bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neural correlates of gait adaptation in younger and older adults
Authors: Fettrow Tyler , Hupfeld Kathleen , Hass Chris , Pasternak Ofer , Seidler Rachael 
Published: August 2022

Abstract
Mobility decline is a major concern for older adults.A key component of maintaining mobility with advancing age is the ability to learn and adapt to the environment.The split-belt treadmill paradigm is an experimental protocol that tests the ability to adapt to a dynamic environment.Here we examined the magnetic resonance imaging (MRI) derived structural neural correlates of individual differences in adaptation to split-belt walking for younger and older adults.We have previously shown that younger adults adopt an asymmetric walking pattern during split-belt walking, particularly in the medial-lateral (ML) direction, but older adults do not.We collected \emph{T}$_1$-weighted and diffusion-weighted MRI scans to quantify brain morphological characteristics (i.e.in the gray matter and white matter) on these same participants.We investigated two distinct questions: 1) Are there structural brain metrics that are associated with the ability to adopt asymmetry during split-belt walking; and 2) Are there different brain-behavior relationships for younger and older adults? Given the growing evidence that indicates the brain has a critical role in the maintenance of gait and balance,we hypothesized that brain areas commonly associated with locomotion (i.e. basal ganglia, sensorimotor cortex, cerebellum) would be associated with ML asymmetry and that older adults would show more associations between split-belt walking and prefrontal brain areas.We identified multiple brain-behavior associations.More gray matter volume in the superior frontal gyrus and cerebellar lobules VIIB and VIII, more sulcal depth in the insula, more gyrification in the pre/post central gyri, and more fractional anisotropy in the corticospinal tract and inferior longitudinal fasciculus corresponded to more gait asymmetry.These associations did not differ between younger and older adults.This work progresses our understanding of how brain structure is associated with balance during walking, particularly during adaptation.
Investigation of the Convex Time Budget Experiment by Parameter Recovery Simulation
Authors: Shimodaira Yuta , Shiozawa Kohei , Inukai Keigo 
Published: August 2022

Abstract
The convex time budget (CTB) method is a widely used experimental method for eliciting an individual’s time preference. Researchers adopting the CTB experiment usually assume quasi-hyperbolic discounting utility as a behavioural model and estimate the parameters of the utility function. However, few studies using the CTB method have examined parameter recovery. We conduct simulations and find that the estimation error of the present bias parameter is so large that its effect is difficult to detect. The large error is due to the improper combination of the experimental method and the utility model, and it is not a problem we can deal with after the data collection. This paper suggests the importance of running parameter recovery simulations to audit estimation errors in the experimental design.
Transfer and transformation of mercury in cement production
Authors: Yuan Chongrui , Wang Yifan , Yang Jie , Yang Shuqing , Fu Junlin , Liu Shengyu 
Published: August 2022

Abstract
In the previous study, the Ontario method was used to sample and analyze some production links of cement plants, but only the morphological distribution of mercury before and after the dust collector was obtained. Few researches have been carried out to analyse and test the whole process of cement plant production. In this study, based on the method of combining theoretical analysis with field sampling, the mercury levels in solid samples and gas samples was analyzed and then compared with the results obtained from theoretical analysis. In this work, the results of the theoretical analysis and the sampling can be derived towards a consistent trend, so the theoretical analysis results have a certain credibility. Then the theoretical analysis of each link in the cement production process was carried out to obtain the morphological distribution of mercury in the main link, and then the thermodynamic analysis was carried out to obtain the form distribution, migration and transformation of mercury in each link of cement production. It provides a theoretical basis for local mercury pollution control, later mercury emission reduction, coordinated disposal and management.
Incidence, risk factors, and clinical characteristics of airway complications after lung transplantation
Authors: Kim Hyeon Hwa , Jo Kyung-Wook , Shim Tae Sun , Ji Wonjun , Ahn Jee Hwan , Oh Dong Kyu , Hong Sang-Bum , Yun Jae Kwang , Lee Geun Dong , Choi Sehoon , Kim Dong Kwan , Park Seung-Il , Kim Ho Cheol 
Published: August 2022

Abstract
Airway complications still occur after lung transplantation and are associated with considerable rates of morbidity and mortality. We investigated the incidence, risk factors, and clinical characteristics of these complications. We retrospectively reviewed the medical records of 137 patients who underwent lung transplantation between 2008 and 2021. The median follow-up period was 20 months. Of the 137 patients, 30 (21.9%) had postoperative airway complications, out of which 2 had two different types of airway complications. The most common airway complication was bronchial stenosis, affecting 23 patients (16.8%). Multivariable Cox analysis revealed that a transplant recipient’s body mass index measuring ≥25 kg/m2 (hazard ratio [HR], 2.663; p = 0.013) was a significant independent risk factor for airway complications, as was postoperative treatment with extracorporeal membrane oxygenation (ECMO; HR, 3.340; p = 0.034). Of the 30 patients who had airway complications, 21 (70.0%) were treated with bronchoscopic intervention. Rates of survival did not differ significantly between patients with and without airway complications. Thus, our study revealed that one fifth of patients who underwent lung transplantation experienced airway complications during the follow-up period. Obesity and receiving postoperative ECMO are risk factors for airway complications, and close monitoring is warranted in such cases.
What do Black-box Machine Learning Prediction Models See?- An Application Study With Sepsis Detection
Authors: Strickler Ethan A. T. , Thomas Joshua , Thomas Johnson P. , Benjamin Bruce , Shamsuddin Rittika 
Published: August 2022

Abstract
Purpose: The purpose of this study is to identify additional clinical features for sepsis detection through the use of a novel mechanism for interpreting black-box machine learning models trained and to provide a suitable evaluation for the mechanism.Methods: We use the publicly available dataset from the 2019 PhysioNet Challenge. It has around 40,000 Intensive Care Unit (ICU) patients with 40 physiological variables. Using Long Short-Term Memory (LSTM) as the representative black-box machine learning model, we adapted the Multi-set Classifier to globally interpret the black-box model for concepts it learned about sepsis. To identify relevant features, the result is compared against: i) features used by a computational sepsis expert, ii) clinical features from clinical collaborators, iii) academic features from literature, and iv) significant features from statistical hypothesis testing. Results: Random Forest (RF) was found to be the computational sepsis expert because it had high accuracies for solving both the detection and early detection, and a high degree of overlap with clinical and literature features. Using the proposed interpretation mechanism and the dataset, we identified 17 features that the LSTM used for sepsis classification, 11 of which overlaps with the top 20 features from the RF model, 10 with academic features and 5 with clinical features. Clinical opinion suggests, 3 LSTM features have strong correlation with some clinical features that were not identified by the mechanism. We also found that age, chloride ion concentration, pH and oxygen saturation should be investigated further for connection with developing sepsis.Conclusion: Interpretation mechanisms can bolster the incorporation of state-of-the-art machine learning models into clinical decision support systems, and might help clinicians to address the issue of early sepsis detection. The promising results from this study warrants further investigation into creation of new and improvement of existing interpretation mechanisms for black-box models, and into clinical features that are currently not used in clinical assessment of sepsis.
Impaired macroglial development and axonal conductivity contributes to the neuropathology of DYRK1A-related intellectual disability syndrome
Authors: Pijuan Isabel , Balducci Elisa , Soto-Sánchez Cristina , Fernández Eduardo , Barallobre María José , Arbonés Maria L. 
Published: August 2022

Abstract
The correct development and activity of neurons and glial cells is necessary to establish proper brain connectivity. DYRK1A encodes a protein kinase involved in the neuropathology associated with Down syndrome that influences neurogenesis and the morphological differentiation of neurons. DYRK1A loss-of-function mutations in heterozygosity cause a well-recognizable syndrome of intellectual disability and autism spectrum disorder. In this study, we analysed the developmental trajectories of macroglial cells and the properties of the corpus callosum, the major white matter tract of the brain, in Dyrk1a+/− mice, a mouse model that recapitulates the main neurological features of DYRK1A syndrome. We found that Dyrk1a+/− haploinsufficient mutants present an increase in astrogliogenesis in the neocortex and a delay in the production of cortical oligodendrocyte progenitor cells and their progression along the oligodendroglial lineage. There were fewer myelinated axons in the corpus callosum of Dyrk1a+/− mice, axons that are thinner and with abnormal nodes of Ranvier. Moreover, action potential propagation along myelinated and unmyelinated callosal axons was slower in Dyrk1a+/− mutants. All these alterations are likely to affect neuronal circuit development and alter network synchronicity, influencing higher brain functions. These alterations highlight the relevance of glial cell abnormalities in neurodevelopmental disorders.
Critical Public Infrastructure Underwater: The Flood Risk Profile of Florida Hospitals
Authors: Sun Pin , Entress Rebecca , Tyler Jenna , Sadiq Abdul-Akeem , Noonan Douglas 
Published: August 2022

Abstract
Hospitals play a critical role during disasters where they provide critical medical care to disaster victims and help the community to respond more effectively and recover quicker. However, hospitals face risks from the natural environment, such as floor risks. Amid the increasing flood risks due to climate change, it is essential to examine hospitals’ risk exposure. Motivated by this, this paper aims to answer four specific questions related to hospitals in Florida: 1) Are hospitals located in flood zones? 2) What is the relationship between hospital network size and flood risk? 3) To what extent does hospital flood risk vary by hospital attributes? 4) How do hospitals' flood risks differ from other public structures' flood risks? By leveraging two micro-level datasets, we found that approximately 12% of Florida hospitals are in flood zones, and that hospitals’ flood risk is not influenced by hospital network size or hospital attributes. We also find that hospitals are one of the most flood-prone public structures in our sample, raising questions about public infrastructure in flood management. We conclude by offering recommendations for improving hospital resilience to future disasters.
The Adaptive Significance of Human Scleral Brightness. An Experimental Study
Authors: Wacewicz Sławomir , Danel Dariusz , Lewandowski Zdzisław , Perea-Garcia Juan Olvido 
Published: August 2022

Abstract
Homogeneously depigmented sclerae have long been proposed to be uniquely human - an adaptation to enable cooperative behaviour by facilitating interpersonal coordination through gaze following. However, recent evidence has shown that deeply pigmented sclerae also afford gaze following if surrounding a bright iris. Furthermore, while current scleral depigmentation is clearly adaptive in modern humans, it is less clear how the evolutionarily intermediate stages of scleral pigmentation may have been adaptive. In sum, it is unclear why scleral depigmentation became the norm in humans, while not so in sister species like chimpanzees, or why some extant species (presumably as our ancestors did at some point) display intermediate degrees of pigmentation. We created realistic facial images of 20 individually distinct hominins with diverse facial morphologies, each face in the (i) humanlike bright sclera and (ii) generalised apelike dark sclera version. Participants in two online studies rated the bright-sclera hominins as younger, healthier, more attractive and trustworthy, but less aggressive than the dark-sclera hominins. Our results support the idea that the perceptual affordances of more depigmented sclerae increased perceived traits that fostered trust, increasing fitness for those individuals and resulting in depigmentation as a fixed trait in extant humans.
Formal verification of Reentrancy Vulnerability Based on CPN
Authors: He Yaqiong , Dong Hanjie , Wu Huaiguang , Duan Qianheng 
Published: August 2022

Abstract
A smart contract is a special form of computer program running on a blockchain, which provides a new way to implement financial and business transactions in a free-of-conflicts and transparent environment. In blockchain systems, such as Ethereum, smart contracts can handle and autonomously transfer assets of considerable value to other parties. Hence, it is particularly important to ensure that smart contracts function as intended since bugs or vulnerabilities may lead and indeed have led, to substantial economic losses and erosion of trust for blockchain. While a number of approaches and tools have been developed to find vulnerabilities, formal method presents the highest level of confidence about the security of smart contracts. In this paper, we propose a formal solution to model smart contract based on Colored Petri Net (CPN). Herein we focus on the most common type of security bugs in smart contract, i.e., reentrancy bug, which led to a serious financial loss of around $60 million in 2016. We present a hierarchical CPN modelling method to analyze potential security vulnerabilities at the contract’s source code level. Then modeling analysis methods such as correlation matrix, state space report and state space graph generated by CPN Tools simulation were exploited for formal analysis of smart contracts. The example shows the full state space and wrong path in accordance with our expected results. Finally, the conclusion was verified in the Ethereum network based on Remix platform.
Dynamic analysis of a rigid-flexible inflatable space structure coupled with control moment gyroscopes
Authors: Sun Jialiang , Cai Zhengzheng , Sun Jiahao , Jin Dongping 
Published: August 2022

Abstract
The vibration generated by the inflatable structure after deployment has a great impact on the performance of the payloads. In this paper, the influence of the control moment gyroscope (CMG) on the dynamic responses and characteristics of an inflatable space structure is studied, based on the flexible multibody dynamics in combination of the absolute nodal coordinate formulation (ANCF) and the natural coordinate formulation (NCF). Firstly, the ANCF and NCF are used to accurately describe the large deformations and large overall motions of flexible inflatable tubes and rigid satellites, respectively. Afterwards, by using the Lagrange equation, a rigid body dynamic model of the CMG is established in detail, which can be attached to and coupled with any flexible bodies without any assumptions. Then, the orbital dynamic equations of the inflatable space structure coupled with distributed CMGs are obtained by considering the effects of Coriolis force, centrifugal force, and gravity gradient through coordinate transformation. The dynamic characteristics of the inflatable space structure are also analyzed by deriving the eigenvalue problem of a flexible multibody system. Finally, the accuracy of the CMG dynamic model is verified via a classic heavy top example. And several numerical examples are presented to study the influence of the magnitudes and directions of the rotor angular momentum of the CMG on the dynamic responses and characteristics of the inflatable space structure.
Characterization of various Appel polynomials sequences
Authors: Drissi Driss 
Published: August 2022

Abstract
In this paper, we characterize various sequences of the Appell polynomials by means of the formula of representation of powers viewed from a linear operator perspective. First we construct some Gauss-Weierstrass integral representation operators for various sequence of Appell polynomials such as Euler-Frobenius polynomials, Degenerate Bernoulli polynomials, Bell-Touchard polynomials and for the generalized Tempesta-Bernoulli polynomials. Secondly, we introduce the Appell polynomials as well as the Hurwitz zeta function as eigenfunctions (eigenvectors) of certain well chosen discrete version of Gauss-Weierstrass integral operators. Our approach is inspired by the Gauss-Weierstrass transform for Hermite polynomials.
Alert System for Epileptic Seizure
Authors: Elma K.Johny , P Nithiyashree , A Savitha , S Sneha 
Published: August 2022

Abstract
Covid 19 has given way to a disruptive and transformative digital automation in health sector worldwide with multi fold investments for upgradation. Benefits could extend across health management with more innovations. Epilepsy, the fourth most common chronic neurological disorder, characterized by recurrent involuntary seizures affects everyone. Worldwide, 70 million people are affected, including 12 million in India, about one-sixth of the global burden. Epilepsy is unpredictable with violent seizures leading to sudden fluctuations in heart rate and involuntary muscle movements leading to death. Therefore, prompt medical attention is essential. Collectively, epilepsy has an effect on the quality of life, career development, and social behaviour, due to an imbalance of the patient’s nervous system. Pre-Covid epilepsy management is largely traditional with little advancement in smartwatches, apps like Apple smartwatches, Android apps, and more. expensive. Covid's new normal has led many to develop cost-effective digital health technology using existing smartphones with smartwatches built in. Epilepsy management systems can also be made affordable. We propose to take advantage of current advancements in smartwatches and smartphone apps by integrating them and adding new features such as video camera activation, photos and automation in sending alerts to, friends and care takers.
Optical Fiber Link Parameter Estimation: A Cascaded Neural Network Approach
Authors: Dhelawat Yuvi , Shukla Abhishek Mani , Gupta Sumanta 
Published: August 2022

Abstract

A multi-parameter estimation scheme for optical fiber link is proposed using deep learning (DL) technique. Instead of using a single model for multi-parameter estimation, a cascaded neural network architecture comprised of convolutional neural networks (CNN) is proposed, where the predicted value for each stage becomes an input parameter for the next stage. The proposed cascaded structure is employed for modulation format identification (MFI), optical signal-to-noise ratio (OSNR) estimation, and fibre link length estimation, in the same order. The input dataset used in this work consists of in-phase and quadrature (I/Q) currents as obtained from coherent detection. The proposed scheme needs no prior pre-processing steps, and the model can be deployed directly in the optical fiber transmission system. The OSNR and fibre link length estimation are treated as regression tasks, whereas MFI is treated as a classification task in our proposed cascaded model. The model attains 100% accuracy for MFI. Moreover, the mean absolute error (MAE) stands at 0.3246 dB for OSNR and 0.1140 km for fibre link length estimation. The model is also tested against intermediate values for fibre link lengths, which were not used during training. The MFI accuracy obtained for this case is 99.95% for QPSK and 100% for all other modulation schemes under consideration. The OSNR estimation has an MAE of 0.8945 dB, and the fibre link length estimation has an MAE of 0.854 km for the unseen values.
Mixed Culture Biocatalytic Production of the High-Value Biochemical 7-Methylxanthine
Authors: Mock Meredith B. , Summers Ryan M. 
Published: August 2022

Abstract
Background
7-Methylxanthine, a derivative of caffeine noted for its lack of toxicity and ability to treat and even prevent myopia progression, is a high-value biochemical with limited natural availability. Attempts to produce 7-methylxanthine through purely chemical methods of synthesis are faced with complicated chemical processes and/or the requirement of a variety of hazardous chemicals, resulting in low yields and racemic mixtures of products. In recent years, we have developed engineered microbial cells to produce several methylxanthines, including 3-methylxanthine, theobromine, and paraxanthine. The purpose of this study is to establish a more efficient biosynthetic process for the production of 7-methylxanthine from caffeine.
Results
Here, we describe the use of a mixed-culture system composed of Escherichia coli strains engineered as caffeine and theobromine “specialist” cells. Optimal reaction conditions for the maximal conversion of caffeine to 7-methylxanthine were determined to be equal concentrations of caffeine and theobromine specialist cells at an optical density (600 nm) of 50 reacted with 2.5 mM caffeine for 5 hours. When scaled-up to 560 mL, the simple biocatalytic reaction produced 183.81 mg 7-methylxanthine from 238.38 mg caffeine under ambient conditions, an 85.6% molar conversion. Following HPLC purification and solvent evaporation, 153.3 mg of dried 7-methylxanthine powder was collected, resulting in an 83.4% product recovery.
Conclusions
We present the first report of a biocatalytic process designed specifically for the production and purification of the high-value biochemical 7-methylxanthine from caffeine using a mixed culture of E. coli strains. This process constitutes the most efficient method for the production of 7-methylxanthine from caffeine to date.
A Road Network Simplification Algorithm that Preserves Topological Properties
Authors: Pung Jinyoung , D'Souza Raissa , Ghosal Dipak , Zhang Michael 
Published: August 2022

Abstract
A road network can be represented as a weighted directed graph with the nodes being the traffic intersections, the edges being the road segments, and the weights being some attribute of a road segment. Such a representation enables researchers to analyze road networks in consistent and automatable ways from the perspectives of graph theory. For example, analysis of the graph along with the traffic demand pattern can identify critical road segments based on centrality measures. However, due to the complexity of real-world road networks and the computationally expensive algorithms, it is challenging to extend the such methods to a large-scale road network. In this paper, we present a simple yet efficient network simplification framework based on graph theory that sub-samples and simplifies the graph while preserving key topological characteristics in the original network. Our method iteratively identifies and removes network elements that do not contribute to transportation functionality, such as self-loops, dead-ends, and interstitial nodes that lies on the same road line. We applied this method to three small cities with distinct street patterns and one large city, and showed that topological characteristics in the original networks are preserved by comparing two distinct kinds of centrality distributions in the original and simplified networks.