bluuebunny/crossref_metadata_2025 huggingface dataset:
Free-space combiner based on holographic mirrors for head-mounted displays
Authors: Solomashenko A. B. , Afanaseva O. L. , Markin V. V. , Kuznetsov A. S. , Lushnikov D. S.
Published: January 2024

The paper presents an augmented reality display based on the free-space combiner, consisting of two holographic mirrors: flat and spherical. A feature of such a system is a high-reflection coefficient of mirrors up to 90% for one wavelength and a high transmittance to the lumen up to 67% throughout the rest of the visible spectrum, unlike similar solutions implementing principles of polarization or dichroic beam splitting. The recording scheme and calculation of a separate flat holographic mirror and spherical holographic mirror are described. The proposed augmented reality display can provide multifocality, i.e., reproduction of virtual images at several distances, which demonstrates a certain perspective of this implementation in terms of compensation for the vergence accommodation conflict.
Birefringence characterization in a dual-hole microstructured optical fiber using an OFDR method
Authors: Meng Xin , Luo Mingming , Liu Jianfei , Zhao Shuai , Zhou Ran
Published: January 2024

The birefringence in a dual-hole microstructured optical fiber is numerically calculated and characterized with an optical frequency domain reflectometry (OFDR) method. Due to the asymmetric dual air holes in the cross-section, the polarized LP01
x
and LP01
y
modes propagate with different group velocities and time delays. Through a polarized coherent OFDR system in experiment, the Fresnel reflection peaks for each mode are separated in the frequency domain with their corresponding beat frequency. Thus, the group birefringence −9.68×10−4 is calculated with a beat frequency difference of 50.03 Hz between the LP01
x
and LP01
y
modes at a 6.2 m fiber end, which is in good agreement with that of −9.54×10−4 from the theoretical simulation. Our demonstration provides an accurate and flexible method for group birefringence characterization in microstructured optical fibers with complex cross-sectional structures.
Energy efficiency optimization in a parallel relay-assisted UWOC system with simultaneous lightwave information and power transfer
Authors: Li Gan , Shang Tao , Kong Wanqiu , Li Qian , Tang Tang
Published: January 2024

In this paper, we investigate the energy
efficiency optimization for a parallel relay-assisted underwater
wireless optical communication (UWOC) system with simultaneous
lightwave information and power transfer (SLIPT) over an aggregate
channel. In this system, relay nodes are equipped with energy
harvesting devices, getting energy from the direct current component
of the received signal transmitted by the source node. These nodes
utilize the harvested energy to transmit the signal to the destination
node with the decoding and forwarding strategy. The harvested energy
for each relay node is derived by the Gauss–Laguerre quadrature
formula and the outage probability is deduced by the Meijer-G
function. Then, the system’s energy efficiency can be calculated and
an energy efficiency maximization problem is built up with respect to
the bias current. We propose a three-level-iteration algorithm to
solve this problem. In the first level, the Dinkelbach method is used
to represent energy efficiency in a parametric subtractive form. In
the second level, we use the penalty function method to convert the
object function and constraint. In the third level, the objective
function is transformed into a quadratic function by using a
successive convex approximate method, thereby solving for the bias
current. The effects of system parameters on energy efficiency are
also analyzed. Theoretical results and Monte Carlo simulations suggest
that employing the solved bias current can significantly improve the
system’s energy efficiency.
Biofilm formation and manipulation with optical tweezers
Authors: Camba Czarlyn , Walter-Lakes Brooke , Digal Phillip , Taheri-Araghi Sattar , Bezryadina Anna
Published: January 2024

Some bacterial species form biofilms in suboptimal growth and environmental conditions. Biofilm structures allow the cells not only to optimize growth with nutrient availability but also to defend each other against external stress, such as antibiotics. Medical and bioengineering implications of biofilms have led to an increased interest in the regulation of bacterial biofilm formation. Prior research has primarily focused on mechanical and chemical approaches for stimulating and controlling biofilm formation, yet optical techniques are still largely unexplored. In this paper, we investigate the biofilm formation of Bacillus subtilis in a minimum biofilm-promoting medium (MSgg media) and explore the potential of optical trapping in regulating bacterial aggregation and biofilm development. Specifically, we determine the most advantageous stage of bacterial biofilm formation for optical manipulation and investigate the impact of optical trapping at different wavelengths on the aggregation of bacterial cells and the formation of biofilm. The investigation of optically regulated biofilm formation with optical tweezers presents innovative methodologies for the stimulation and suppression of biofilm growth through the application of lasers.
Coherent full microwave scattering formulation for random layered media
Authors: Calzetta Esteban , Franco Mariano
Published: January 2024

We present a fully coherent, analytic model of the backscattering intensity in all HH,HV,VH, and VV channels, for the volume scattering
of radiation from a layer of finite thickness, such as a vegetation
layer over bare soil. We aim for a simple, not numerically intensive,
model that could be used either as a forward model in a Bayesian
estimation scheme, or else as a preliminary means to identify key
features of a concrete problem, for its further analysis by more
sophisticated theoretical and numerical approaches.
Broadband continuous-wave differential absorption lidar for atmospheric remote sensing of water vapor
Authors: Yu Jiheng , Cheng Yuan , Kong Zheng , Song Jiaming , Chang Yupeng , Liu Kun , Gong Zhenfeng , Mei Liang
Published: January 2024

What we believe to be a novel low-cost broadband continuous-wave water vapor differential absorption lidar (CW-DIAL) technique has been proposed and implemented by combing the Scheimpflug principle and the differential absorption method. The broadband CW-DIAL technique utilizes an 830-nm high-power multimode laser diode with 3-W output power as a tunable light source and a CMOS image sensor tilted at 45° as the detector. A retrieval algorithm dedicated for the broadband CW-DIAL technique has been developed to obtain range-resolved water vapor concentration from the DIAL signal. Atmospheric remote sensing of water vapor has been carried out on a near-horizontal water vapor path to validate the performance of the broadband CW-DIAL system. The retrieved water vapor concentration showed a good consistency with those measured by an air quality monitoring station, with a correlation coefficient of 0.9669. The fitting error of the water vapor concentration is found to be less than 10%. Numerical simulation studies have revealed that the aerosol-induced error on the water vapor concentration is below 5% with a background water vapor concentration of 5 g/m3 for most atmospheric conditions. The experimental results have successfully demonstrated the feasibility of the present broadband CW-DIAL technique for range-resolved water vapor remote sensing.
Reliable image dehazing by NeRF
Authors: Jin Zheyan , Xu Zhihai , Feng Huajun , Li Qi , Chen Yueting
Published: January 2024

Image dehazing is a typical low-level visual task. With the continuous improvement of network performance and the introduction of various prior knowledge, the ability of image dehazing is becoming stronger. However, the existing dehazing methods have problems such as the inability to obtain real shooting datasets, unreliable dehazing processes, and the difficulty to deal with complex lighting scenes. To solve these problems, we propose a new haze model combining the optical scattering model and the computer graphics rendering. Based on the new haze model, we propose a high-quality and widely applicable dehazing dataset generation pipeline that does not require paired-data training and prior knowledge. We reconstruct the three-dimensional fog space with array camera and remove haze by thresholding voxel deletion. We use the Unreal Engine 5 to generate simulation datasets and the real shooting in laboratory to verify the effectiveness and the reliability of our generation pipeline. Through our pipeline, we can obtain wonderful dehaze results and dehaze datasets under various complex outdoors lighting conditions. We also propose a dehaze dataset enhancement method based on voxel control. Our pipeline and data enhancement are suitable for the latest algorithm model, these solutions can obtain better visual effects and objective indicators.
The study of computational ghost imaging in presence of atmospheric turbulence
Authors: Soleimani Parisa , Kheradmand Reza , Kandjani Sohrab Ahmadi
Published: January 2024

The influence of atmospheric turbulence is investigated on computational ghost imaging (CGI). The results indicate that turbulence disrupts the resolution of computational ghost imaging, necessitating an alternative high-resolution imaging strategy. The Differential Computational ghost imaging (DCGI) are used to mitigate its impact. DCGI substantially enhances imaging resolution through engineered structured illumination. Furthermore, the DCGI scheme exhibits adaptability under atmospheric turbulence, facilitating real-time non-imaging edge detection in practical scenarios. The experimental and theoretical findings highlight the impact of atmospheric turbulence on imaging resolution and underscore DCGI's resilience to such effects where the computational ghost imaing unable to achieve a good quality of image. The DCGI is used in turbulent mediume and shows that the resolution of image in contrast to the CGI is very high.
Cell size homeostasis is tightly controlled throughout the cell cycle
Authors: Liu Xili , Yan Jiawei , Kirschner Marc W.
Published: January 2024

To achieve a stable size distribution over multiple generations, proliferating cells require a means of counteracting stochastic noise in the rate of growth, the time spent in various phases of the cell cycle, and the imprecision in the placement of the plane of cell division. In the most widely accepted model, cell size is thought to be regulated at the G1/S transition, such that cells smaller than a critical size pause at the end of G1 phase until they have accumulated mass to a predetermined size threshold, at which point the cells proceed through the rest of the cell cycle. However, a model, based solely on a specific size checkpoint at G1/S, cannot readily explain why cells with deficient G1/S control mechanisms are still able to maintain a very stable cell size distribution. Furthermore, such a model would not easily account for stochastic variation in cell size during the subsequent phases of the cell cycle, which cannot be anticipated at G1/S. To address such questions, we applied computationally enhanced quantitative phase microscopy (ceQPM) to populations of cultured human cell lines, which enables highly accurate measurement of cell dry mass of individual cells throughout the cell cycle. From these measurements, we have evaluated the factors that contribute to maintaining cell mass homeostasis at any point in the cell cycle. Our findings reveal that cell mass homeostasis is accurately maintained, despite disruptions to the normal G1/S machinery or perturbations in the rate of cell growth. Control of cell mass is generally not confined to regulation of the G1 length. Instead mass homeostasis is imposed throughout the cell cycle. In the cell lines examined, we find that the coefficient of variation (CV) in dry mass of cells in the population begins to decline well before the G1/S transition and continues to decline throughout S and G2 phases. Among the different cell types tested, the detailed response of cell growth rate to cell mass differs. However, in general, when it falls below that for exponential growth, the natural increase in the CV of cell mass is effectively constrained. We find that both mass-dependent cell cycle regulation and mass-dependent growth rate modulation contribute to reducing cell mass variation within the population. Through the interplay and coordination of these 2 processes, accurate cell mass homeostasis emerges. Such findings reveal previously unappreciated and very general principles of cell size control in proliferating cells. These same regulatory processes might also be operative in terminally differentiated cells. Further quantitative dynamical studies should lead to a better understanding of the underlying molecular mechanisms of cell size control.
Harnessing the flexibility of neural networks to predict dynamic theoretical parameters underlying human choice behavior
Authors: Ger Yoav , Nachmani Eliya , Wolf Lior , Shahar Nitzan
Published: January 2024

Reinforcement learning (RL) models are used extensively to study human behavior. These rely on normative models of behavior and stress interpretability over predictive capabilities. More recently, neural network models have emerged as a descriptive modeling paradigm that is capable of high predictive power yet with limited interpretability. Here, we seek to augment the expressiveness of theoretical RL models with the high flexibility and predictive power of neural networks. We introduce a novel framework, which we term theoretical-RNN (t-RNN), whereby a recurrent neural network is trained to predict trial-by-trial behavior and to infer theoretical RL parameters using artificial data of RL agents performing a two-armed bandit task. In three studies, we then examined the use of our approach to dynamically predict unseen behavior along with time-varying theoretical RL parameters. We first validate our approach using synthetic data with known RL parameters. Next, as a proof-of-concept, we applied our framework to two independent datasets of humans performing the same task. In the first dataset, we describe differences in theoretical RL parameters dynamic among clinical psychiatric vs. healthy controls. In the second dataset, we show that the exploration strategies of humans varied dynamically in response to task phase and difficulty. For all analyses, we found better performance in the prediction of actions for t-RNN compared to the stationary maximum-likelihood RL method. We discuss the use of neural networks to facilitate the estimation of latent RL parameters underlying choice behavior.
Explaining the flaws in human random generation as local sampling with momentum
Authors: Castillo Lucas , León-Villagrá Pablo , Chater Nick , Sanborn Adam
Published: January 2024

In many tasks, human behavior is far noisier than is optimal. Yet when asked to behave randomly, people are typically too predictable. We argue that these apparently contrasting observations have the same origin: the operation of a general-purpose local sampling algorithm for probabilistic inference. This account makes distinctive predictions regarding random sequence generation, not predicted by previous accounts—which suggests that randomness is produced by inhibition of habitual behavior, striving for unpredictability. We verify these predictions in two experiments: people show the same deviations from randomness when randomly generating from non-uniform or recently-learned distributions. In addition, our data show a novel signature behavior, that people’s sequences have too few changes of trajectory, which argues against the specific local sampling algorithms that have been proposed in past work with other tasks. Using computational modeling, we show that local sampling where direction is maintained across trials best explains our data, which suggests it may be used in other tasks too. While local sampling has previously explained why people are unpredictable in standard cognitive tasks, here it also explains why human random sequences are not unpredictable enough.
sc2MeNetDrug: A computational tool to uncover inter-cell signaling targets and identify relevant drugs based on single cell RNA-seq data
Authors: Feng Jiarui , Goedegebuure S. Peter , Zeng Amanda , Bi Ye , Wang Ting , Payne Philip , Ding Li , DeNardo David , Hawkins William , Fields Ryan C. , Li Fuhai
Published: January 2024

Single-cell RNA sequencing (scRNA-seq) is a powerful technology to investigate the transcriptional programs in stromal, immune, and disease cells, like tumor cells or neurons within the Alzheimer’s Disease (AD) brain or tumor microenvironment (ME) or niche. Cell-cell communications within ME play important roles in disease progression and immunotherapy response and are novel and critical therapeutic targets. Though many tools of scRNA-seq analysis have been developed to investigate the heterogeneity and sub-populations of cells, few were designed for uncovering cell-cell communications of ME and predicting the potentially effective drugs to inhibit the communications. Moreover, the data analysis processes of discovering signaling communication networks and effective drugs using scRNA-seq data are complex and involve a set of critical analysis processes and external supportive data resources, which are difficult for researchers who have no strong computational background and training in scRNA-seq data analysis. To address these challenges, in this study, we developed a novel open-source computational tool, sc2MeNetDrug (https://fuhaililab.github.io/sc2MeNetDrug/). It was specifically designed using scRNA-seq data to identify cell types within disease MEs, uncover the dysfunctional signaling pathways within individual cell types and interactions among different cell types, and predict effective drugs that can potentially disrupt cell-cell signaling communications. sc2MeNetDrug provided a user-friendly graphical user interface to encapsulate the data analysis modules, which can facilitate the scRNA-seq data-based discovery of novel inter-cell signaling communications and novel therapeutic regimens.
Rapid detection of drug-resistant Mycobacterium tuberculosis by Modified MODS assay suitable for resource-poor settings
Authors: Fomda Bashir Ahamd , Bashir Gulnaz , Baqal Sehrish , Mir Yaawar Bashir , Ali Rehana , Khan Altaf Hussain , Khan Asiya , Bashir Anis , Chuloo G. M.
Published: January 2024

Background

Cross contamination and biosafety are concerns with the microscopic observation drug susceptibility assay. To address these issues, we modified the MODS technique in the current study.

Methodology/Principal findings

Two hundred and seventy-five samples were processed on LJ media and drug susceptibility was performed by the Indirect agar proportion method. A modified MODS test was done in tissue culture bottles. GenoType MTBDRplus assay was performed to detect the resistance and mutational pattern associated with the resistances. Sensitivity, specificity, positive predictive value, and negative predictive value for the detection of tuberculosis by modified MODS were 97.44%, 80.00%, 97.44%, and 80.00% respectively. The perfect agreement was seen between modified MODS and the Indirect agar proportion method for drug susceptibility testing of isoniazid (kappa = 0.923) and rifampicin (kappa = 1). The contamination rate, cost and TAT for modified MODS were less as compared to the solid media.

In the case of MDR-TB isolates S531L (66.66%) was the most prevalent mutation in the rpoB gene followed by S315T2 mutation (58.33%) and T8C (41.66%) in katG and inhA gene respectively. In hetero-resistant strains, C-15T mutation (37.50%) was the most common followed by A-16G (12.50%) in the inhA gene. In INH mono-resistant strains only two mutations were observed i.e., S-315T1(50%) and C-15T (50%) in the katG and inhA genes respectively.

Conclusions/Significance

Modified MODS proved to be cost-effective and user-friendly, with minimal risk to the handler and no cross-contamination between samples were observed. Hence, it can be used in low-income countries for early detection of tuberculosis and its resistance.
Cytotaxonomic characterization and estimation of migration patterns of onchocerciasis vectors (Simulium damnosum sensu lato) in northwestern Ethiopia based on RADSeq data
Authors: Hedtke Shannon M. , Post Rory J. , Feleke Sindew Mekasha , Gebretsadik Fikre Seife , Boakye Daniel A. , Krueger Andreas , Grant Warwick N. , Wilding Craig S.
Published: January 2024

Background

While much progress has been made in the control and elimination of onchocerciasis across Africa, the extent to which vector migration might confound progress towards elimination or result in re-establishment of endemism in areas where transmission has been eliminated remains unclear. In Northern Ethiopia, Metema and Metekel—two foci located near the Sudan border—exhibit continuing transmission. While progress towards elimination has been faster in Metema, there remains a problematic hotspot of transmission. Whether migration from Metekel contributes to this is currently unknown.

Methodology/Principle findings

To assess the role of vector migration from Metekel into Metema, we present a population genomics study of 151 adult female vectors using 47,638 RADseq markers and mtDNA CoI sequencing. From additional cytotaxonomy data we identified a new cytoform in Metema, closely related to S. damnosum s.str, here called the Gondar form. RADseq data strongly indicate the existence of two distinctly differentiated clusters within S. damnosum s.l.: one genotypic cluster found only in Metema, and the second found predominantly in Metekel. Because blackflies from both clusters were found in sympatry (in all four collection sites in Metema), but hybrid genotypes were not detected, there may be reproductive barriers preventing interbreeding. The dominant genotype in Metema was not found in Metekel while the dominant genotype in Metekel was found in Metema, indicating that (at the time of sampling) migration is primarily unidirectional, with flies moving from Metekel to Metema. There was strong differentiation between clusters but little genetic differentiation within clusters, suggesting migration and gene flow of flies within the same genetic cluster are sufficient to prevent genetic divergence between sites.

Conclusions/Significance

Our results confirm that Metekel and Metema represent different transmission foci, but also indicate a northward movement of vectors between foci that may have epidemiological importance, although its significance requires further study.
A single-armed proof-of-concept study of Lymfit: A personalized, virtual exercise intervention to improve health outcomes in lymphoma survivors in the pandemic
Authors: Angelillo Christopher , Tock Wing Lam , Salaciak Matthew , Reid Ryan E. R. , Andersen Ross E. , Maheu Christine , Johnson Nathalie A.
Published: January 2024

Background and objective

Treatments of lymphoma can lead to reduced physical functioning, cancer-related fatigue, depression, anxiety, and insomnia. These side effects can negatively impact the cancer survivor’s quality of life. Mounting evidence indicates that physical activities are highly therapeutic in mitigating the short- and long-term side effects of cancer treatments. Yet, lymphoma survivors’ participation in physical activities remains suboptimal, which has been further exacerbated by the deleterious effects of isolation during the COVID-19 pandemic. TheLymfitintervention aims to offer motivational support, expert guidance, and a personalized exercise prescription to optimize physical activities among lymphoma survivors. This proof-of-concept study explores implementation feasibility (retention, technical and safety), and the preliminary effects ofLymfiton various health outcomes.

Method

This was a single-armed trial with a pre-and post-test design. Twenty lymphoma survivors were recruited to participate in the 12-weekLymfitintervention. Wearable activity trackers (Fitbit) were given to participants as a motivational tool and for data collection purposes. Participants received a personalized exercise prescription designed by a kinesiologist. Physiologic metrics were collected by the Fitbit monitors and were stored in theLymfitdatabase. Self-reported questionnaires measuring health outcomes were collected at baseline and post-intervention.

Results

The retention rate of this trial was 70%. Minimal technical issues and no adverse effects were reported.Lymfitled to significant improvements in sleep disturbances and the ability to participate in social activities and decreased fear of cancer recurrence. It also increased daily steps and decreased sedentary time in participants who did not meet the recommended physical activity guidelines.

Significance

With access to resources and fitness centers being limited during the pandemic, theLymfitintervention filled an immediate need to provide physical activity guidance to lymphoma survivors. Findings provide preliminary support that implementing theLymfitintervention is feasible and demonstrated promising results.
Effect of non-invasive neuromodulation techniques on vascular cognitive impairment: A Bayesian network meta-analysis protocol
Authors: Yan Long , Wu Linna , Li Hong , Qian Yulin , Wang Meng , Wang Yu , Dou Baomin , Yu Tao
Published: January 2024

Background

VCI is a severe public health problem facing the world today. In addition to pharmacological treatment, non-invasive neuromodulation techniques have also been effective. At this stage, non-invasive neuromodulation techniques combined with pharmacological treatment are the mainstay of clinical treatment, and clinical trials are continuing to be conducted, which is becoming the direction of treatment for VCI. Therefore, we outline this systematic review and network meta-analysis protocol to evaluate and rank clinical data in future studies which can develop optimal protocols for the clinical treatment of VCI with non-invasive neuromodulation techniques in combination with drugs.

Methods

The network meta-analysis will search eight databases, including PubMed, Embase, Cochrane Library, Web of Science, China Knowledge Infrastructure Library (CNKI), China Biology Medicine disc (CBM)), Wanfang Data Knowledge Service Platform and Vipshop Journal Service Platform (VIP), for a period of from the establishment of the library to January 30 2022. The quality of the studies will be evaluated using the Cochrane Review’s Handbook 5.1 and the PEDro scale to assess the evidence and quality of the included randomised controlled trials. Risk of bias assessment and heterogeneity tests will be performed using the Review Manager 5.4 program, and Bayesian network meta-analysis will be performed using the Stata 16.0 and WinBUGS 1.4.3 program.

Results

The results of the network meta-analysis will be published in a peer-reviewed journal.

Conclusions

Our study is expected to provide high quality evidence-based medical evidence for the treatment of VCI by clinicians.

Trial registration

PROSPERO: CRD42022308580.
TUBER: Time-aware UAV-based energy-efficient reconfigurable routing scheme for smart wireless livestock sensor network
Authors: Bouchekara Houssem R. E. H. , Salami Abdulazeez F. , Sha’aban Yusuf A. , Nahas Mouaaz , Shahriar Mohammad S. , Alanezi Mohammed A.
Published: January 2024

This paper is a follow-up to a recent work by the authors on recoverable UAV-based energy-efficient reconfigurable routing (RUBER) scheme for addressing sensor node and route failure issues in smart wireless livestock sensor networks. Time complexity and processing cost issues connected to the RUBER scheme are consequently treated in this article by proffering a time-aware UAV-based energy-efficient reconfigurable routing (TUBER) scheme. TUBER scheme employs a synchronized clustering-with-backup strategy, a minimum-hop neighborhood recovery mechanism, and a redundancy minimization technique. Comparative network performance of TUBER was investigated and evaluated with respect to RUBER and UAV-based energy-efficient reconfigurable routing (UBER) schemes. The metrics adopted for this comparative performance analysis are Cluster Survival Ratio (CSR), Network Stability (NST), Energy Dissipation Ratio (EDR), Network Coverage (COV), Packet Delivery Ratio (PDR), Fault Tolerance Index (FTI), Load Balancing Ratio (LBR), Routing Overhead (ROH), Average Routing Delay (ARD), Failure Detection Ratio (FDR), and Failure Recovery Ratio (FRR). With reference to best-obtained values, TUBER demonstrated improvements of 36.25%, 24.81%, 34.53%, 15.65%, 38.32%, 61.07%, 31.66%, 63.20%, 68.96%, 66.19%, and 78.63% over RUBER and UBER in terms of CSR, NST, EDR, COV, PDR, FTI, LBR, ROH, ARD, FDR, and FRR, respectively. These experimental results confirmed the relative effectiveness of TUBER against the compared routing schemes.
A parallel Canny edge detection algorithm based on OpenCL acceleration
Authors: Song Yupu , Li Cailin , Xiao Shiyang , Zhou Qinglei , Xiao Han
Published: January 2024

In the process of Canny edge detection, a large number of high complexity calculations such as Gaussian filtering, gradient calculation, non-maximum suppression, and double threshold judgment need to be performed on the image, which takes up a lot of operation time, which is a great challenge to the real-time requirements of the algorithm. The traditional Canny edge detection technology mainly uses customized equipment such as DSP and FPGA, but it has some problems, such as long development cycle, difficult debugging, resource consumption, and so on. At the same time, the adopted CUDA platform has the problem of poor cross-platform. In order to solve this problem, a fine-grained parallel Canny edge detection method is proposed, which is optimized from three aspects: task partition, vector memory access, and NDRange optimization, and CPU-GPU collaborative parallelism is realized. At the same time, the parallel Canny edge detection methods based on multi-core CPU and CUDA architecture are designed. The experimental results show that OpenCL accelerated Canny edge detection algorithm (OCL_Canny) achieves 20.68 times acceleration ratio compared with CPU serial algorithm at 7452 × 8024 image resolution. At the image resolution of 3500 × 3500, the OCL_Canny algorithm achieves 3.96 times the acceleration ratio compared with the CPU multi-threaded Canny parallel algorithm. At 1024 × 1024 image resolution, the OCL_Canny algorithm achieves 1.21 times the acceleration ratio compared with the CUDA-based Canny parallel algorithm. The effectiveness and performance portability of the proposed Canny edge detection parallel algorithm are verified, and it provides a reference for the research of fast calculation of image big data.
Research on military-civilian collaborative innovation of science and technology based on a stochastic differential game model
Authors: Liang Xin , Liang Yunjuan , Kang Weijia , Wei Hua
Published: January 2024

The construction of an integrated national strategic system and capability is an essential goal of implementing the strategy of military-civilian integration in the contemporary era. And the collaborative innovation of military-civilian S&T is an inevitable choice to achieve this goal. Due to the dynamic, complex, and stochastic characteristics of military-civilian S&T collaborative innovation, the level of S&T innovation is highly volatile. This paper takes the internal and external stochastic disturbance factors of military-civilian S&T collaborative innovation as the perspective, studies the strategy selection problem of military-civilian S&T collaborative innovation under military domination, constructs a differential game model to explore the innovation strategies under the non-cooperative model without military subsidies, the non-cooperative model with military subsidies, and the collaborative model. Finally, we use numerical experiments to verify the validity of the conclusions. The study shows that: (1) Within a reasonable range of values of the benefit distribution coefficient, the system can achieve the Pareto optimum, and the collaborative model is conducive to improving the S&T innovation level and the optimum benefit level of the system. (2) Military subsidies can increase the benefits of the system and the parties involved to achieve Pareto improvement. (3) The level of S&T innovation under the collaborative model has dynamic evolutionary characteristics of maximum expectation and variance. As the intensity of disturbance increases, the stability of the system may be destroyed. Risk-averse civil enterprises prefer the cooperative mode, whereas risk-averse civil enterprises prefer the non-cooperative model.
Integrated bioinformatics analysis and experimental validation identified CDCA families as prognostic biomarkers and sensitive indicators for rapamycin treatment of glioma
Authors: Li Ren , Chen Yang , Yang Biao , Li Ziao , Wang Shule , He Jianhang , Zhou Zihan , Li Xuepeng , Li Jiayu , Sun Yanqi , Guo Xiaolong , Wang Xiaogang , Wu Yongqiang , Zhang Wenju , Guo Geng
Published: January 2024

The cell division cycle associated (CDCA) genes regulate the cell cycle; however, their relationship with prognosis in glioma has been poorly reported in the literature. The Cancer Genome Atlas (TCGA) was utilized to probe the CDCA family in relation to the adverse clinical features of glioma. Glioma single-cell atlas reveals specific expression of CDCA3, 4, 5, 8 in malignant cells and CDCA7 in neural progenitor cells (NPC)-like malignant cells. Glioma data from TCGA, the China Glioma Genome Atlas Project (CGGA) and the gene expression omnibus (GEO) database all demonstrated that CDCA2, 3, 4, 5, 7 and 8 are prognostic markers for glioma. Further analysis identified CDCA2, 5 and 8 as independent prognostic factors for glioma. Lasso regression-based risk models for CDCA families demonstrated that high-risk patients were characterized by high tumor mutational burden (TMB), low levels of microsatellite instability (MSI), and low tumor immune dysfunction and rejection (TIDE) scores. These pointed to immunotherapy for glioma as a potentially viable treatment option Further CDCA clustering suggested that the high CDCA subtype exhibited a high macrophage phenotype and was associated with a higher antigen presentation capacity and high levels of immune escape. In addition, hsa-mir-15b-5p was predicted to be common regulator of CDCA3 and CDCA4, which was validated in U87 and U251 cells. Importantly, we found that CDCAs may indicate response to drug treatment, especially rapamycin, in glioma. In summary, our results suggest that CDCAs have potential applications in clinical diagnosis and as drug sensitivity markers in glioma.
Community-based rehabilitation/community based inclusive development functioning during the COVID-19 pandemic: A secondary analysis of qualitative data
Authors: Ahmed Ansha Nega , Nuri Reshma Parvin , Xu Xiaolin , Balakrishna Venkatesh , Sebeh Alaa , Maholo Carolyne , Aldersey Heather Michelle
Published: January 2024

Introduction

The coronavirus (COVID-19) became a global pandemic in March 2020 and impacted nations worldwide not only because of the disease but also because the containment measures-imposed created ripple effects for the populations in each country. The COVID-19 pandemic disproportionately affected vulnerable groups, such as persons with disabilities. This study aimed to understand the impact of COVID-19 on the function of Community-Based Rehabilitation (CBR)/Community-Based Inclusive Development (CBID) across nations and for their target communities—persons with disabilities. The current article also described some measures CBR/CBID programs took in light of service closure to facilitate access to needed services for persons with disabilities.

Methods

We conducted a secondary analysis of qualitative data to understand the impact of COVID-19 on the functioning of CBR/CBID programs and their target communities. The original qualitative data were collected through online dialogues among CBR/CBID partners across five regions of the world, facilitated for understanding of their practices on five other topics.

Findings

COVID-19 significantly impacted the function of CBR/CBID programs across the world. Many services were halted due to public health measures, such as maintaining social distancing or lockdowns. The COVID-19 pandemic also had a negative impact on access to health, education and livelihood support for persons with disabilities. Additionally, many people with disabilities did not have access to COVID-19 related information and services like vaccines. However, we found that technology played a significant role in revitalizing CBR/CBID programs during COVID-19. CBR/CBID service providers across five regions used online platforms to disseminate information about COVID-19. Professionals also used technology to provide rehabilitation and educational services to people with disabilities through online platforms.

Conclusion

Our findings suggest that technology can play a vital role in continuing many services (e.g., CBR/CBID) that cannot be offered in person during crises like COVID-19. However, it is important to remember that technology may not be accessible to many individuals with disabilities, specifically those who reside in rural areas and who experience adverse situations like financial constraints. Additionally, many persons with disabilities may not have the necessary knowledge and skills to use technology. CBR personnel must consider that before adopting technology to provide services under CBR programs.
Post COVID-19 condition among adults in Malaysia following the Omicron wave: A prospective cohort study
Authors: Tok Peter Seah Keng , Kang Kong Yeow , Ng Sock Wen , Ab Rahman Norazida , Syahmi Muhammad Aminul , Pathmanathan Mohan Dass , Appannan Maheshwara Rao , Peariasamy Kalaiarasu M. , Sivasampu Sheamini
Published: January 2024

Post COVID-19 condition is an important public health problem as we emerge from the COVID-19 pandemic. In this prospective cohort study, we aimed to determine the prevalence of this condition and assess its associated factors and impact on health-related quality of life in a population setting in Malaysia. Study was conducted from April to June 2022 when the Omicron variant predominated. All individuals testing positive for SARS-CoV-2 infection (RT-PCR, RTK-Ag) were invited for participation. Study questionnaires were delivered via the MySejahtera platform (mobile application). From the total of 44,386 participants who provided responses up to 3-months interval, 1,510 participants (3.4%) fulfilled the post COVID-19 condition criteria. Majority of the affected participants (83.8%, n = 1,265) experienced either cough, fatigue or forgetfulness–the three most common symptoms. Being females, having existing comorbidities, presence of symptoms and requiring hospital admission during the acute illness were associated with higher likelihoods of developing the post COVID-19 condition at 3-months interval. Amongst the 1,510 individuals, one in five had limitations in performing their usual daily activities while at least one in three expressed that their work was affected. Understanding this condition better is essential to guide strategic and responsive plans of action, which may require coordinated multidisciplinary interventions.
Association of Kawasaki disease with urbanization level and family characteristics in Taiwan: A nested case–control study using national-level data
Authors: Tseng Chung-Fang , Lin Hsiao-Chen , Tzeng Chung-Yuh , Huang Jing-Yang , Yeh Chih-Jung , Wei James Cheng-Chung
Published: January 2024

Kawasaki disease (KD) is an inflammatory vasculitis disorder of unknown etiology. It is a rare but fatal disease and the leading cause of acquired coronary heart disease in children under the age of 5 years. We examined the association of KD with the demographics of family members, parents’ characteristics, and perinatal factors in Taiwanese children. This nested case–control study used data from Taiwan’s Health and Welfare Data Science Center and initially included children born in Taiwan between January 1, 2006, and December 31, 2015 (n = 1,939,449); the children were observed for KD development before the age of 5 years (n = 7870). The control group consisted of children without KD who were matched with each KD case by sex and birth date at a ratio of 8:1. The odds ratio (ORs) of the aforementioned associations were estimated using conditional logistic regression. The risk of KD decreased in children with younger parents [<25 years; younger maternal age, OR = 0.72, 95% confidence interval (CI), 0.66–0.79; younger paternal age, OR = 0.68, 95% CI, 0.59–0.78], lower socioeconomic status, more than 2 siblings (OR = 0.80, 95% CI, 0.73–0.89), and siblings with a history of KD (OR = 4.39, 95% CI, 3.29–5.86). Children living in suburban (OR = 0.95, 95% CI, 0.90–1.00) and rural (OR = 0.81, 95%CI, 0.74–0.90) areas exhibited a lower risk of KD than children living in urban areas. In conclusion, a higher incidence rate of KD was observed in children aged <5 years who had an urban lifestyle, had siblings with KD, were born to older mothers, and belonged to high-income and smaller families. Parental allergic or autoimmune diseases were not associated with the risk of KD.
Endorsement of COVID-19 misinformation among criminal legal involved individuals in the United States: Prevalence and relationship with information sources
Authors: Zhao Xiaoquan , Hingle Aayushi , Shaw Cameron C. , Murphy Amy , Riddick Breonna R. , Davidson Mhonde Rochelle R. , Taylor Bruce G. , Lamuda Phoebe A. , Pollack Harold A. , Schneider John A. , Taxman Faye S.
Published: January 2024

Criminal legal system involvement (CLI) is a critical social determinant of health that lies at the intersection of multiple sources of health disparities. The COVID-19 pandemic exacerbates many of these disparities, and specific vulnerabilities faced by the CLI population. This study investigated the prevalence of COVID-19-related misinformation, as well as its relationship with COVID-19 information sources used among Americans experiencing CLI. A nationally representative sample of American adults aged 18+ (N = 1,161), including a subsample of CLI individuals (n = 168), were surveyed in February-March 2021. On a 10-item test, CLI participants endorsed a greater number of misinformation statements (M = 1.88 vs. 1.27) than non-CLI participants, p < .001. CLI participants reported less use of government and scientific sources (p = .017) and less use of personal sources (p = .003) for COVID-19 information than non-CLI participants. Poisson models showed that use of government and scientific sources was negatively associated with misinformation endorsement for non-CLI participants (IRR = .841, p < .001), but not for CLI participants (IRR = .957, p = .619). These findings suggest that building and leveraging trust in important information sources are critical to the containment and mitigation of COVID-19-related misinformation in the CLI population.
Decoding the interface: Exploring women's perspectives on integrating AI in professional work
Authors: Woźniak-Jęchorek Beata , Rydzak Waldemar , Kuźmar Sławomir
Published: January 2024

AI's impact on jobs varies by gender, with women facing higher replacement risks. This discrepancy is intensified by the digital divide, insufficient knowledge and skills, and a less open attitude towards AI among women, thereby limiting women's access to AI-driven opportunities. This paper's primary objective is to scrutinize women's self-assessment of digital competencies when utilizing AI in professional settings. Drawing from a survey conducted among Polish women, our findings reveal that the adoption of AI is linked to factors such as age, education, work experience, and location of residence. Women with higher levels of education residing in larger cities, as well as younger individuals with less work experience, are more likely to recognize the advantages of utilizing AI. Their concerns are less about the necessity for continuous development of digital skills, but rather about the potential impact of AI on their work-life balance and the possibility of a decrease in earnings, despite the anticipated improvements in productivity and time management efficiency.
Combretastatina-A1 e derivados: estudo teórico das propriedades ópticas não lineares
Authors: B. S. Costa Marconi
Published: January 2024

Através de cálculos de estrutura eletrônica, foram investigadas as propriedades ópticas não lineares, isto é, a primeira (β) e a segunda (γ) hiperpolarizabilidade, do fármaco natural antitumoral Combretastatina-A1 e derivados. Os resultados mostram que é possível incrementar as magnitudes das hiperpolarizabilidades da Combretastatina-A1 pela introdução de artifícios que levam a mudanças em sua estrutura (derivados). O uso de grupos doadores-receptores de elétrons e pontes insaturadas (ricas em elétrons π) constitui uma estratégia promissora. A análise quimiométrica de parâmetros estruturais e eletrônicos demonstra não haver relação direta entre as propriedades ópticas não lineares e a atividade biológica da Combretastatina-A1.
A New Ehrlich-Type Sixth-Order Simultaneous Method for Polynomial Complex Zeros
Authors: Guerreiro Lopes Luiz , Neves Machado Roselaine
Published: January 2024

This paper presents a new iterative method for the simultaneous determination of simple polynomial zeros. The proposed method is obtained from the combination of the third-order Ehrlich iteration with an iterative correction derived from Li's fourth-order method for solving nonlinear equations. The combined method developed has order of convergence six. Some examples are presented to illustrate the convergence and efficiency of the proposed Ehrlich-type method with Li correction for the simultaneous approximation of polynomial zeros.
Continuing Medical Education Questions: January 2024
Authors: Karna Rahul
Published: January 2024

Article Title: ACG Clinical Guideline—Alcohol-Associated Liver Disease
Exploring Sustainability Challenges of Government-Funded Community Projects in South Africa
Authors: Tobela Nota Gladstone Phillip , Hoque Muhammad , Ehsanul Muhammad
Published: January 2024

In recent times, the sustainability of government-funded community projects has emerged as a significant concern for both governmental entities and donors. The objective of this study was to investigate the sustainability obstacles faced by the Peach Value Addition Cooperative project in the Eastern Cape Province of South Africa. The research was conducted using a qualitative technique and under an interpretivist paradigm. A purposive sampling strategy was employed to select ten senior managers from cooperatives who have a minimum of five years of professional experience. Thematic analysis was conducted on the data. The study's findings revealed that the Peach Value Addition Cooperative project encountered difficulties related to funding and financial matters. Additionally, the cooperative faced challenges stemming from a low market demand for their products. The study also identified issues within the cooperative's leadership, including instances of nepotism, favouritism, patronage, and corruption. Furthermore, the cooperative experienced high rates of absenteeism and exhibited selective application of consequences for cooperative members who committed offences. The study's results also confirmed that leadership deficiencies, unethical behaviours, inadequate financial management, lack of skills, and ineffective governance were identified as key concerns impacting the long-term viability of the Peach Value Addition Cooperative project. The study suggests that the implementation of effective governance practices, including the eradication of corruption, fraud, favouritism, and nepotism, the establishment of checks and balances to mitigate authoritarianism, the development of a transparent succession plan, and the adoption of a comprehensive code of ethics and code of conduct, are strategies that would contribute to the long-term viability of the Peach Value Addition Cooperative project in the Umzimvubu area.