Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacterial Communities in Concrete Reflect Its Composite Nature and Change with Weathering

Concrete is the most-used building material in the world and a biologically extreme environment, with a microbiome composed of bacteria that likely come from concrete precursor materials, aerosols, and environmental deposition. These microbes, though seeded from a variety of materials, are all subject to desiccation, heating, starvation, high salinity, and very high pH. ABSTRACT Concrete is an extreme but common environment and is home to microbial communities adapted to alkaline, saline, and oligotrophic conditions. Microbes inside the concrete that makes up buildings or roads have received little attention despite their ubiquity and capacity to interact with the concrete. Because concrete is a composite of materials which have their own microbial communities, we hypothesized that the microbial communities of concrete reflect those of the concrete components and that these communities change as the concrete ages. Here, we used a 16S amplicon study to show how microbial communities change over 2 years of outdoor weathering in two sets of concrete cylinders, one prone to the concrete-degrading alkali-silica reaction (ASR) and the other having the risk of the ASR mitigated. After identifying and removing taxa that were likely laboratory or reagent contaminants, we found that precursor materials, particularly the large aggregate (gravel), were the probable source of ∼50 to 60% of the bacteria observed in the first cylinders from each series. Overall, community diversity decreased over 2 years, with temporarily increased diversity in warmer summer months. We found that most of the concrete microbiome was composed of Proteobacteria, Firmicutes, and Actinobacteria, although community composition changed seasonally and over multiyear time scales and was likely influenced by environmental deposition. Although the community composition between the two series was not significantly different overall, several taxa, including Arcobacter, Modestobacter, Salinicoccus, Rheinheimera, Lawsonella, and Bryobacter, appear to be associated with ASR. IMPORTANCE Concrete is the most-used building material in the world and a biologically extreme environment, with a microbiome composed of bacteria that likely come from concrete precursor materials, aerosols, and environmental deposition. These microbes, though seeded from a variety of materials, are all subject to desiccation, heating, starvation, high salinity, and very high pH. Microbes that survive and even thrive under these conditions can potentially either degrade concrete or contribute to its repair. Thus, understanding which microbes survive in concrete, under what conditions, and for how long has potential implications for biorepair of concrete. Further, methodological pipelines for analyzing concrete microbial communities can be applied to concrete from a variety of structures or with different types of damage to identify bioindicator species that can be used for structural health monitoring and service life prediction.
Enhancing Mobile Edge Computing with Efficient Load Balancing Using Load Estimation in Ultra-Dense Network

With the exponential growth of mobile devices and the emergence of computationally intensive and delay-sensitive tasks, the enormous demand for data and computing resources has become a big challenge. Fortunately, the combination of mobile edge computing (MEC) and ultra-dense network (UDN) is considered to be an effective way to solve these challenges. Due to the highly dynamic mobility of mobile devices and the randomness of the work requests, the load imbalance between MEC servers will affect the performance of the entire network. In this paper, the software defined network (SDN) is applied to the task allocation in the MEC scenario of UDN, which is based on routing of corresponding information between MEC servers. Secondly, a new load balancing algorithm based on load estimation by user load prediction is proposed to solve the NP-hard problem in task offloading. Furthermore, a genetic algorithm (GA) is used to prove the effectiveness and rapidity of the algorithm. At present, if the load balancing algorithm only depends on the actual load of each MEC, it usually leads to ping-pong effect. It is worth mentioning that our method can effectively reduce the impact of ping-pong effect. In addition, this paper also discusses the subtask offloading problem of divisible tasks and the corresponding solutions. At last, simulation results demonstrate the efficiency of our method in balancing load among MEC servers and its ability to optimize systematic stability.
Equilibrium and Kinetic Study of Anionic and Cationic Pollutants Remediation by Limestone–Chitosan–Alginate Nanocomposite from Aqueous Solution

In this work, low-cost and readily available limestone was converted into nanolimestone chitosan and mixed with alginate powder and precipitate to form a triple nanocomposite, namely limestone—chitosan–alginate (NLS/Cs/Alg.), which was used as an adsorbent for the removal of brilliant green (BG) and Congo red (CR) dyes in aqueous solutions. The adsorption studies were conducted under varying parameters, including contact time, temperature, concentration, and pH. The NLS/Cs/Alg. was characterized by SEM, FTIR, BET, and TEM techniques. The SEM images revealed that the NLS/Cs/Alg. surface structure had interconnected pores, which could easily trap the pollutants. The BET analysis established the surface area to be 20.45 m2/g. The recorded maximum experimental adsorption capacities were 2250 and 2020 mg/g for CR and BG, respectively. The adsorption processes had a good fit to the kinetic pseudo second order, which suggests that the removal mechanism was controlled by physical adsorption. The CR and BG equilibrium data had a good fit for the Freundlich isotherm, suggesting that adsorption processes occurred on the heterogeneous surface with a multilayer formation on the NLS/Cs/Alg. at equilibrium. The enthalpy change (ΔH0) was 37.7 KJ mol−1 for CR and 8.71 KJ mol−1 for BG, while the entropy change (ΔS0) was 89.1 J K−1 mol−1 for CR and 79.1 J K−1 mol−1 BG, indicating that the adsorption process was endothermic and spontaneous in nature.
Application of Novel Machine Learning Techniques for Predicting the Surface Chloride Concentration in Concrete Containing Waste Material

Structures located on the coast are subjected to the long-term influence of chloride ions, which cause the corrosion of steel reinforcements in concrete elements. This corrosion severely affects the performance of the elements and may shorten the lifespan of an entire structure. Even though experimental activities in laboratories might be a solution, they may also be problematic due to time and costs. Thus, the application of individual machine learning (ML) techniques has been investigated to predict surface chloride concentrations (Cc) in marine structures. For this purpose, the values of Cc in tidal, splash, and submerged zones were collected from an extensive literature survey and incorporated into the article. Gene expression programming (GEP), the decision tree (DT), and an artificial neural network (ANN) were used to predict the surface chloride concentrations, and the most accurate algorithm was then selected. The GEP model was the most accurate when compared to ANN and DT, which was confirmed by the high accuracy level of the K-fold cross-validation and linear correlation coefficient (R2), mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) parameters. As is shown in the article, the proposed method is an effective and accurate way to predict the surface chloride concentration without the inconveniences of laboratory tests.
Whole Cell Recognition of Staphylococcus aureus Using Biomimetic SPR Sensors

Over the past few decades, a significant increase in multi-drug-resistant pathogenic microorganisms has been of great concern and directed the research subject to the challenges that the distribution of resistance genes represent. Globally, high levels of multi-drug resistance represent a significant health threat and there is a growing requirement of rapid, accurate, real-time detection which plays a key role in tracking of measures for the infections caused by these bacterial strains. It is also important to reduce transfer of resistance genes to new organisms. The, World Health Organization has informed that millions of deaths have been reported each year recently. To detect the resistant organisms traditional detection approaches face limitations, therefore, newly developed technologies are needed that are suitable to be used in large-scale applications. In the present study, the aim was to design a surface plasmon resonance (SPR) sensor with micro-contact imprinted sensor chips for the detection of Staphylococcus aureus. Whole cell imprinting was performed by N-methacryloyl-L-histidine methyl ester (MAH) under UV polymerization. Sensing experiments were done within a concentration range of 1.0 × 102–2.0 × 105 CFU/mL. The recognition of S. aureus was accomplished by the involvement of microcontact imprinting and optical sensor technology with a detection limit of 1.5 × 103 CFU/mL. Selectivity of the generated sensor was evaluated through injections of competing bacterial strains. The responses for the different strains were compared to that of S. aureus. Besides, real experiments were performed with milk samples spiked with S. aureus and it was demonstrated that the prepared sensor platform was applicable for real samples.
2D Dynamic Directional Amplification (DDA) in Phononic Metamaterials

Phononic structures with unit cells exhibiting Bragg scattering and local resonance present unique wave propagation properties at wavelengths well below the regime corresponding to bandgap generation based on spatial periodicity. However, both mechanisms show certain constraints in designing systems with wide bandgaps in the low-frequency range. To face the main practical challenges encountered in such cases, including heavy oscillating masses, a simple dynamic directional amplification (DDA) mechanism is proposed as the base of the phononic lattice. This amplifier is designed to present the same mass and use the same damping element as a reference two-dimensional (2D) phononic metamaterial. Thus, no increase in the structure mass or the viscous damping is needed. The proposed DDA can be realized by imposing kinematic constraints to the structure’s degrees of freedom (DoF), improving inertia and damping on the desired direction of motion. Analysis of the 2D lattice via Bloch’s theory is performed, and the corresponding dispersion relations are derived. The numerical results of an indicative case study show significant improvements and advantages over a conventional phononic structure, such as broader bandgaps and increased damping ratio. Finally, a conceptual design indicates the usage of the concept in potential applications, such as mechanical filters, sound and vibration isolators, and acoustic waveguides.
Physicians’ Perspectives of Telemedicine During the COVID-19 Pandemic in China: Qualitative Survey Study

Background Generalized restriction of movement due to the COVID-19 pandemic, together with unprecedented pressure on the health system, has disrupted routine care for non–COVID-19 patients. Telemedicine should be vigorously promoted to reduce the risk of infections and to offer medical assistance to restricted patients. Objective The purpose of this study was to understand physicians’ attitudes toward and perspectives of telemedicine during and after the COVID-19 pandemic, in order to provide support for better implementation of telemedicine. Methods We surveyed all physicians (N=148), from October 17 to 25, 2020, who attended the clinical informatics PhD program at West China Medical School, Sichuan University, China. The physicians came from 57 hospitals in 16 provinces (ie, municipalities) across China, 54 of which are 3A-level hospitals, two are 3B-level hospitals, and one is a 2A-level hospital. Results Among 148 physicians, a survey response rate of 87.2% (129/148) was attained. The average age of the respondents was 35.6 (SD 3.9) years (range 23-48 years) and 67 out of 129 respondents (51.9%) were female. The respondents come from 37 clinical specialties in 55 hospitals located in 14 provinces (ie, municipalities) across Eastern, Central, and Western China. A total of 94.6% (122/129) of respondents’ hospitals had adopted a telemedicine system; however, 34.1% (44/129) of the physicians had never used a telemedicine system and only 9.3% (12/129) used one frequently (≥1 time/week). A total of 91.5% (118/129) and 88.4% (114/129) of physicians were willing to use telemedicine during and after the COVID-19 pandemic, respectively. Physicians considered the inability to examine patients in person to be the biggest concern (101/129, 78.3%) and the biggest barrier (76/129, 58.9%) to implementing telemedicine. Conclusions Telemedicine is not yet universally available for all health care needs and has not been used frequently by physicians in this study. However, the willingness of physicians to use telemedicine was high. Telemedicine still has many problems to overcome.
Vectors of Dutch Elm Disease in Northern Europe

Simple Summary Dutch elm disease (DED) has been killing elms for more than a century in northern Europe; the trees’ health status has worsened substantially in recent decades. Elm bark beetles Scolytus spp. are vectors of DED. Our aim was to estimate the distribution range of elm bark beetles and to detect potential new vectors of DED agents in northern Europe. Beetles were caught with bottle traps and manually. Then DNA from each specimen was extracted and analysed by the third generation sequencing method. DED agents were detected on the following bark beetles for Europe: Scolytus scolytus, S. triarmatus, S. multistriatus, S. laevis, and on new vectors: Xyleborus dispar and Xyleborinus saxesenii. The spread of Scolytus triarmatus, S. multistriatus and Xyleborinus saxesenii has been remarkable for the last two decades, and S. triarmatus and X. saxesenii are relatively recent newcomers in the northern Baltics. The problem is that the more vectoring beetles there are, the faster spread of Dutch elm disease from tree to tree. Abstract Potential Dutch elm disease vector beetle species were caught with pheromone bottle traps and handpicked in 2019: in total, seven species and 261 specimens were collected. The most common was Scolytus triarmatus, but by percent, the incidence of Ophiostoma novo-ulmi was highest in Scolytus scolytus, followed by Xyleborinus saxesenii and S. triarmatus. We analysed the beetles’ DNA using PacBio sequencing to determine vector beetles of Ophiostoma novo-ulmi. Ophiostoma novo-ulmi was found on six out of seven analysed beetle species: Scolytus scolytus, S. triarmatus, S. multistriatus, S. laevis, Xyleborinus saxesenii and Xyleborus dispar. The last two beetles were detected as vectors for Ophiostoma novo-ulmi for the first time. Previous knowledge on the spread of beetles is discussed.
Characterization of Patients With Obstructed Defecation and Slow Transit Constipation With a Simulated Stool

INTRODUCTION: Defecatory disorders including obstructed defecation (OD) are currently diagnosed using specialized investigations including anorectal manometry and the balloon expulsion test. Recently, we developed a simulated stool named Fecobionics that provides a novel type of pressure measurements and analysis. The aim was to study OD phenotypes compared with slow transit constipation (STC) patients and normal subjects (NS). METHODS: Fecobionics expulsion parameters were assessed in an interventional study design. The Fecobionics device contained pressure sensors at the front, rear, and inside a bag. All constipation patients had colon transit study, defecography, anorectal manometry, and balloon expulsion test performed. The Fecobionics bag was distended in the rectum until desire-to-defecate in 26 OD compared with 8 STC patients and 10 NS. Rear-front pressures (preload-afterload parameters) and defecation indices (DIs) were compared between groups. RESULTS: The Wexner constipation scoring system score was 13.8 ± 0.9 and 14.6 ± 1.5 in the OD and STC patients (P > 0.5). The median desire-to-defecate volume was 80 (quartiles 56–80), 60 (54–80), and 45 (23–60) mL in OD, STC, and NS, respectively (P < 0.01). The median expulsion duration was 37 (quartiles 15–120), 6 (3–11), and 11 (8–11) seconds for the 3 groups (P < 0.03). Fecobionics rear-front pressure diagrams demonstrated clockwise loops with distinct phenotype differences between OD and the other groups. Most DIs differed between OD and the other groups, especially those based on the anal afterload reflecting the nature of OD constipation. Several OD subtypes were identified. DISCUSSION: Fecobionics obtained novel pressure phenotypes in OD patients. DIs showed pronounced differences between groups. Larger studies are needed on OD subtyping.
Longer term patient management following stroke: A systematic review

Background Tremendous progress in acute stroke therapy has improved short-term outcome but part of this achievement may be lost in the long run. Concepts for a better long-term management of stroke survivors are needed to address their unmet needs and to reduce the burden of post-stroke complications, residual deficits, and recurrent vascular events. Aims This review summarizes current knowledge on post-hospital care and the scientific evidence supporting individual programs. Summary of review A systematic search of electronic databases according to PRISMA guidelines identified 10,374 articles, 77 of which met the inclusion criteria. One large randomised controlled trial on a multifaceted care program delivered by the multidisciplinary stroke team reduced recurrent vascular events and improved quality of life and functional outcome one year after the event, while a number of studies offer solutions for individual components of post-hospital disease management like patient education, counselling, and self-management or the management of post-stroke complications and residual deficits. A majority of studies, however, was small in size and limited by a short follow-up. Most initiatives with a narrow focus on risk factor control failed to lower the risk of recurrent events. The caregivers’ central role in post-stroke patient management is broadly neglected in research. Conclusions Over the past years, first knowledge on how to best organize post-hospital care of stroke patients has emerged. Comprehensive and pragmatic programs operated by the multidisciplinary stroke team hold promise to reduce the long-term health burden of stroke. There is a clear need for further high-quality studies with both clinical endpoints and patient-reported outcomes to establish sustainable solutions in different settings and regions to improve life after stroke, a key priority of the Stroke Action Plan for Europe 2018–2030.
Facile route to a conducting ternary polyaniline@TiO2/GN nanocomposite for environmentally benign applications: photocatalytic degradation of pollutants and biological activity

A polyaniline@TiO2/graphene (Pani@TiO2/GN) nanocomposite was prepared by the in situ oxidative polymerization of aniline in the presence of TiO2 and GN nanoparticles. The resulting Pani@TiO2/GN nanocomposite was characterized by UV-visible diffuse absorbance/reflectance spectroscopy (DRS), photoluminescence spectroscopy (PL), transmission electron microscopy, scanning electron microscopy, X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). The observance of peaks of Pani, TiO2 and GN in XRD and XPS as well as the observance of TiO2 nanoparticles well distributed inside the network of the Pani and GN nanosheets from morphological characterizations suggests the successful formation of Pani@TiO2/GN nanocomposites. DRS and PL analysis showed that Pani@TiO2/GN had higher visible light absorption and a lower recombination rate than Pani@TiO2. The visible light photocatalytic activity of the Pani@TiO2/GN nanocomposite was tested for methylene blue (MB) degradation. The results revealed high photocatalytic activity, which is partly due to the sensitizing effect of Pani and the low recombination rate due to the GN electron scavenging property. The rate of MB degradation on the Pani@TiO2/GN nanocomposite was strongly dependent on the solution pH, reaction time, catalyst dose, and the initial MB concentration. The high regeneration degradation efficiency of the Pani@TiO2/GN nanocomposite showed high stability and the effectiveness of the synthesized photocatalyst. In a continuation of environmental remediation studies, Pani@TiO2/GN revealed high antibacterial activity towards Escherichia coli and Enterobacter ludwigii, highlighting its potential as a photocatalyst with antibacterial properties for different industrial and medical purposes.
Protocol of a Single-Blind Two-Arm (Waitlist Control) Parallel-Group Randomised Controlled Pilot Feasibility Study for mHealth App among Incontinent Pregnant Women

Background: The delivery of pelvic floor muscle training (PFMT) through mHealth apps has been shown to produce promising results in improving pelvic floor muscle strength and urinary incontinence (UI). However, there is limited evidence on mHealth apps designed for pregnant women who are at high risk of developing UI. This pilot study aims to evaluate the feasibility of conducting an effectiveness trial for a newly developed PFMT app among pregnant women in Malaysia. Methods: This is a prospective, single-centre, single-blind, randomised controlled pilot feasibility study: The Kegel Exercise Pregnancy Training app (KEPT-app) Trial. Sixty-four incontinent pregnant women who attended one primary care clinic for the antenatal follow-up will be recruited and randomly assigned to either intervention or waitlist control group. The intervention group will receive the intervention, the KEPT-app developed from the Capability, Opportunity, Motivation-Behaviour (COM-B) theory with Persuasive Technology and Technology Acceptance Model. Discussion: This study will provide a fine-tuning for our future randomised control study on the recruitment feasibility methods, acceptability, feasibility, and usability of the KEPT-app, and the methods to reduce the retention rates among pregnant women with UI. Trial registration: This study was registered on ClinicalTrials.gov on 19 February 2021 (NCT04762433) and is not yet recruiting.
Effective Elements for Workplace Responses to Critical Incidents and Suicide: A Rapid Review

Despite high rates of critical incidents (CIs) in working class occupations, there is a significant gap in our understanding of responses to these events. In this study, we aimed to inform a response training module by synthesising the key elements of pre-, during- and post-incident responses to CIs and suicide in the workplace. A rapid review identified studies on responses to CIs or suicide deaths in the workplace published between January 2015 and June 2020. A systematic search of six databases (Medline, CINAHL, PsycINFO, Sociology Collection, Academic Search and Business Search Complete) and grey literature was performed. Studies were excluded if the focus was on non-colleagues. Two reviewers independently conducted record screening, a review of the full text and assessed study quality. The existing evidence was synthesised and interventions were categorised using Haddon’s Matrix. Five studies were included, reporting on CIs across a range of workplace settings, including railways, factories, police and military, along with external critical response units. Overall, study quality was assessed as being poor. Most of the evidence focused on the pre-incident and post-incident stage. There is little evidence on responses to CIs in the workplace. Evidence-based education and training is necessary to establish organisational responses to assist with supporting workers exposed to workplace CIs.