bluuebunny/crossref_metadata_2025 huggingface dataset:
Embuilds volume determination using the GNSS and laser scanning method
Authors:   LTD Navigation and Geodetic Center, HOLOVACHOV V.
Published: April 2024

In the modern period, the calculation of volumes of embankments plays an important role in a number of industries, starting from construction and ending with mining. This calls for the improvement of methods and technologies to ensure accurate and operational calculations of embankment volumes. One of the promising directions in this context is the use of Triangulated Irregular Networks (TIN) and Mesh models based on data obtained during geodetic measurements. Surveying is a large amount of accurate spatial measurement data that is necessary to create detailed geometric models of objects. The obtained geodetic data allow creating TIN and Mesh models that reflect the relief of the land surface with the necessary accuracy and detail. The use of these models to calculate the volumes of embankments becomes a key element in improving the processes of design, construction and management of natural resources. The purpose of this work is to compare the accuracy of the calculation of embankment volumes based on the data obtained by the hand-held laser scanner Stonex X120GO and the GNSS receiver Stonex S700A. Method. The method of comparing equal-precision measurements was used. Since there were no reference volumes of embankments at the site of the works, the difference between the volumes calculated on the basis of the data obtained with the hand-held laser scanner Stonex X120GO and the GNSS receiver Stonex S700A was used. Also, comparative and visual analysis was used to compare the difference between Mesh models obtained on the basis of different data sources. The results. The accuracy of determining the volumes of embankments obtained by a handheld laser scanner Stonex X120GO and a GNSS receiver Stonex S700A was studied. The average error of the differences between the determined volumes was 4.62%. Point clouds and Mesh models themselves were also analyzed (number of points, triangles, surface shape). The advantages and disadvantages of using a GNSS receiver and a hand-held laser scanner to collect data for calculating the volumes of material mounds are identified. Scientific novelty and practical significance. A technique for checking the accuracy of determining the volume of embankments without known reference values is proposed. The influence of the embankment area error on the accuracy of volume determination was studied. According to the results of the study, it is possible to assert the advantages in the detail of the received data and the speed of shooting when using a manual laser scanner, and about some difficulties associated with the desired presence of a powerful computer, a large array of data, an increase in the volume of camera work in comparison with the data obtained under the time of application of the GNSS receiver and the RTK method for determining the volumes of embankments
Research of the state of forests in the precarpathian region by satellite images using the method of supervised classification
Authors:   Lviv Polytechnic National University, PETRYK YU. , BURSHTYNSKA Kh. ,   Lviv Polytechnic National University, POLISHCHUK B. ,   Lviv Polytechnic National University
Published: April 2024

The purpose of the research is to monitor the forest objects of the Rava-Ruska forestry and determine changes in their areas from 2002 to 2022. The methodology of monitoring the state of the forests of the Rava-Ruska forestry is based on the using of multi-temporal medium-resolution satellite images with their subsequent processing using geographic information systems. For processing, we use images from Landsat 7 (July 2002) and Sentinel-2 (August 2022). We use csupervised classification using the maximum likelihood method. To post-process the classification results, we use Majority Filter. Based on the results, we calculate the area of classes for the relevant years. We perform a comparative analysis of these areas to determine changes in forest objects. Results. The research was conducted on a part of the territory of the Rava-Ruska forestry. Training samples were created for the following objects: deciduous and coniferous forest, fresh deforestation and overgrown deforedtation, open ground and roads, water and agricultural land. Histograms and scatter plots are used to evaluate the training samples. The suoervised classification was carried out using the maximum likelihood method on a part of the forestry territory with further post-processing. As a result of using GIS tools, a comparison of forest changes over two decades was made. The monitoring of the forests of the Rava-Ruska forestry allowed us to identify changes in forest objects, in particular deforestation, which in 2022 amounted to 679.2 hectares. Scientific novelty and practical significance. A methodology for monitoring forests using remote sensing materials has been developed. The possibilities of detecting changes in forest objects using the method of supervised classification are investigated.
Doktrin Pilihan Allah Dalam Roma 9 Bagi Peneguhan Iman Jemaat
Authors: Priyono Joko
Published: April 2024

The doctrine of God's choice of believers is a concept that is difficult to explain and has become a theological polemic to this day. This concept polemic occurs in groups that emphasize works as the basis of salvation and groups that emphasize grace as the basis of salvation. The Bible explains that the doctrine of choice of believers (predestination) is a very important part, and this doctrine is closely related to the teaching of salvation. Specifically, the Bible explains the doctrine of God's choice of believers in the letter Romans 9. Therefore, the author uses the exegetical method to find the meaning of God's choice of believers as an effort to strengthen the congregation's faith. God chooses His chosen people based on God's covenant, God's purposes, God's generosity, and God's sovereignty. And Allah chooses His chosen people through faith, and not because of good deeds. Faith here is faith in the Lord Jesus who is the center and target of faith.
Studi Eksegesis 1 Korintus 2:14-3:1 Sebagai Kajian Psikobiblika Dalam Memahami Perilaku Umat Kristen
Authors: Juanda Juanda , Karina Nina Astrid
Published: April 2024

Interpretations regarding the meanings of the phrases "spiritual man" and "natural man" as found in the text 1 Corinthians 2:14-3:1 have led to differences of opinion among scholars and theologians. There are at least three concepts related to the terms "spiritual man" and "natural man". First, these entities refer to the core of human nature which possesses contrasting characteristics. Second, there is a gradual development of the spiritual dimension within a person. Third, the inner state of humans is also characterized by the alternating dominance between spiritual and worldly aspects. The possible causes of variations in interpretations related to the terminology of "spiritual man" and "natural man" may be due to differences in the usage of different original texts, especially "natural man" which uses ψυχικὸς ἄνθρωπος in chapter 2 and σαρκίνοις in chapter 3. Differences in textual sources indicate variations in contexts and usage, which can lead to diverse understandings of these terms. Research conducted using Grassmick's nine-step qualitative exegesis method aims to seek the meanings of the phrases "spiritual man" and "natural man". From a series of exegetical processes that have been carried out, the analysis results show that the concept of "natural man" (ψυχικὸς ἄνθρωπος and σαρκίνοις) has fundamental differences with the "spiritual man" (ὁ πνευματικὸς), as these terms not only refer to sequential or interchangeable spiritual conditions, but also describe a fundamental status in someone's regeneration in Christ.
Jemaat Laodikia (Wahyu 3:14-22) Sebuah Tinjuan dari Bahasa Yunani
Authors: Chia Philip Suciadi
Published: April 2024

The congregation of Laodicea stands out as the sole assembly within the Book of Revelation that does not receive commendation from Christ. This article undertakes an examination of various factors contributing to the lack of praise bestowed upon the Laodicean congregation by Christ, employing a linguistic analysis encompassing Greek syntax, aspect, and aktionsart. Through a detailed exploration of these linguistic dimensions, insights into the theological implications surrounding the Laodicean community's portrayal in Revelation are elucidated, shedding light on its significance within the broader narrative of the text.
An improved radial basis function neural network for displacement prediction of a reservoir slope
Authors: Zhang Xin , Luo Weihua , Liu Guoyang , Yu Bo , Bo Wu , Zhao Penghui
Published: April 2024

Landslide prediction necessitates viewing the past, present, and future states of a slope as a constantly changing dialectical unity, with prediction laws derived from known past and present information. Through in-depth analysis of the structure and training methods of radial basis function (RBF) neural networks, an optimization method of RBF network diffusion velocity function based on the particle swarm optimization (PSO) algorithm was introduced in this study, aiming at the problem of limited coverage of spread value range determined by the empirical value or trial calculation method, so as to realize the large-scale and efficient search of RBF network diffusion function. To address the problem that the prediction accuracy of the data-driven model based on displacement increment sequences built by RBF intelligent algorithm is difficult to be guaranteed when the displacement increment mutation point exists, the PSO-RBF intelligent coupling model based on gray system theory pre-processing is constructed to improve the prediction accuracy of the model from the perspective of improving the prediction accuracy of displacement increment mutation points. Taking the data from ZG88 monitoring point of Shuping landslide as a case study, the slope displacement prediction analysis is carried out. The results demonstrate that the optimization method for RBF network diffusion velocity parameters based on PSO can efficiently and accurately identify the global optimal value within the range of 0–1,000. The computation process takes approximately 13 min, significantly enhancing the calculation efficiency. The RBF mixed model, incorporating gray system theory, leverages the valuable information extracted from prior calculations of the GM(1,1) model group. This integration enhances prediction accuracy compared with that achieved by the singular PSO-RBF method. The developed algorithms and research results may be expected to be applied in practical engineering.
Score based on contrast-enhanced ultrasound predict central lymph node metastasis in papillary thyroid cancer
Authors: He Lin , Chen Xiao , Hu Jiayin , Meng Yun , Zhang Yan , Chen Wei , Fan Yuhong , Li Tao , Fang Jingqin
Published: April 2024

Objectives

To investigate the association between contrast-enhanced ultrasound (CEUS) features of PTC and central lymph node metastasis (CLNM) and to develop a predictive model for the preoperative identification of CLNM.

Methods

This retrospective study evaluated 750 consecutive patients with PTC from August 2020 to April 2023. Conventional ultrasound and qualitative CEUS features were analyzed for the PTC with or without CLNM using univariate and multivariate logistic regression analysis. A nomogram integrating the predictors was constructed to identify CLNM in PTC. The predictive nomogram was validated using a validation cohort.

Results

A total of 684 patients were enrolled. The 495 patients in training cohort were divided into two groups according to whether they had CLNM (pCLNM, n= 191) or not (nCLNM, n= 304). There were significant differences in terms of tumor size, shape, echogenic foci, enhancement direction, peak intensity, and score based on CEUS TI-RADS between the two groups. Independent predictive US features included irregular shape, larger tumor size (≥ 1.0cm), and score. Nomogram integrating these predictive features showed good discrimination and calibration in both training and validation cohort with an AUC of 0.72 (95% CI: 0.68, 0.77) and 0.79 (95% CI: 0.72, 0.85), respectively. In the subgroup with larger tumor size, age ≤ 35 years, irregular shape, and score > 6 were independent risk factors for CLNM.

Conclusion

The score based on preoperative CEUS features of PTC may help to identify CLNM. The nomogram developed in this study provides a convenient and effective tool for clinicians to determine an optimal treatment regimen for patients with PTC.
Hydrodynamic analysis of a floating platform integrated with buoys and spring components for energy conversion
Authors: Sun Shi Yan , Gao Ruili , Li Yueyang , Ren Kang
Published: April 2024

Introduction: The study presents an integrated system comprising a central platform and four wave-energy converters, with a focus on investigating their coupled motions induced by ocean waves. The interaction between the buoys and the central platform is achieved through the implementation of spring components. The power take-off system is simulated by incorporating damping coefficients and stiffness into these spring components, enabling a detailed analysis of the energy conversion of such system.

Methods: Numerical simulations based on the continuity equation and the Reynolds-Averaged Navier-Stokes (RANS) equations, coupled with the realizable k−ε turbulence model, are conducted. The two-phase flow model employs the Volume of Fluid (VOF) method to accurately capture free surface elevations. Additionally, frequency-domain predictions, based on the linearized velocity potential flow theory, are provided for a single central platform and buoy for comparative purposes.

Results: Detailed results regarding the effects of wave frequency and the damping coefficient of the power take-off system are presented.

Discussion: The results reveal that while both the platform’s motion and the relative motions between buoys and the platform are suppressed, the absolute motion of buoys varies depending on their respective locations within the system and ocean waves. This variation is deeply influenced by the interaction between incident, reflected and diffracted waves within the system.
Multi-omics-based investigation of Bifidobacterium’s inhibitory effect on glioma: regulation of tumor and gut microbiota, and MEK/ERK cascade
Authors: Fan Huali , Wang Yuhan , Han Mingyu , Wang Li , Li Xue , Kuang Xi , Du Junrong , Peng Fu
Published: April 2024

Glioma, the most prevalent primary tumor of the central nervous system, is characterized by a poor prognosis and a high recurrence rate. The interplay between microbes, such as gut and tumor microbiota, and the host has underscored the significant impact of microorganisms on disease progression. Bifidobacterium, a beneficial bacterial strain found in the human and animal intestines, exhibits inhibitory effects against various diseases. However, the existing body of evidence pertaining to the influence of Bifidobacterium on glioma remains insufficient. Here, we found that Bifidobacterium reduces tumor volume and prolongs survival time in an orthotopic mouse model of glioma. Experiments elucidated that Bifidobacterium suppresses the MEK/ERK cascade. Additionally, we noted an increase in the α-diversity of the tumor microbiota, along with an augmented relative abundance of Bifidobacterium in the gut microbiota. This rise in Bifidobacterium levels within the intestine may be attributed to a concurrent increase in Bifidobacterium within the glioma. Additionally, Bifidobacterium induced alterations in serum metabolites, particularly those comprised of organonitrogen compounds. Thus, our findings showed that Bifidobacterium can suppress glioma growth by inhibiting the MEK/ERK cascade and regulating tumor, and gut microbiota, and serum metabolites in mice, indicating the promising therapeutic prospects of Bifidobacterium against glioma.
NmrB (AN9181) expression is activated under oxidative stress conditions acting as a metabolic repressor of Aspergillus nidulans
Authors: Jorge João M. P. , Martins Celso , Domingos Patrícia , Martins Tiago M. , Hartmann Diego O. , Goldman Gustavo H. , Silva Pereira Cristina
Published: April 2024

Aspergilli comprise a diversity of species that have been extensively studied due to their catabolic diversity, biotechnological and ecological value, and pathogenicity. An impressive level of structural and functional conservation has been shown for aspergilli, regardless of many (yet) cryptic genomic elements. We have hypothesized the existence of conserved genes responsive to stress in aspergilli. To test the hypothesis of such conserved stress regulators in aspergilli, a straightforward computational strategy integrating well-established bioinformatic tools was used as the starting point. Specifically, five transcriptome-based datasets on exposure to organic compounds were used, covering three distinct Aspergillus species. Among the identified up-regulated genes, only one gene showed the same response in all conditions, AN9181. This gene encodes a protein containing a phenylcoumaran benzylic ether reductase-like domain and a Nitrogen metabolite repressor regulator domain (NmrA). Deletion of this gene caused significant phenotypic alterations compared to that of the parental strain across diverse conditions. Specifically, the deletion of AN9181 raised the mutant’s metabolic activity in different nitrogen sources. The acquired data supports that AN9181 acts by repressing (slowing down) A. nidulans growth when exposed to aromatic compounds in a concentration dependent manner. The same phenotype was observed for amphotericin B. Finally, AN9181 underwent differential upregulation under oxidative stress conditions. Collectively, the data suggest that AN9181, herein assigned as NmrB (Nitrogen Metabolite Repression Regulator B), builds up the genetic machinery of perception of oxidative stress by negatively regulating growth under such conditions.
EMPT: a sparsity Transformer for EEG-based motor imagery recognition
Authors: Liu Ming , Liu Yanbing , Shi Weiyou , Lou Yitai , Sun Yuan , Meng Qi , Wang Dezheng , Xu Fangzhou , Zhang Yang , Zhang Lei , Leng Jiancai
Published: April 2024

Introduction

Transformer network is widely emphasized and studied relying on its excellent performance. The self-attention mechanism finds a good solution for feature coding among multiple channels of electroencephalography (EEG) signals. However, using the self-attention mechanism to construct models on EEG data suffers from the problem of the large amount of data required and the complexity of the algorithm.

Methods

We propose a Transformer neural network combined with the addition of Mixture of Experts (MoE) layer and ProbSparse Self-attention mechanism for decoding the time-frequency-spatial domain features from motor imagery (MI) EEG of spinal cord injury patients. The model is named as EEG MoE-Prob-Transformer (EMPT). The common spatial pattern and the modified s-transform method are employed for achieving the time-frequency-spatial features, which are used as feature embeddings to input the improved transformer neural network for feature reconstruction, and then rely on the expert model in the MoE layer for sparsity mapping, and finally output the results through the fully connected layer.

Results

EMPT achieves an accuracy of 95.24% on the MI EEG dataset for patients with spinal cord injury. EMPT has also achieved excellent results in comparative experiments with other state-of-the-art methods.

Discussion

The MoE layer and ProbSparse Self-attention inside the EMPT are subjected to visualisation experiments. The experiments prove that sparsity can be introduced to the Transformer neural network by introducing MoE and kullback-leibler divergence attention pooling mechanism, thereby enhancing its applicability on EEG datasets. A novel deep learning approach is presented for decoding EEG data based on MI.
Predicting the occurrence of mild cognitive impairment in Parkinson’s disease using structural MRI data
Authors: Beheshti Iman , Ko Ji Hyun
Published: April 2024

Introduction

Mild cognitive impairment (MCI) is a common symptom observed in individuals with Parkinson’s disease (PD) and a main risk factor for progressing to dementia. Our objective was to identify early anatomical brain changes that precede the transition from healthy cognition to MCI in PD.

Methods

Structural T1-weighted magnetic resonance imaging data of PD patients with healthy cognition at baseline were downloaded from the Parkinson’s Progression Markers Initiative database. Patients were divided into two groups based on the annual cognitive assessments over a 5-year time span: (i) PD patients with unstable healthy cognition who developed MCI over a 5-year follow-up (PD-UHC, n = 52), and (ii) PD patients who maintained stable healthy cognitive function over the same period (PD-SHC, n = 52). These 52 PD-SHC were selected among 192 PD-SHC patients using propensity score matching method to have similar demographic and clinical characteristics with PD-UHC at baseline. Seventy-five percent of these were used to train a support vector machine (SVM) algorithm to distinguish between the PD-UHC and PD-SHC groups, and tested on the remaining 25% of individuals. Shapley Additive Explanations (SHAP) feature analysis was utilized to identify the most informative brain regions in SVM classifier.

Results

The average accuracy of classifying PD-UHC vs. PD-SHC was 80.76%, with 82.05% sensitivity and 79.48% specificity using 10-fold cross-validation. The performance was similar in the hold-out test sets with all accuracy, sensitivity, and specificity at 76.92%. SHAP analysis showed that the most influential brain regions in the prediction model were located in the frontal, occipital, and cerebellar regions as well as midbrain.

Discussion

Our machine learning-based analysis yielded promising results in identifying PD individuals who are at risk of cognitive decline from the earliest disease stage and revealed the brain regions which may be linked to the prospective cognitive decline in PD before clinical symptoms emerge.
Generic orphan drug substitution: a critical analysis of global practices and Saudi Arabia’s perspective
Authors: Alakeel Yousif S. , Rampakakis Emmanouil , AlRumaih Ali , AlRuwaisan Rana , Abushal Maha , AlDalaan Abdullah M. , Idrees Majdy M. , Alanazi Zaid D. , AlKoait Hanouf , Muaadi Abdulrahman , AlAfra Majed Ali M. , AlShaya Shaya A. , AlHomida Suliman
Published: April 2024

In an era of cost pressure, substituting generic drugs represents one of the main cost-containment strategies of healthcare systems. Despite the obvious financial benefits, in a minority of cases, substitution may require caution or even be contraindicated. In most jurisdictions, to obtain approval, the bioequivalence of generic products with the brand-name equivalent needs to be shown via bioavailability studies in healthy subjects. Rare diseases, defined as medical conditions with a low prevalence, are a group of heterogenous diseases that are typically severe, disabling, progressive, degenerative, and life-threatening or chronically debilitating, and disproportionally affect the very young and elderly. Despite these unique features of rare diseases, generic bioequivalence studies are typically carried out with single doses and exclude children or the elderly. Furthermore, the excipients and manufacturing processes for generic/biosimilar products can differ from the brand products which may affect the shelf-life of the product, its appearance, smell, taste, bioavailability, safety and potency. This may result in approval of generics/biosimilars which are not bioequivalent/comparable in their target population or that meet bioequivalence but not therapeutic equivalence criteria. Another concern relates to the interchangeability of generics and biosimilars which cannot be guaranteed due to the phenomenon of biocreep. This review summarizes potential concerns with generic substitution of orphan drugs and discusses potentially problematic cases including narrow therapeutic index drugs or critical conditions where therapeutic failure could lead to serious complications or even death. Finally, we put forward the need for refining regulatory frameworks, with emphasis on Saudi Arabia, for generic substitution and recent efforts toward this direction.
Learning by observing: a systematic exploration of modulatory factors and the impact of observationally induced placebo and nocebo effects on treatment outcomes
Authors: Klauß Helena , Kunkel Angelika , Müßgens Diana , Haaker Jan , Bingel Ulrike
Published: April 2024

Introduction

Observational learning (OL) refers to learning through observing other people’s behavior. OL has been suggested as an effective and simple tool to evoke treatment expectations and corresponding placebo and nocebo effects. However, the exact mechanisms by which OL shapes treatment outcomes, its moderating factors and possible areas of application remain unclear. We thus reviewed the existing literature with two different literature searches to answer the following questions: Which influencing factors contribute to OL-induced placebo and nocebo effects (in healthy volunteers and patients) and how large are these effects (search 1)? In which medical fields has OL been used so far to modulate treatment expectancy and treatment outcomes in patients, their caregivers, and at-risk groups (search 2)? We also aimed to explore whether and how the assessment of treatment expectations has been incorporated.

Methods

We conducted two independent and comprehensive systematic literature searches, both carried out on September 20, 2022.

Results

We identified 21 studies that investigated OL-mediated placebo and nocebo effects for pain and itch, the (placebo) efficacy of sham treatment on anxiety, and the (nocebo) induction of medication side effects (search 1). Studies showed that OL can efficiently induce placebo and nocebo effects across different presentation modes, with medium effect sizes on average: placebo effects, d = 0.79 (range: d = −0.36–1.58), nocebo effects, d = 0.61 (range: d = 0.04–1.5). Although several moderating factors have been investigated, their contribution to OL-induced effects remains unclear because of inconsistent results. Treatment expectation was assessed in only four studies. Regarding medical applications of OL (search 2), we found 12 studies. They showed that OL was effectively applied in preventive, therapeutic and rehabilitative interventions and that it was mainly used in the field of psychosomatics.

Discussion

OL effects on treatment outcomes can be both positive and negative. Future research should investigate which individuals would benefit most from OL and how OL can be implemented most effectively to induce placebo and avoid nocebo effects in clinical settings.

Systematic review registration

This work was preregistered at the Center for Open Science as open-ended registration (doi: 10.17605/OSF.IO/FVHKE). The protocol can be found here: https://archive.org/details/osf-registrations-fvhke-v1.
Perceived social support, perceived stress, and quality of sleep among COVID-19 patients in Iran: assessing measurement invariance of the multidimensional scale of perceived social support across gender and age
Authors: Habibi Asgarabad Mojtaba , Vahabi Zahra , Cheung Ho Nam , Ahmadi Reza , Akbarpour Samaneh , Sadeghian Mohammad Hossein , Etesam Farnaz
Published: April 2024

Background

Perceived social support (PSS) plays a considerable role in mental health. The Multidimensional Scale of Perceived Social Support (MSPSS) is one of the most widely used scales, leading to much research evidence. The present study investigated its measurement model, equivalence across gender (male and female) and age groups (older patients= above 60 and non-older patients= below 60), and concurrent validity.

Methods

A cross-sectional survey was conducted between March and October 2020, on patients hospitalized due to COVID-19 in Tehran, Iran. The scales were administered to 328 COVID-19 patients (54.6% male, aged 21 to 92) from two general hospitals; participants completed MSPSS (including friends, family, and significant others subscales), Pittsburgh Sleep Quality Index (PSQI, include sleep latency, subjective sleep quality, habitual sleep efficiency, sleep duration, use of sleep medication, daytime dysfunction, and sleep disturbances subscales), and the Perceived Stress Scale-10 (PSS-10, to assess patients’ appraisal of stressful conditions).

Results

The MSPSS three-factor structure was confirmed among COVID-19 patients by Confirmatory Factor Analysis (CFA). The results support the MSPSS internal consistency and configural, metric, and scalar invariance across gender and age groups. Nevertheless, small but significant differences were found across ages based on the latent factor mean of the MSPSS from friends, with a lower mean level in older patients. The coefficients of Cronbach’s alpha (ranging from.92 to.96), the ordinal theta (ranging from.95 to.98), and Omega (ranging from.93 to.97) suggested high internal consistency of MSPSS. The concurrent validity of MSPSS was evidenced by its significant negative correlation with PSS-10 (τb = -.13, p <.01) and also subjective sleep quality (τb = -.22, p <.01), sleep disturbances (τb = -.26, p <.001), and daytime dysfunction (τb = -.26, p <.001).

Conclusions

The MSPSS was valid and reliable for measuring individuals’ perception of social support between males and females and older and non-older COVID-19 patients.
A bidirectional causal relationship study between mental disorders and male and female infertility
Authors: Chen Xiangyu , Hao Xuexue , Xie Lijun , Liu Xiaoqiang
Published: April 2024

Background

The relation between mental disorders (MDs) and infertility can be reciprocal. But exactly which MD affects infertility remains controversial. Our aim was to use Mendelian randomization (MR) to explore bidirectional causality between 15 MDs and male infertility and female infertility.

Methods

The data of MDs, male infertility, and female infertility were derived from published genome-wide association studies (GWAS). The inverse variance weighted method was considered to be the main analytical approach. Sensitivity analysis was performed using MR-Egger, Cochran’s Q, radial MR, and MR-PRESSO tests.

Results

Our results found that mood disorders (OR, 1.4497; 95% CI, 1.0093 – 2.0823; P = 0.0444) and attention deficit hyperactivity disorder (OR, 1.3921; 95% CI, 1.0943 – 1.7709; P = 0.0071) were positively correlated with male infertility, but obsessive-compulsive disorder (OR, 0.8208; 95% CI, 0.7146 – 0.9429; P = 0.0052) was negatively associated with male infertility. For females, anorexia nervosa (OR, 1.0898; 95% CI, 1.0070 – 1.1794; P = 0.0329), attention deficit hyperactivity disorder (OR, 1.1013; 95% CI, 1.0041 – 1.2079; P = 0.0406), and major depressive disorder (OR, 1.1423; 95% CI, 1.0213 – 1.2778; P = 0.0199) increased risk of infertility. In reverse relationship, female infertility increased the incidence of bipolar disorder (OR, 1.0009; 95% CI, 1.0001 – 1.0017; P = 0.0281).

Conclusion

We demonstrated the association between five MDs and male or female infertility. Female infertility was also found to be associated with an increased risk of one MD. We look forward to better designed epidemiological studies to support our results.
Neural dynamics of robust legged robots
Authors: Rush Eugene R. , Heckman Christoffer , Jayaram Kaushik , Humbert J. Sean
Published: April 2024

Legged robot control has improved in recent years with the rise of deep reinforcement learning, however, much of the underlying neural mechanisms remain difficult to interpret. Our aim is to leverage bio-inspired methods from computational neuroscience to better understand the neural activity of robust robot locomotion controllers. Similar to past work, we observe that terrain-based curriculum learning improves agent stability. We study the biomechanical responses and neural activity within our neural network controller by simultaneously pairing physical disturbances with targeted neural ablations. We identify an agile hip reflex that enables the robot to regain its balance and recover from lateral perturbations. Model gradients are employed to quantify the relative degree that various sensory feedback channels drive this reflexive behavior. We also find recurrent dynamics are implicated in robust behavior, and utilize sampling-based ablation methods to identify these key neurons. Our framework combines model-based and sampling-based methods for drawing causal relationships between neural network activity and robust embodied robot behavior.
Sexual and Reproductive Health and Rights for Young Migrants in Sweden: An Ideal-Type Analysis Exploring Regional Variations of Accessible Documents
Authors: Brunet Johansson Albert , Hurtig Anna-Karin , Nkulu Kalengayi Faustine Kyungu
Published: April 2024

Objectives: This study aims to map sexual and reproductive health and rights (SRHR) policies, strategies, and interventions targeting young migrants and describe the patterns of organisation, resources, and services across Sweden’s 21 regions.

Methods: We conducted a document analysis of accessible online documents on SRHR policies, strategies, and interventions targeting young migrants in Sweden’s 21 regions. We used ideal-type analysis of the documents to create a typology, which formed the basis of a ratings system illustrating variations in organisation, resources, and services across regions.

Results: Findings suggest that efforts aimed at addressing young migrants’ SRHR are fragmented and unequal across regions. While SRHR policies and strategies are commonplace, they routinely lack specificity. Available resources vary depending on region and resource type. Additionally, information and interventions, although common, do not consistently meet the specific needs of migrant youths.

Conclusion: This study suggests that fragmented efforts are fuelling geographic inequalities in fulfilling SRHR among young migrants. There is an urgent need to improve national coordination and collaboration between national and local actors in SRHR efforts targeting young migrants to ensure equity.
Period-Multiplying Bifurcations in the Gravitational Field of Asteroids
Authors: Krishna P. Rishi , Manathara Joel George
Published: April 2024

Periodic orbit families around asteroids serve as potential trajectories for space probes, mining facilities, and deep space stations. Bifurcations of these families provide additional candidate orbits for efficient trajectory design around asteroids. While various bifurcations of periodic orbit families around asteroids have been extensively studied, period-multiplying bifurcations have received less attention. This paper focuses on studying period-multiplying bifurcations of periodic orbit families around asteroids. In particular, orbits with periods of approximately 7 and 17 times that of the rotational period of asteroid 216 Kleopatra were computed. The computation of high-period orbits provides insights into the numerical aspects of simulating long-duration trajectories around asteroids. The previous literature uses single-shooting and multiple-shooting methods to compute bifurcations of periodic orbit families around asteroids. Computational difficulties were encountered while using the shooting methods to obtain period-multiplying bifurcations of periodic orbit families around asteroids. This work used the Legendre–Gauss collocation method to compute period-multiplying bifurcations around asteroids. This study recommends the use of collocation methods to obtain long-duration orbits around asteroids when computational difficulties are encountered while using shooting methods.
Long-Duration Dynamic Numerical Simulation of Combustion and Flow in Hybrid Rocket Motors Considering Nozzle Erosion
Authors: Meng Xiangyu , Tian Hui , Niu Xiaoting , Zhu Hao , Gao Jingfei , Cai Guobiao
Published: April 2024

Hybrid rocket motors have great development potential due to their outstanding thrust adjustment flexibility and long-term operation ability. However, nozzle erosion during the motor operation can cause an increase in the throat area of the nozzle, which leads to a decrease in combustion chamber pressure and nozzle efficiency. Therefore, a performance prediction model for hybrid rocket motors considering nozzle erosion has become a key technology that must be addressed when developing hybrid rocket motors. This study uses dynamic grid technology to simulate the regression of the combustion surface and nozzle erosion, which fits well with experimental values. The behavior of high-energy particles in the combustion chamber is simulated through a discrete phase model. Notably, distinctive behavior is observed in Al and Mg droplets, with Al droplets exhibiting incomplete vaporization in the combustion chamber while Mg droplets completely vaporize. A ground firing test using the Φ336 mm hybrid rocket motor lasting 200 s is conducted. The results show that the dynamic numerical simulation, accounting for nozzle erosion, substantially enhances performance prediction accuracy. The average deviation in motor thrust remains below 1.8%, and the combustion chamber pressure deviation stays under 2.6%, confirming the precision of the model. Ultimately, both simulation and experimental outcomes indicate a gradual decrease in specific impulse and characteristic velocity over the long-term operation, attributed to the gradual deviation of the oxygen-fuel ratio. This research provides valuable insights for guiding hybrid rocket motor design and optimizing design parameters to improve overall performance. This model can achieve long-duration and high-precision performance predictions for hybrid rocket motors.
The Effect of Lysophospholipids and Sex on Growth Performance and Small Intestine Morphology in Weanling Pigs, 7–30 kg
Authors: Grove Sabine Stoltenberg , Dall Jacob , Madsen Johannes Gulmann
Published: April 2024

Inclusion of lysophospholipids (LPL) has been proposed to increase growth performance in broilers and pigs, acting as emulsifiers through mixed micelle formation. The aim of this study was to investigate the effect of feeding LPL in weanling pig diets on growth performance and intestinal morphology. Eight hundred pigs (weight 6.96 kg ± SD 1.58 kg) were assigned to one of two dietary treatments, i.e., a basal diet (CON) or a basal diet + 0.05% lysophospholipids (LPL). The experimental period lasted for 42 days, and on days 40 and 41, 32 pigs in total were euthanized for intestinal tissue samples. From days 14 to 21, feed intake and average daily gain increased, as well as FCR, from days 28 to 42, in the LPL group compared with the CON group. In the overall period, no differences in growth performance were present between the groups. However, females displayed increased ADG from days 21 to 28 compared with castrates. The villous height tended (p = 0.051) to be lower in LPL in the proximal jejunum compared with CON. In the proximal jejunum, villus was higher (p > 0.01) in females, and in the distal jejunum, higher crypt cell proliferation (p < 0.01) and a tendency to deeper crypts (p = 0.064) were observed in female pigs as well. In conclusion, lysophospholipids did not increase growth performance in this study; however, the rate of recovery from a poorer starting point was noted, as growth rates recovered and increased faster in the LPL group. In conclusion, unlike the first phase, the LPL group recovered the growth from days 14 to 21 through higher feed intake and weight gain than the CON group. Eventually, the LPL group displayed improved FCR compared with the CON group from days 28 to 42. Further studies are needed to investigate whether this effect continues into the grower–finisher phase.
Evaluation of Increasing Dietary Concentrations of a Multi-Enzyme Complex in Feedlot Lambs’ Rations
Authors: Mendoza-Martínez Germán David , Hernández-García Pedro Abel , Díaz-Galván Cesar , Razo-Ortiz Pablo Benjamín , Ojeda-Carrasco Juan José , Sánchez-López Nalley , de la Torre-Hernández María Eugenia
Published: April 2024

The objective of this study was to evaluate the effects of increasing levels of the M-E complex (xylanase, glucanase, cellulase, and invertase) Optimax E® on the performance of growing lambs, their digestibility, and their rumen microbiota, and to estimate NEm, NEg, and ruminal methane levels. Forty lambs (Katahdin x Dorset; 22.91 ± 4.16 kg) were randomly assigned to dietary concentrations of ME (0, 0.2, 0.4, and 0.8% DM) and fed individually for 77 days. Increasing M-E improved feed conversion (p < 0.05) as well as NEm and NEg (p < 0.05), which were associated with increased in vivo DM and NDF digestion (linear and quadratic p < 0.01). Few microbial families showed abundancy changes (Erysipelotrichaceae, Christensenellaceae, Lentisphaerae, and Clostridial Family XIII); however, the dominant phylum Bacteroidetes was linearly reduced, while Firmicutes increased (p < 0.01), resulting in a greater Firmicutes-to-Bacteroidetes ratio. Total Entodinium showed a quadratic response (p < 0.10), increasing its abundancy as the enzyme dose was augmented. The daily emission intensity of methane (per kg of DMI or AGD) was reduced linearly (p < 0.01). In conclusion, adding the M-E complex Optimax E® to growing lambs’ diets improves their productive performance by acting synergistically with the rumen microbiota, modifying the Firmicutes-to-Bacteroidetes ratio toward more efficient fermentation, and shows the potential to reduce the intensity of greenhouse gas emissions from lambs.
Impact of Agro-Byproduct Supplementation on Carcass Traits and Meat Quality of Hair Sheep and Wool × Hair Crossbreds Grazing on Fescue Pasture
Authors: Lee Jung Hoon , Wildeus Stephan , O’Brien Dahlia , Kouakou Brou
Published: April 2024

The effects of breed type (purebred or crossbred) and supplementation of agro-byproducts on the growth, carcass characteristics, and meat quality of landrace hair (Barbados Blackbelly; BB and St. Croix; SX) lambs was evaluated. Thirty-six 7.5-month-old purebred hair (BB and SX; body weight = 24.1 ± 4.26 kg) and terminal sire (Dorset; DO) crossbred lambs (DO × BB and DO × SX; body weight = 31.4 ± 3.50 kg) rotationally grazed predominantly on Jesup tall fescue pasture during spring with or without agro-byproduct supplementation (soyhull or corn gluten feed at 2% of BW). Following a 77d grazing period, the lambs were harvested, and their carcass characteristics and meat composition were evaluated. Both supplementation and crossbreeding significantly increased their carcass weight and primal cuts, whereas only supplementation increased (p < 0.01) the dressing percentage, and crossbreeding increased the shear force (p < 0.01). Regardless of breed type, supplementing agro-byproducts improved the lipid oxidation stability and texture properties of the fresh lamb, whereas the pasture-only lambs had healthier fatty acid profiles compared with the supplemented lambs. The results indicate that both terminal sire crossbreeding and byproduct supplementation can be used to affect the carcass characteristics and meat composition of landrace hair sheep lambs.
DTONet a Lightweight Model for Melanoma Segmentation
Authors: Hao Shengnan , Wang Hongzan , Chen Rui , Liao Qinping , Ji Zhanlin , Lyu Tao , Zhao Li
Published: April 2024

With the further development of neural networks, automatic segmentation techniques for melanoma are becoming increasingly mature, especially under the conditions of abundant hardware resources. This allows for the accuracy of segmentation to be improved by increasing the complexity and computational capacity of the model. However, a new problem arises when it comes to actual applications, as there may not be the high-end hardware available, especially in hospitals and among the general public, who may have limited computing resources. In response to this situation, this paper proposes a lightweight deep learning network that can achieve high segmentation accuracy with minimal resource consumption. We introduce a network called DTONet (double-tailed octave network), which was specifically designed for this purpose. Its computational parameter count is only 30,859, which is 1/256th of the mainstream UNet model. Despite its reduced complexity, DTONet demonstrates superior performance in terms of accuracy, with an IOU improvement over other similar models. To validate the generalization capability of this model, we conducted tests on the PH2 dataset, and the results still outperformed existing models. Therefore, the proposed DTONet network exhibits excellent generalization ability and is sufficiently outstanding.
Evaluation of Deep Learning Model Architectures for Point-of-Care Ultrasound Diagnostics
Authors: Hernandez Torres Sofia I. , Ruiz Austin , Holland Lawrence , Ortiz Ryan , Snider Eric J.
Published: April 2024

Point-of-care ultrasound imaging is a critical tool for patient triage during trauma for diagnosing injuries and prioritizing limited medical evacuation resources. Specifically, an eFAST exam evaluates if there are free fluids in the chest or abdomen but this is only possible if ultrasound scans can be accurately interpreted, a challenge in the pre-hospital setting. In this effort, we evaluated the use of artificial intelligent eFAST image interpretation models. Widely used deep learning model architectures were evaluated as well as Bayesian models optimized for six different diagnostic models: pneumothorax (i) B- or (ii) M-mode, hemothorax (iii) B- or (iv) M-mode, (v) pelvic or bladder abdominal hemorrhage and (vi) right upper quadrant abdominal hemorrhage. Models were trained using images captured in 27 swine. Using a leave-one-subject-out training approach, the MobileNetV2 and DarkNet53 models surpassed 85% accuracy for each M-mode scan site. The different B-mode models performed worse with accuracies between 68% and 74% except for the pelvic hemorrhage model, which only reached 62% accuracy for all model architectures. These results highlight which eFAST scan sites can be easily automated with image interpretation models, while other scan sites, such as the bladder hemorrhage model, will require more robust model development or data augmentation to improve performance. With these additional improvements, the skill threshold for ultrasound-based triage can be reduced, thus expanding its utility in the pre-hospital setting.
Associations between Skin Autofluorescence Levels with Cardiovascular Risk and Diabetes Complications in Patients with Type 2 Diabetes
Authors: Reurean-Pintilei Delia , Pantea Stoian Anca , Salmen Teodor , Stoica Roxana-Adriana , Mititelu-Tartau Liliana , Lazăr Sandra , Timar Bogdan
Published: April 2024

Advanced Glycation End Products (AGEs) contribute to the pathophysiology of type 2 diabetes mellitus (T2DM) and cardiovascular (CV) diseases (CVDs), making their non-invasive assessment through skin autofluorescence (SAF) increasingly important. This study aims to investigate the relationship between SAF levels, cardiovascular risk, and diabetic complications in T2DM patients. We conducted a single-center, cross-sectional study at Consultmed Hospital in Iasi, Romania, including 885 T2DM patients. The assessment of SAF levels was performed with the AGE Reader™, (Diagnoptics, Groningen, The Netherlands). CVD prevalence was 13.9%, and according to CV risk category distribution, 6.1% fell into the moderate-risk, 1.13% into the high-risk, and 92.77% into the very-high-risk category. The duration of DM averaged 9.0 ± 4.4 years and the mean HbA1c was 7.1% ± 1.3. After adjusting for age and eGFR, HbA1c values showed a correlation with SAF levels in the multivariate regression model, where a 1 SD increase in HbA1c was associated with a 0.105 SD increase in SAF levels (Nagelkerke R2 = 0.110; p < 0.001). For predicting very high risk with an SAF cut-off of 2.35, sensitivity was 67.7% and specificity was 56.2%, with an AUC of 0.634 (95% CI 0.560–0.709, p = 0.001). In T2DM, elevated SAF levels were associated with higher CV risk and HbA1c values, with 2.35 identified as the optimal SAF cut-off for very high CV risk.