Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of delayed antiretroviral therapy initiation among people living with HIV: A systematic review and meta-analysis

Objective HIV continues to be a global challenge. Key recommendations for HIV prevention and treatment are presented on rapid antiretroviral therapy (ART) initiation. However, several studies showed a high prevalence of delayed ART initiation. The aim of this systematic review and meta-analysis was to assess the prevalence of delayed ART initiation among HIV-infected patients globally. Methods This review summarised eligible studies conducted between January 2015 and August 2022 on the prevalence of delayed ART initiation in HIV-infected adults (age ≥ 15). Relevant studies were systematic searched through PubMed/Medline, EMBASE, Web of Science, China National Knowledge Infrastructure, Wanfang, and Chongqing VIP databases. Random-effects models were used to calculate pooled prevalence estimates. The heterogeneity was evaluated using Cochran’s Q test and I2 statistics. Moreover, potential sources of heterogeneity were explored using univariate subgroup analysis. Results Data on the prevalence of delayed ART initiation was pooled across 29 studies involving 34,937 participants from 15 countries. The overall pooled prevalence of delayed ART initiation was 36.1% [95% confidence interval (CI), 29.7–42.5%]. In subgroup analysis, the estimated pooled prevalence decreased with age. By sex, the prevalence was higher among male patients (39.3%, 95% CI: 32.2–46.4%) than female (36.5%, 95% CI: 26.9–50.7%). Patients with high CD4 cell count were more likely to delay ART initiation than those with low CD4 cell count (>500cells/mm3: 40.3%; 201-500cells/mm3: 33.4%; and ≤200cells/mm3: 25.3%). Conclusions Our systematic review and meta-analysis identified a high prevalence of delayed ART initiation. The prolonged time interval between diagnosis and treatment is a prevalent and unaddressed problem that should spur initiatives from countries globally. Further research is urgently needed to identify effective strategies for promoting the early ART initiation.
Characterization of 2014 summer drought over Henan province using remotely sensed data

An exceptional drought struck Henan province during the summer of 2014. It caused directly the financial loss reaching to hundreds of billion Yuan (RMB), and brought the adverse influence for people’s life, agricultural production as well as the ecosystem. The study in this paper characterized the Henan 2014 summer drought event through analyzing the spatial distribution of drought severity using precipitation data from Tropical Rainfall Measuring Mission (TRMM) sensor and Normalized difference vegetation index (NDVI) and land surface temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The trend analysis of the annual precipitation from 2003 to 2014 showed that the region over Henan province is becoming dry. Especially in the east of Henan province, the decrease of precipitation is more obvious with the maximum change rate of ~48 mm/year. The rainfall in summer (from June to August) of 2014 was the largest negtive anomaly in contrast with the same period of historical years, which was 43% lower than the average of the past ten years. Drought severity derived from Standardized Precipitation Index (SPI) indicated that all areas of Henan province experienced drought in summer of 2014 with different severity levels. The extreme drought, accounting for about 22.7 % of Henan total area, mainly occurred in Luohe, Xuchang, and Pingdingshan regions, and partly in Nanyang, Zhengzhou, and Jiaozuo. This is consistent with the statistics from local municipalities. The Normalized Drought Index Anomaly (NDAI), calculated from MODIS NDVI and LST products, can capture the evolution of the Henan 2014 summer drought effectively. Drought severity classified by NDAI also agreed well with the result from the SPI.
Intermittency across Reynolds numbers – the influence of large-scale shear layers on the scaling of the enstrophy and dissipation in homogenous isotropic turbulence

Abstract Direct numerical simulations up to Reλ = 1445 show that the scaling exponents for the enstrophy and the dissipation rate extrema are different and depend on the Reynolds number. A similar Reynolds number dependence of the scaling exponents is observed for the moments of the dissipation rate, but not for the moments of the enstrophy. Significant changes in the exponents occur at approximately Reλ ≈ 250, where Reλ is the Taylor based Reynolds number, which coincides with structural changes in the flow, in particular the development of large-scale shear layers. A model for the probability density functions (PDFs) of the enstrophy and dissipate rate is presented, which is an extension of our existing model (Proc. R. Soc. A, vol. 476, 2020, p. 20200591) and is based on the mentioned development of large-scale layer regions within the flow. This model is able to capture the observed Reynolds number dependencies of the scaling exponents, in contrast to the existing theories which yield constant exponents. Moreover, the model reconciles the scaling at finite Reynolds number with the theoretical limit, where the enstrophy and dissipation rate scale identically at infinite Reynolds number. It suggests that the large-scale shear layers are vital for understanding the scaling of the extrema. Furthermore, to reach the theoretical limit, the scaling exponents must remain Reynolds number dependent beyond the present Reλ range.
Visitor counting with accoustic slab sensors in the Swiss national park

Monitoring of visitor flow in recreational parks is important to various tasks of management, e.g. to assess the impact of visitors to the nature, to get information about the signification to the regional market or to estimate the demand trends for the future (Cessford & Muhar 2003). However, data acquisition is a very time-consuming and money-intensive assignment. There are three main categories of data collection methods: self-counting, directcounting and indirect counting (Hollenhorst et al. 1992). Depending on the goal of visitor monitoring, different data collection types are used. Self-counting methods are quite uncertain because their backflow is low. With direct-counting methods a lot of information, such as visitor characteristics, visitor behaviour and visitor numbers can be collected. The disadvantage of these methods is their big costs. A lot of human resources are needed to collect data. Indirect-counting systems generate simple estimations of recreational use, which are quite accurate after calibration (Hollenhorst et al. 1992).
The extend wedge method for the measurement of friction in atomic force microscope under oil lubrication

The measurement of friction on the surface at micro-load is significant to reveal the tribological properties of sample surface. Based on the traditional wedge method, a standard grating is used to calibrate the lateral force of the AFM and the method of solving lateral calibration factor α is given when considering the influence of the adhesive force on the calibration. What’s more, the friction between the probe and silicon surface is measured under oil lubrication. The result shows that the friction coefficient decreases with the increase of the load, and becomes stable when the load is larger than 2. 5μN, the lateral calibration factor α fluctuates greatly under the influence of the load. Under the condition of pentaerythritol oleate lubrication, the friction between probe and silicon surface is directly proportional to the load, and the sliding speed of probe has no obvious effect on the friction.
Fine-Grained Deposits and Biofacies of the Cretaceous Western Interior Seaway: Evidence of Cyclic Sedimentary Processes

Fine-Grained Deposits and Biofacies of the Cretaceous Western Seaway: Evidence of Cyclic Sedimentary Processes - This volume emphasizes the influence of cyclic sedimentary processes on the distribution of rock types and faunas in the Cretaceous strata in Colorado. As a whole, the volume provides an interdisciplinary view of the causes and consequences of gradual cyclic, periodic, and catastrophic changes in environmental conditions recorded by strata in the Kiowa-Skull Creek, Greenhorn, and Niobrara Cyclothems.
Buckling modal analysis of a rotary steering drilling tool

The emergence of rotary steering drilling system is well adapted to the needs of high-difficult drilling operations in directional wells. Buckling analysis of bottom hole assembly can guide drilling operation and has guiding significance for field application of rotary steering drilling system. Based on the structure of a push-type rotary steering system, this paper uses Abaqus finite element software to solve the buckling mode of RSBHA and further solve the critical buckling load of RSBHA.
Investigation on the influence trajectory of organizational learning and green innovation towards sustained competitive superiority

In the landscape of today's global sustainability, the enduring competitive edge of businesses has emerged as a vital survival determinant. A quantitative analysis approach was adopted in this study, and a Structural Equation Model was devised to scrutinize the effect of cognitive, social, and experiential learning on green innovation. This innovation subsequently influences the enduring competitive superiority. Our results expose the positive correlation between the aforementioned types of learning and green innovation. Additionally, green innovation serves as a bridge connecting these learning methods and sustainable competitiveness. This research provides an academic blueprint, suggesting that organizations can amplify their sustainable competitive edge through nurturing diverse organizational learning strategies and advocating for green innovation.
Exploring the relationship between green human resource management (GHRM) and organizational sustainable development performance

In order to successfully attain the goals of "peak carbon emissions and carbon neutrality," a comprehensive and transformative shift is imperative. The green and sustainable development of organizations is progressively recognized as a vital strategic priority for achieving the "dual carbon" objectives and driving high-quality development. Within the present context, the importance of incorporating green human resource management (GHRM) practices into organizational frameworks to foster understanding and implementation of sustainable practices becomes increasingly crucial. Consequently, this study seeks to fill information gaps by studying the relationship between GHRM practices and their impact on long-term development outcomes. Depend on the social exchange theory, an empirical approach using a questionnaire survey was employed, and statistical analysis techniques were applied to test the hypotheses. The findings demonstrate the positive influence of GHRM on organizational sustainable development performance by emphasizing the mediating function of employee green behavior and identifying the positive moderating effect of green self-efficacy. This research enhances our understanding of the relationship between GHRM and organizational sustainable development and has important implications for organizations aiming to improve sustainability practices and performance outcomes.
Stability prediction of micro-milling with tool runout and centrifugal force via using FEM and time-domain formulation

Micro-milling is one of important methods for producing miniature components with high-accuracy. During the cutting process, the chatter vibration which can result in instability and poor surface finish may considerably be disturbed by the unpredictable tool runout and centrifugal force with ultra high speeds of micro-mill. This paper tries to develop a time domain dynamic model for depicting chatter vibration of micro-mill with the concerns of tool runout incorporated in cutting forces and centrifugal force included in external force work via combing FEM and time-domain formulation. Several simulations carried out illustrates the validity of the proposed model from the perspectives of FRF, SLD and time domain response.
Design, manufacturing, and characterization of x-ray optics for the cavity-based x-ray free-electron laser project

Here, we report the design, manufacturing, and characterization of x-ray optical components for the cavity-based x-ray free-electron laser (CBXFEL) cavity, in the framework of the CBXFEL R&D collaborative project of Argonne National Laboratory, SLAC National Accelerator Laboratory, and SPring-8. The optical components include high-reflectivity diamond crystal mirrors, reflecting and output coupling diamond drumhead crystal with thin membranes, focusing beryllium refractive lenses, and channel-cut Si crystal monochromators. All the designed optical components have been fully characterized at the Advanced Photon Source to demonstrate their desired performance for the CBXFEL cavity.
SimEdge: Towards Accelerated Real-Time Augmented Reality Simulations Using Adaptive Smart Edge Computing

Real-time simulation in augmented reality environments is an important area of research. The simulation model used in this paper simulates the musculoskeletal system, which has many potential applications in physiotherapy, medical education, and rehabilitation. To enable such real-time simulations in augmented reality, high-performance computing clusters are typically required, which can be costly and infeasible in terms of high network delay. This paper proposes SimEdge, a domain-specific edge computing system that enables real-time pervasive simulation in augmented reality environments on heterogeneous providers. This is done by smart offloading decisions based on a continuously updated list of resource providers. SimEdge builds on previous work using surrogate models and leverages scheduling improvements and context-aware data and task placement. Significant improvements in frame rate and input lag are achieved, as well as a reduction in energy consumption. The experimental results show that the proposed approach leads to an 8.3-fold increase in frame rate and a 65.14% reduction in input lag, as well as a 35.07% reduction in energy consumption compared to the local baseline system. These results demonstrate the effectiveness of the approach in improving efficiency and responsiveness.
Efficient and Effective Proactive Scheduling for mmWave WLANs

To cope with growing wireless bandwidth demand, millimeter wave (mmWave) communication has been identified as a promising technology to deliver Gbps throughput. However, due to the susceptibility of mmWave signals to blockage, applications can experience significant performance variability as users move around due to rapid and significant variation in channel conditions. In this context, proactive schedulers that make use of future data rate prediction have potential to bring a significant performance improvement as compared to traditional schedulers. In this work, we propose an efficient proactive algorithm that prioritizes the scheduling of scarce resources to achieve better performance than traditional schedulers. The results show that our scheduler can increase average data rate by up to 20% compared to non-proactive scheduling and achieves from 60% to 75% of the performance gain of an optimal proactive scheduler.
Identification of RF Interference in Astronomical Observations Using Weakly Supervised Machine Learning Classifiers

Radio frequency interference (RFI) is a major concern for passive radioastronomical observations. There is a great interest within the wireless and radioastronomy communities to identify in real time man-made RFI in the vicinity of a telescope. This paper proposes the use of weakly supervised machine learning (ML) techniques to detect the presence of RFI in captured astronomical scans. Weakly supervised training is particularly appropriate when only a small subset of captured data is labeled, as is the case with many radioastronomical datasets. Our study is based on scans obtained from the Arizona Radio Observatory (ARO) at Kitt Peak, Arizona. We rely on the experience of astronomical engineers to label ten 20 MHz channels of a small fraction of the captured scans as "clean" or "dirty". The remaining channels of 4 GHz of the observed spectrum are unlabeled. We first use human-labeled data as ground truth and train two ML classifiers in a supervised manner: a Convolutional Neural Networks - Bidirectional Long Short Term Memory (CNN-BiLSTM) classifier and a Deep CNN classifier. For the unlabeled channels, a semi-supervised technique is adopted, whereby the unlabeled data is first fed to the trained supervised classifier and the outputs with high confidence are assigned pseudo labels. These pseudo-labeled data are further used to train a semi-supervised classifier. To test the performance of the semi-supervised technique, the two classifiers are considered again. We observe test accuracies of 94.55% and 93.69% respectively under weakly supervised training.
CR-TransR: A Knowledge Graph Embedding Model for Cultural Domain

As a combination of information computing technology and the cultural field, cultural computing is gaining more and more attention. The knowledge graph is also gradually applied as a particular data structure in the cultural area. Based on the domain knowledge graph data of the Beijing Municipal Social Science Project ”Mining and Utilization of Cultural Resources in the Ancient Capital of Beijing,” this paper proposes a graph representation learning model CR-TransR that integrates cultural attributes. Through the analysis of the data in the cultural field of the ancient capital of Beijing, a cultural feature dictionary is constructed, and a domain-specific feature matrix is constructed in the form of word vector splicing. The feature matrix is used to constrain the embedding graph model TransR, and then the feature matrix and the TransR model are jointly trained to complete the embedded expression of the knowledge graph. Finally, a comparative experiment is carried out on the Beijing ancient capital cultural knowledge graph dataset and the effects of the classic graph embedding algorithms TransE, TransH, and TransR. At the same time, we try to reproduce the embedding method with the core idea of neighbor node information aggregation as the core idea, and CRTransR are compared. The experimental tasks include link prediction and triplet classification, and the experimental results show that the CRTransR model performs better.
Wikipedia Addbot: Is Good Governance the Answer to Our Ills?

The Wikipedia "addbot" was controversial when it was first created and used. In only two days it made almost 150,000 revisions to works made by previous bots. A close analysis of the bot, and the system of governance employed by Wikidata, reveals that not only did the bot do its job, but it was also vetted, retooled, re-coded, and then executed effectively. Wikipedia's system of planning and governance, including bot governance, ensures that bots are used as tools and not agents of misinformation, disruption, or destruction. How Wikipedia administrators achieve this is relatively simple and involves controlling and mediating the automated nature of the bots and their explosive rhetorical agency. Conversely, sites such as Facebook and Twitter, which do not employ good bot governance, are known for hosting toxic and "viral" digital ecosystems that rely on anonymity and the automating power and agency of bots. The Wikipedia model demonstrates a system that encourages ethical behaviors, accountability, and governance that theoretically could be used across other social media platforms or technology ecosystems.
QUICL: A QUIC Convergence Layer for Disruption-tolerant Networks

Disruption-tolerant networks (DTNs) have a wide range of applications, such as emergencies where traditional communication infrastructure has been destroyed, remote rural deployments where communication infrastructure has never existed, and environmental monitoring where animals are equipped with sensors and transmit data whenever they come into contact with a base station. Using the de-facto DTN protocol standard, i.e., Bundle Protocol version 7 (BPv7), nodes transmit data via so-called Convergence Layer Protocols (CLPs) that act as general abstractions for the underlying communication technologies. BPv7 specifies MTCP and TCPCL as the two current CLPs for DTNs. However, both of them have different but equally undesirable shortcomings in terms of functionality, complexity, performance, and reliability. In this paper, we present QUICL, a novel CLP for DTNs. QUICL is based on the QUIC transport protocol and fully leverages QUIC's advantages over TCP-based transport protocols in a DTN environment. In particular, QUICL provides improved congestion control, allows multiplexing, ensures reliable transmission, effectively manages unreliable links, and uses encryption by default. Our prototypical implementation, already merged upstream, is based on the free and open-source DTN7-go protocol suite and the QUIC-go implementation. Our experimental evaluation shows that even with 30% packet loss, QUICL can still deliver data with minimal CPU overhead in scenarios where most other DTN/CLP combinations fail to transmit any data successfully.
Diagnostic value of rapid test for malaria among febrile neonates in a tertiary hospital in North-East Nigeria: a prospective cross-sectional study

Objective The WHO recommends testing using microscopy or rapid diagnostic test (RDT) before treatment for malaria. However, the use of RDT to diagnose neonatal malaria has not been widely validated with most studies limited to the first week of life. Thus, we conducted this study to determine the utility of RDT in the diagnosis of congenital and acquired malaria in febrile neonates in Nigeria. Design This prospective cross-sectional descriptive study consecutively recruited 131 febrile neonates at the Special Care Baby Unit (SCBU) of the Federal Teaching Hospital Gombe, Nigeria. All study participants concurrently had RDT (HRP2, LDH) and malaria microscopy. The performance of both methods was then compared. Result Seventy-eight of 131 neonates tested for malaria by blood smear microscopy demonstrated malaria parasites; a prevalence of 59.5%. Parasite count ranged from 16 to 520 /μL and the median parasite count was 81.0 /μL with IQR (40.0–134.5). The majority of patients (93.5%) had low-density parasitaemia (≤2+). All species identified were Plasmodium falciparum. None of the 131 neonates tested positive on RDT. The sensitivity and positive predictive value of RDT for neonatal malaria was zero. Congenital malaria was the most common form of neonatal malaria, accounting for 75.6%, while acquired and transfusion-related malaria were estimated at 12.8% and 11.6%, respectively. Conclusion The RDT used in this study was not sensitive in the diagnosis of congenital or acquired neonatal malaria; therefore, microscopy remains the preferred method of diagnosis of neonatal malaria.