Miracle-dz/UniFAR-FTUs huggingface dataset:
The Use of Bio-Inks and the Era of Bioengineering and Tooth Regeneration

Objective: To review existing literature and provide an update on the current use of Bio-Inks and potential future use. Material and Methods: A MeSH keyword search was conducted to find out relevant articles for this short review. Results: Bio inks used in 3D printing grafting require various properties essential for the selection. Combining multiple methods and improved properties is essential for developing successful bio-inks for 3D grafting of functional tissues and tooth pulp regeneration from stem cells. To date, researchers have made many efforts to grow teeth based on stem cells and inculcate regeneration of teeth along with surrounding tissues like alveolar bones and periodontal ligaments. Conclusion: 3D printing with Bio-Inks requires strict adherence to safety protocols for successful outcomes, making it difficult to employ this routinely.
Comparison of Palm Oil Fresh Fruit Bunches (FFB) Ripeness Classification Technique using Deep Learning Method

The ripeness of palm oil fruit is currently determined through manual visual inspection by palm oil estate workers that could result inconsistent and inaccurate fruit grading. Moreover, the manual inspection is time-consuming and exhausting duty for humans to complete the daily repetitive task. To overcome this issue, this paper proposes an automatic fruit grading classification by utilizing computer vision technologies. A comparison using image classification (ResNet50) and object detection (YOLOv3) technique is analysed in this work. It is clearly demonstrated that object detection model is remarkable in improving ripeness category based on the finer level of feature that has been extracted during the convolutional process.
Improving the entrepreneurial ecosystem through education: The influence of entrepreneurship education on students’ entrepreneurial intention in Morocco – A quantitative survey

ABSTRACT According to the Global Entrepreneurship Monitors 2020–2021 report, Morocco has very low rates of achievement in entrepreneurship education. Hence, considerable efforts remain to be made in this strategic area. Consequently, the research question of this article is: What is the influence of entrepreneurship education on the entrepreneurial intention of students in Morocco and more specifically in the region of Rabat-Sale-Kenitra? The empirical exercise relies on structural equation modeling based on data from 387 students from different universities. Results indicate that Ajzen’s theory of planned behavior is also valid in the Moroccan context. From a practical standpoint, this research can provide policy makers and academics with a better understanding of the phenomenon studied and provide them with guidance in program development by encouraging them to integrate entrepreneurship throughout their academic curriculum.
Curvature Emission and Absorption: Single Particle Treatment

Abstract The absorption counterpart of curvature emission is reexamined based on the Landau-Lifshitz approach. Early derivations led to the conclusion that maser emission is not possible, but these early derivations neglected a drift effect which was first discussed by Zheleznyakov and Shaposhnikov. When the drift effect is included, the derivation implies that curvature maser emission is possible. It is shown that for maser emission to be possible, the Lorentz factor needs to satisfy γ ≳ 103 for radius of curvature of the magnetic field lines RB ≈ 106 to 109cm and frequency ω ≈ 107 to 1011 s−1. Possible application to pulsars is discussed.
Application of arti ﬁ cial intelligence technologies in metallographic analysis for quality assessment in the shipbuilding industry

The necessity to improve the metallographic analysis systems to automate diagnostics of the condition of the metals for all their characteristics has been substantiated. The metallographic analysis algorithm based on the use of neural networks for recognizing metal microstructures and a case-based reasoning approach for determining the metal grade is proposed. The structure of a multilayer neural network to determine the metals quantitative parameters has been developed. The recognizing results by neural networks for determining the metal quantitative parameters are shown. The high accuracy of determining the metals quantitative parameters by neural networks is presented. The specialized metallographic software to automate the recognition of metal micro-structures and to determine the metal grade has been developed. Comparative results of carrying out metallo-graphic studies with the developed neural network software to determine the metals quantitative parameters are shown.
An Efficient Real-Time FPGA-Based ORB Feature Extraction for an UHD Video Stream for Embedded Visual SLAM

The detection and description of feature points are important components of many computer vision systems. For example, in the field of autonomous unmanned aerial vehicles (UAV), these methods form the basis of so-called Visual Odometry (VO) and Simultaneous Localisation and Mapping (SLAM) algorithms. In this paper, we present a hardware feature points detection system able to process a 4K video stream in real-time. We use the ORB algorithm—Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features)—to detect and describe feature points in the images. We make numerous modifications to the original ORB algorithm (among others, we use the RS-BRIEF instead of classic R-BRIEF) to adapt it to the high video resolution, make it computationally efficient, reduce the resource utilisation and achieve lower power consumption. Our hardware implementation supports a 4 ppc (pixels per clock) format (with simple adaptation to 2 ppc, 8 ppc, and more) and real-time processing of a 4K video stream (UHD—Ultra High Definition, 3840×2160 pixels) @ 60 frames per second (150 MHz clock). We verify our system using simulations in the Vivado IDE and implement it in hardware on the ZCU 104 evaluation board with the AMD Xilinx Zynq UltraScale+ MPSoC device. The proposed design consumes only 5 watts.
A multi-objective home healthcare routing problem

ABSTRACT As demand for home health care (HHC) services surges due to an aging population and public health constraints, HHC companies need to optimize their activities. Increasing costs to deliver care and the need to optimize the capacity of acute care settings such as hospitals, make the planning of HHC services more challenging. To optimally deliver care, the caregivers’ activities must be planned considering conflicting objectives. The proposed multi-objective HHC problem considers three components in the planning process: patients, nurses, and providers. An exact method is presented to efficiently solve a multi-objective HHC routing problem balancing the schedules of the nurses while maximizing quality of service (time windows, continuity, and consistency of care) and provider’s profit. A mixed-integer linear programming (MILP) model is formulated using the ϵ-constraint method and small- and medium-size problems are solved. Computational results on modified benchmark instances from the literature are used to test the method’s efficiency. A Pareto Frontier Analysis is used to evaluate optimality conditions for the provider, and it found that failing to satisfy the preferences of nurses has a larger impact on the provider’s bottom line. Furthermore, it was found that adjusting the patients’ preferences is not as taxing as adjusting the nurses’ preferences.
Incorporating Sulfur and CO2 Emission Reduction Options into the Container Fleet Capacity Renewal Alternatives for a Shipping Operator in the Post-COVID-19 Era

In this article, a cost-benefit decision framework is proposed to analyze the three alternative options of the container fleet capacity renewal for a ship operator. In this decision framework, the ship operator can trade off the following factors: MGO fuel or LNG option vessels, carbon neutrality, and other investment factors. The following variables are considered: the distance of the round trip, the prices of LNG and MGO, the freight rates of each option, and the initial investment ratios of new vessels. It was found that (1) the retrofitted vessels were more stable and suitable in an uncertain shipping market and have better investment potential. (2) The MGO option was the best option before the epidemic of COVID-19. In the postepidemic era, under the double carbon (carbon neutral and carbon peaking) policy, the advantage of low fuel consumption for the LNG ships disappeared due to the increase in LNG prices, and the NPV advantage of MGO ships becomes significant.
Principal Component Tracking for Massive MIMO Channels in High Mobility Scenarios With Diagonal Step Size Matrix

The present article proposes a novel adaptive algorithm with an optimal diagonal step size matrix for multi-dimensional channel principal component tracking in two dimensional massive multiple-input and multiple-output (M-MIMO) systems. First, we prove that the weighted subspace algorithm globally converges to the stationary stochastic process’ major eigenvectors. Then, using the maximum likelihood criterion, we optimize the weight coefficient matrix and derive the convergent condition for the step size range in order to maintain the algorithm stability. To accelerate the convergence, we initially suggest the diagonal step size matrix for multi-dimensional eigenvector tracking. Simultaneously, an optimal diagonal step size matrix is derived, which not only accelerates the convergence speed distinctively but also improves the tracking of multi-dimensional eigenvectors. Moreover, the transient behavior during the adaptation process is investigated in a straight-forward way and the relationship between the convergence time constant and the eigenvalues of the received signals is uncovered. Finally, simulations reveal that the proposed approach outperforms established algorithms such as Oja $^{\prime}\text{s}$ , Delmas and gradient descent algorithms. This approach establishes a sound foundation for tracking channel state information in M-MIMO systems with great mobility.
Antioxidant Potential of Some Plant Foods Commonly Consumed in Cameroon

Plant foods contain antioxidants and their efficiency in the management of non-communicable diseases like cancer, diabetes, cardiovascular diseases, and neurodegenerative diseases has long been proven. Nonetheless, the antioxidant potential of plant foods is continuously being studied with the aim of valorizing those foods that are still not well known. As such, the aqueous filtrates of forty-eight (48) plant foods currently consumed in Cameroon were screened for antioxidant potential. Their polyphenol content, ability to scavenge the 2,2’azinobis (3ethylbenzo-tiazoline-6-sulfonic acid) diammonium salt (ABTS) free radicals as well as their Ferric reducing antioxidant potential (FRAP) were assessed. Seven of these plant foods which exhibited very high antioxidant capacity in their filtrates were selected and their aqueous and hydroethanolic extracts prepared for antioxidant evaluation using six methods notably, FRAP, polyphenol, scavenging of ABTS, 1, 1-Diphenyl-2-Picrilhydrazyl (DPPH) and Nitric oxide (NO) free radicals as well as metal chelating capacity. It was found that; Raphia farinifera (Raffia fruit), Spondias cytherea Sonner (Casmango) fruit, Manihot utilissima (Cassava leaf), Solanum scabrum (small leaf Garden huckle berry), Cola verticillata (Bamiléké Kola) and Colocasia esculenta (Taro leaf) portayed very high antioxidant potential. The evaluation of their antioxidant capacity showed that all seven selected foods could be considered for studies related to the management of age-related diseases, especially R. farinifera, Cola verticillata and S. scabrum.
Improving Madden–Julian oscillation simulation in atmospheric general circulation models by coupling with a one-dimensional snow–ice–thermocline ocean model

Abstract. A one-column, turbulent, and kinetic-energy-type ocean mixed-layer model (snow–ice–thermocline, SIT), when coupled with three atmospheric general circulation models (AGCMs), yields superior Madden–Julian oscillation (MJO) simulations. SIT is designed to have fine layers similar to those observed near the ocean surface; therefore, it can realistically simulate the diurnal warm layer and cool skin. This refined discretization of the near-surface ocean in SIT provides accurate sea surface temperature (SST) simulation, and thus facilitates realistic air–sea interaction. Coupling SIT with the European Centre/Hamburg Model version 5, the Community Atmosphere Model version 5, and the High-Resolution Atmospheric Model significantly improved MJO simulation in three coupled AGCMs compared to the AGCM driven by a prescribed SST. This study suggests two major improvements to the coupling process. First, during the preconditioning phase of MJO over the Maritime Continent (MC), the often underestimated surface latent heat bias in AGCMs can be corrected. Second, during the phase of strongest convection over the MC, the change in intraseasonal circulation in the meridional circulation enhancing near-surface moisture convergence is the dominant factor in the coupled simulations relative to the uncoupled experiments. The study results show that a fine vertical resolution near the surface, which better captures temperature variations in the upper few meters of the ocean, considerably improves different models with different configurations and physical parameterization schemes; this could be an essential factor for accurate MJO simulation.
Tandem Mass Tag-Based Quantitative Proteomics Analysis of Gonads Reveals New Insight into Sexual Reversal Mechanism in Chinese Soft-Shelled Turtles

Simple Summary The Chinese soft-shelled turtle has obvious sex dimorphism, which is an important aquatic economic species in China. Exogenous hormones can cause the sexual reversal of P. sinensis, but the molecular mechanism remains unclear. Here, TMT-based quantitative proteomics analysis of four types of P. sinensis (i.e., female (F), male (M), pseudo-female (PF), pseudo-male (PM)) gonads were performed. We found that there were common pathways, such as focal adhesion, endocytosis, apoptosis, ribosome, and spliceosome, which both played crucial roles in two comparison groups, including F vs. PM and M vs. PF. Furthermore, these differentially expressed proteins were associated with various biological processes, such as embryonic development and catabolic process, which were closely related to the sexual reversal of P. sinensis. Abstract Chinese soft-shelled turtles display obvious sex dimorphism. The exogenous application of hormones (estradiol and methyltestosterone) can change the direction of gonadal differentiation of P. sinensis to produce sex reversed individuals. However, the molecular mechanism remains unclear. In this study, TMT-based quantitative proteomics analysis of four types of P. sinensis (female, male, pseudo-female, and pseudo-male) gonads were compared. Quantitative analysis of 6107 labeled proteins in the four types of P. sinensis gonads was performed. We identified 440 downregulated and 423 upregulated proteins between pseudo-females and males, as well as 394 downregulated and 959 upregulated proteins between pseudo-males and females. In the two comparisons, the differentially expressed proteins, including K7FKG1, K7GIQ2, COL4A6, K7F2U2, and K7FF80, were enriched in some important pathways, such as focal adhesion, endocytosis, apoptosis, extracellular matrix-receptor interaction, and the regulation of actin cytoskeleton, which were upregulated in pseudo-female vs. male and downregulated in pseudo-male vs. female. In pathways such as ribosome and spliceosome, the levels of RPL28, SRSF3, SNRNP40, and HNRNPK were increased from male to pseudo-female, while they decreased from female to pseudo-male. All differentially expressed proteins after sexual reversal were divided into six clusters, according to their altered levels in the four types of P. sinensis, and associated with cellular processes, such as embryonic development and catabolic process, that were closely related to sexual reversal. These data will provide clues for the sexual reversal mechanism in P. sinensis.
Dual‐mode and triple‐band 10‐antenna handset array and its multiple‐input multiple‐output performance evaluation in 5G

A 10‐element multiple‐input multiple‐output (MIMO) handset antenna array with triple‐band operation in the long‐term evolution band 42 (3400‐3600 MHz), band 43 (3600‐3800 MHz), and band 46 (5150‐5925 MHz) is studied in this article. Acceptable antenna performances are obtained by using polarization and pattern diversity techniques. To assess the multiplexing performances of the handset array in 5G, an 8‐element base station array covering 3.4‐7.1 GHz is presented and studied. An 8 × 10 MIMO system incorporating 8 transmit antennas, propagation scenario and 10 receive antennas is successfully reported, and its multiplexing performances are evaluated. The computed channel capacities in the low and high bands can be as high as 43.3 bps/Hz and 41.6 bps/Hz, which are promising for multi‐gigabit‐per‐second (multi‐Gbps) data transmission in 5G. The effects of user's hand and low MIMO order on the channel capacities are also investigated. Results show the robust performances of the proposed antenna system.
Low-Profile Uni-Cavity High-Gain FPC Antenna Covering Entire Global 2.4 GHz and 5 GHz WiFi-Bands Using Uncorrelated Dual-Band PRS and Phase Compensation AMC

A design methodology of the dual-band Fabry–Perot-cavity (FPC) antenna is proposed, realizing dual-broadband high gain and keeping the simplicity of one low-profile resonant cavity. A ray optics model is applied to obtain the phase resonance condition for dual-band FPC antennas. The proposed antenna employs a tightly stratified partial-reflective-surface (PRS), an artificial-magnetic-conductor (AMC) ground, and a dual-band microstrip feed. The PRS modulates independently the dual-band reflection coefficient to maintain a large amplitude and a positive phase gradient. Meanwhile, an AMC ground is distinctively employed to compensate for the transmission phase difference of the lower band when the cavity height meets half the wavelength of the upper one, enabling eventually a low-profile uni-cavity. Furthermore, a dual-band microstrip feed with two asymmetric slots is customized as the primary radiator. Detailed electromagnetic studies are carried out to illustrate the operating mechanisms of these components. Finally, a proof-of-concept prototype is fabricated covering the entire global 2.4 and 5 GHz WiFi bands. The measurement results agree well with the simulation, and the 3 dB gain bandwidths of 7.2% and 16.2% with peak gains of 13.6 and 15.0 dBi over two wide bands of 2.42–2.60 and 5.1–6 GHz are achieved, respectively, with a single cavity height of 26.8 mm.
An Eight-Port Planar Antenna for 3-D Beam Steering

An eight-port planar leaky-wave antenna (LWA) is proposed. This antenna has the capability of beam steering at an elevation angle by changing the frequency at eight azimuth angles. The antenna is planar and has an array of ring slots embedded in a microstrip parallel plate waveguide. We investigate the simulation and experimental results. The measured results have good agreement with the simulation and confirmed the leaky-wave (LW) concept. The proposed antenna yields an attractive, simple, and cost-effective beam scanning over the 3-D space.
Planning and Scheduling of High Rise Building Using Primavera

Planning and scheduling is important role in construction projects because of the increasing complexities in construction field. Construction Planning is the necessary warning to Scheduling and determining general sequence, defining labor tasks, construction methods and assigning responsibilities and cost overruns. Inappropriate planning can lead to major delays in the project work. For the planning and scheduling huge amount of paperwork is needed, this makes very difficult to handle large construction project through management. These problems can be solved using a project management software which helps to give a planned approach to planning. The benefits of effective planning, scheduling and control of construction projects are: reduced construction time, reduced cost overruns and the minimization of disputes. These benefits accrue to the contractors, owners, suppliers and workers in the form of improvements in productivity, quality and resource utilization. It helps to avoid the construction interruption, keep the continuity of crew work, and avoid the delay of construction and cost overruns.
Two Distributed Arithmetic Based High Throughput Architectures of Non-Pipelined LMS Adaptive Filters

Distributed arithmetic (DA) is an efficient look-up table (LUT) based approach. The throughput of DA based implementation is limited by the LUT size. This paper presents two high-throughput architectures (Type I and II) of non-pipelined DA based least-mean-square (LMS) adaptive filters (ADFs) using two’s complement (TC) and offset-binary coding (OBC) respectively. We formulate the LMS algorithm using the steepest descent approach with possible extension to its power-normalized LMS version and followed by its convergence properties. The coefficient update equation of LMS algorithm is then transformed via TC DA and OBC DA to design and develop non-pipelined architectures of ADFs. The proposed structures employ the LUT pre-decomposition technique to increase the throughput performance. It enables the same mapping scheme for concurrent update of the decomposed LUTs. An efficient fixed-point quantization model for the evaluation of proposed structures from a realistic point-of-view is also presented. It is found that Type II structure provides higher throughput than Type I structure at the expense of slow convergence rate with almost the same steady-state mean square error. Unlike existing non-pipelined LMS ADFs, the proposed structures offer very high throughput performance, especially with large order DA base units. Furthermore, they are capable of performing less number of additions in every filter cycle. Based on the simulation results, it is found that <inline-formula> <tex-math notation="LaTeX">$256^{\mathrm {th}}$ </tex-math></inline-formula> order filter with <inline-formula> <tex-math notation="LaTeX">$8^{\mathrm {th}}$ </tex-math></inline-formula> order DA base unit using Type I structure provides <inline-formula> <tex-math notation="LaTeX">$9.41 \times $ </tex-math></inline-formula> higher throughput while Type II structure provides <inline-formula> <tex-math notation="LaTeX">$16.68 \times $ </tex-math></inline-formula> higher throughput as compared to the best existing design. Synthesis results show that <inline-formula> <tex-math notation="LaTeX">$32^{\mathrm {nd}}$ </tex-math></inline-formula> order filter with <inline-formula> <tex-math notation="LaTeX">$8^{\mathrm {th}}$ </tex-math></inline-formula> order DA base unit using Type I structure achieves 38.76% less minimum sampling period (MSP), occupies 28.62% more area, consumes 67.18% more power, utilizes 49.06% more slice LUTs and 3.31% more flip-flops (FFs), whereas Type II structure achieves 51.25% less MSP, occupies 21.42% more area, consumes 47.84% more power, utilizes 29.10% more slice LUTs and 1.47% fewer FFs as compared to the best existing design.
Role of Microglia in Herpesvirus-Related Neuroinflammation and Neurodegeneration

Neuroinflammation is defined as an inflammatory state within the central nervous system (CNS). Microglia conprise the resident tissue macrophages of the neuronal tissue. Upon viral infection of the CNS, microglia become activated and start to produce inflammatory mediators important for clearance of the virus, but an excessive neuroinflammation can harm nearby neuronal cells. Herpesviruses express several molecular mechanisms, which can modulate apoptosis of infected neurons, astrocytes and microglia but also divert immune response initiated by the infected cells. In this review we also describe the link between virus-related neuroinflammation, and development of neurodegenerative diseases.