Potential Model Research Articles

The Significance of Disseminating Sexual Education Among Adolescents in China

In China, most adolescents do not have access to formal sexual and reproductive health education and services. This essay delves into the critical role of sexual education in enhancing the well-being of Chinese adolescents. The exploration begins by addressing the evolving cultural concepts surrounding sexuality in China, challenging traditional norms influenced by Confucianism. Subsequently, it underscores the significance of sexual education in mitigating health risks, offering insights into successful international programs as potential models. The discussion extends to the pivotal role of comprehensive sex education in promoting gender equality, combating discrimination against sexual and gender minorities, and addressing issues of consent. Despite the recognized importance of sexual education, challenges persist in its implementation, primarily due to resistance and personal biases from educators and policymakers. The essay concludes by proposing effective strategies to overcome these challenges, emphasizing the role of higher education, gender science, and decolonizing education in shaping a more inclusive and informed approach to sexual health among Chinese adolescents.

Do calcium channel blockers applied to cardiomyocytes cause increased channel expression resulting in reduced efficacy?

In the initial hours following the application of the calcium channel blocker (CCB) nifedipine to microtissues consisting of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), we observe notable variations in the drug’s efficacy. Here, we investigate the possibility that these temporal changes in CCB effects are associated with adaptations in the expression of calcium ion channels in cardiomyocyte membranes. To explore this, we employ a recently developed mathematical model that delineates the regulation of calcium ion channel expression by intracellular calcium concentrations. According to the model, a decline in intracellular calcium levels below a certain target level triggers an upregulation of calcium ion channels. Such an upregulation, if instigated by a CCB, would then counteract the drug’s inhibitory effect on calcium currents. We assess this hypothesis using time-dependent measurements of hiPSC-CMs dynamics and by refining an existing mathematical model of myocyte action potentials incorporating the dynamic nature of the number of calcium ion channels. The revised model forecasts that the CCB-induced reduction in intracellular calcium concentrations leads to a subsequent increase in calcium ion channel expression, thereby attenuating the drug’s overall efficacy. The data and fit models suggest that dynamic changes in cardiac cells in the presence of CCBs may be explainable by induced changes in protein expression, and that this may lead to challenges in understanding calcium based drug effects on the heart unless timings of applications are carefully considered.

Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials

We present an automated data-collection pipeline involving a convolutional neural network and a large language model to extract user-specified tabular data from peer-reviewed literature. The pipeline is applied to 74 reports published between 1957 and 2014 with experimentally-measured oxidation potentials for 592 organic molecules (−0.75 to 3.58 V). After data curation (solvents, reference electrodes, and missed data points), we trained multiple supervised machine learning (ML) models reaching prediction errors similar to experimental uncertainty (∼0.2 V). For experimental measurements of identical molecules reported in multiple studies, we identified the most likely value based on out-of-sample ML predictions. Using the trained ML models, we then estimated oxidation potentials of ∼132k small organic molecules from the QM9 (quantum mechanics data for organic molecules with up to 9 atoms not counting hydrogens) data set, with predicted values spanning 0.21–3.46 V. Analysis of the QM9 predictions in terms of plausible descriptor-property trends suggests that aliphaticity increases the oxidation potential of an organic molecule on average from ∼1.5 V to ∼2 V, while an increase in number of heavy atoms lowers it systematically. The pipeline introduced offers significant reductions in human labor otherwise required for conventional manual data collection of experimental results, and exemplifies how to accelerate scientific research through automation.

Computational models of compound nerve action potentials: Efficient filter-based methods to quantify effects of tissue conductivities, conduction distance, and nerve fiber parameters.

Peripheral nerve recordings can enhance the efficacy of neurostimulation therapies by providing a feedback signal to adjust stimulation settings for greater efficacy or reduced side effects. Computational models can accelerate the development of interfaces with high signal-to-noise ratio and selective recording. However, validation and tuning of model outputs against in vivo recordings remains computationally prohibitive due to the large number of fibers in a nerve. We designed and implemented highly efficient modeling methods for simulating electrically evoked compound nerve action potential (CNAP) signals. The method simulated a subset of fiber diameters present in the nerve using NEURON, interpolated action potential templates across fiber diameters, and filtered the templates with a weighting function derived from fiber-specific conduction velocity and electromagnetic reciprocity outputs of a volume conductor model. We applied the methods to simulate CNAPs from rat cervical vagus nerve. Brute force simulation of a rat vagal CNAP with all 1,759 myelinated and 13,283 unmyelinated fibers in NEURON required 286 and 15,860 CPU hours, respectively, while filtering interpolated templates required 30 and 38 seconds on a desktop computer while maintaining accuracy. Modeled CNAP amplitude could vary by over two orders of magnitude depending on tissue conductivities and cuff opening within experimentally relevant ranges. Conduction distance and fiber diameter distribution also strongly influenced the modeled CNAP amplitude, shape, and latency. Modeled and in vivo signals had comparable shape, amplitude, and latency for myelinated fibers but not for unmyelinated fibers. Highly efficient methods of modeling neural recordings quantified the large impact that tissue properties, conduction distance, and nerve fiber parameters have on CNAPs. These methods expand the computational accessibility of neural recording models, enable efficient model tuning for validation, and facilitate the design of novel recording interfaces for neurostimulation feedback and understanding physiological systems.

Hydrogeological Potential 3D Model Analysis in Groundwater Basins in Volcanic Areas of North Maluku

Hydrogeological Potential 3D Model Analysis in Groundwater Basins in Volcanic Areas of North Maluku

Biogeography, speciation and niche evolution of doraditos (Aves: Pseudocolopteryx)

AbstractEcological and geographical factors shape the current distribution of species. Analysing their interplay in a phylogenetic framework is key to understand the historical processes that have shaped the evolution of a group. Here, we modelled the ecological niches and geographic distributions of the five species of doraditos (Pseudocolopteryx spp.) to study their biogeographic histories, niche evolution and speciation process in a phylogenetic framework. Our potential distribution models uncovered novel range‐wide distributional patterns and seasonal movements in the doraditos, where four species are migratory with distinct breeding and non‐breeding distributions, and one (P. sclateri) exhibits a complex spatiotemporal distribution indicating nomadism. Ecological niche pairwise comparisons showed that none of the doraditos have equivalent niches and that niche differences are due to species‐specific habitat preferences. Phylogenetically weighted geographical and ecological analyses showed patterns of allopatric speciation and niche lability in the evolution of doraditos. The divergence of P. sclateri seems tied to its tropical‐to‐temperate wetland specialization. The montane P. acutipennis expanded to human‐modified lowlands following speciation, highlighting the need to control for post‐speciational changes in ecological niche comparisons as done here. In turn, P. dinelliana, P. citreola and P. flaviventris showed essentially allopatric breeding distributions, as a product of environmentally mediated divergence during their speciation processes. The distribution and migration data of the recently diverged cryptic sister species P. citreola and P. flaviventris are consistent with two possible speciation scenarios: peripatric speciation and migration dosing speciation.

Enthalpy, mean energy, entropy, and Gibbs free energy of lithium dimer under magnetic field

It is well known that the lithium diatomic molecule has important potential application in engineering, and industry. For this purpose, in this research, the thermal properties of the lithium diatomic molecule are theoretically calculated taking into account both an external magnetic field and Aharonov-Bohm (AB) flux. To this end, the interaction in the diatomic molecule is proposed as an improved Scarf ΙΙ potential model (ISPM). The Schrödinger equation is solved using an appropriate Pekeris-like approximation form for the centrifugal barrier and the energy spectrum and wave functions are obtained. Then, the partition function is obtained to study the thermal properties of the lithium dimer. The calculated thermal properties of 7Li2 (2 3Πg) in this work are mean energy, entropy, specific heat, enthalpy, and Gibbs free energy. Our theoretical results are also compared with the experimental data. The findings show that the obtained results are in good agreement with experimental data. Without considering the magnetic field and AB flux, the deviation of specific heat, Gibbs free energy, and enthalpy are 3.73%, 4.96%, and 5.31%, respectively. By considering the magnetic field and AB flux, we find that the deviation of the aforementioned properties are 1.91%, 2.04%, and 2.32%, respectively. Therefore, it is found that the external magnetic field and AB flux have great influences on the thermal properties of lithium.

Multiple mediation of the association between childhood emotional abuse and adult obesity by anxiety and bulimia – a sample from bariatric surgery candidates and healthy controls

Bulimia, which means a person has episodes of eating a very large amount of food (bingeing) during which the person feels a loss of control over their eating, is the most primitive reason for being overweight and obese. The extended literature has indicated that childhood emotional abuse has a close relationship with adverse mood states, bulimia, and obesity. To comprehensively understand the potential links among these factors, we evaluated a multiple mediation model in which anxiety/depression and bulimia were mediators between childhood emotional abuse and body mass index (BMI). A set of self-report questionnaires, including the Childhood Trauma Questionnaire (CTQ), Beck Anxiety Inventory, Beck Depression Inventory (BDI), and Eating Disorder Inventory (EDI), was sent out. Clinical data from 37 obese patients (age: 29.65 ± 5.35, body mass index (BMI): 37.59 ± 6.34) and 37 demographically well-matched healthy people with normal body weight (age: 31.35 ± 10.84, BMI: 22.16 ± 3.69) were included in the investigation. We first performed an independent t-test to compare all scales or subscale scores between the two groups. Then, we conducted Pearson correlation analysis to test every two variables’ pairwise correlation. Finally, multiple mediation analysis was performed with BMI as the outcome variable, and childhood emotional abuse as the predictive variable. Pairs of anxiety, bulimia, and depression, bulimia were selected as the mediating variables in different multiple mediation models separately. The results show that the obese group reported higher childhood emotional abuse (t = 2.157, p = 0.034), worse mood state (anxiety: t = 5.466, p < 0.001; depression: t = 2.220, p = 0.030), and higher bulimia (t = 3.400, p = 0.001) than the healthy control group. Positive correlations were found in every pairwise combination of BMI, childhood emotional abuse, anxiety, and bulimia. Multiple mediation analyses indicate that childhood emotional abuse is positively linked to BMI (β = 1.312, 95% CI = 0.482–2.141). The model using anxiety and bulimia as the multiple mediating variables is attested to play roles in the relationship between childhood emotional abuse and obesity (indirect effect = 0.739, 95% CI = 0.261–1.608, 56.33% of the total effect). These findings confirm that childhood emotional abuse contributes to adulthood obesity through the multiple mediating effects of anxiety and bulimia. The present study adds another potential model to facilitate our understanding of the eating psychopathology of obesity.

"The Only Reason I Am Willing to Do It at All": Evaluation of VA's SUpporting Primary care Providers in Opioid Risk reduction and Treatment (SUPPORT) Center.

Medication treatment for opioid use disorder (MOUD) is effective and recommended for outpatient settings. We implemented and evaluated the SUpporting Primary care Providers in Opioid Risk reduction and Treatment (SUPPORT) Center-a quality improvement partnership to implement stepped care for MOUD in 2 Veterans Health Administration (VA) primary care (PC) clinics. SUPPORT provided a dedicated clinical team (nurse practitioner prescriber and social worker) and stepped care ([1] identification, assessment, referral; [2] MOUD induction; [3] stabilization; and [4] maintenance supporting PC providers [PCPs] to initiate and/or sustain treatment) coupled with ongoing internal facilitation (consultation, trainings, informatics support). Qualitative interviews with stakeholders (PCPs and patients) and meeting notes identified barriers and facilitators to implementation. Electronic health record and patient tracking data measured reach, adoption, and implementation outcomes descriptively. SUPPORT's implementation barriers included the need for an X-waiver, VA's opioid tapering policies, patient and PCP knowledge gaps and PCP discomfort, and logistical compatibility and sustainability challenges for clinics. SUPPORT's dedicated clinical staff, ongoing internal facilitation, and high patient and PCP satisfaction were key facilitators. SUPPORT (January 2019 to September 2021) trained 218 providers; 63 received X-waivers, and 23 provided MOUD (10.5% of those trained). SUPPORT provided care to 167 patients, initiated MOUD for 33, and provided education and naloxone to 72 (all = 0 in year before launch). SUPPORT reached many PCPs and patients and resulted in small increases in MOUD prescribing and high levels of stakeholder satisfaction. Dedicated clinical staff was key to observed successes. Although resource-intensive, SUPPORT offers a potential model for outpatient MOUD provision.

Towards a Sustainable Power System: A Three-Stage Demand Response Potential Evaluation Model

Developing flexible resources is a key strategy for advancing the development of new power systems and addressing the issue of climate change. Demand response is a crucial flexibility resource that is extensively employed due to its sustainability and economy. This work develops a three-stage demand response potential evaluation model based on “theoretical potential–realizable potential–multi-load aggregation potential” in response to the issues of inadequate consideration of numerous complicated agents and time in previous research. Firstly, the traditional method calculates the theoretical maximum demand response potential of a single industry in each period. Based on this, the industry characteristics are taken into account when establishing the demand response potential evaluation model. Lastly, the time variation of the demand response potential is taken into consideration when evaluating the demand response potential of multiple load aggregation. For the analysis, three industries are chosen as examples. The results show that the potential of peak shaving and valley filling obtained by using the model is smaller than that of the traditional method, the reduction range of peak cutting demand response potential calculated by multi-load aggregation is 19–100%, and the reduction range of valley filling demand response potential is 20–89%. The results are closer to reality, which is conducive to improving the accuracy of relevant departments in making relevant decisions and promoting the sustainable development of a new power system.

Magnus Force Estimation Using Gauss’s Principle of Least Constraint

The flow around a rotating cylinder is one of the fundamental problems that have piqued the interests of many venerable fluid mechanicians since the time of Rayleigh. The force caused by the rotation of the cylinder has always been considered as an immediate consequence of viscosity, since the potential flow model failed entirely to predict the value of the circulation due to the lack of a Kutta-like condition. On the other hand, Glauert modeled the flow outside the boundary layer of a rotating cylinder as a potential flow with an unknown circulation. He then obtained an approximate solution of Prandtl’s boundary-layer equations and applied the no-slip condition to estimate the circulation in the outer flow. Interestingly, for rapidly rotating cylinders (α=(ωR/U)≫1), up to fourth-order in the small parameter ϵ=(1/α), the obtained circulation is independent of viscosity. In this work, we use Glauert’s model of the outer flow (i.e., a potential flow with an unknown circulation). However, instead of the tedious boundary-layer calculations, we rely on Gauss’s principle of least constraint to obtain the unknown circulation. A perfect match with Glauert’s solution is found. Moreover, our solution, in contrast to Glauert’s, points to the existence of different physics at small rotational speeds. The obtained results, given their perfect matching with Glauert’s solution (relying on the no-slip condition), point to a potential equivalence between the no-slip condition and fluid body forces.

Prediction of Metastable Zone Widths: Optimizing the Nucleation Potential Model with Solid–Liquid Interfacial Energy

Prediction of Metastable Zone Widths: Optimizing the Nucleation Potential Model with Solid–Liquid Interfacial Energy

Prediction on the alpha decay half-lives of 223−243Am isotopes

Prediction on the alpha decay half-lives of 223−243Am isotopes

Dissecting the roles of calcium cycling and its coupling with voltage in the genesis of early afterdepolarizations in cardiac myocyte models.

Early afterdepolarizations (EADs) are abnormal depolarizations during the plateau phase of the action potential, which are known to be associated with lethal arrhythmias in the heart. There are two major hypotheses for EAD genesis based on experimental observations, i.e., the voltage (Vm)-driven and intracellular calcium (Ca)-driven mechanisms. In ventricular myocytes, Ca and Vm are bidirectionally coupled, which can affect each other's dynamics and result in new dynamics, however, the roles of Ca cycling and its coupling with Vm in the genesis of EADs have not been well understood. In this study, we use an action potential model that is capable of independent Vm and Ca oscillations to investigate the roles of Vm and Ca coupling in EAD genesis. Four different mechanisms of EADs are identified, which are either driven by Vm oscillations or Ca oscillations alone, or oscillations caused by their interactions. We also use 5 other ventricular action potential models to assess these EAD mechanisms and show that EADs in these models are mainly Vm-driven. These mechanistic insights from our simulations provide a theoretical base for understanding experimentally observed EADs and EAD-related arrhythmogenesis.

Authentic braille literacy development through interdisciplinary instruction and learning

Incorporating braille across disciplines and into authentic settings may increase motivation and acquisition. This paper explores the merging of science content instruction with authentic braille literacy development using drama strategies during a summer camp for elementary students with visual impairments and the co-occurring teacher preparation for authentic braille instruction. This study measured braille proficiency in reading and writing and science content knowledge of student participants before and after the weeklong interdisciplinary summer camp. Pre-service teachers of students with visual impairments (TSVIs) that were co-teaching with in-service TSVIs also completed the braille proficiency measures in reading and writing. The interdisciplinary camp experience and culminating museum event described in the present study provides a potential model for how to design interdisciplinary learning experiences for students with visual impairments to develop braille literacy and science content understanding.

Fractal study of electrical conductivity and streaming potential in rough fractured porous media

Research has demonstrated the significant influence of surface roughness on electrical conductivity and streaming potential. This article presents a model for the flow potential in a porous medium with rough fractures, based on fractal theory and representative elementary volume theory. Expressions for the model’s permeability, conductivity, and coupling coefficient between flow and potential are derived. The results indicate that both the relative roughness and structural parameters of the model have certain effects on the conductivity and coupling coefficient. By comparing experimental data from previous literature with the predicted values from the model, the correctness and effectiveness of the model are validated.

Computed tomography-based body composition parameters can predict short-term prognosis in ulcerative colitis patients.

Emerging evidence suggests a potential relationship between body composition and short-term prognosis of ulcerative colitis (UC). Early and accurate assessment of rapid remission based on conventional therapy via abdominal computed tomography (CT) images has rarely been investigated. This study aimed to build a prediction model using CT-based body composition parameters for UC risk stratification. In total, 138 patients with abdominal CT images were enrolled. Eleven quantitative parameters related to body composition involving skeletal muscle mass, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were measured and calculated using a semi-automated segmentation method. A prediction model was established with significant parameters using a multivariable logistic regression. The receiver operating characteristic (ROC) curve was plotted to evaluate prediction performance. Subgroup analyses were implemented to evaluate the diagnostic efficiency of the prediction model between different disease locations, centers, and CT scanners. The Delong test was used for statistical comparison of ROC curves. VAT density, SAT density, gender, and visceral obesity were significantly statistically different between remission and invalidation groups (all p < 0.05). The accuracy, sensitivity, specificity, and area under the ROC curve (AUC) of the prediction model were 82.61%, 95.45%, 69.89%, and 0.855 (0.792-0.917), respectively. The positive predictive value and negative predictive value were 70.79% and 93.88%, respectively. No significant differences in the AUC of the prediction model were found in different subgroups (all p > 0.05). The predicting model constructed with CT-based body composition parameters is a potential non-invasive approach for short-term prognosis identification and risk stratification. Additionally, VAT density was an independent predictor for escalating therapeutic regimens in UC cohorts. The CT images were used for evaluating body composition and risk stratification of ulcerative colitis patients, and a potential non-invasive prediction model was constructed to identify non-responders with conventional therapy for making therapeutic regimens timely and accurately. • CT-based prediction models help divide patients into invalidation and remission groups in UC. • Results of the subgroup analysis confirmed the stability of the prediction model with a high AUC (all > 0.820). • The visceral adipose tissue density was an independent predictor of bad short-term prognosis in UC.

Establishing chronic models of age-related macular degeneration via long-term iron ion overload.

Age-related macular degeneration (AMD) is characterized by the degenerative senescence in the retinal pigment epithelium (RPE) and photoreceptors, which is accompanied by the accumulation of iron ions in the aging retina. However, current models of acute oxidative stress are still insufficient to simulate the gradual progression of AMD. To address this, we established chronic injury models by exposing the aRPE-19 cells, 661W cells, and mouse retina to iron ion overload over time. Investigations at the levels of cell biology and molecular biology were performed. It was demonstrated that long-term treatment of excessive iron ions induced senescence-like morphological changes, decreased cell proliferation, and impaired mitochondrial function, contributing to apoptosis. Activation of the mitogen-activated protein kinase (MAPK) pathway and the downstream molecules were confirmed both in the aRPE-19 and 661W cells. Furthermore, iron ion overload resulted in dry AMD-like lesions and decreased visual function in the mouse retina. These findings suggest that chronic exposure to overloading iron ions plays a significant role in the pathogenesis of retinopathy and provide a potential model for future studies on AMD.NEW & NOTEWORTHY To explore the possibility of constructing reliable research carriers on age-related macular degeneration (AMD), iron ion overload was applied to establish models in vitro and in vivo. Subsequent investigations into cellular physiology and molecular biology confirmed the presence of senescence in these models. Through this study, we hope to provide a better option of feasible methods for future researches into AMD.

EXPRESS CALCULATION OF OXYGEN REGIME IN WASTEWATER FACILITIES

Problem statement. The efficiency of biological water purification depends significantly on the concentration of dissolved oxygen in the volume of the bioreactor. But during the operation of bioreactors, the oxygen regime changes, so it is important to predict the oxygen concentration for different modes of operation of treatment plants. Simplified mathematical models are used to calculate the oxygen regime, but these models are designed for typical bioreactors. An important task is the development of effective multivariate numerical models for evaluating the oxygen regime in reactors of different geometric shapes, which differ from “classical” reactors. The purpose of the article. Development of a CFD model for operational evaluation of the oxygen regime in bioreactors. Methodology. For mathematical modeling of the oxygen regime in the bioreactor, a two-dimensional mass transfer equation is used, which takes into account the place of oxygen supply from the aerator located in the building, the hydrodynamics of the flow in the bioreactor, and the diffusion process. The potential motion model was used to solve the hydrodynamic problem. Numerical integration of modeling equations is carried out by using finite-difference splitting schemes. At each splitting step, the difference equations are solved using explicit schemes. This allows a simple computer implementation of the numerical model. Scientific novelty. A multifactor two-dimensional CFD model was developed, which allows for a quick assessment of the oxygen regime in a bioreactor used for wastewater treatment. Practical significance. The developed CFD model and computer code can be used at the stage of designing or re-engineering bioreactors in order to find the optimal location of aerators in the structure. Conclusions. The software implementation of the developed numerical model was carried out. The results of a computational experiment on the study of the wastewater treatment process in a sedimentation tank are presented.

Brain-like illusion produced by Skye's Oblique Grating in deep neural networks.

The analogy between the brain and deep neural networks (DNNs) has sparked interest in neuroscience. Although DNNs have limitations, they remain valuable for modeling specific brain characteristics. This study used Skye's Oblique Grating illusion to assess DNNs' relevance to brain neural networks. We collected data on human perceptual responses to a series of visual illusions. This data was then used to assess how DNN responses to these illusions paralleled or differed from human behavior. We performed two analyses:(1) We trained DNNs to perform horizontal vs. non-horizontal classification on images with bars tilted different degrees (non-illusory images) and tested them on images with horizontal bars with different illusory strengths measured by human behavior (illusory images), finding that DNNs showed human-like illusions; (2) We performed representational similarity analysis to assess whether illusory representation existed in different layers within DNNs, finding that DNNs showed illusion-like responses to illusory images. The representational similarity between real tilted images and illusory images was calculated, which showed the highest values in the early layers and decreased layer-by-layer. Our findings suggest that DNNs could serve as potential models for explaining the mechanism of visual illusions in human brain, particularly those that may originate in early visual areas like the primary visual cortex (V1). While promising, further research is necessary to understand the nuanced differences between DNNs and human visual pathways.