Nigussie Mandefro , Geleti Diriba , Abebe Nigusie , Dechassa Nigussie , Anchala Chimdo , Gemechu Getu , Bogale Teshome , Girma Dejene , Berisso Feto Esimo
Published: October 2023

The aim of this paper is to assess and document the experience of the successful irrigated wheat initiative in Ethiopia, identify potential limitations, and suggest alternative options that contribute towards the sustainability of the program. In the past decades, Ethiopia has initiated several projects to ensure food and wheat security but did not achieve the anticipated impact as planned. In 2019, however, the current government of Ethiopia put in place structural, economic, and sectorial reforms, with wheat chosen as a strategic commodity for food security, raw material for the agroindustry, import substitution that transits to export, and job creation along the value chain. With a total of 2.6 million ha of land cultivated under both rain-fed and irrigated systems, followed by a record amount of wheat harvest (8.2 million tons) in 2022, Ethiopia achieved a wheat self-sufficiency ratio of 100% and more than 1 million tons of surplus for export, indicating that the new irrigated wheat initiative of Ethiopia has been found transformational and is becoming a game changer. Moreover, modest case scenario projections revealed that Ethiopia will become a net exporter of wheat by 2023, indicating that the country is achieving not only wheat security but also championing the possibility of replicating Asia’s Green Revolution in Africa. Yet, the sustainability of the current initiative relies on an efficient water management system, private sector engagement, sustainable input supply, well-established input and output marketing systems, and leadership commitment at all levels.
Contextualizing and hybridizing academic identity formation: an analysis of international returnees and locally trained scholars in China
Authors: Dai Kun , Hardy Ian
Published: October 2023

Academic identity formation is strongly influenced by higher education contexts. In the past decades, the Chinese higher education sector has attempted to integrate academic internationalization at the local level. In this context, international returnees and locally trained scholars may encounter different issues in the process of constructing academic identities at various stages of their careers. However, relatively few studies have critically analyzed how international returnees and locally trained scholars understand their academic identity formation during their student years, as they transition to becoming academics, and as they begin to become more established in academic roles under increasingly complex global-national-local conditions. Drawing upon the concept of social hybridization and the notion of global-national-local imbrications, this narrative study investigates six scholars’ trajectories of academic identity formation across different stages of the early phase of their careers, including during their doctoral studies and their initial period as early career academics. The findings show that academics’ identity development entails a process of struggle and confusion during earlier stages through to the construction of a more hybrid academic identity. By exploring the challenges and issues experienced by different cohorts of academics, scholars may better understand the internationalization of Chinese higher education and interweaving relationships with the global context.
Fundamental Equation of State for Fluid Tetrahydrofuran
Authors: Fiedler Felix , Karog Joel , Lemmon Eric W. , Thol Monika
Published: October 2023

An empirical fundamental equation of state in terms of the Helmholtz energy for tetrahydrofuran is presented. In the validity range from the triple-point temperature up to 550 K and pressures up to 600 MPa, the equation of state enables the calculation of all thermodynamic properties in the liquid, vapor, and super-critical regions including saturation states. Based on an extensive literature review, experimental data are represented within their experimental uncertainty. In the homogeneous liquid phase at atmospheric pressure, the uncertainty in density is 0.015 %, speed of sound is represented with an uncertainty of 0.03 %, and isobaric heat capacity has an uncertainty of 0.4 %. Isobaric heat capacities in the homogeneous vapor phase are described with an uncertainty of 0.2 %. Higher uncertainties occur above atmospheric pressure for all homogeneous properties. Depending on the temperature range, vapor pressure can be calculated with an uncertainty from 0.02 % to 3 %. The extrapolation behavior is evaluated, showing reasonable extrapolation behavior towards extreme conditions.
Response inhibition training as an intervention to modify liking and wanting for foods based on energy density: a proof of concept study
Authors: Moore Halim , White Melanie J. , Finlayson Graham , King Neil
Published: October 2023

The ubiquity of energy-dense, processed foods has been implicated as a salient feature of the modern ‘obesogenic’ environment. Cognitive strategies, such as response inhibition training, have been demonstrated to reduce the hedonic value of such foods in previous studies. However, this effect has generally been inconsistent or heterogenous, depending on the outcome measure, characteristics of the sample, and the specificity of food stimuli. Characterising the extent of generalised effects may help define the application of this type of intervention in natural settings. A repeated-measures, proof-of-concept study, using mobile app-based response inhibition training (RIT) versus a control app-based activity (N = 25), was undertaken to establish the valid application of a food reward measure to assess intervention efficacy. Liking (i.e., affect) and wanting (i.e., motivation) for food stimuli categorised by energy density were taken concurrently pre- and post-training. A statistically significant reduction in explicit liking, but not implicit wanting, for foods irrespective of their energy density was observed during the RIT app-based training session relative to the control (p = .041, ηp2 = .16). However, effect sizes associated with devaluation of energy-dense relative to low calorie food stimuli, although non-significant, were higher when measured as implicitly wanting (p = .098, ηp2 = .11) than explicit liking (p = .756, ηp2 = .00). Trends in explicit stimulus evaluations were empirically discordant from implicit evaluations for low calorie foods in particular. Additional research is needed to investigate whether these trends are reproducible with larger samples, trained and novel food stimuli in outcome measures, and more comprehensive training protocols.
Truth Meets Vagueness. Unifying the Semantic and the Soritical Paradoxes
Authors: Bruni Riccardo , Rossi Lorenzo
Published: October 2023

Semantic and soritical paradoxes display remarkable family resemblances. For one thing, several non-classical logics have been independently applied to both kinds of paradoxes. For another, revenge paradoxes and higher-order vagueness—among the most serious problems targeting solutions to semantic and soritical paradoxes—exhibit a rather similar dynamics. Some authors have taken these facts to suggest that truth and vagueness require a unified logical framework, or perhaps that the truth predicate is itself vague. However, a common core of semantic and soritical paradoxes has not been identified yet, and no explanation of their relationships has been provided. Here we aim at filling this lacuna, in the framework of many-valued logics. We provide a unified diagnosis of semantic and soritical paradoxes, identifying their source in a general form of indiscernibility. We then develop our diagnosis into a theory of paradoxicality, which formalizes both semantic and soritical paradoxes as arguments involving specific instances of our generalized indiscernibility principle, and correctly predicts which logics can non-trivially solve them.
Maternal Dietary Patterns and Risk of Postpartum Depression: A Systematic Review
Authors: Sun Yuyue , Ferguson Megan , Reeves Marina M. , Kelly Jaimon T.
Published: October 2023

Objective

Postpartum depression (PPD) has deleterious effects on both maternal and child outcomes. Poor maternal nutrition during pregnancy has been implicated in the development of PPD. This review aimed to explore the association between the overall dietary intake patterns during pregnancy and the development of PPD.

Methods

A literature search was performed in PubMed, Embase, Scopus, CINAHL, and PsycINFO databases for relevant randomized controlled trials, cohort and cross-sectional studies published up to 17th September 2020. Included studies assessed at least one dietary pattern during pregnancy and reported on PPD. The Newcastle Ottawa Scale and the Joanna Briggs Institute critical appraisal tools were used to assess the quality of methodology. A narrative analysis was conducted.

Results

Ten studies (eight cohort and two cross-sectional) were included with substantial heterogeneity in measurements of dietary intake exposures and PPD. The studies identified several types of healthy dietary patterns, including a ‘healthy’, ‘health conscious’, ‘Japanese’, ‘high-glycemic index/glycemic load’, ‘Vegetable’, ‘Nut-Fruit’, ‘Seafood’, and ‘compliance with the Australian Dietary Guidelines’. The ‘Western’, ‘unhealthy’, ‘Beverage’, ‘Cereal-Meat’, and ‘Egg’ were labelled as unhealthy dietary patterns. Four of the eight studies showed an inverse association between adherence to healthy diets and risk of PPD, whereas only one of the seven studies showed that adherence to unhealthy diets was associated with increased risk of PPD. Methodological quality of the studies varied across the sample.

Conclusions

Our findings indicate that adherence to a healthy diet may be beneficial for PPD. However, the relationship between unhealthy diets and PPD needs to be corroborated by more high-quality studies.
Exudyn – a C++-based Python package for flexible multibody systems
Authors: Gerstmayr Johannes
Published: October 2023

The present contribution introduces the design, methods, functionalities, and capabilities of the open-source multibody dynamics code Exudyn, which has been developed since 2019. The code has been designed for rigid and flexible multibody systems, with a focus on performance for multicore desktop processors. It includes script-language-based modeling and it is intended to be used in science and education, but also in industry. The open-source code is available on GitHub and consists of a main C++ core, a rich Python interface including pre- and postprocessing modules in Python, and a collection of rigid and flexible bodies with appropriate joint, load, and sensor functionality. Integrated solvers allow explicit and implicit time integration, static solution, eigenvalue analysis, and optimization. In the paper, the code design, structure, computational core, computational objects, and multibody formulations are addressed. In addition, the computational performance is evaluated with examples of rigid and flexible multibody systems. The results show the significant impact of multithreading especially for small systems, but also for larger models.
Investigation of the driving characteristics of electric bicycles by means of multibody simulation
Authors: Bolk Johannes , Corves Burkhard
Published: October 2023

Electrically assisted bicycles lead to a change in the driving characteristics compared to conventional bicycles because of the additionally attached masses of motor and battery. In order to describe the resulting interaction of the electric drive components on the driving characteristics, this paper examines simulations of the driving behavior of bicycles with different positions of battery and motor in open- and closed-loop tests. The integration of human driving behavior by control loops allows the evaluation of driving characteristic under more realistic driving conditions compared to the existing studies of the eigenbehavior. The results are analyzed using characteristic values that describe the system behavior in a suitable way. Furthermore, a design of experiments is performed to classify the influence of the presented research results in relation to other system parameters, such as different types of bicycles and different rider postures.
Are models our tools not our masters?
Authors: Jacobs Caspar
Published: October 2023

It is often claimed that one can avoid the kind of underdetermination that is a typical consequence of symmetries in physics by stipulating that symmetry-related models represent the same state of affairs (Leibniz Equivalence). But recent commentators (Dasgupta in Philos Perspect 25:115–160, 2011; Pooley in: Knox and Wilson (eds) The Routledge companion to the philosophy of physics, Routledge, Milton Park, 2021; Pooley and Read in Br J Philos Sci, 2021, https://doi.org/10.1086/718274; Teitel in J Philos 119:233–278, 2021) have responded that claims about the representational capacities of models are irrelevant to the issue of underdetermination, which concerns possible worlds themselves. In this paper I distinguish two versions of this objection: (1) that a theory’s formalism does not (fully) determine the space of physical possibilities, and (2) that the relevant notion of possibility is not physical possibility. I offer a refutation of each.