Miracle-dz/UniFAR-FTUs huggingface dataset:
A Bacteria and Cell Repellent Zwitterionic Polymer Coating on Titanium Base Substrates towards Smart Implant Devices

Biofouling and biofilm formation on implant surfaces are serious issues that more than often lead to inflammatory reactions and the necessity of lengthy post-operation treatments or the removal of the implant, thus entailing a protracted healing process. This issue may be tackled with a biocompatible polymeric coating that at the same time prevents biofouling. In this work, oxygen plasma-activated silanized titanium substrates are coated with poly(sulfobetaine methacrylate), a zwitterionic antibiofouling polymer, using photopolymerization. The characterization of polymer films includes FT-IR, AFM, and adhesion strength measurements, where adhesion strength is analyzed using a cylindrical flat punch indenter and water contact angle (WCA) measurements. Both cytotoxicity analysis with primary human fibroblasts and fluorescence microscopy with fibroblasts and plaque bacteria are also performed is this work, with each procedure including seeding on coated and control surfaces. The film morphology obtained by the AFM shows a fine structure akin to nanoropes. The coatings can resist ultrasonic and sterilization treatments. The adhesion strength properties substantially increase when the films are soaked in 0.51 M of NaCl prior to testing when compared to deionized water. The coatings are superhydrophilic with a WCA of 10° that increases to 15° after dry aging. The viability of fibroblasts in the presence of coated substrates is comparable to that of bare titanium. When in direct contact with fibroblasts or bacteria, marginal adhesion for both species occurs on coating imperfections. Because photopolymerization can easily be adapted to surface patterning, smart devices that promote both osseointegration (in non-coated areas) and prevent cell overgrowth and biofilm formation (in coated areas) demonstrate practical potential.
Mortality in Edentulous Patients: A Registry-Based Cohort Study in Sweden Comparing 8463 Patients Treated with Removable Dentures or Implant-Supported Dental Prostheses

Objectives The purpose of this study was to investigate if edentulism is associated with all-cause mortality. The aims were to analyze the association between age, socioeconomic factors, and mortality in edentulous patients treated with either removable dentures or implant-supported prostheses. Methods All patients who became edentulous according to the Swedish Social Insurance Agency (SSIA) between 2009 and 2013 (N = 8463) were analyzed regarding prosthetic treatment, age, gender, and socioeconomic status. The patients were divided into two groups, depending on whether they were treated with dental implants (implant group; IG) or with conventional removable dentures (denture group; DG). Data on mortality for all included individuals were obtained from the Swedish National Cause of Death Register and compared to a reference population. Cumulative survival rates were calculated, and a multivariable regression analysis for the included variables was performed. Results Between 2009 and 2018, 2192 of the patients (25.9%) were treated with implant-supported dental prostheses (IG) and 6271 patients (74.1%) were treated with removable dentures without support of dental implants (DG). Altogether 2526 patients (30%) died until December 31, 2019, and the overall mortality was significantly higher for the DG compared to the IG during follow-up (p < 0.001). Younger edentulous patients (≤59 years) presented a higher mortality than the reference population, while implant patients over 79 years of age demonstrated a lower mortality. The final results from the multivariable logistic analysis showed that lower equalized disposable income (EDI) and the choice of conventional removable dentures are the most important factors for increased patient mortality (p < 0.001). Conclusions Edentulous patients have an overall higher mortality compared to a reference population. Low socioeconomic status increases all-cause mortality. Individuals treated with dental implants show statistically significant lower 10-year mortality compared to patients treated with conventional removable dentures, regardless of socioeconomic status.
Application of Chitosan/Alginate Nanocomposite Incorporated with Phycosynthesized Iron Nanoparticles for Efficient Remediation of Chromium

Biopolymers and nanomaterials are ideal candidates for environmental remediation and heavy metal removal. As hexavalent chromium (Cr6+) is a hazardous toxic pollutant of water, this study innovatively aimed to synthesize nanopolymer composites and load them with phycosynthesized Fe nanoparticles for the full Cr6+ removal from aqueous solutions. The extraction of chitosan (Cht) from prawn shells and alginate (Alg) from brown seaweed (Sargassum linifolium) was achieved with standard characteristics. The tow biopolymers were combined and cross-linked (via microemulsion protocol) to generate nanoparticles from their composites (Cht/Alg NPs), which had a mean diameter of 311.2 nm and were negatively charged (−23.2 mV). The phycosynthesis of iron nanoparticles (Fe-NPs) was additionally attained using S. linifolium extract (SE), and the Fe-NPs had semispherical shapes with a 21.4 nm mean diameter. The conjugation of Cht/Alg NPs with SE-phycosynthesized Fe-NPs resulted in homogenous distribution and stabilization of metal NPs within the polymer nanocomposites. Both nanocomposites exhibited high efficiency as adsorbents for Cr6+ at diverse conditions (e.g., pH, adsorbent dose, contact time and initial ion concentration) using batch adsorption evaluation; the most effectual conditions for adsorption were a pH value of 5.0, adsorbent dose of 4 g/L, contact time of 210 min and initial Cr6+ concentration of 75 ppm. These factors could result in full removal of Cr6+ from batch experiments. The composited nanopolymers (Cht/Alg NPs) incorporated with SE-phycosynthesized Fe-NPs are strongly recommended for complete removal of Cr6+ from aqueous environments.
Impacts of Modified Graphite Oxide on Crystallization, Thermal and Mechanical Properties of Polybutylene Terephthalate

In this study, the surface modification on graphene oxide (GO) was performed using octadecylamine (ODA). Furthermore, polybutylene terephthalate/GO (PBT/GO) composites were prepared to elucidate the role of GO surface modification on the mechanical performance, thermal stability and crystallization behavior. Results of Fourier transform infrared spectra (FT-IR), Raman spectrum, thermogravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS) and transmission electron microscope (TEM) revealed that ODA was successfully grafted on GO. Differential scanning calorimetry (DSC), wide-angle X-ray diffraction (WAXD), tensile test, Izod impact strength test and TGA were carried out on the PBT/GO composites. Results indicated that the addition of raw GO can enhance the crystallization temperature and degree of crystallinity and can slightly improve the thermal stability and tensile strength of the composites. However, the impact strength and elongation at break were seriously decreased owing to the poor compatibility between the GO and PBT matrix. Once the modified GO was added, the crystallization temperature and degree of crystallinity were greatly increased. The tensile strength increased greatly while the elongation at break and Izod impact strength were efficiently maintained; these were evidently higher than those of PBT/raw GO. Moreover, thermal stability was greatly enhanced. SEM (scanning electron microscope) observation results on the impact-fractured surface clearly confirmed the improved compatibility between the modified GO and PBT matrix. A related mechanism had been discussed.
A Small World Graph Approach for an Efficient Indoor Positioning System

The main goal of an Indoor Positioning System (IPS) is to estimate the position of mobile devices in indoor environments. For this purpose, the primary source of information is the signal strength of packets received by a set of routers. The fingerprint technique is one of the most used techniques for IPSs. By using supervised machine learning techniques, it trains a model with the received signal intensity information so it can be used to estimate the positions of the devices later in an online phase. Although the k-Nearest Neighbors (kNN) is one of the most widely used classification methods due to its accuracy, it has no scalability since a sample that needs to be classified must be compared to all other samples in the training database. In this work, we use a novel hierarchical navigable small world graph technique to build a search structure so the location of a sample can be efficiently found, allowing the IPSs to be used in large-scale scenarios or run on devices with limited resources. To carry out our performance evaluation, we proposed a synthetic IPS dataset generator as well as implemented a complete real-world, large-scale IPS testbed. We compared the performance of our graph-based solution with other known kNN variants, such as Kd-Tree and Ball-Tree. Our results clearly show the performance gains of the proposed solution at 98% when compared to the classic kNN and at least 80% when compared to tree-based approaches.
Multipurpose Prevention Technologies: Oral, Parenteral, and Vaginal Dosage Forms for Prevention of HIV/STIs and Unplanned Pregnancy

There is a high global prevalence of HIV, sexually transmitted infections (STIs), and unplanned pregnancies. Current preventative daily oral dosing regimens can be ineffective due to low patient adherence. Sustained release delivery systems in conjunction with multipurpose prevention technologies (MPTs) can reduce high rates of HIV/STIs and unplanned pregnancies in an all-in-one efficacious, acceptable, and easily accessible technology to allow for prolonged release of antivirals and contraceptives. The concept and development of MPTs have greatly progressed over the past decade and demonstrate efficacious technologies that are user-accepted with potentially high adherence. This review gives a comprehensive overview of the latest oral, parenteral, and vaginally delivered MPTs in development as well as drug delivery formulations with the potential to advance as an MPT, and implementation studies regarding MPT user acceptability and adherence. Furthermore, there is a focus on MPT intravaginal rings emphasizing injection molding and hot-melt extrusion manufacturing limitations and emerging fabrication advancements. Lastly, formulation development considerations and limitations are discussed, such as nonhormonal contraceptive considerations, challenges with achieving a stable coformulation of multiple drugs, achieving sustained and controlled drug release, limiting drug–drug interactions, and advancing past preclinical development stages. Despite the challenges in the MPT landscape, these technologies demonstrate the potential to bridge gaps in preventative sexual and reproductive health care.
Silane grafted natural rubber and its compatibilization effect on silica-reinforced rubber tire compounds

Natural Rubber (NR) grafted with 3-octanoylthio-1-propyltriethoxysilane (NXT) was prepared by melt mixing using 1,1′-di(tert-butylperoxy)-3,3,5-trimethylcyclohexane as initiator at 140 °C with NXT contents of 10 and 20 parts per hundred rubber [phr] and initiator 0.1 phr. The silane grafted on NR molecules was confirmed by Fourier transform infrared (FTIR), proton nuclear magnetic resonance (1H-NMR) and scanning electron icroscopy/energy dispersive X-ray spectroscopy (SEM-EDX). Based on1H-NMR, the use of 10 and 20 phr (parts per hundred resin) of silane resulted in grafted NXT onto NR of 0.66 and 1.32 mol%, respectively, or a grafting efficiency of approx.38%. The use of NXT-grafted NR as compatibilizer in silica-filled NR compounds, to give a total amount of NXT in both grafted and non-grafted forms in the range of 0.8-6.1 wt% relative to the silica, decreases the Mooney viscosity and Payne effect of the compounds, improves filler-rubber interaction, and significantly increases the tensile properties of the silica-filled NR-compounds compared to the non-compatibilized one. At the same silane-content, the use of silane-grafted NR gives slightly better properties than the straight use of the same silane. With sulfur compensation, the use of NXT-grafted-NR with about 6 wt% NXT relative to the silica gives technical properties that reach the levels obtained for straight use of bis-(3-triethoxysilyl-propyl) tetrasulfide (TESPT) at 8.6 wt% relative to the silica.
Effects of Non-thermal Ultrasound on a Fibroblast Monolayer Culture: Influence of Pulse Number and Pulse Repetition Frequency

Despite the use of therapeutic ultrasound in the treatment of soft tissue pathologies, there remains some controversy regarding its efficacy. In order to develop new treatment protocols, it is a common practice to carry out in vitro studies in cell cultures before conducting animal tests. The lack of reproducibility of the experimental results observed in the literature concerning in vitro experiments motivated us to establish a methodology for characterizing the acoustic field in culture plate wells. In this work, such acoustic fields are fully characterized in a real experimental configuration, with the transducer being placed in contact with the surface of a standard 12-well culture plate. To study the non-thermal effects of ultrasound on fibroblasts, two different treatment protocols are proposed: long pulse (200 cycles) signals, which give rise to a standing wave in the well with the presence of cavitation (ISPTP max = 19.25 W/cm2), and a short pulse (five cycles) of high acoustic pressure, which produces a number of echoes in the cavity (ISPTP = 33.1 W/cm2, with Pmax = 1.01 MPa). The influence of the acoustic intensity, the number of pulses, and the pulse repetition frequency was studied. We further analyzed the correlation of these acoustic parameters with cell viability, population, occupied surface, and cell morphology. Lytic effects when cavitation was present, as well as mechanotransduction reactions, were observed.
Retinal Nerve Fiber Layer and Macular Thickness in Parkinson's Disease Patients

Objective: This study aimed to evaluate the retinal nerve fiber layer (RNFL) thickness and macular thickness in Parkinson’s disease (PD) patients. Methods: The present study is a comparative cross-sectional, hospital-based study. A total number of 64 PD patients and 64 controls were recruited. Candidates that fulfilled the criteria with normal ocular examinations were undergone optical coherent tomography (OCT) examinations of the right eye. RNFL and macular thickness were evaluated. Results: There was a statistically significant reduction in RNFL thickness in average (adjusted mean 84.32 vs 95.93, p ≤ 0.001), superior (adjusted mean 105.15 vs 118.13, p ≤ 0.010), and inferior (adjusted mean 104.95 vs 126.55, p ≤ 0.001) PD group compared to the control group. The macula thickness also was significantly reduced in average (adjusted mean 266.51 vs 281.34, p = 0.015), central (adjusted mean 236.37 vs 255.55, p = 0.001), outer superior (adjusted mean 269.16 vs 278.19, p = 0.014), outer inferior (adjusted mean 256.34 vs 272.24, p ≤ 0.001), and outer nasal (adjusted mean 287.64 vs 302.84, p = 0.001) PD group compared to the control group. There was a significant positive correlation between RNFL thickness and visual acuity among PD patients in the inferior segment with p = 0.020 and nasal segment with p ≤ 0.001. There was also a significant positive correlation between macular thickness and visual acuity among PD patients in the inner temporal segment with p = 0.006, outer superior segment with p = 0.003, and outer temporal segment with p ≤ 0.001. Conclusion: The mean of the average, superior, and inferior RNFL thickness was significantly lower in the PD group compared to the control. The mean of the average, central, outer superior, outer inferior, and outer nasal macular thickness was significantly lower in the PD group compared to the control.
Spiral SAR Imaging with Fast Factorized Back-Projection: A Phase Error Analysis

This paper presents a fast factorized back-projection (FFBP) algorithm that can satisfactorily process real P-band synthetic aperture radar (SAR) data collected from a spiral flight pattern performed by a drone-borne SAR system. Choosing the best setup when processing SAR data with an FFBP algorithm is not so straightforward, so predicting how this choice will affect the quality of the output image is valuable information. This paper provides a statistical phase error analysis to validate the hypothesis that the phase error standard deviation can be predicted by geometric parameters specified at the start of processing. In particular, for a phase error standard deviation of ~12°, the FFBP is up to 21 times faster than the direct back-projection algorithm for 3D images and up to 13 times faster for 2D images.
Oriented Thin Films of Insoluble Polythiophene Prepared by the Friction Transfer Technique

A thin film of unsubstituted polythiophene (PT), an insoluble conjugated polymer, with molecular chains uniaxially oriented in plane was prepared by the friction transfer method. The structure of highly oriented thin films of PT was investigated using grazing-incidence X-ray diffraction (GIXD), ultraviolet–visible (UV–vis) spectroscopy, and infrared (IR) spectroscopy. The polarized UV–vis and IR spectra and GIXD measurements showed the PT molecular chains were well aligned in parallel to the friction direction. The GIXD studies clarified that the polymer backbones were aligned with very narrow distribution, such that the half-width was about 4 degrees. The degree of orientation of the PT friction-transferred film was higher compared with those of regioregular poly(3-alkylthiophene)s. Moreover, the GIXD results show a preferred orientation where the a-axis is perpendicular to the substrate plane.
The Importance of Clinical Data for the Diagnosis of Breast Tumours in North Afghanistan

Background This study was performed in knowledge of the increasing gap between breast disease treatment in countries with restricted resources and developed countries with increasingly sophisticated examination methods. Methods The authors present the analysis of a breast disease register consisting of diagnostic cases from Mazar e Sharif and Herat in 2018 and 2019. The study comprises a total of 567 cases, which were presented to experts via telemedicine for final diagnosis. 62 cases (10.9%) were excluded due to inacceptable data or insufficient image quality. These data provided by daily diagnostic classification were used for the built-up of a profile for each frequent breast disease and a breast cancer register. All images and cases were seen by at least 3 independent experts. The diagnoses were made in 60% of cases by cytology of fine needle aspiration and in 40% by histological images. Results For each entity of breast diseases (e.g., fibroadenoma), a profile of context variables was constructed allowing to assist medical decisions, as “wait and see,” elective surgery or immediate surgical intervention with R0 (complete) resection. These “profiles” could be described for fibroadenoma, mastitis, galactocele, fibrous-cystic disease, and invasive breast cancer. Conclusions The presented preliminary data set could serve as a cost-effective basis for a North Afghan breast cancer registry, with option to extent to a national model. These preliminary data are transformed in profiles of breast diseases, which are used by the local physicians in charge of breast disease patients. Each new case can be compared by the local treating physician with the profile of all preceded cases with the same diagnosis.
Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks

Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming concern in regard to the physical infrastructure security, safety and privacy has arisen due to the potential of their use in malicious activities. To address this problem, we propose a novel solution that automates the drone detection and identification processes using a drone’s acoustic features with different deep learning algorithms. However, the lack of acoustic drone datasets hinders the ability to implement an effective solution. In this paper, we aim to fill this gap by introducing a hybrid drone acoustic dataset composed of recorded drone audio clips and artificially generated drone audio samples using a state-of-the-art deep learning technique known as the Generative Adversarial Network. Furthermore, we examine the effectiveness of using drone audio with different deep learning algorithms, namely, the Convolutional Neural Network, the Recurrent Neural Network and the Convolutional Recurrent Neural Network in drone detection and identification. Moreover, we investigate the impact of our proposed hybrid dataset in drone detection. Our findings prove the advantage of using deep learning techniques for drone detection and identification while confirming our hypothesis on the benefits of using the Generative Adversarial Networks to generate real-like drone audio clips with an aim of enhancing the detection of new and unfamiliar drones.
Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications

Respiratory monitoring is receiving growing interest in different fields of use, ranging from healthcare to occupational settings. Only recently, non-contact measuring systems have been developed to measure the respiratory rate (fR) over time, even in unconstrained environments. Promising methods rely on the analysis of video-frames features recorded from cameras. In this work, a low-cost and unobtrusive measuring system for respiratory pattern monitoring based on the analysis of RGB images recorded from a consumer-grade camera is proposed. The system allows (i) the automatized tracking of the chest movements caused by breathing, (ii) the extraction of the breathing signal from images with methods based on optical flow (FO) and RGB analysis, (iii) the elimination of breathing-unrelated events from the signal, (iv) the identification of possible apneas and, (v) the calculation of fR value every second. Unlike most of the work in the literature, the performances of the system have been tested in an unstructured environment considering user-camera distance and user posture as influencing factors. A total of 24 healthy volunteers were enrolled for the validation tests. Better performances were obtained when the users were in sitting position. FO method outperforms in all conditions. In the fR range 6 to 60 breaths/min (bpm), the FO allows measuring fR values with bias of −0.03 ± 1.38 bpm and −0.02 ± 1.92 bpm when compared to a reference wearable system with the user at 2 and 0.5 m from the camera, respectively.