A Novel Channel Estimation Framework in MIMO Using Serial Cascaded Multiscale Autoencoder and Attention LSTM with Hybrid Heuristic Algorithm

In wireless communication, multiple signals are utilized to receive and send information in the form of signals simultaneously. These signals consume little power and are usually inexpensive, with a high data rate during data transmission. An Multi Input Multi Output (MIMO) system uses numerous antennas to enhance the functionality of the system. Moreover, system intricacy and power utilization are difficult and highly complicated tasks to achieve in an Analog to Digital Converter (ADC) at the receiver side. An infinite number of MIMO channels are used in wireless networks to improve efficiency with Cross Entropy Optimization (CEO). ADC is a serious issue because the data of the accepted signal are completely lost. ADC is used in the MIMO channels to overcome the above issues, but it is very hard to implement and design. So, an efficient way to enhance the estimation of channels in the MIMO system is proposed in this paper with the utilization of the heuristic-based optimization technique. The main task of the implemented channel prediction framework is to predict the channel coefficient of the MIMO system at the transmitter side based on the receiver side error ratio, which is obtained from feedback information using a Hybrid Serial Cascaded Network (HSCN). Then, this multi-scaled cascaded autoencoder is combined with Long Short Term Memory (LSTM) with an attention mechanism. The parameters in the developed Hybrid Serial Cascaded Multi-scale Autoencoder and Attention LSTM are optimized using the developed Hybrid Revised Position-based Wild Horse and Energy Valley Optimizer (RP-WHEVO) algorithm for minimizing the "Root Mean Square Error (RMSE), Bit Error Rate (BER) and Mean Square Error (MSE)" of the estimated channel. Various experiments were carried out to analyze the accomplishment of the developed MIMO model. It was visible from the tests that the developed model enhanced the convergence rate and prediction performance along with a reduction in the computational costs.

An accelerated sine mapping whale optimizer for feature selection

An improved whale optimization algorithm (SWEWOA) is presented for global optimization issues. Firstly, the sine mapping initialization strategy (SS) is used to generate the population. Secondly, the escape energy (EE) is introduced to balance the exploration and exploitation of WOA. Finally, the wormhole search (WS) strengthens the capacity for exploitation. The hybrid design effectively reinforces the optimization capability of SWEWOA. To prove the effectiveness of the design, SWEWOA is performed in two test sets, CEC 2017 and 2022, respectively. The advantage of SWEWOA is demonstrated in 26 superior comparison algorithms. Then a new feature selection method called BSWEWOA-KELM is developed based on the binary SWEWOA and kernel extreme learning machine (KELM). To verify its performance, 8 high-performance algorithms are selected and experimentally studied in 16 public datasets of different difficulty. The test results demonstrate that SWEWOA performs excellently in selecting the most valuable features for classification problems.

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm

Cloud computing plays an important role in every IT sector. Many tech giants such as Google, Microsoft, and Facebook as deploying their data centres around the world to provide computation and storage services. The customers either submit their job directly or they take the help of the brokers for the submission of the jobs to the cloud centres. The preliminary aim is to reduce the overall power consumption which was ignored in the early days of cloud development. This was due to the performance expectations from cloud servers as they were supposed to provide all the services through their services layers IaaS, PaaS, and SaaS. As time passed and researchers came up with new terminologies and algorithmic architecture for the reduction of power consumption and sustainability, other algorithmic anarchies were also introduced, such as statistical oriented learning and bioinspired algorithms. In this paper, an indepth focus has been done on multiple approaches for migration among virtual machines and find out various issues among existing approaches. The proposed work utilizes elastic scheduling inspired by the smart elastic scheduling algorithm (SESA) to develop a more energy-efficient VM allocation and migration algorithm. The proposed work uses cosine similarity and bandwidth utilization as additional utilities to improve the current performance in terms of QoS. The proposed work is evaluated for overall power consumption and service level agreement violation (SLA-V) and is compared with related state of art techniques. A proposed algorithm is also presented in order to solve problems found during the survey.

Acoustic Wave Reflection in Water Affects Underwater Wireless Sensor Networks

The phenomenon of acoustic wave reflection off fluid-solid surfaces is the focus of this research. This research aims to measure the effect of material physical qualities on oblique incidence acoustic attenuation across a large frequency range. To construct the extensive comparison shown in the supporting documentation, reflection coefficient curves were generated by carefully adjusting the porousness and permeability of the poroelastic solid. The next stage in determining its acoustic response is to determine the pseudo-Brewster angle shift and the reflection coefficient minimum dip for the previously indicated attenuation permutations. This circumstance is made possible by modeling and studying the reflection and absorption of acoustic plane waves encountering half-space and two-layer surfaces. For this purpose, both viscous and thermal losses are taken into account. According to the research findings, the propagation medium has a significant impact on the form of the curve that represents the reflection coefficient, whereas the effects of permeability, porosity, and driving frequency are relatively less significant to the pseudo-Brewster angle and curve minima, respectively. This research additionally found that as permeability and porosity increase, the pseudo-Brewster angle shifts to the left (proportionally to porosity increase) until it reaches a limiting value of 73.4 degrees, and that the reflection coefficient curves for each level of porosity exhibit a greater angular dependence, with an overall decrease in magnitude at all incident angles. These findings are given within the framework of the investigation (in proportion to the increase in porosity). The study concluded that when permeability declined, the angular dependence of frequency-dependent attenuation reduced, resulting in iso-porous curves. The study also discovered that the matrix porosity largely affected the angular dependency of the viscous losses in the range of 1.4 × 10^-14 m² permeability.

Hybrid Deep Learning and Discrete Wavelet Transform-Based ECG Biometric Recognition for Arrhythmic Patients and Healthy Controls

The intrinsic and liveness detection behavior of electrocardiogram (ECG) signals has made it an emerging biometric modality for the researcher with several applications including forensic, surveillance and security. The main challenge is the low recognition performance with datasets of large populations, including healthy and heart-disease patients, with a short interval of an ECG signal. This research proposes a novel method with the feature-level fusion of the discrete wavelet transform and a one-dimensional convolutional recurrent neural network (1D-CRNN). ECG signals were preprocessed by removing high-frequency powerline interference, followed by a low-pass filter with a cutoff frequency of 1.5 Hz for physiological noises and by baseline drift removal. The preprocessed signal is segmented with PQRST peaks, while the segmented signals are passed through Coiflets' 5 Discrete Wavelet Transform for conventional feature extraction. The 1D-CRNN with two long short-term memory (LSTM) layers followed by three 1D convolutional layers was applied for deep learning-based feature extraction. These combinations of features result in biometric recognition accuracies of 80.64%, 98.81% and 99.62% for the ECG-ID, MIT-BIH and NSR-DB datasets, respectively. At the same time, 98.24% is achieved when combining all of these datasets. This research also compares conventional feature extraction, deep learning-based feature extraction and a combination of these for performance enhancement, compared to transfer learning approaches such as VGG-19, ResNet-152 and Inception-v3 with a small segment of ECG data.

Energy-Aware IoT-Based Method for a Hybrid On-Wrist Fall Detection System Using a Supervised Dictionary Learning Technique

In recent decades, falls have posed multiple critical health issues, especially for the older population, with their emerging growth. Recent research has shown that a wrist-based fall detection system offers an accessory-like comfortable solution for Internet of Things (IoT)-based monitoring. Nevertheless, an autonomous device for anywhere-anytime may present an energy consumption concern. Hence, this paper proposes a novel energy-aware IoT-based architecture for Message Queuing Telemetry Transport (MQTT)-based gateway-less monitoring for wearable fall detection. Accordingly, a hybrid double prediction technique based on Supervised Dictionary Learning was implemented to reinforce the detection efficiency of our previous works. A controlled dataset was collected for training (offline), while a real set of measurements of the proposed system was used for validation (online). It achieved a noteworthy offline and online detection performance of 99.8% and 91%, respectively, overpassing most of the related works using only an accelerometer. In the worst case, the system showed a battery consumption optimization by a minimum of 27.32 working hours, significantly higher than other research prototypes. The approach presented here proves to be promising for real applications, which require a reliable and long-term anywhere-anytime solution.

Mathematical COVID-19 model with vaccination: a case study in Saudi Arabia

The discovery of a new form of corona-viruses in December 2019, SARS-CoV-2, commonly named COVID-19, has reshaped the world. With health and economic issues at stake, scientists have been focusing on understanding the dynamics of the disease, in order to provide the governments with the best policies and strategies allowing them to reduce the span of the virus. The world has been waiting for the vaccine for more than one year. The World Health Organization (WHO) is advertising the vaccine as a safe and effective measure to fight off the virus. Saudi Arabia was the fourth country in the world to start to vaccinate its population. Even with the new simplified COVID-19 rules, the third dose is still mandatory. COVID-19 vaccines have raised many questions regarding in its efficiency and its role to reduce the number of infections. In this work, we try to answer these question and propose a new mathematical model with five compartments, including susceptible, vaccinated, infectious, asymptotic and recovered individuals. We provide theoretical results regarding the effective reproduction number, the stability of endemic equilibrium and disease free equilibrium. We provide numerical analysis of the model based on the Saudi case. Our developed model shows that the vaccine reduces the transmission rate and provides an explanation to the rise in the number of new infections immediately after the start of the vaccination campaign in Saudi Arabia.

Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts

Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resource planning and forecasting are essential steps for resource allocation. This study proposes a reliable hybrid dynamic bandwidth slice forecasting framework that combines the long short-term memory (LSTM) neural network and local smoothing methods to improve the network forecasting model. Moreover, the proposed framework can dynamically react to all the changes occurring in the data series. Backbone traffic was used to validate the proposed method. As a result, the forecasting accuracy improved significantly with the proposed framework and with minimal data loss from the smoothing process. The results showed that the hybrid moving average LSTM (MLSTM) achieved the most remarkable improvement in the training and testing forecasts, with 28% and 24% for long-term evolution (LTE) time series and with 35% and 32% for the multiprotocol label switching (MPLS) time series, respectively, while robust locally weighted scatter plot smoothing and LSTM (RLWLSTM) achieved the most significant improvement for upstream traffic with 45%; moreover, the dynamic learning framework achieved improvement percentages that can reach up to 100%.

Breast Implant-Associated Anaplastic Large Cell Lymphoma (BIA-ALCL): Review of Epidemiology and Prevalence Assessment in Europe

BACKGROUND

Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) epidemiologic studies focus on incidence and risk estimates.

OBJECTIVES

The aim of this study was to perform a thorough literature review, and to provide an accurate estimate of BIA-ALCL prevalence in Europe.

METHODS

We searched PubMed, Web of Science, SCOPUS, and Google Scholar databases to identify publications reporting BIA-ALCL epidemiology. Research was conducted between November 2019 and August 2020. European prevalence was assessed as the ratio between pathology-confirmed cases and breast implant-bearing individuals. The Committee on Device Safety and Development (CDSD) collected data from national plastic surgery societies, health authorities, and disease-specific registries to calculate the numerator. The denominator was estimated by combining European demographic data with scientific reports.

RESULTS

Our research identified 507 articles: 106 were excluded for not being relevant to BIA-ALCL. From the remaining 401 articles, we selected 35 that discussed epidemiology and 12 reviews. The CDSD reported 420 cases in Europe, with an overall prevalence of 1:13,745 cases in the 28 member states of the European Union (EU-28). Countries where specific measures have been implemented to tackle BIA-ALCL account for 61% of the EU-28 population and actively reported 382 cases with an overall prevalence of 1:9121.

CONCLUSION

Countries where specific measures have been implemented show a higher prevalence of BIA-ALCL compared with the European mean, suggesting that these countries have improved the detection of the condition and reduced underreporting, which affects the numerator value. Other nations should adopt projections based on these measures to avoid underestimating how widespread BIA-ALCL is.

LEVEL OF EVIDENCE: 4

Sire contribution to fertilization failure and early embryo survival in cattle

Despite passing routine laboratory tests of semen quality, bulls used in artificial insemination (AI) exhibit a significant range in field fertility. The objective of this study was to determine whether subfertility in AI bulls is due to issues of sperm transport to the site of fertilization, fertilization failure, or failure of early embryo or conceptus development. In experiment 1, Holstein-Friesian bulls (3 high fertility, HF, and 3 low fertility, LF) were selected from the national population of AI bulls based on adjusted fertility scores from a minimum of 500 inseminations (HF: +4.37% and LF: -12.7%; mean = 0%). Superovulated beef heifers were blocked based on estimated number of follicles at the time of AI and inseminated with semen from HF or LF bulls (n = 3-4 heifers per bull; total 19 heifers). Following slaughter 7 d later, the number of corpora lutea was counted and the uteri were flushed. Recovered structures (oocytes/embryos) were classified according to developmental stage and stained with 4',6-diamidino-2-phenylindole to assess number of cells and accessory sperm. Overall recovery rate (total structures recovered/total corpora lutea) was 52.6% and was not different between groups. Mean (± standard error of the mean) number of embryos recovered per recipient was 8.7 ± 5.2 and 9.4 ± 5.5 for HF and LF, respectively. Overall fertilization rate of recovered structures was not different between groups. However, more embryos were at advanced stages of development (all blastocyst stages combined), reflected in a greater mean embryo cell number on d 7 for HF versus LF bulls. Number of accessory sperm was greater for embryos derived from HF than for LF bulls. The aim of experiment 2 was to evaluate the effect of sire fertility on survival of bovine embryos to d 15. Day 7 blastocysts were produced in vitro using semen from the same HF (n = 3) and LF (n = 3) bulls and transferred in groups of 5-10 to synchronized heifers (n = 7 heifers per bull; total 42 heifers). Conceptus recovery rate on d 15 was higher in HF (59.4%,) versus LF (45.0%). Mean length of recovered conceptuses for HF bulls was not affected by fertility status. In conclusion, while differences in field fertility among AI sires used in this study were not reflected in fertilization rate, differences in embryo quality were apparent as early as d 7. These differences likely contributed to the higher proportion of conceptuses surviving to d 15 in HF bulls.

36 Analysis of miRNA content of oviduct and uterine extracellular vesicles across the bovine estrous cycle

With the aim of investigating the possible hormonal regulatory effect of the oestrous cycle on miRNA content in the extracellular vesicles (EVs) of bovine oviducal and uterine fluids (OF, UF), we performed a bioinformatic analysis of these miRNAs, their target genes, and their biological pathways. Reproductive tracts were collected from slaughtered heifers and selected according to their corpus luteum morphology, corresponding to the 4 stages of the oestrous cycle (n=5 per stage; S1: days 1 to 4, S2: days 5–10, S3: days 11–17, S4: days 18–20) and transported to the laboratory on ice. EVs were obtained by size exclusion chromatography (PURE-EVs-Hansa Biomed) from the flushing of 1.2mL and 2.5mL of OF and UF, respectively. To concentrate the EVs, they were ultracentrifuged and suspended in 100µL of PBS. Total RNA extraction was obtained from 70µL of the previous pellet, using miRNeasy Mini Kit (Qiagen). Then, 100 to 200ng of the obtained RNA was reverse transcribed using miScript II RT Kit (Qiagen). MicroRNA (miRNA) expression profiling was done by primer-based real-time quantitative PCR of 383 mature miRNA sequences. Possible miRNA target genes and their biological pathways were predicted using the miRWalk database. Among EV miRNAs in OF, bta-miR-130a, bta-miR-382, and bta-miR-1291 were the most abundant at all stages of the oestrous cycle, displaying a significantly progressive increase from stages 1 to 4 (P<0.05). In UF, bta-miR-17-5p, bta-miR-206, bta-miR-22-5p, bta-miR-502a, and bta-miR-503-3p were the most abundant at all stages of the cycle, showing greater differences between S1 and S3 (P<0.05). Other miRNAs were exclusively present in a specific stage of the oestrous cycle in OF: bta-miR-21-5p (S1), bta-miR-146a (S2), bta-miR-128 (S3), and bta-miR-147 (S4). In UF, bta-miR-218 (S1), bta-miR-208b (S2), bta-miR-340 (S3), and bta-miR-335 (S4) were found. Table 1 presents some of these miRNAs, their predicted target genes, and functional pathways. In conclusion, this study highlights the effect of the oestrous cycle on miRNAs contained in the EVs of OF and UF. These miRNAs are related to relevant biological pathways implicated in oviduct and uterus modulation across the cycle, but they may also prepare those organs for embryo/conceptus presence and development. Table 1. Micro (mi)RNAs of oviductal (OF) and uterine fluid (UF) extracellular vesicles (EVs), their target genes, and biological pathways Reproductive fluid miRNAs Target genes Target pathways OF bta-miR-130a BMPR2, SMAD5, SMAD4 BMP signalling bta-miR-1291 SLC2A1 Glucagon signalling bta-miR-21–5p LIF Pluripotency stem cells regulation UF bta-miR-17-5p STAT3 Prolactin signalling bta-miR-206 ESR1 Oestrogen signalling bta-miR-340 HRAS Ras/MAPK/ERK signalling (embryo implantation) This research was funded by MINECO-Spain AGL2015-70140-R, PID2019-111641RB-I00, RTI2018-093548-B-I00; SENESCYT-Ecuador (YNC); FAPESP-Brazil 2017/20339-3 (CLVL), 2014/22887-0 (JCS), 2019/04981-2 (RM); CNPq-Brazil 304276/2018-9, 420152/2018-0 (CLVL).

52 Extracellular vesicles from oviduct and uterus in sequential invitro culture affects mitochondrial activity and lipid metabolism transcripts in bovine embryos

Oviducal fluid (OF) and uterine fluid (UF) improve the quality of embryos during invitro culture, and their extracellular vesicles (EV) may be involved in such an effect. We aimed to evaluate the effect of EV from OF and UF in sequential invitro culture on the development and quality of bovine embryos. Zygotes were cultured in synthetic oviduct fluid supplemented either with 3mg mL−1 BSA (n=1584) or 5% EV-depleted fetal calf serum (dFCS, n=1594) in absence or presence (BSAEV, n=1853 and dFCSEV, n=1473) of 3×105 EV mL−1 from OF (Day 1 to Day 4) and UF (Day 5 to Day 8), mimicking invivo conditions. EV from oviducts (early luteal phase) and uterine horns (mid luteal phase) from slaughtered heifers were isolated by size exclusion chromatography; size and concentration were assessed by nanotracking analysis (NTA) and morphology by transmission electron microscopy (TEM). Blastocyst rate was recorded on Days 7–8 and their quality was assessed for mitochondrial activity by staining with Mitotracker Deep Red (ThermoFisher Scientific), survival rate after vitrification/warming by invitro culture for up to 72h, and relative mRNA abundance of lipid metabolism-related transcripts by quantitative PCR. Housekeeping genes were H2AFZ and ACTB. Data were analysed by one-way ANOVA and Tukey test. TEM confirmed the presence and morphology of EVs, and NTA indicated mode size and concentration of particles (137.2 and 151.2 nm; 2.97×1010 and 7.98×1010 particles mL−1, for OF and UF, respectively). Blastocyst yield was lower (P<0.05) in BSA groups compared with dFCS groups (BSA: 16.2±1.5 and 31.0±1.9; BSAEV: 14.1±1.6 and 26.2±2.0% vs. dFCS: 30.5±2.0 and 40.6±2.4; dFCSEV: 31.1±2.5 and 39.8±2.7%, Day 7 and Day 8, respectively), irrespective of EV supplementation. Blastocyst mitochondrial activity was increased (P<0.05) by EV in dFCSEV compared with the other groups. No differences in survival rate after vitrification/warming were found (range at 72 h: 67.1±8.1 to 87.8±5.7%). PPARGC1B was downregulated and ACC upregulated by EV, irrespective of protein source in medium (P<0.05). In contrast, EV affected some transcripts depending on the protein source in the medium (CD36 upregulated in dFCSEV, downregulated in BSAEV; PLIN2 downregulated in dFCSEV and ATGL downregulated in BSAEV, P<0.05). In conclusion, mimicking physiological conditions using EV from OF and UF in sequential IVC does not affect development but improves embryo quality by increasing blastocysts’ mitochondrial activity and favours the expression of specific lipid metabolism transcripts. Functional effects of EV may be influenced by the protein source in the medium. This research was funded by MINECO-Spain AGL2015-70140-R, PID2019-111641RB-I00, RTI2018-093548-B-I00; YN Cajas, SENESCYT-Ecuador; CLV Leal, FAPESP-Brazil 2017/20339-3, CNPq-Brazil 304276/2018-9.

76 Extracellular vesicles from oviduct and uterus in sequential culture improve the quality of bovine embryos produced invitro

Extracellular vesicles (EVs) are released by cells and transport cargo that affect functions of other cells. Oviductal fluid (OF) and uterine fluid (UF) have been shown to improve quality of embryos during invitro culture (Hamdi et al. 2017 Reprod. Fertil. Dev. 30, 935-945) which may be due to their content of EV (Lopera-Vásquez et al. 2017 Reproduction 153, 461-470). Thus, the aim of this study was to evaluate the effect of EVs from OF and UF on a sequential invitro culture system on the development and quality of bovine embryos. Zygotes were cultured in synthetic oviduct fluid (SOF) supplemented with 3mgmL−1 bovine serum albumin (BSA; n=1228) or 5% EV-depleted fetal calf serum (dFCS, n=1261) in the presence (BSAEV, n=1265 and dFCSEV, n=1253) or absence of 3×105 EVmL−1 from OF (Day 1 to Day 4) and UF (Day 4 to Day 9), mimicking invivo conditions. The EVs pooled from 5 oviducts (early luteal phase) and 5 uterine horns (middle luteal phase) from slaughtered heifers were isolated by a Size Exclusion Chromatography kit (Hansa BioMed). The EV size and concentration were assessed by the nanotracking analysis system and morphology by transmission electron microscopy. Embryo development was recorded on Days 7/9. Day 7/8 blastocysts were assessed for quality by staining with (a) Hoechst 33342 (10 µgmL−1, 30min) for total cell number, (b) Bodipy 493/503 (20 µgmL−1, 1h) for lipid content (lipid droplet area in µm2), and (c) for survival rate after vitrification/warming. Data were analysed by one-way ANOVA and Tukey test. The EV concentration was 2.97 and 7.98×1010 particlesmL−1, and mode size 137.2 and 151.2nm for OF and UF, respectively. Transmission electron microscopy confirmed EV presence and size, showing typical cup-shaped morphology. Blastocyst yield was lower (P<0.05) on Day 7 in the BSA groups (BSA: 15.7±1.9 and BSAEV: 15.2.4%) compared with serum groups (dFCS: 28.1±2.6 and dFCSEV: 30.1±2.9%) irrespective of EV supplementation; however, these differences were compensated at Days 8 and 9 (range: 30.0±3.2-40.8±3.9%). The EVs increased (P<0.05) blastocyst total cell number in dFCSEV (152.6±2.9) and BSAEV (140.5±1.5) compared with dFCS (117.9±2.0) and BSA groups (122.4±1.1). However, lipid content was decreased (P<0.05) in the presence of EVs only in dFCSEV (0.231±0.05µm2) compared with BSA (0.393±0.03µm2) and BSAEV (0.379±0.03µm2) groups. The dFCS did not differ from any group (0.371±0.05µm2; P>0.05). Blastocyst survival after vitrification/warming was high in all groups up to 72h (range: 80.0±3.8-100%; P>0.05). In conclusion, mimicking physiological conditions using EV from OF and UF during invitro culture does not affect development but improves embryo quality by increasing blastocyst total cell numbers and decreasing lipid contents. These results provide evidence of the association of the reproductive tract environment and developing embryo, confirming embryo-maternal communication. Funding was provided by MINECO-Spain AGL2015-70140-R; Y. N. Cajas, SENESCYT-Ecuador; C. L. V. Leal, FAPESP-Brazil 2017/20339-3.

In vitro evaluation of novel low-pressure spark plasma sintered HA–BG composite scaffolds for bone tissue engineering

The low-pressure spark plasma sintering (SPS) technique is adopted to fabricate hydroxyapatite–bioglass (HA–BG) scaffolds while maintaining the physical properties of both components, including their bulk and relative density and hardness. However, prior to their orthopaedic and dental applications, these scaffolds must be validated via pre-clinical assessments. In the present study, scaffolds with different ratios of HA : BG, namely, 100 : 0 (HB 0 S), 90 : 10 (HB 10 S), 80 : 20 (HB 20 S) and 70 : 30 (HB 30 S) were fabricated. These scaffolds were characterized by investigating their physicochemical properties (X-ray diffraction (XRD) and surface wettability), bioactivity in a simulated body fluid (SBF) (field emission scanning electron microscopy (FESEM), Fourier-transform infrared spectroscopy (FTIR) and calcium dissolution), antimicrobial properties, biocompatibility and osteoinduction of human bone marrow-derived mesenchymal stromal cells (hBMSCs) and human monocyte immune cell response. The XRD and surface wettability results confirmed no formation of undesirable phases and the enhanced surface hydrophilicity of the scaffolds, respectively. The bioactivity in SBF indicated the formation of bone-like apatite on the surface of the scaffolds, corresponding to an increase in BG%, which was confirmed through FTIR spectra and the increasing trend of calcium release in SBF. The scaffolds showed inhibition properties against Staphylococcus aureus and Staphylococcus epidermidis. The scanning electron microscopy (SEM) micrographs and Alamar Blue proliferation assay indicated the good attachment and significant proliferation, respectively, of hBMSCs on the scaffolds. Alizarin Red S staining confirmed that the scaffolds supported the mineralisation of hBMSCs. The osteogenic protein secretion (bone morphogenetic protein-2 (BMP2), type-I collagen (COL1) and osterix (OSX)) was significant on the HB 30 S-seeded hBMSCs when compared with that of HB 0 S. The monocyte migration was significantly halted in response to HA–BG-conditioned media when compared with the positive control (monocyte chemoattractant protein-1: MCP-1). In conclusion, the HB 30 S composite scaffold has a greater potential to substitute bone grafts in orthopaedic and dental applications.

HB 30 S composite scaffold inhibits Staphylococcus spp., supports the biocompatibility and osteogenic differentiation of hBMSCs and resists monocyte migration.

Shape-from-focus for real-time terahertz 3D imaging

Thanks to significant advances in real-time terahertz imaging in terms of resolution and image quality, adapting and extending optical methods for 3D imaging at the millimeter scale is now promising. The shape-from-focus algorithm is a post-processing tool used in optical microscopy to reconstruct the external shape surface of a convex surface object. Images acquired at different distances from the object-side focal plane are implemented in this algorithm. We localize the best focus position in the stack of images for each pixel and then reconstruct the object in 3D due to the short depth of field. In this Letter, we propose an application of this algorithm in active and real-time terahertz imaging. We achieve the experimental reconstruction in 3D with a terahertz waves imaging system composed of a powerful source and a real-time terahertz camera.