Ultrasonography is a relevant diagnostic tool extensively used andrology of human and do-mestic animals, including dogs. The present review aimed to describe all the technologies based on ultrasound, starting with the basic B-Mode ultrasonography to the recent contrast-enhanced ultrasonography (CEUS) and the ultrasound elastography, available to assess the testicle of the dog. The principles of the different technologies and the relevant findings in normal and ab-normal testicular conditions were described and discussed. B-mode ultrasonography aims at the examination of the testis detecting focal lesions but lacks objectivization. Other technologies, such as Doppler ultrasonography, B-Flow, and CEUS allow the definition of vascular patterns, that could be measured with specific applications, such as spectral Doppler or quantitative CEUS. Finally, ultrasound elastography allows the estimation of parenchyma stiffness, in both qualitatively and quantitatively manner. Ultrasound-based technologies assist the andrology in the evaluation of the testicular function and integrity, offering valuable information to define pathological conditions that could have an impact on the health and life quality of the male dog.

Future climate change is expected to affect components of the hydrological cycle. However geologic factors can sometimes be more important than the climate with regarding to change hydrological processes. The Keriya River is a large glacier-fed river in the western Tibet Plateau, its upper reaches flow across active fault zones, which have experienced four medium-sized earthquakes within four months 1974. These active faults have made difficult to identify normal meltwater changes using a snow-ice melt model. Because of the seismic events, the river has experienced substantial changes in their drainage systems and complex hydrological processes. Both the Mann-Kendall trend test and a correlation analysis were applied to detect the monthly patterns of stream flows, the change points and the correlations among both summer discharge and air temperature before and after seismic events. We found significant correlations between monthly air temperature and meltwater flow in the summer June during the pre-earthquake of 1958-1974, but none in July and August in the post-earthquake of 1975-1980, and we found no correlation following the earthquake. The correlations were the inverse by losing the former and setting up the latter alternately since the multiple earthquakes. Clearly, the earthquakes and changes in the faults can greatly induce hydrological processes.

Blood flow-restricted training (BFR) is constantly growing in popularity. Despite growing evidence of the significant influence of BFR training on different body functions, its impact on the vascular system, especially the arteries, is controversial. Therefore, the objective of our study was to analyze how BFR exercise, compared to other types of exercise without restriction of blood flow or other active intervention, influences arterial functions and angiogenesis in adults. Studies comparing the effect of BFR versus non-BFR training on arterial parameters are divided into three categories. Endothelial function, angiogenesis, and other vasculature functions. The search was based on three databases (Cochrane Library, PubMed®, Embase). In this systematic review, 38 studies were included. Meta-analysis revealed a more significant improvement in flow-mediated dilatation (FMD) (p=0.002) and the production of the primary angiogenesis biomarker Vascular Endothelial Growth Factor (VEGF) (p=0.009) after training in BFR compared to nonBFR (p=0.002). Analysis of pulse wave velocity, ankle-brachial index, systolic blood pressure, or heart rate did not show a significant difference in changes between BFR and non-BFR training. Other parameters examined were not sufficiently provided to be included in the meta-analysis. The results obtained, present trends suggesting the significant impact of BFR training on endothelial functions and angiogenesis. Unfortunately, there is still a lack of multicenter randomized clinical trials, including many participants, that are necessary to confirm the advantage of BFR over non-BFR activity.

CC chemokine receptor 6 (CCR6) is a member of the G protein-coupled receptor (GPCR) family that is highly expressed in B lymphocytes, effector and memory T cells, regulatory T cells, and immature dendritic cells. CCR6 has been revealed to have important functions in many pathological conditions, such as cancer, intestinal bowel disease, psoriasis, and autoimmune diseases. The only CCR6 chemokine ligand, CC motif chemokine ligand 20 (CCL20), is also involved in pathogenesis by interacting with CCR6. The CCL20/CCR6 axis is drawing attention as an attractive therapeutic target for various diseases. In this study, we developed novel monoclonal antibodies (mAbs) against human CCR6 (hCCR6) using the peptide immunization method, which are applicable to flow cytometry and immunohistochemistry. The established anti-hCCR6 mAb, clone C6Mab-19 (mouse IgG1, kappa), reacted with hCCR6-overexpressed Chinese hamster ovary-K1 (CHO/hCCR6), HepG2 (human liver carcinoma), and HuH-7 (human differentiated hepatoma) cells in flow cytometry. The dissociation constant (KD) of C6Mab-19 was determined as 3.0 × 10−10 M for CHO/hCCR6, 6.9 × 10−10 M for HepG2, and 1.8 × 10−10 M for HuH-7. Thus, C6Mab-19 could bind to exogenously and endogenously expressed hCCR6 with extremely high affinity. Furthermore, C6Mab-19 could stain formalin-fixed paraffin-embedded lymph node tissues from a patient with non-Hodgkin lymphoma by immunohistochemistry. Therefore, C6Mab-19 is suitable for detecting hCCR6-expressing cells and tissues, and could be useful for pathological analysis and diagnosis.

In recent years, functional fluidic electrohydrodynamic (EHD) pumps have attracted considerable attention due to their remarkable features, such as simple structure, quiet operation, and energy-efficient utilization. EHD liquid pumps can be used in various industrial applications, like flow transfer, thermal management, and actuator drive. In this paper, the author reviewed EHD liquid pump research in these specific aspects: the first observation of the EHD effect, its mathematical modeling, and the choice of pump structure, electrode configuration, and working medium. Based on the review, a summary of the development and latest research on EHD pumps can be provided for the readers.

A novel physiologically based algorithm (PBA) for fast CFD computation of Flow Fractional Reserve (FFR) in Coronary Artery Trees (CATs) is proposed and developed, which, unlike traditional methods, is based on the extension of the Murray’s law for blood vessels at the outlets and extra inlet conditions prescribed alternatively and iteratively. The PBA is then implemented in both SimVascular and Ansys CFD for testing and validation. For validation purpose, 3D models of CATs are built by using their CT images and computational meshes generated for mesh convergence study. Results obtained are then compared with Invasive Coronary Angiographic (ICA) data for validation and evaluation of its accuracy and computational efficiency. It is found that discrepancies between experimental and calculated values of pressure and flow rate at the inlet were less than 0.1% at the end of the 10^th round of iteration or less. Further validation shows that the difference between estimated and experimental FFR agree with each other with a maximum difference of 1.62% after convergence is achieved. The PBA is found to be a robust patient-specific and physiologically sound method that can be a good alternative to the existing Lumped Parameter Model (LPM) which is based on empirical scaling correlations using limited population-averaged data and requires nonlinear iterative computation for convergence.

This paper presents additional results of the generalized bathtub model for urban networks, including a simpler derivation and exact solutions for uniformly distributed trip lengths. It is shown that in steady state this trip-based model is equivalent to the more parsimonious accumulation-based model, and that the trip-length distribution has merely a transient effect on traffic dynamics, which converge to the same point in the macroscopic fundamental diagram (MFD). To understand the statistical properties of the system, a queueing approximation method is proposed to compute the network accumulation variance. It is found that (i) the accumulation variance is much larger than predicted by traditional queueing models, due to the nonlinear dynamics imposed by the MFD, (ii) the trip-length distribution has no effect on the accumulation variance, indicating that the proposed formula for the variance might be universal, (iii) the system exhibits critical behavior near the capacity state where the variance diverges to infinity. This indicates that the tools from critical phenomena and phase transitions might be useful to understand congestion in cities.

In geotechnical engineering applications, it is very important to obtain the undrained shear strength of remolded soils accurately and reliably. This study aims to obtain a trustworthy solution to determine the undrained shear strength of remolded clay mixtures using Atterberg limit test results in various states of consistency. An experimental study was carried out involving a wide range of clay mixtures of varying plasticity and geological origin. In the analyses, the variation of the remolded undrained shear strength depending on the cone penetration depth, water content, flow index, liquidity index and log liquidity index were investigated. In the study, the highest undrained shear strength of 100% Na-montmorillonite (NaM) was obtained at 171.89 kPa at 56.60% water content, while the lowest undrained shear strength was obtained for 100% Sepiolite (S), 9.28 kPa at 31.65% water content. The results of this study revealed that the shear strength is significantly affected by soil conditions, rather than dominant clay mineral. Besides, it was observed that the undrained shear strength at the plastic limit was approximately 30-35 times greater than that at liquid limit. The equations of liquid limit-flow index and plasticity index- flow index were proposed. It was concluded that the interdependence between undrained shear strength, liquidity index, log liquidity index, and flow index is not unique due to the different physical and chemical properties of clays.

Debris-flows are recurrent events on mountain- and hill- slopes, and they have been the object of numerous field investigations and sampling, however most of this work reposes on imagery and outcrop analysis, in such a way that there are still only a handful of studies investigating the internal architecture of these events’ deposits. In the present contribution, we aims at underneath the internal structure of a portion of a debris-flow deposit that was accessible in the aftermath of the 2018 heavy-rainfall debris-flows in Hiroshima Japan. Using a Ramac Pro-Ex GPR with 500 MHz and 800 MHz antenna, a set of longitudinal and transversal transects was used to characterize the deposit. The results demonstrated that a set of subhorizontal layers have filled the valley, and interacting with local terrace edges, these layers have piled up and overcome the obstacle. Across the valleys, a set of trough suggest the presence of channels that were also filled during the event. Finally, in the channel post-event, a set of radargram “cross-bedded units” shows that the final deposition in the channel was of a more dilute flow, typical of a Newtonian flow. This set of units was not to be found at the surface of the post-event pseudo-surface, suggesting that the flow ended as a debris-flow on this surface, and that it is only when the flow dug the final channel that the nature of the flow returned from debris-flow to Newtonian flow.

Biology is about structure. Structures within structures. Organs within animals, tissues within organs, cells within tissues, and molecules, often proteins within cells. The structures are so complex that they can only be described by numbers. No numbers are of more importance than those that describe proteins. The numbers that describe coordinates of its atoms, often determined by Patterson functions (which are inverse Fourier Transforms of intensities) of crystal diffraction. Without these numbers, structural biology would hardly exist. Without numbers, engineering would not exist. Numbers are surely needed by the engineers who produce the x-rays diffracting from atoms of protein crystals. Devices of engineering have function. They are built to implement equations. Engineering devices use structures to implement equations, when power is supplied at the right places, that produces appropriate flows. Flows are the essence of life. Equilibrium means death in most living systems. Flows in biological structures are hard to analyze because we do not know input output equations in advance. Sometimes we do not know their function. Flows, forces, and structures of life (like those of engineering) are related by field equations of conservation laws, partial differential equations, constrained by location and properties of structures. Constraints are boundary conditions located on the complicated domain of biological structure. Dealing with this complexity is simplified if one systematically analyzes structure using the most general field theory known, electricity described by the Maxwell equations, without significant known error. Currents are involved because flows of biology usually involve migration of charges, convection of water and solutes, diffusion of ions that form the plasma of life, and their interactions. Interactions can dominate function. Here I show how a few complex structures can be understood in engineering detail. This approach may be useful in dealing with biological and medical issues in many other cases. In one limited case—the clearance of a toxic waste (potassium ions) from the optic nerve—this approach seems to have succeeded.

Based on the textured controllable interface effect, the dynamic performances of the textured and ordinary pilot valve are analyzed experimentally, and the influence of the textured controllable interface on the response of pilot valve is studied. Results show that when Pin is small, the textured surface shortens the reciprocating time of valve core, increasing the flow rate, and speeds up the piston stroke of oil cylinder. The valve core actions much more stable and sensitivity. Meanwhile, combined with the theoretical calculation, the operation mechanism of texturing the pilot valve is analyzed. It is concluded that the stress of textured valve core sealing surface is greater than that of ordinary one, and the pressure difference gradually decreases with the increase of Pin, and the flow difference is basically the same as the force on the sealing surface. This indicates that the textured surface improves lubrication characteristics, reduces the friction between components. The textured valve makes the velocity changes gently, and enhances the responsiveness and stability of the valve. Those related results provide a new idea for enhancing the response design of the pilot valve.

Immune Checkpoint Inhibitors are monoclonal antibodies that are used to treat over one in three cancer patients. While they have changed the natural history of disease, prolonging life and preserving quality of life, they are highly active in less than 40% of patients, even in the most responsive malignancies such as melanoma, and cause significant autoimmune side effects. Licenced biomarkers include tumour Programmed Death Ligand 1 expression by immunohistochemistry, microsatellite instability, and Tumour Mutational Burden, none of which are particularly sensitive or specific. Emerging tumour and immune tissue biomarkers such as novel immunohistochemistry scores, tumour, stromal and immune cell gene expression profiling, and liquid biomarkers such as systemic inflammatory markers, kynurenine/tryptophan ratio, circulating immune cells, cytokines and DNA are discussed in this review. We also examine the influence of the faecal microbiome on treatment outcome and its use as a biomarker of response and toxicity.

This paper proposes a neural network which fuses the data received from a camera system on a gantry, to detect moving objects and calculate relative position and velocity of the vehicles traveling on a freeway, this information is used to estimate the traffic flow. To estimate the traffic flow at both microscopic and macroscopic view, this paper used YOLO v4 and DeepSORT for vehicle detection and tracking, then counting the number of vehicles pass through the freeway by drawing virtual lines and hot zones, also counting the velocity of each vehicles. The information is then pass to the traffic control center, in order to monitoring and control traffic flow on freeways, and analyzing freeway conditions.

Wood-borer extermination by a dry heat clean-up is the essential method from the point of view of sustainability of historical wooden structures like trusses and ceilings in heritage-listed buildings. The wooden components are heated by a hot air of temperature about 100°C until the temperature in the centre of the wooden structures reaches 55°C to kill the wood-borers. In this article we review the method and present solution of the heat equation for structural wooden components. We also suggest an approximate formula that enables to estimate the necessary heating time for different cross sections of wooden components and can be used in technical application of the method.

Cannabis is a flowering plant that has long been used for medicinal, therapeutic, and recreational purposes. Cannabis contains more than 500 different compounds, including a unique class of terpeno-phenolic compounds known as cannabinoids; Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) are the most prevalent cannabinoids and have been associated with the therapeutic and medicinal properties of the cannabis plant. In this paper, continuous flow microwave assisted extraction (MAE) is presented and compared with other methods for commercial cannabis extraction. The practical issues of each extraction method are discussed. The main advantages of MAE are: continuous-flow method which allows for higher volumes of biomass to be processed in less time than existing extraction methods, improved extraction efficiency leading to increased final product yields, improved extract consistency and quality because the process does not require stopping and restarting material flows, and ease of scale-up to industrial scale without the use of pressurised batch vessels. Moreover, due to the flexibility of changing the operation conditions, MAE eliminates additional steps required in most extraction methods, such as biomass decarboxylation, winterisation, which typically adds at least a half day to the extraction process. Another factor that sets MAE apart is the ability to achieve high extraction efficiency even at the industrial scale. Whereas the typical recovery of active compounds using supercritical CO¬2 remains around 70-80%, via MAE up to 95% of the active compounds from cannabis biomass can be recovered at the industrial scale.

Where genetic variation promoting speciation originates is a crucial question in evolutionary genomics. In a recent article, Marques et al. (2019) seek to address this question in lake and stream threespine stickleback fish from the Lake Constance (hereafter LC) basin in Central Europe. Based on population genetic methods, they conclude that incipient speciation between lake and stream stickleback was facilitated by the mixing of genetic variation from old lineages evolved in isolation (i.e., admixture following secondary contact). In this comment, I discuss conceptual and methodological problems and unrecognized conflicts with existing evidence that cast doubt on Marques et al.’s conclusion.

Hydroxychloroquine, a known antiviral metabolite of chloroquine, is increasingly used along with antibiotic azithromycin for the treatment of COVID-19 infection. In about one month India, the world’s largest manufacturer, delivered hydroxychloroquine for treating COVID-19 to over 50 countries. The therapy is being used across the world both for patients staying at home at the early phase of symptoms, as well as for patients hospitalized. We summarize achievements as of late April 2020, review possible modes of action and suggest avenues for the quick scale-up of production of hydroxychloroquine.

This paper updates earlier thoughts by the author on a putative electromagnetic propulsion system, to perform a more detailed energy balance. The previous paper demonstrated how momentum could be dumped to the ground state of the electromagnetic field but a claim was left somewhat hanging at the end of the previous paper, that the work done in changing the craft's velocity would effectively shift the centre of mass of the field - although that would be an infinitesimal shift in practice. The craft must always supply work to change velocity, such as by an accelerate/de-accelerate cycle and superficially this looks to violate the conservation of energy; we prove that this isn't so.

Due to metal leaching and poor catalyst stability, the chemical industry’s fine chemical and pharmaceutical sectors have been historically reluctant to use supported transition metal catalysts to manufacture fine chemicals and active pharmaceutical ingredients. With the advent of new generation supported metal catalysts and flow chemistry, we argue in this study, this situation is poised to quickly change. Alongside heterogenized metal nanoparticles, both single-site molecular and single-atom catalyst will become ubiquitous. This study offers a critical outlook taking into account both technical and economic aspects.

The Surface Water and Ocean Topography (SWOT) mission, to be launched in 2021, will provide water surface elevations, slopes, and river width measurements for rivers wider than 100 m. In this study, synthetic SWOT data are assimilated in a regional hydrometeorological model in order to improve the dynamics of continental waters over the Garonne catchment, one of the major French catchments. The aim of this paper is to demonstrate that the sequential assimilation of SWOT-like river depths allows the correction of river bed roughness coefficients and thus simulated river depths. An extended Kalman Filter is implemented and the data assimilation strategy was applied to four experiments of gradually increasing complexity regarding observation and model error over the 1995-2000 period. With respect to a “true” river state, assimilating river depths allows the proper retrieval of constant and spatially distributed roughness coefficients with a root mean square error of 1 m1/3 s-1, and the estimation of associated river depths. It was also shown that river depth differences can be assimilated, resulting in a higher root mean square error for roughness coefficients with respect to the true river state. The last study shows how one can take into account more realistic sources of SWOT error measurements, in particular the importance of the estimation of the tropospheric water content in the process.

Accurate and fast traffic flow forecasting is vital in intelligent transportation system because many of the advanced features in intelligent transportation systems are based on it. However, existing methods have poor performance regarding accuracy and computational efficiency in long-term traffic flow forecasting under big data. Hence, we propose an improved Long short-term memory (LSTM) Network and its cluster computing implementation in this paper to address the above challenge. We propose a singular point probability LSTM (SDLSTM) algorithm. The method discards the units of the network according to the singular point probability during the training process and amends the SDLSTM by Autoregressive Integrated Moving Average Model (ARIMA) to achieve the accurate prediction of 24-hour traffic flow data. Furthermore, the paper designs a scheme for implementing this method through cluster computing to shorten the calculation time and improve the system's operating speed. Theoretical analysis and experimental results show that SDLSTM gains a higher accuracy rate and better stability in the long-term traffic flow forecasting compared with previous methods.

Bio-separation of natural molecules as well as clinical compounds has been constantly developed in last decades. Several techniques are available but the majority of them presents drawbacks such us impossibility to be applied for industrial purposes. The main limitations for the scaling up are high costs and the fact that the devices work with microfluid dynamics. Nevertheless, magnetic bio-separation is considered the most prone to be used for large scale applications. Herein, we propose a simple magnetic separation method that is not based on microfluid dynamics, can work in a continuous- and high-flow rate and can be easily automated in order to be used for standard separation purposes. It is based on the use of an anisotropic flexible ferric magnetic strip, Teflon hoses and a pumping device. We show the modelling of the separation process along with an experimental test on iron oxide magnetic particles. The results showed that it is possible to remove, and separately collect, more than 92% of magnetic particles from a liquid solution of 100 ml in roughly 15 minutes.

Numerical simulations of turbulent flows in a stirred dead-end membrane bioreactor are performed by the RNG k-ε model based on finite volume method using Fluent codes. Comparisons of numerical and experimental results confirm the reliability and feasibility of the constructed model. Flow structures such as wake flows and circulation loops in stirred flows were well simulated. An increase of stirring speed is proposed to use to minimize the low velocity region. The single vane stirrer is found to be beneficial for biological separations. Results reveal that the increase of vane number can enhance the mixing effect in flow domains. However, a circular disk stirrer goes against the formation of vertical circulations. The six-vane stirrer is found to be able to provide a uniform distribution of high shear stress.

We present an exact expression for the upscaled dynamic dispersion coefficient (D) for one-dimensional transport by Hagen-Poiseuille flow which is the basis for modeling transport in porous media idealized as capillary tubes. The theoretical model is validated by comparing the breakthrough curves (BTCs) from a 1D advection-dispersion model with dynamic D to that from direct numerical solutions utilizing a 2D advection-diffusion model. Both Taylor dispersion theory and our new theory are good predictors of D at lower Peclet Number (Pe) regime, but gradually fail to capture most parts of BTCs as Pe increases. However, our model generally predicts the mixing and spreading of solutes better than Taylor’s theory since it covers all transport regimes from molecular diffusion, through anomalous transport, and to Taylor dispersion. The model accurately predicts D based on the early part of BTCs even at relatively high Pe regime (~62) where the Taylor’s theory fails. Furthermore, the model allows for calculation of the time scale that separates Fickian from non-Fickian transport. Therefore, our model can readily be used to calculate dispersion through short tubes of arbitrary radii such as the pore throats in a pore network model.

The consumption of rice, which recently increases globally, leads to requirement for planning sustainable water management for paddy cultivation. In this research, SWAT model was modified to evaluate sustainability of paddy cultivation. Modifications to simulate paddy cultivation are 1) to equip with a new water balance model of impounded fields, 2) to add an irrigation management option for paddy fields, which is characterized by flood irrigation managed by farmers on a daily basis, 3) to consider puddling operation that influences water quality and infiltration rate of soil. The enhanced model, named SWAT-PADDY, was applied to an agricultural watershed in Japan as a case study. The modified model succeeded in representing paddy cultivation in the study area. However, SWAT-PADDY underestimated base flow in irrigation period. The cause of this is inferred that the modified model doesn’t represent return flow of excess withdrawal of river water. In conclusion, addition of the models of impoundment and management practices in paddy fields to SWAT improved field scale simulation of water balance and irrigation in paddy fields. However, further improvement of the model on irrigation return flow process is needed to better predict hydrology of watersheds dominated by paddy irrigation.

A techno-economic model was developed to investigate the influence of components on the system costs of redox flow batteries. Sensitivity analyses were carried out based on a example of a 10 kW/120 kWh vanadium redox flow battery system and the costs of the individual components were analyzed. Particular consideration was given to the influence of material costs and resistances of bipolar plates and energy storage media as well as voltages and electric currents. Based on the developed model it was possible to formulate statements about the targeted optimization of existing battery systems and general aspects for future developments of redox flow batteries.

In this work, we analyzed non-Darcy two-component single-phase isothermal flow in naturally fractured tight gas reservoirs for enhanced gas recovery (EGR) and carbon dioxide storage as a possible application. We used the Peng-Robinson equation of state to evaluate the thermodynamic properties of the components, and we performed the discretization of the governing partial differential equations using the Finite Volume Method. This process leads to two subsystems of algebraic equations, which, after linearization and use of an operator splitting method, are solved by the Conjugate Gradient (CG) and Biconjugate Gradient Stabilized (BiCGSTAB) methods for determining the pressure and fraction molar, respectively. We include inertial effects using the Barree and Conway model, gas slippage via a more recent model than Klinkenberg’s and we use a simplified model for the effects of effective stress. We also utilize a mesh refinement technique to represent the discrete fractures. Finally, we implemented simulations to show the influence of inertial, slippage and stress effects on production in fractured tight gas reservoirs.

Dam breaches have catastrophic consequences, causing severe property damage, life loss, and environmental impact. The Kulekhani reservoir rockfill dam break was studied to evaluate the downstream impact. The appropriate breaching parameter of MacDonald and Langridge (1984) regression equations was selected based on the sixteen observed dam failure cases and cross-sectional geometry of the existing dam of Kulekhani. The 2D Diffusion Wave and Full Dynamic Wave Equation were applied for downstream flood assessment, Full Dynamic Wave was able to capture the physical flow phenomena like river bend effects resulting in higher flow velocity at the outer bend, and formation of eddies considering losses. The application of a Full Dynamic Equation was found to be appropriate for rapidly varying unsteady flow considering steep slopes, and sudden changes in channel geometry. Flood mapping of water depth, flow velocity, flood intensity, and arrival time were carried out for flood hazard assessment classified by the American Society of Civil Engineers (ASCE). Flow depth and extension of the flow area were compared to identify the affected area, higher flow depth and larger extension were observed using a Full Dynamic Wave Equation as a result of less flow velocity considering the losses. Almost 17 minutes of the arrival time of peak difference at the Bagmati River confluence was evaluated between the models which plays an important role in decision-making for selection of the flood model. Flood mitigation with river diversion works through a hydraulic measure of Levee was suggested to protect the highly affected households of Ranche, Nagmar, Khanikhet, and Debaltar towns. Most of the household was found to be safe after the construction of the Levee except for eleven houses that lie along the river below flood elevation of 1269.6 m.a.s.l. This signifies the importance of room for the rivers and the human settlement near the river might be life-threatening.

In this work, we focus on investigating electrothermal flow in a rotating electric field (ROT-ETF), with primary attention paid to the horizontal traveling-wave electrothermal (TWET) vortex induced at the center of the electric field. The frequency-dependent flow profiles in the microdevice are analyzed using different heat transfer models. Accordingly, we address in particular the importance of electrode cooling in ROT-ETF as metal electrodes of high thermal conductivity while substrate material of low heat dissipation capability are employed to develop such microfluidic chips. Under this circumstance, cooling of electrode array due to external natural convection on millimeter-scale electrode pads for external wire connection occurs and makes the internal temperature maxima shift from the electrode plane to a bit of distance right above the cross-shaped interelectrode gaps, giving rise to reversal of flow rotation from a typical repulsion-type to attraction-type induction vortex, which is in good accordance with our experimental observations of co-field TWET streaming at frequencies on the order of reciprocal charge relaxation time of the bulk fluid. These results point out a way to make a correct interpretation of out-of-phase electrothermal streaming behavior, which holds great potential for handing high-conductivity analytes in modern microfluidic systems.

Three-dimensional convolutional neural networks (3D CNN) as a type of artificial intelligence (AI) are powerful in image processing and recognition using deep learning to perform generative and descriptive tasks. The advantage of CNN compared to its predecessors is that it automatically detects the important features without any human supervision. 3D CNN are used to extract features in three dimensions where input is a 3D volume or a sequence of 2D pictures e.g., slices in a cone-beam computer tomography scan (CBCT). The main aim of this article was to bridge interdisciplinary cooperation between forensic medical experts and deep learning engineers. With emphasis activating clinical forensic experts in the field with possibly basic knowledge of advanced artificial intelligence techniques with interest in its implementation in their efforts to advance the forensic research further. This paper introduces a novel workflow of 3D CNN analysis of full-head CBCT scans. Authors explore and present 3D CNN method for forensic research design concept in five perspectives: (1) sex determination, (2) biological age estimation, (3) 3D cephalometric landmark annotation, (4) growth vectors prediction, (5) facial soft-tissue estimation from the skull and vice versa. In conclusion, 3D CNN application can be a watershed moment in forensic medicine, leading to unprecedented improvement of forensic analysis workflows based on 3D neural networks.

Acute kidney injury (AKI), especially if recurring represents a risk factor for future chronic kidney disease. In intensive care units, increased intraabdominal pressure is well-recognized as a significant contributor of AKI. However, the importance of transiently increased intra-abdominal pressures procedures is less commonly appreciated during laparoscopic surgery, the use of which has rapidly increased over the last few decades. Unlike the well-known autoregulation of the renal cortical circulation, medulla perfusion is modulated via partially independent regulatory mechanisms and strongly impacted by changes in venous and lymphatic pressures. In our review paper, we will provide a comprehensive overview of this evolving topic, covering a broad range from basic pathophysiology up to and including current clinical relevance. Key regulators of oxidative stress such as ischemia-reperfusion injury, the activation of inflammatory response and humoral changes interacting with procedural pneumoperitoneum formation and AKI risk will be recounted. Moreover, we present an in-depth review of the interaction of pneumoperitoneum formation with general anesthetic agents and animal models of congestive heart failure. A better understanding of the relationship between pneumoperitoneum formation and renal perfusion will support basic and clinical research, leading to improved clinical care and collaboration among specialists.

The coronavirus disease caused by SARS-CoV-2 (known as COVID 19) is highly contagious and has spread rapidly over 200 countries over last three months. WHO suggested urgent escalation in testing, isolation and contact tracing, as the "backbone" of managing the pandemic. Globally, the detection of SARS-CoV-2 in patients are done by RT-PCR and blood antibody-based testing. In addition to the existing processes, flow-cytometry could be used as a high-throughput and efficient diagnostic method for detection of COVID 19. The suspected COVID 19 samples can be analyzed using ‘Indirect flow cytometry’, with the specific primary antibody and fluorescent tagged secondary antibodies. The fluorescence signal can distinguish the infected v/s non-infected samples. In the present article, we have summarized the applications of Flow virometry to study various viruses and have proposed possible application in the detection of COVID 19.

Camouflage is a natural or artificially process to prevent an object from being detected while camouflage breaking is a countering process for the identification of the concealed object. We report that a perfectly camouflaged object in a two-dimensional scene can be retrieved and detected with stereo-vision assisted three-dimensional (3D) imaging perceived with stereopsis. The analysis is based on binocular energy model applied to general 3D settings. We show that a perfectly concealed object with random noise background can be retrieved with vision’s stereoacuity to resolve the hidden structures. The theoretical analysis is further tested and demonstrated with distant natural images taken by a drone-camera, processed with a computer and displayed in an autostereoscopy. The recovered imaging is presented with removal of the background interference to demonstrate the general applicability for camouflage breaking with stereo imaging and sensing.

In the present investigation, the crank-slider and crank-rocker off-center mechanisms are used to control 1-DOF in a solar tracker focused on improving the conversion of solar to electrical energy. Likewise, the kinematic equations of these mechanisms are presented that allow us to know their operating pattern in the work range of the follower and their comparative analysis between them. Finally, the scale construction with 3D printing is shown to verify the functionality of each 4-bar system.

The monocular structured light measurement system has low cost, simple algorithms, and a wide measurement range, making it widely applicable in multiple fields. However, in practical applications, the system may be affected by various factors including noise, non-linear intensity, changes in the reflectivity of the object being measured, and the calibration method and accuracy of the system, thereby reducing the measurement accuracy. In order to solve these issues, this paper proposes a new monocular structured light measurement method, mainly comprises the following two points: (a) A denoising algorithm for phase images based on DAE is proposed, which calculates the wrapped phase of the phase-shifted fringes after initial denoising by DAE. Then, a new phase-shifted fringe pattern is generated and input into DAE for iterative denoising, achieving high-performance image denoising and high-precision wrapped phase solution. (b) A new absolute phase height calibration algorithm is proposed, which introduces camera internal and external parameters and uses a two-layer feedforward network to directly establish the relationship between phase and the 3D coordinate system. Without the need for high-precision motion platforms, high-precision phase height calibration is attainable. In general, compared to conventional methods, the experimental results indicate the effectiveness of the proposed method for low-quality phase-shifted fringe 3D reconstruction. In addition, the measurement method described in this article also demonstrates effectiveness in high-dynamic scenes.

Diagnosing congenital heart disease (CHD) remains challenging because of its complex morphology. Representing the intricate structures of CHD on conventional two-dimensional flat screens is difficult owing to wide variations in the pathologies. Technological advancements, such as three-dimensional printed heart models (3DPHM) and virtual reality (VR), could potentially address the limitations of viewing complex structures using conventional methods. This study aimed to investigate the usefulness and clinical value of four visualization modalities across three different cases of CHD, including ventricular septal defect, double outlet right ventricle, and tetralogy of fallot. Seventeen cardiac specialists were invited to participate in this study, which was aimed at assessing the usefulness and clinical value of four visualization modalities, namely, DICOM images, 3DPHM, VR, and 3D PDF. Of these modalities, 76.4% of the specialists ranked VR as the best for understanding the spatial associations among cardiac structures and for presurgical planning. Meanwhile, 94.1% ranked 3DPHM as the best modality for communicating with patients and their families. Of the various visualization modalities, VR was the best tool for assessing anatomical locations and vessels, comprehending the spatial relationships among cardiac structures, and for presurgical planning. The 3DPHM models were the best tool for medical education as well as communication. In summary, both 3DPHM and VR have their own advantages and outperform the other two modalities, i.e., DICOM images and 3D PDF, in terms of visualizing and managing CHD.

Digital twin technology is revolutionizing traditional manufacturing paradigms. In modern manufacturing systems, digital twin technology is fraught with challenges due to the scarcity of labeled data. Specifically, existing supervised machine learning algorithms, with their reliance on voluminous training data, find their applicability constrained in real-world production settings. This paper introduces an unsupervised 3D reconstruction approach tailored for industrial applications, aimed at bridging the data void in creating digital twin models. Our proposed model, by ingesting high-resolution 2D images, autonomously reconstructs precise 3D digital twin models without the need for manual annotations or prior knowledge. Through comparisons with multiple baseline models, we demonstrate the superiority of our method in terms of accuracy, speed, and generalization capabilities. This research not only offers an efficient approach to industrial 3D reconstruction but also paves the way for the widespread adoption of digital twin technology in manufacturing.

This study extends the CGAN-based MODIS cloud vertical-profile (64×64-scene, about 70km width×15km height) retrieval technique developed by Leinonen et al. (2019) [1] to construct seamless 3D cloud fields for the MODIS granules [2]. Firstly, the accuracy and spatial continuity of the Leinonen et al. [1] retrievals are statistically evaluated. Then, according to the characteristics of the retrieval error, a spatially overlapping-scene ensemble generation method and a bi-directional Ensemble Binning Probability Fusion (CGAN-BEBPF) technique are developed, which improves the CGAN retrieval accuracy and support to construct seamless 3D clouds. The CGAN-BEBPF technique involves three steps: cloud masking, intensity scaling, and optimal value selection. It ensures adequate coverage of the low reflectivity areas while preserving the high reflectivity cloud cores. The technique is applied to retrieve the 3D cloud fields of Typhoon Chaba and a multi-cell convective system. The cloud structures of the CGAN-BEBPF results are highly consistent with the ground-based radar observations. It can retrieve weak clouds at the top levels of convective storms and hurricanes that were missed by ground-based radars and fill the gaps of the ground-based radar lower-level PPI scan. Overall, CGAN-BEBPF can be automated to retrieve the rich informative 3D structures of typhoons and severe convective systems over the oceans along the MODIS swath, which certainly presents great value for improving maritime and near-shore typhoons and convection prediction and other cloud-sensitive applications.

Shigella and Salmonella have been implicated in neonatal sepsis, food poisoning, and bacteremia. Their increasing resistance to antibiotics has undermined treatment options, constituting a public health crisis. Also, the scarcity of new antibiotics in the development pipeline compounds multidrug-resistance (MDR). Hence, there is a need to potentiate antibiotics to mitigate resistance. This study leveraged riboflavin to re-sensitize fluoroquinolones and carbapenems against MDR Shigella and Salmonella spp. Disk diffusion, microbroth-dilution, chequerboard, and time-kill assays were used to determine resistance profiles and riboflavin-antibiotic activity. Biofilm-formation and bacterial viability (after riboflavin-antibiotic challenge) was determined with crystal-violet and Macrophage infection assays, respectively. Strains exhibited >80% resistance to fluoroquinolones and carbapenems, with 160–320 µg MIC ranges and 0.5–2 FIC, indicating no synergy. At 40–80 µg riboflavin, there was two-fold reduction in bacterial survival, with meropenem-riboflavin exhibiting significant reduction and FIC of 0.075 indicating high synergistic activity. Biofilm-formation was altered (from strong to weak phenotype) with 40 µg riboflavin-antibiotic treatment. There was a 40–70% reduction in bacterial survival in THP-1 cells treated with meropenem-riboflavin after 3 hours, and complete clearance between 24-48 hpi. Riboflavin potentiated fluoroquinolones and meropenem, leading to modulation of the host immune response for the clearance of the strains.

RFID based technology innovated a new field of wireless sensing, which has been applied in posture recognition, object localization and the other sensing fields, the existing sensing methods often require tags to be attached to dynamic targets (because RFID signals are more sensitive to moving target), significantly limiting their applications. It is a challenging task to sensing a static target without tag attached in NLOS (Non-Line-of-Sight). We utilized RFID technologies to sense the static foreign objects in agricultural products, and taken metal, rock, rubber and clod as sensing targets that are common in agricultural. By deploying a tag matrices to create a sensing region, we observed the signal variations before and after the appearance of the targets in this sensing region, determined the targets’ positions and their types. Here, we buried the targets in the media of seedless cotton and wheat, and detected static targets with a non-contact method in the NLOS. Researches illustrated that by deploying appropriate tag matrices and adjusting the angle of a single RFID antenna, the matrices signals can be sensitive to the static targets’ positions and their properties,i.e. matrices signals vary with different targets and their positions. Specifically, we achieved a 100% success rate in locating metallic targets, while the success rate for clods was the lowest at 86%. We achieved a 100% recognition rate for the types of all the four objects.

Aqueous Zinc ion batteries (ZIBs) possess significant potential in large energy storage systems due to their cost-effectiveness and environmental protection. However, the limited voltage window and poor reaction kinetics of the cathode material are still bottlenecks, restricting the further development of ZIBs. In this work, we rationally design Ni-doped V2O5@3D Ni core/shell composite on carbon cloth electrode (Ni-V2O5@3D Ni@CC) by growing Ni-V2O5 on the free-standing 3D Ni metal nanonets for high-voltage and high-capacity ZIBs. Impressively, the embedded Ni doping increases the interlayer spacing of V2O5, extending the working voltage and improving the Zn2+ kinetics reaction of the cathode materials, at the same time the 3D structure with high specific surface area and superior electronic conductivity benefits to fast Zn2+ transport. Consequently, the as-designed Ni-V2O5@3D Ni@CC cathodes can operate within a wide voltage window from 0.3 to 1.8 V vs. Zn/Zn2+ and deliver a high capacity of 270 mAh g-1 at a high current density of 0.8 A g-1. In addition, the reversible Zn2+ (de)-incorporation reaction mechanisms in the Ni-V2O5@3D Ni@CC cathodes are investigated by multiple characterization methods. As a result, we achieve a big step toward the practical applications of commercial ZIBs.

Advancements in 3D printing technologies have led to new implementations in rapid prototyping, microfluidics, tooling, dentistry, biomedical devices, drug delivery, and tissue engineering. Stereolithography techniques, which are photopolymerization-based processes, contribute to the optical, chemical, and mechanical properties of 3D printed materials using versatile polymer chemistry. This study used potassium titanate powder (K2Ti8O17) as an additive to enhance the mechanical strength of photocurable resins. PEG was selected as the stabilizer to optimize the dispersion and precipitation of potassium titanate. The flexural strength, hardness, and tensile strength were compared to assess the mechanical strength of the 3D printing resin. The flexural strengths of the printed specimens were in the range of 15–39 N/mm2. The measured surface hardness and tensile strength were 41–80 HV and 2.3–15 N/mm2, respectively. The output resolution of the potassium titanate/acrylate resin was tested using a line-pattern structure. 3D printing resin without stabilizers produced lines with a thickness of 0.3 mm, whereas 3D printing resin containing a stabilizer produced lines with a thickness of 0.2 mm. The flexural strength and pattern thickness results suggest that the potassium titanate/acrylate resin can be utilized as a 3D printer resin, suggesting new possibilities for potassium titanate materials.

The future of intelligent manufacturing machines involves autonomous selection of process parameters to maximize productivity while maintaining quality within specified constraints. To effectively optimize process parameters, these machines need to adapt to existing uncertainties in the physical system. This paper proposes a novel framework and methodology for feedrate optimization that is based on a physics-informed data-driven digital twin with quantified uncertainty. The servo dynamics are modeled using a digital twin, which incorporates the known uncertainty in the physics-based models and predicts the distribution of contour error using a data-driven model that learns the unknown uncertainty on-the-fly by sensor measurements. Using the quantified uncertainty, the proposed feedrate optimization maximizes productivity while maintaining quality under desired servo error constraints and stringency (i.e., the tolerance for constraint violation under uncertainty) using a model predictive control framework. Experimental results obtained using a 3-axis desktop CNC machine tool and a desktop 3D printer demonstrate significant cycle time reductions of up to 38% and 17% respectively, while staying close to the error tolerances compared to the existing methods.

The present work fronts the human pose estimation problem, developing a method that enables automated ergonomic risk assessment. A research methodology is developed to calculate joint angles from digital snapshots or videos by using computer vision and machine learning techniques to get a more accurate ergonomic risk assessment. Starting from an ergonomic analysis, the study explores the use of a semi-supervised training method to detect the skeletons of workers. The research methodology developed aims to infer the positions and angles of the joints, to calculate the criticality index based on the RULA scores and fuzzy rules. Then, to prevent work-related musculoskeletal disorders (WMSD), improve production capacity and decrease the ergonomic risk, the system uses joint with a collaborative robot to support the worker in carrying out the most critical operations. The method has been tested on a real industrial case in which manual assembly activities of electrical components are conducted. The approach developed can overcome the limitations of recent developments based on computer vision or wearable measurement, sensors by performing an assessment with an objective and flexible ap-proach to postural analysis development.

Introduction: There is no standardised, universal method to assess physical conditions such as pressure in the pelvicalyceal system in real time during RIRS (retrograde intrarenal surgery). Therefore, the problem concerning increased pressure in the upper urinary tract during the procedure is underestimated. Moreover, it potentially may cause micro-damage and longer postoperative recovery. The aim of this study was to evaluate intrapelvic pressure (IPP) during RIRS procedures. Materials and methods: The 3D printed models of the pelvicalyceal system were printed based on CT-scan of real patient. They were used to perform 50 RIRS procedures with laser lithotripsy of artificially synthesised kidney stones with two different sizes of ureteral access sheath-UAS (10/12Fr vs. 12/14Fr) together with different energy settings generated by the holmium:YAG laser. IPP monitoring during RIRS was performed with the use of the PressureWire X Guidewire compatible with the CoroFlow system. Results and Conclusions: The results showed that high IPP of up to 400 cmH2O would be achieved using a 10/12Fr UAS, while the use of a 12/14Fr UAS would significantly reduce the peak pressure to approximately 100 cmH2O, hence the size of the UAS is a pivotal factor of the IPP generated during the procedure.

3D printing technology has brought about a paradigm shift in the delivery of clinical care in medicine and dentistry. There are several different 3D printing technologies, which, along with different printable materials with unique biomechanical properties, allows for a wide range of applications for 3D printing in dentistry. The clinical use of 3D printing has created versatile applications which streamline our digital workflow. Technological advancements have also paved the way for the integration of new dental materials in dentistry. This paper provides an overview of the mechanisms of 3D printing, the dental materials relevant to each mechanism and the possible applications of these materials within different areas of dentistry. Understanding the existing spectrum of 3D printing applications in dentistry will serve to further expand its use in the dental field.

Forests play a pivotal role within the ecological milieu, with alterations to forested areas not only impacting the local environment but also serving as a significant contributing factor to the occurrence of landslide disasters. However, the significance of forests in connection with deep seated landslides is diminished. In instances of extreme events, heavy rainfall, highly weak slopes, or seismic events, it is improbable for forest cover to exert any influence. Due to extensive agricultural irrigation, the Heifangtai terrace of China has experienced a significant rise in groundwater levels, leading to the occurrence of numerous landslides. Through field investigations and remote sensing interpretation, this study has revealed dramatical geomorphological changes in the Heifangtai terrace due to the occurrence of widespread landslides. These changes are likely to disrupt the pre-existing hydrological balance within the study area, thereby altering the conditions for landslides. Therefore, understanding how the evolution patterns of loess landslides can be assessed is a crucial scientific issue for predicting the conditions of landslide occurrence. Taking the evolution of landslides along the edge of the Heifangtai terraces as an example, this study first classified different types of loess landslides. Subsequently, the temporal and spatial distribution characteristics of these landslides were analyzed. Finally, utilizing the FLAC3D software, the stability of the loess slopes at the edge of the Heifangtai terrace was examined under the lateral evolution mode. The research findings indicate that the current loess landslides in the Heifangtai terrace exhibits longitudinal multi-periodicity and lateral group-occurring behavior, which is significant for assessing loess landslides along the edge of Heifangtai terraces.

Printed oral splints are a therapeutic alternative in the treatment of functional disorders. Their mechanical properties are crucial to their clinical success and their performance can vary depending on cleaning, post-polymerization, or build orientation. This in vitro study aimed to compare the biaxial flexural strength of the chosen materials depending on the aforementioned parameters. 720 discs (n = 15 per group, 16 mm x 2 mm) were printed from splint materials. Printing was performed under 90°, 45°, or 0° orientation to the building platform with supporting structures. Specimens were either automatically or manually cleaned with isopropanol. Post-polymerization was performed with LED- or Xenon-light. Biaxial flexural strength (BFS) was determined with a piston-on-3-ball test after 24 hours or 60 days water storage (37°C). Test specimens were preloaded with 0.5 N and the load was applied by a piston of 1.6 mm in diameter at 1 mm/min crosshead speed. Statistics were performed by using descriptive statistics, ANOVA, and Levene-tests. Mean BFS after 24 hours of storage varied between 79 MPa and 157 MPa. After 60 hours the BFS significantly decreased and revealed values ranging from 72-127 MPa (mean24 113 MPa, mean60 97 MPa; p<0.001). No significant differences could be determined between the materials (p=0.103) or between the different cleaning procedures (p=0.321). Post-polymerization yielded higher means with LED- (P1: 115 MPa) than with Xenon-light (P2: 95 MPa; p<0.001). Regarding position, the mean values ranged from 101 MPa for 0°, 102 MPa for 45°, and 115 MPa for 90°, which was significantly different (p<0.001). Build orientation of 90° and post-polymerization with LED-light provided significantly higher biaxial flexural strength and should be used to guarantee optimal strength of splint materials. Aging decreased the biaxial flexural strength of the tested specimens.

Traditional lithium-ion batteries cannot meet the high flexibility and bendability requirements of modern flexible electronic devices due to the limitations of their electrode materials. Therefore, the development of high-performance flexible energy storage devices is of great significance for promoting flexible electronics. In recent years, one-dimensional flexible fiber lithium-ion batteries have been rapidly developed due to the advantages of high flexibility and bendability. However, it is still a big challenge to realize 1D flexible fiber lithium-ion batteries with excellent electro-chemical properties and good mechanical performance. In this work, a reduced graphene ox-ide-based printing ink is proposed to fabricate flexible Li4Ti5O12/graphene fiber electrodes through a 3D printing assembly strategy. It is noteworthy that the green reducing agent vitamin C was used to reduce graphene oxide in one step, which improved the conductivity of the fiber elec-trode. Furthermore, a 3D conductive network is constructed inside the fiber electrodes due to the high specific surface area of reduced graphene oxide, which enhances the electronic conductivity and ion mobility. The fiber electrode not only has good mechanical performance, but also has ex-cellent electrochemical properties. Equally important, the method is simple and efficient, and the working environment is flexible. It can precisely control the shape, size and structure of the one-dimensional fiber flexible electrode, which is of great significance for the development of fu-ture flexible electronic devices.

The research on calcium leaching of 3D printed cement pastes (3DPC) exposed in aggressive water is limited, and the mechanism underlying its effect needs to be better understood. The performance anisotropy of degraded 3DPC due to calcium leaching is investigated in this paper. Samples with aggregate micro fines (AMF) and fly ash (FA) were prepared. A 6 mol/L NH₄Cl solution was used in the accelerated experiment. At specific leaching durations, performances were tested on the samples in different leaching directions. Results show that the performances of 3DPC in aggressive water have a significant anisotropic behavior. The evolution of pore defects and hydration products mainly governs the performance anisotropy of degraded 3DPC. The remaining hydration products of the surface of 3DPC leached in the Z direction are less than the other two directions because calcium ions leached in the Z direction are difficult to be compensated through weak interfaces between layers.

Background: Our objective was to conduct a comprehensive analysis of the reproducibility of foot and ankle anthropometric measurements with a three-dimensional (3D) optical scanner. Methods: We evaluated thirty-nine different anthropometric parameters obtained with 3D Laser UPOD-S Full-Foot Scanner in a healthy population of twenty subjects. We determined the variance of the measurements for each foot/ankle, and the average variance among different subjects. Results: For 40 feet and ankles (15 women and 5 men; mean age 35.62 +/- 9.54 years, range 9-75 years), the average variance was 1.4 ± 2 (range 0,1 to 8). Overall, the mean absolute measurement error was < 1 mm, with a maximum variance percentage of 8.3%. Forefoot and midfoot circumferences had a low variance < 2.5, with variance percentages < 1%. Hindfoot circumferences, malleolar heights, and the length of the first and fifth metatarsal to the ground contact points showed the highest variance (range 1 to 7). Conclusion: This optical scanner achieved a good reproducibility of a large set of foot and ankle anthropometric measurements. It is a valuable tool for clinical and research purposes.

High-performance electromagnetic interference (EMI) shielding materials with ultralow density and environment friendly properties are greatly demanded to address electromagnetic radiation pollution. Herein, carbon nanotubes/polylactic acid (CNTs/PLA) materials with different CNTs contents, which exhibit characteristics of light weight, environmental protection and good chemical stability, are fabricated by 3D printing technology, where CNTs are evenly distributed and bind well with PLA. The performances of 3D printed CNTs/PLA composite are improved compared to pure 3D printed PLA composite, which include mechanical properties, conductive behaviors and electromagnetic interference (EMI) shielding. The EMI shielding effectiveness (SE) of CNTs/PLA composite could be improved when the contents of CNTs increase. When it reaches 15 wt%, the EMI SE of 3D printed CNTs/PLA composite could get up to 47.1 dB, which shields 99.998% of electromagnetic energy. Meanwhile, the EMI shielding mechanism of 3D printed CNTs/PLA composite is mainly of absorption loss, and it generally accounted for more than 80% of the total shielding loss. These excellent comprehensive performances endow the 3D printed CNTs/PLA composite with great potential for use in industrial and aerospace area.

This research focused on the perception of visually impaired individuals regarding tactile image creation using 3D printing. We developed and applied an experiment with 28 participants with visual impairments. They performed tasks based on skills whose foundations are needed and used in their daily lives, such as scanning, tactile discrimination, picture and spatial comprehension. The tactile images used in this study were developed by additive manufacturing and printed over 180 g/m² sulphite paper. The best performances were obtained when (1) the tactile image contour line heights were between 0.2 mm and 0.4 mm; and (2) the texture presented densities between 10% and 50%, when alone, or between 10% and 90%, when combined with another texture. The tested line widths (0.8 mm and 1.2 mm) did not present statistically significant differences in the results. Vision status (low vision or blindness) and moment of vision loss (congenital or late blind) did not influence the results. Schooling affected the activities of identifying objects and locating their copies. In the Conclusion section, there is a detailed recommendation list for the production and application of tactile materials, which range from simplifying forms to encouraging the use of both hands during content assimilation.

The aim of this study was to measure the effects on 3D active cervical Range of Motion (ACROM) and perceived pain of a n elastic taping (ET) application in the cervical area. Thirty participants (n: 22M and 8F, age 35.4±4.4 years; body height 173.1±8.4 cm; body mass 73.5±12.8 kg) for the study group (SG) and twenty subjects (n: 11M and 9F, age 32.6±3.9 years; body height 174.9±10.9 cm; body mass 71.2±12.9 kg) for the control group (CG) were recruited. All subjects were symptomatic for neck and cervical pain in baseline condition. Each group performed on ACROM test and the perceived pain on neck basing as Numerical Rating Scale (NRS 0-10, a.u.): at the baseline (T0); after 20' from ET application (T1); after three days of wearing the ET application (T2). Between T0 and T1 an ET was applied on the cervical area of the SG participants. Statistical analysis did not show any significant change in CG in any measurement session for ACROM and neck pain parameters. Conversely, the SG showed significant improvements for ACROM rotation left (T0 64.8 ± 7.7° - T2 76.0 ± 11.1° p &lt; 0.000) and right (T0 66.0 ± 11.9° - T2 74.2 ± 9.6° p &lt; 0.000); lateral inclination left (T0 37.5 ± 6.9° - T2 40.6 ± 10.8° p &lt; 0.000) and right (T0 36.5 ± 7.9° - T2 40.9 ± 5.2° p &lt; 0.000); flexion posterior (T0 47.0 ± 12.9° - T2 55.1 ± 12.3° p &lt; 0.001) and anterior (T0 55.0 ± 3.6° - T2 62.9 ± 12.0° p &lt; 0.006). A significant decrease was measure also in SG for pain NRS between T0 and T2 (T0 7.5 ± 1.0° - T1 5.5 ± 1.4 - T2 1.4 ± 1.5° p &lt; 0.000). In conclusion, the results of this study underline the usefulness of a bilateral and symmetrical ET cervical application in terms to enhance multiplanar ACROM and to reduce subjective self-perceived cervical pain when it is needed. These findings can be applied for managing musculoskeletal health of different kind of individuals.

Medical management of chronic canine pruritic dermatologic conditions is challenging and often frustrating. This is a report that shows one way of aiding the management of pruritic dogs using a remote monitoring device. It is often difficult for veterinarians to get dog owners to return to the clinic once a dog is treated. It is possible that a 3-D accelerometer device could provide information to the clinic staff on the success or failure of a pruritus treatment plan while the dog was cared for at home. Eighty-seven dogs and their owners came to a Florida dermatology specialty clinic or its general practice hospital to be evaluated and treated for pruritus. An ANIMO® 3-D accelerometer was placed on the collar of dogs diagnosed and treated for pruritus. Dogs that completed the study were monitored for 120 days (4 months). The ANIMO app monitored a dog’s daily scratching, shaking, sleeping, activity, resting, barking and calories consumed and summarized this information in a daily report visible on the pet owner’s smart phone. An additional variable (grooming minutes per day) could be seen by the Sure Petcare R&amp;D Team that was not yet available in the app. The use of a 3-D accelerometer enabled veterinarians to continuously monitor dogs at home when they were being treated for itching. Clinic staff kept in touch with the owners by phone and could change therapy or bring the dog back for a recheck if problems were seen. Daily reports were combined into line charts that showed plots of scratching, shaking, grooming and sleeping over four months. Veterinarians were able to remotely monitor dogs that had been treated for pruritus for up to four months through the use of a collar-borne monitoring device. Dog owners and clinic staff used the daily summaries which were accessible through a smart phone app. Dogs seemed to tolerate the device well because of its small size and unobtrusive nature.

Small molecules that can modulate or stabilize cell-cell interactions are valuable tools for investigating the impact of collective cell behavior on various biological processes such as development/morphogenesis, tissue regeneration and cancer progression. Recently, we showed that budesonide, a glucocorticoid widely used as anti-asthmatic drug, is a potent regulator of stem cell pluripotency. Here we tested the effect of different budesonide derivatives and identified CHD-030498 as a more effective analogue of budesonide. CHD-030498 was able to prevent stem cell pluripotency exit in different cell-based models, including embryonic stem-to-mesenchymal transition, spontaneous differentiation and 3D gastruloid development, and at lower doses compared to budesonide.

Plant breeding aims to develop elite crop varieties appropriate for various environments with higher quality and quantity of production. Researchers use quantitative trait loci (QTL) mapping and association studies to identify regions in the genome responsible for the variation of the quantitative traits of interest. However, mapped regions do not always translate to functional proteins, which makes it challenging to identify genes associated with traits of interest. The biological functions of proteins are strongly dependent on their 3D structure. Alternatively, if proteins can be directly linked with the phenotypes, the effect of mutations on phenotypic changes can be assessed. Innovation of deep learning models in biology opens new avenues of exploration. AlphaFold is an AI system that predicts the 3D structure of a protein from its amino acid sequence with near experimental accuracy and was used in this study. Point mutations with a significant influence on the 3D structure of a protein can capture the effect on phenotypes through association study, and this provides insights into the regions that are of functional importance. In the current study, 534 plants were selected based on plant vigor, and 154 missense variants that change amino acid sequences, including 5 significant hits from previous study, were included. The changes in protein 3D structure were assessed by association with the phenotype. The analysis identified five significant associations, four of which were also identified in previous study of SNPs GWAS, however, a new fifth association was also identified which was annotated as disease resistance gene in Medicago truncatula. This study helps to associate SNPs that could be missed by GWAS due to stringent Bonferroni corrected p-values by providing a more robust filter for SNPs using features from predicted protein 3D structures.

Background. To prospectively evaluate the reliability of a portable optical scanner compared to the water displacement technique for volumetric measurements of the foot and ankle, and to compare the acquisition time associated with these two methods. Methods. Foot volume was measured in 29 healthy volunteers (58 feet, 24 female/5 male) by a 3D scanner (UPOD-S 3D Laser Full-Foot Scanner ®) and by water-displacement volumetry. Measurements were performed on both feet, up to a height of 10 cm above the ground. The acquisition time for each method was evaluated. Kolmogorov-Smirnov test, Lin's Concordance Correlation Coefficient, and a Student’s t-test were performed. Results: Mean foot volume was 869.7+/-165.1cm3 (3D scanner) versus 867.9+/-155.4cm3 (water-displacement volumetry) (p <10-5). Concordance of measurements was 0.93, indicative of a high correlation between the two techniques. Volumes were 47.8 cm3 lower when using the 3D scanner versus water volumetry. After statistically correcting this underestimation, the concordance was improved (0.98, residual bias = -0.03 +/- 35.1 cm3). Mean examination time was 4.2 +/-1.7 min (3D optical scanner) versus 11.1 +/-2.9 min (water volumeter) (p<10-4). Conclusion: Ankle/foot volumetric measurements performed using this portable 3D scanner are reliable and fast, and can be used in clinical practice and research.

Non-pneumatic tires have gained a lot of attention due to their advantages, including not having to worry about getting a flat tire. In this type of tire, metamaterial cells replace the pneumatic part of the tire. In general, metamaterials are formed by stacking cells together. These cells are obtained by various methods including topology optimization. Therefore, in this research, to achieve a metamaterial cell suitable for a non-pneumatic tire with the objective function of increasing compressive strength and bending fatigue life, optimization for three types of geometry including (1) square plane, (2) rectangular plane, and (3) entire circumference of tire and three types of material including polylactic acid (PLA), thermoplastic polyurethane (TPU) and void have been done. Optimization has been implemented by using MATLAB code in 2D mode. The cubic cell is obtained from extruding the optimized response of the square plane. From the optimized response of the rectangular plane, the cylindrical cell and from extruding the optimized response of the entire circumference of tire to the tire cross-section size, the main geometry of the tire has been calculated. Finally, to check the quality of 3D printing in producing cells and how they are connected, the optimal cell fabricated by the fused deposition modeling (FDM) method has been observed using a field-emission scanning electron microscopy (FE-SEM). The results show that in the optimization of the square plane, the sample with the minimum remaining weight constraint equal to 40% and in the optimization of the rectangular plane and the entire circumference of tire, the sample with the minimum remaining weight constraint equal to 60% was selected as the optimal sample. From checking the quality of 3D printing, it has been concluded that PLA and TPU materials are completely connected.

3D object detection is crucial for autonomous driving to understand the driving environment. Since the pooling operation causes information loss in the standard CNN, we have designed a wavelet multiresolution analysis-based 3D object detection network without a pooling operation. Additionally, instead of using a single filter like the standard convolution, we use the lower-frequency and higher-frequency coefficients as a filter. These filters capture more relevant parts than a single filter, enlarging the receptive field. The model comprises a discrete wavelet transform (DWT) and an inverse wavelet transform (IWT) with skip connections to encourage feature reuse for contrasting and expanding layers. The IWT enriches the feature representation by fully recovering the lost details during the downsampling operation. Element-wise summation is used for the skip connections to decrease the computational burden. We train the model for the Haar and Daubechies (Db4) wavelets. The two-level wavelet decomposition result shows that we can build a lightweight model without losing significant performance. The experimental results on the KITTI’s BEV and 3D evaluation benchmark show our model outperforms the Pointpillars base model by up to 14 \% while reducing the number of trainable parameters. Code will be released.

3D reconstruction from a single 2D input is a classic problem in the field of computer vision. With the advancements in deep learning, the performance of 3D reconstruction has also significantly improved. The reconstruction task is more difficult for objects with no textures or complex deformations. This paper serves as a review of recent literature on 3D reconstruction from a single view, with a focus on deep learning methods from 2018 to 2021. Due to lack of standard datasets or 3D shape representation methods, it is hard make direct comparisons between all reviewed methods. However, this paper reviews different approaches for reconstructing 3d shape as depth maps, surface normals, point clouds and meshes; along with various loss functions and evaluation metrics used to train and evaluate these methods.

Weaving is an ancient and effective structural forming technique characterized by the ability to convert two-dimensional ribbons to three-dimensional structures. However, most 3D structures woven from straight ribbons have topological defects. Baek et al. proposed a method to weave smoother continuous 3D surface structures using naturally curved (in-plane) ribbons, obtained a new surface structure with relatively continuous variation of Gaussian curvature, and analyzed its geometric properties. We believe that this new 3D surface structure with smooth geometric properties must correspond to new mechanical properties. To this end, we investigated a 3D surface structure using naturally curved (in-plane) ribbon weaving, and the results of calculations and experiments show that such structures have better buckling stability than those woven with straight ribbons. It is observed that the number of ribbons influences the buckling behavior of different types of woven structures.

Shell-like, double curved and thus above-average performance structures, are usually produced monolithically on site. For industrial advancement, however, they must be divided into transportable modules which can be assembled on the construction site (design for assembly). Models are lattice shells made of steel and glass, in which predominantly flat sub-surfaces (modules) are used. Therefore, the main question is: Which modularizations are suitable for flow production with mineral building materials? In this paper designed free-form surface is going to be discretized as PQ circular mesh system, suitable modules for 3D concrete printing. Moreover, the multi-criteria optimization is done with Response Surface Methodology (RSM) in order to get optimal final shape. The goal is to start from the arbitrary shape, that can be generated from two curves, with possible two-way division into modules and compare it with the resulted discretized PQ circular mesh system, realized with new algorithm. The comparison can be defined through two main criteria: geometrical and structural.

Numerous cases and a shortage of resources usually limit wild animal rescue. New technology implemented might save these severely injured wild animals from the situation of euthanasia by easing the requirement of intensive medication. Three-dimensional (3D) technologies provide precise and accurate results that improve the quality of the medical application. These 3D tools have become relatively low-cost and accessible in the past years. In the medical field of exotic animal, turtle shell defect is highly challenging because of inevitable water immersion. This report is the first attempt to apply the combination of 3D scanning, computer-aid design (CAD), and 3D printing to make a protective device that frees the wound from exposure to water or infection sources. The presenting techniques successfully extricate a wild freshwater turtle from an extensive shell defect within a short period. Integration of multiple sciences to 3D technology can provide a facile model for veterinary medical applications.

Abstract: The calibrator is one of the most important factors in the calibration of various laser 3D scanning instruments. The requirements for diffuse reflection surface are specially emphasized in many national standards. In this study, the spherical calibrator and plane calibrator compara-tive measurement experiments were carried out. The black ceramic standard sphere, white ce-ramic standard sphere, metal standard sphere, metal standard plane and white ceramic standard plane were used to test the laser 3D scanner. In the spherical calibrators comparative measure-ment experiments, the results indicated that the RMS of the white ceramic spherical calibrator with reflectance about 60% is 10 times that of the metal spherical calibrator with the reflectance of about 15%, and the RMS of the black ceramic spherical calibrator with reflectance of about 11% is of the same order as the metal spherical calibrator. In the plane calibrators comparative measurement experiments, the RMS of flatness measurement is 0.077 mm for metal plane cali-brator with reflectance of 15%, and 2.915 mm for ceramic plane calibrator with reflectance of 60%. The results show that when the optimal measurement distance and incident angle are selected, the reflectance of the calibrator has a great effect on the measurement results, regardless of the outlines or profiles. Based on the experiments, it is recommended to use the spherical calibrator or the standard plane with reflectance of around 18% as the standard, which can obtain the rea-sonable results. In addition, it is necessary to clearly provide the material category and surface reflectance information of the standard when calibrating the scanner according to the measure-ment standard.

The effects of residual stress in a tungsten gate on a polysilicon channel in scaled 3D NAND flash memories were investigated using a technology computer-aided design simulation. The NAND strings with respect to the distance from the tungsten slit were also analyzed. The scaling of the spacer thickness and hole diameter induced compressive stress on the polysilicon channel. Moreover, the residual stress of polysilicon in the string near the tungsten slit had greater compressive stress than the string farther away. The increase in compressive stress in the polysilicon channel degraded the Bit-Line current (Ion) because of stress-induced electron mobility deterioration. Moreover, a threshold voltage shift (△Vth) occurred in the negative direction because of conduction band lowering.

This article presents, for the first time, the kinetics and the general conversion features of free radical polymerization (FRP) in a 3-component system (A/B/N), with [A] being the initiator, and [B] and [N] are additives, based on the proposed mechanism of Rahal et al. Higher FRP can be achieved by additives [B] and [N], via the dual function of (i) regeneration [A], and (ii) generation of extra radicals (R) via the radicals (S' and S) produced by N.The initiator (coumarin) shows a dual photo-oxidation and photo-reduction character for high efficacy. The FRP conversion efficacy (CE) depends not only on the property of the initiator [A], the additives [B] and [N}, but also the types of monomers. For example, when [A]=CoumC, [A]/NPG is more efficient than [A]/Iod, but revserse trend occurs in some monomers. However, 2-component systems (with CE=0% to 80%) are always less efficient than that of 3-component systems (with CE=70% to 86%, in TMPTA). Specific systems with [A]=coumarins, [B]=Iodonium salt, and N=NPG are analyzed. Analytical formulas for the role of each component concentration, light intensity and coupling rates on the conversion efficacy are derived.

Introduction: The current generation of 3D printers are lighter, cheaper, and smaller, making them more accessible to the chairside digital dentist than ever before. 3D printers in general in the industrial and chairside setting can work with various types of materials including, metals, ceramics, and polymers. Evidence presented in many studies show that an ideal material used for dental restorations is characterised by several properties related to durability, cost-effectiveness, and high performance. This review is the second part in a 3D Printing series that looks at the literature on material science and applications for these materials in 3D printing as well as a discussion on the potential further development and future evolution in 3D printing materials. Conclusions: Current materials in 3D printing provide a wide range of possibilities for providing more predictable workflows as well as improving efficiency through less wasteful additive manufacturing in CAD/CAM procedures. Incorporating a 3D printer and a digital workflow into a dental practice is challenging but the wide range of manufacturing options and materials available mean that the dentist should be well prepared to treat patients with a more predictable and cost effective treatment pathway. As 3D printing continues to become a commonplace addition to chair side dental clinics, the evolution of these materials, in particular reinforced PMMA, resin incorporating zirconia and glass reinforced polymers offer increased speed and improved aesthetics that will likely replace subtractive manufacturing milling machines for most procedures.

Introduction: The term 3D printing is commonly used to depict an assembling method whereby the final form of an object is the result of the addition of different layers to build the frame of an object. This procedure is more accurately portrayed as additive manufacturing and is likewise alluded to as fast prototyping. The term 3D printing, in any case, is generally new and has been an active part of current developments in Dentistry. Much publicity encompasses the evolution of 3D printing, which is hailed as an innovation that will perpetually change CAM manufacturing, including in the dental sector. This review is the first part in a 3D Printing series that looks at the history of 3D Printing, the technologies available and reviews the literature relating to the accuracy of these technologies. Conclusions: The recent advancement in digital dentistry to incorporate these tools has modernised dental practices by paving the way for computer-aided design (CAD) technology and rapid prototyping. The use of 3D printing has led to 3D digital models produced with intraoral scanners (IOS), which can be manipulated easily for diagnosis, treatment planning, mockups, and a multitude of other uses. Combining 3D Printing with a 3D intraoral scan eliminates the need for physical storage but makes it to retrieve a 3D models for use within all dental modalities.

The article proposes an indirect measurement method based on a dimensional and shape analysis of forgings for the evaluation of the manufacture and the proper operation of the key elements of the crank press, in which after modernization, a quick tool assembly based on SMED (Single Minute Exchange of Die) was implemented. As a result of the introduced changes aiming at improving the forging aggregate and increasing the production efficiency, errors were observed on the manufactured products-forgings in the form of twists and joggles. The preliminary analysis showed that they can be clearances and dynamic deformation in the kinematic chain, the occurrence of side forces during automatic forging of the forging in a two-component system (a long, thin element), as well as the design and construction errors in the joining of the SMED instrument with the table tops of the press. In order to solve the presented problem, in the first place, a separate dimensional and shape analysis was made of selected elements of the press and the instrumentation with the use of the 3D scanning method with the purpose to analyze the construction tolerances of the key elements of the press geometry. Next, an evaluation of the effect of clearances and dynamic deformations of the press as well as the force distribution during the forging process was made through numerical modelling. Despite all of the above, such an approach did not make it possible to solve the problem. A proprietary method with the use of 3d reverse scanning was proposed, which allowed to solve the problem of forgings errors. Based on the measurement results and analyses for a few variants of production cycles the necessary changes was obtained, making it possible to minimize the errors and obtain proper products in respect of geometry and quality.

Marketing is one of the important stages, the decisive factor affecting the success of production and business activities of every business. Therefore, marketing is considered to be the first and most important stage in the process of introducing, bringing products to market and branding of businesses, especially in the period when the disease situation is taking place very complicated worldwide. This study provides both qualitative and quantitative results for the following research objectives. Firstly, the study will assess the situation and analyze the appropriateness of marketing models in the current market situation trend. Secondly, the study proposes an approach in building a new type of marketing model, which is 3D web-based marketing applied in e-commerce to support the modeling of enterprise products in the form of Interactive 3D products are similar to real products. Thirdly, testing and evaluating 3D e-commerce web marketing model at Truong Hai Auto Showroom, Thai Nguyen City branch. This study also proposes a number of solutions for the research and deployment of 3D web marketing model application for businesses in the current market situation.

The aim of this study was to clarify degradation characteristics in each tissue of the knee complex of a medial meniscectomy (MMx)-induced knee osteoarthritis (KOA) animal model using classical methods and a new comprehensive evaluation method called contrast-enhanced X-ray micro-computed tomography (CEX-μCT), which was developed in the study. Surgical MMx was performed in the right knee joints of five male Wistar rats to induce KOA. At 4 wk post-surgery, the synovitis was evaluated using qPCR. Degradations of the articular cartilage of the tibial plateau were evaluated using classical methods and CEX-μCT. Evaluation of the synovitis demonstrated significantly increased expression levels of inflammation-associated marker genes in MMx-treated knees compared to that in sham-treated knees. Evaluation of the articular cartilage using classical methods showed that MMx fully induced degradation of the cartilage. Evaluation using CEX-μCT showed that local areas of the medial cartilage of the tibial plateau were significantly reduced in MMx-treated knees compared to that in sham-treated knees. On the other hand, total cartilage volumes were significantly increased in MMx-treated knees. Based on the findings of this study, the researchers in KOA research could be helped to select an optimal KOA model to discover new drugs.

Despite the long and extensive history of 3D technology, it has recently attracted the attention of researchers. This technology has become the center of interest of young people because of the real feelings and sensations it creates. People see their environment as 3D because of their eye structure. In this study, it is hypothesized that people lose their perception of depth during sleepy moments and that there is a sudden transition from 3D vision to 2D vision. Regarding these transitions, the EEG signal analysis method was used for deep and comprehensive analysis of 2D and 3D brain signals. In this study, a single-stream anaglyph video of random 2D and 3D segments was prepared. After watching this single video, the obtained EEG recordings were considered for two different analyses: the part involving the critical transition (transition-state) and the state analysis of only the 2D versus 3D or 3D versus 2D parts (steady-state). The main objective of this study is to see the behavioral changes of brain signals in 2D and 3D transitions. To clarify the impacts of the human brain’s power spectral density (PSD) in 2D-to-3D (2D_3D) and 3D-to-2D (3D_2D) transitions of anaglyph video, 9 visual healthy individuals were prepared for testing in this pioneering study. Spectrogram graphs based on Short Time Fourier transform (STFT) were considered to evaluate the power spectrum analysis in each EEG channel of transition or steady-state. Thus, in 2D and 3D transition scenarios, important channels representing EEG frequency bands and brain lobes will be identified. To classify the 2D and 3D transitions, the dominant bands and time intervals representing the maximum difference of PSD were selected. Afterward, effective features were selected by applying statistical methods such as standard deviation (SD), maximum (max), and Hjorth parameters to epochs indicating transition intervals. Ultimately, k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) algorithms were applied to classify 2D_3D and 3D_2D transitions. The frontal, temporal, and partially parietal lobes show 2D_3D and 3D_2D transitions with a good classification success rate. Overall, it was found that Hjorth parameters and LDA algorithms have 71.11% and 77.78% classification success rates for transition and steady-state, respectively.

Electrospinning is known to be an effective and straightforward technique to fabricate polymer non woven matrices made of nano and microfibers. Micro patterned morphology of electrospun matrices results to be outmost advantageous in the biomedical field, since it is able to mimic extracellular matrix (ECM), and favors cell adhesion and proliferation. Controlling electrospun fibers alignment is crucial for the regenerative purposes of certain tissues, such as neuronal and vascular. In this study we investigated the impact of electrospinning process parameters on fiber alignment in tubular nanofibrous matrices made of Poly (L-lactide-co-ε-caprolactone) (PLA-PCL); a Design of Experiments (DoE) approach is here proposed in order to statistically set up the process parameters. The DoE was studied keeping constants the previously set material and environmental parameters; voltage, flow rate and mandrel rotating speed were the process parameters here investigated as variables. Orientation analysis was based on ImageJ and plugin Orientation J analysis of SEM images. The results show that voltage combined with flow rate has significant impact on electrospun fiber orientation, and the greatest orientation is achieved when all the three input parameters (voltage, flow rate and mandrel rotation speed) are at their maximum value.

Direct laser writing based on non-linear 3D nanolithography (also known as 3D laser lithography, 3DLL) is a powerful technology to manufacture polymeric micro-optical components. However, practical applications of these elements are limited due to the lack of knowledge of their optical resilience and durability. In this work, we employ 3DLL for the fabrication of bulk (i.e. fully filled) and woodpile structures out of different photopolymers. We then characterize them using S-on-1 laser induced damage threshold (LIDT) measurements. In this way, quantitative data of LIDT values can be collected. Furthermore, this method permits to gather damage morphologies. The results presented in this work demonstrate that LIDT values depend on the material and the geometry of the structure. Bulk non-photosensitized hybrid organic-inorganic photopolymer SZ2080 structures are found to be the most resilient with a damage threshold being of 169±15 mJ/cm².

We propose a computer-generated hologram method for near-eye virtual reality and augmented reality 3D display. A 3D object located near the holographic plane is projected onto a projection plane to obtain a plurality of projected images with different angles. The hologram is calculated by superposition of projected image convolution with a specific PSF through the interference of reference wave with object wave. Holographic 3D display systems with LED as illumination, 4f optical filtering system and lens as eyepiece for near-eye VR display and HOE as combiner for near-eye AR display are designed. The results show that the proposed method is about 38 times faster than the conventional point cloud method. The proposed method is flexible to produce speckle noise free high-quality VR and AR images with efficient focus and defocus capabilities.

3D-printing with foam concrete, which is known for its distinct physical and mechanical properties, has not yet been purposefully investigated. The article at hand presents a methodological approach for the mixture design of 3D-printable foam concretes and a systematic investigation of the potential application of this type of material in digital construction. Three different foam concrete compositions with water-to-binder ratios between 0.33 and 0.36 and having densities of 1100 to 1580 kg/m³ in the fresh state were produced with a pre-foaming technique using a protein-based foaming agent. Based on the fresh-state tests, including 3D-printing as such, an optimum composition was identified and its compressive and flexural strengths were characterised. The printable foam concrete showed compressive strength above 10 MPa and low thermal conductivity, which make it suitable for 3D-printing applications, while fulfilling both load-carrying and insulating functions.

Culture systems for 3-dimensional tissues, such as multicellular spheroids, are indispensable for high-throughput screening of primary or patient-derived xenograft (PDX)-expanded cancer tissues. Oxygen supply to the center of such spheroids is particularly critical for maintaining cellular functions as well as avoiding the development of a necrotic core. In this study, we evaluated 2 methods to enhance oxygen supply: (1) using culture plate with gas-permeable polydimethylsiloxane (PDMS) membrane at its bottom and (2) embedding hydrogel beads in the spheroids. Culturing spheroids on PDMS increased cell growth and affected glucose/lactate metabolism and CYP3A4 mRNA expression and subsequent enzyme activity. The spheroids comprised 5000 Hep G2 cells and 5000 20 µm-diameter hydrogel beads did not develop a necrotic core for 9 days when cultured on a gas-permeable sheet. In contrast, central necrosis in spheroids lacking hydrogel beads was observed after day 3 of culture, even when using PDMS. These results indicate that the combination of gas-permeable culture equipment and embedded hydrogel beads improves culture 3D spheroids produced from primary or PDX-expanded tumor cells.

Poliovirus 2A protease (PV2Apro) plays a vital role in viral replication and down-regulation of host cell protein synthesis. In order to understand more concerning PV2Apro, the protein was over-expressed in bacteria following amplification using sense and antisense primers and cloning in pET15b. Several expression hosts were tested and BL21 (DE3) pLysS cells gave the best expression of PV2Apro with minimal unwanted protein expression following IPTG induction. The 2Apro protein was purified to homogeneity using column chromatography, its solubility determined and its molecular weight and composition determined by MALDI-TOF mass spectrometry. The protease was found in the insoluble fraction and the purified protein had a slightly lower molecular weight than predicted. Moreover, three dimensional structure was modelled using template 1z8r with 58% identity and validated using ramachandran plot. Results revealed that most of the residues lie in favoured and allowed regions. These findings could help in a better understanding of PV2Apro structure and inhibition thus, highlighting potential targets for antiviral drug development.

The development and generalization of Digital Volume Correlation (DVC) on X-ray computed tomography data highlight the issue of long term storage. The present paper proposes a new model-free method for pruning the DVC data. The size of the remaining sampled data can be user-defined, depending on the needs concerning storage space. The data pruning procedure is deeply linked to hyper-reduction techniques. The DVC data of a resin-bonded sand tested in uniaxial compression is used as an illustrating example. The relevance of the pruned data is tested afterwards for model calibration. A new Finite Element Model Updating (FEMU) technique coupled with an hybrid hyper-reduction method is used to successfully calibrate a constitutive model of the resin bonded sand with the pruned data only.

Fatty Acid Amide Hydrolase (FAAH) is one of the enzymes responsible of endocannabinoids metabolism. The inhibition of FAAH is a useful and indirect strategy to raise endogenous cannabinoid concentrations, which would be useful for the treatment of various pathological processes in which cannabinoid concentrations are lowered. In the present work, we present an extensive 3D-QSAR/CoMSIA study on a series of 90 irreversible inhibitors of FAAH of pyrimidinyl-piperazine-carboxamide structure. The final model obtained was extensively validated (q2 = 0.734; r2test = 0.966; r2m = 0.723), and based on the information derived from the contour maps we reported a series of 10 new compounds designed as powerful FAAH inhibitors (pIC50 of the best-proposed compounds = 12.196; 12.416).

Glioblastoma (GBM), the most common and aggressive primary brain tumor in adults, remains one of the least treatable cancers. Current standard of care—combining surgical resection, radiation, and alkylating chemotherapy—results in a median survival of only 15 months. Despite decades of investment and research into the development of new therapies, most candidate anti-glioma compounds fail to translate into effective treatments in clinical trials. One key issue underlying this failure of therapies that work in pre-clinical models to generate meaningful improvement in human patients is the profound mismatch between drug discovery systems—cell cultures and mouse models—and the actual tumors they are supposed to imitate. Indeed, current strategies that evaluate the effects of novel treatments on GBM cells in vitro fail to account for a wide range of factors known to influence tumor growth. These include secreted factors, the brain’s unique extracellular matrix, circulatory structures, the presence of non-tumor brain cells, and nutrient sources available for tumor metabolism. While mouse models provide a more realistic testing ground for potential therapies, they still fail to account for the full complexity of tumor-microenvironment interactions, as well as the role of the immune system. Based on the limitations of current models, researchers have begun to develop and implement novel culture systems that better recapitulate the complex reality of brain tumors growing in situ. A rise in the use of patient derived cells, creative combinations of added growth factors and supplements, may provide a more effective proving ground for the development of novel therapies. This review will summarize and analyze these exciting developments in 3D culturing systems. Special attention will be paid to how they enhance the design and identification of compounds that increase the efficacy of radiotherapy, a bedrock of GBM treatment.

This work presents datasets that can be used for getting a good understanding of an essential geoscience content knowledge that describe earth’s coordinate systems. This include coordinate system used for spherical/spheroidal earth with latitudes and longitudes and their subsequent transformations to 2d maps on a variety of media (paper as well as digital) using the process of map projections. The datasets include PDF documents that are embedded with 3d models, animations and mathematical equations. The dataset has separate PDF documents for geographic (for spherical earth) and projected (2d) coordinate systems. Additionally, the data set include individual 3d models that can be used in various digital systems (including apps) and the animations in mp4 format that can be watched on most of the modern digital devices.

We propose an approach for estimating the error in depth data provided by generic 3D sensors, which are modern devices capable of generating an image (RGB data) and a depth map (distance) or other similar 2.5D structure (e.g. stereo disparity) of the scene. Our approach starts capturing images of a checkerboard pattern devised for the method. Then proceed with the construction of a dense depth map using functions that generally comes with the device SDK (based on disparity or depth). The 2D processing of RGB data is performed next to find the checkerboard corners. Clouds of corner points are finally created (in 3D), over which an RMS error estimation is computed. We come up with a multi-platform system and its verification and evaluation has been done, using the development kit of the board nVIDIA Jetson TK1 with the MS Kinects v1/v2 and the Stereolabs ZED camera. So the main contribution is the error determination procedure that does not need any data set or benchmark, thus relying only on data acquired on-the-fly. With a simple checkerboard, our approach is able to determine the error for any device. Envisioned application is on 3D reconstruction for robotic vision, with a series of 3D vision sensors embarked in robots (UAV of type quadcopter and terrestrial robots) for high-precision map construction, which can be used for sensing and monitoring.

Ultrafast laser 3D lithography based on non-linear light-matter interactions, widely known as multi-photon lithography (MPL), offers unrivaled precision rapid prototyping and flexible additive manufacturing options. 3D printing equipment based on MPL are already commercially available, yet there is still no comprehensive understanding of factors determining spatial resolution, accuracy, fabrication throughput, repeatability, and standardized metrology methods for the accurate characterization of the produced 3D objects and their functionalities. The photoexcitation mechanisms, spatial-control or photo-modified volumes, and the variety of processable materials are topics actively investigated. The complexity of the research field is underlined by limited understanding and fragmented knowledge of light-excitation and material response. Research to date has only provided case-specific findings on photoexcitation, chemical modification, and material characterization of the experimental data. In this review, we aim to provide a consistent and comprehensive summary of the existing literature on photopolymerization mechanisms under highly confined spatial and temporal conditions, where, besides the excitation and cross-linking, parameters such as diffusion, temperature accumulation, and the finite amount of monomer molecules start to become of critical importance. Key parameters such as, photoexcitation, polymerization kinetics, and the properties of the additively manufactured materials at the nanoscale in 3D are examined, whereas, the perspectives for future research and as well as emerging applications are outlined.

In nature and engineering applications, flexible fiber beds covering biological surfaces can play a role in reducing resistance. These fibers deform under the action of fluids, and this deformation affects the fluid flow state, forming a complex fluid-solid interaction phenomenon. To quantitatively analyze such issues, the physical model is simplified to the deformation problem of an soft hair bed caused by Stokes flow, and the deformation problem of a single fiber caused by Stokes flow is further studied. The deformation problem of an elastic single fiber in a channel caused by Stokes flow can be described by a nonlinear integral equation. We have obtained a new series solution, which has been compared with the previous perturbation method to verify the accuracy and effectiveness of the series solution. Meanwhile, we have further provided an extended form of flexible fiber deformation through experimental fitting. This fluid-solid interaction problem involves multiple fields and is very important in many natural and engineering systems. The research in this paper can not only help us better understand complex phenomena in nature but also delve into the interaction mechanism between fluids and solids, providing a theoretical basis for future scientific research and engineering applications.

The Antarctic photopsychrophile, Chlamydomonas priscuii UWO241 is adapted to extreme environmental conditions, including permanent low temperatures, high salt and shade. During long-term exposure to this extreme habitat, UWO241 appears to have lost several short-term mechanisms in favor of constitutive protection against environmental stress. This study investigated physiological and growth responses of UWO241 to high light conditions, evaluating the impacts of long-term acclimation to high light, low temperature, and high salinity on its ability to manage short-term photoinhibition. We found that UWO241 significantly increased its growth rate and photosynthetic activity at growth irradiances far exceeding native light conditions. Furthermore, UWO241 exhibited robust protection against short-term photoinhibition, particularly in photosystem I. Last, pre-acclimation to high light or low temperatures, but not high salinity, enhanced photoinhibition tolerance. These findings extend our understanding for stress tolerance in extremophilic algae. In the past 2 decades climate change-related increasing glacial stream flow has perturbed long-term stable conditions: in the form of has been associated with lake level rise, thinning of ice covers, and expansion of ice-free perimeters. Our findings have implications on phytoplankton survival and response to change scenarios in the light-limited environment of Antarctic ice-covered lakes.

Knee osteoarthritis is a prevalent joint disease affecting millions of individuals globally. While total knee arthroplasty is an effective treatment for advanced stages of KOA, it may not be suitable for earlier stages or younger patients. Supervised exercise therapy has proven to be the first line treatment of preference in tackling pain and disability caused by KOA. However, the high intensities required to induce positive muscle adaptations are not indicated in this population as this is often accompanied by pain, discomfort, and frustration; leaving low load resistance training as the only feasible method of treatment. Recently, the use of blood flow restriction training began to emerge as a substitute for high load resistance training. With BFRT, a cuff is applied around the proximal aspect of the affected limb, causing partial arterial and full venous occlusion, thereby inducing localized hypoxia and accumulation of metabolites, mimicking the effects of high load resistance training, albeit with low loads. Consequently, BFRT might offer a suitable and more effective alternative for KOA patients who are not (yet) eligible for TKA, compared to the traditional exercise therapy. This review aims to summarize the current evidence as regards the application of Blood Flow Restriction in exercise therapy of knee osteoarthritis patients, with particular consideration of the underlying mechanisms and its safety, as well as general guidelines for practical implementation into clinical practice. In doing so, this narrative review aims to create a framework allowing the translation from theory to practice.

Fluidized beds are pivotal in the process industry and chemical engineering, with Computational Fluid Dynamics (CFD) playing a crucial role in their design and optimization. Challenges in CFD modeling stem from the scarcity or inconsistency of experimental data for validation, along with the uncertainties introduced by numerous parameters and assumptions across different CFD codes. This study navigates these complexities by comparing simulation results from the open-source MFIX and OpenFOAM, and the commercial ANSYS FLUENT, against experimental data. Utilizing a Eulerian-Eulerian framework and the kinetic theory of granular flow (KTGF), the investigation focuses on solid-phase properties through the classical drag laws of Gidaspow and Syamlal-O’Brien across varied parameters. Findings indicate that ANSYS Fluent, MFiX, and OpenFOAM can achieve reasonable agreement with experimental benchmarks, each showcasing distinct strengths and weaknesses. The study also emphasizes that both the Syamlal-O’Brien and Gidaspow drag models exhibit reasonable agreement with experimental benchmarks across the examined CFD codes, suggesting a moderated sensitivity to the choice of drag model. Moreover, the analysis were also carried out for 2D and 3D simulations, revealing that the dimensional approach impacts the predictive accuracy to a certain extent, with both models adapting well to the complexities of each simulation environment. The study highlights the significant influence of restitution coefficients on bed expansion due to their effect on particle-particle collisions, with a value of 0.9 deemed optimal for balancing simulation accuracy and computational efficiency. Conversely, the specularity coefficient, impacting particle-wall interactions, exhibits a more subtle effect on bed dynamics. This finding emphasizes the critical role of carefully choosing these coefficients to effectively simulate the nuanced behaviors of fluidized beds.

This work examines the beneficial role of an unsteady stenosis, operating without the use of any external energy source, as a means for augmenting the flow rate of a valveless pump in a hydraulic loop, including an open tank. In contrast to our previous work that the loop was horizontal, here gravity was taken into account. The stenosis neck cross-sectional area was controlled by the fluid pressure and an opposing force applied externally by a spring of adjustable tension. The pincher compressed and decompressed periodically a part of a flexible tube with frequencies from 5 Hz to 11 Hz and compression ratios Ab from 24% to 65%. The presence of the stenosis increased the net flow rate 19 times for Ab = 24%, and 6.3 times for Ab = 38%, whereas for Ab = 65%, the flow rates were comparable. The volumetric efficiency varied from 30% to 40% under the presence of the stenosis, and from 2% to 20% without the stenosis. The role of the stenosis role was to cause a unidirectional flow, opening during tube compression and closing during decompression. The pressure amplitudes along the flexible tube increased towards the rigid-flexible tube junction (as a result of the wave reflections) which were found to be significantly attenuated by the presence of the stenosis.

Parallax processing and structure preservation has long been important and challenging tasks in image stitching. In this paper, an image stitching method based on sliding camera to eliminate perspective deformation and asymmetric optical flow to solve parallax is proposed. By maintaining the viewpoint of two input images in the mosaic non-overlapping area and creating a virtual camera by interpolation in the overlapping area, the viewpoint is gradually transformed from one to another image view-point so as to complete the smooth transition of the two image viewpoints and reduce perspective deformation. Two coarsely aligned warped images are generated with the help of a global projection plane. After that, the optical flow propagation and gradient descent method are used to quickly calculate the bidirectional asymmetric optical flow between the two warped images, and the optical flow-based method is used to further align the two warped images to reduce parallax. In the image blending, the softmax function and registration error are used to adjust the width of the blending area, further eliminating ghosting and reduce parallax. Finally, the comparative experiments show that our method can effectively eliminate perspective deformation, reduce misalignment, and save running time.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

As the demand for fossil fuels continues to rise and their availability becomes increasingly limited, it is crucial to explore innovative approaches to optimize fuel combustion in existing systems. Among various engines, diesel engines are heavily reliant on fluid motion within the engine cylinder, which plays a critical role in fuel-air mixing. This abstract focuses on the potential of dynamic mathematical model simulation for multi-compartment rotor compressed combustion engines, aiming to revolutionize power generation by enhancing fuel burning efficiency. By leveraging advanced simulation techniques, this research seeks to unlock new insights into fluid dynamics and optimize fuel-air mixing, leading to more efficient and sustainable energy utilization. Through this exploration, we aim to pave the way for groundbreaking advancements in the field of combustion engines, ultimately contributing to a greener and more sustainable future. In the realm of internal combustion engines, the fluid dynamics within the engine cylinder greatly influence the combustion processes and heat transfer. For compression ignition (C.I) engines, both the bulk gas motion and turbulence characteristics play vital roles in engine performance. This study focuses on enhancing the combustibility of the fuel-air mixture in C.I engines by modifying the engine design to induce turbulence through squish and tumble flows. The modification involves creating multiple compartments on the rotor crown, comprising three small chambers spaced 120º apart. By implementing this design, the aim is to optimize the fuel-air mixing and improve the overall combustion efficiency. Through comprehensive analysis and experimentation, we seek to revolutionize C.I engine technology and pave the way for more efficient and environmentally-friendly power generation. In this study, the performance of a compression ignition (C.I) engine with a multiple compartment rotor has been analyzed under motoring conditions using computational fluid dynamics (CFD) simulations with FLUENT software. The obtained results have been compared with those of a base C.I engine. The analysis focused on the effects of the modified engine design on the tumble ratio and squish velocity, which are important parameters for fuel-air mixing and combustion efficiency. The results indicated a significant improvement with the modified engine, with a 35% increase in tumble ratio and a 31% increase in squish velocity compared to the base engine. These findings suggest that the modified engine design has the potential to enhance fuel-air mixing and combustion performance, leading to improved overall engine efficiency. This research presents promising insights into the optimization of C.I engine design and contributes to the development of more efficient and environmentally-friendly power generation technologies..

Background: Early postoperative airway management after laryngo-tracheal surgery is crucial. Acute respiratory failure due to glottis’ oedema may occur, requiring reintubation. This can prolong ventilatory assistance, jeopardizing the anastomosis. To date, only judicious steroid administration and fluid management are available to avoid more invasive procedures. High-Flow-Oxygen-Therapy(HFOT) is a noninvasive O2 support method providing humidification, warmed air, Positive-End-Expiratory-Pressure(AIRVO2). No data exist about HFOT use to prevent early complications after laryngo-tracheal surgery. Methods: Between Sept.2020-Sept.2022, 107 consecutive patients underwent laryngo-tracheal surgery received HFOT(Group A). Data and long-term results were compared with those of 80 patients operated between Sept.2018-Aug.2020(Group B), when HFOT was not available. All patients were operated in a single center. No pre- or post-operative settings changed, except for HFOT introduction. We analyzed and compared the risk for “delayed” reintubation (unexpected reintubation within the first 24-48 hours after extubating/laryngeal mask removal) in the two groups. Results: No patients reported HFOT-related adverse events. Control group(B) presented “delayed” reintubation in 37% (p= 0.027), Intensive Care Unit admission in 67%(p=0.005) and longer hospital stay(p=0.001) compared to HFOT group(A). Minor complications rate was 3% in both group and overall mortality was 0%. Re-stenosis was described in 4.6% of HFOT group, without a statistically significant difference (p=0.7006). Conclusions: Our study is the first to investigate HFOT use in patients undergoing laryngo-tracheal surgery, potentially representing a consistent innovation in the peri-operative management of these patients. With the limit of a retrospective series, we would suggest HFOT use for preventing post-operative reintubation rate, possibly reducing ICU admission and hospital stay.

The main purpose of this study was to design a workplace in the conditions of a digital factory. The goal of this study is to compile a proposal for improving the layout solution in the selected enterprise to reduce material flows between individual workplaces. In addition, the workplace research study uses methods of material flow analysis with the application of visTABLE software support, which serves as a tool for designing production processes. The main result of the study was the reduction of the production time of the beam by 10 minutes and the creation of proposals for solutions for the company. The study helped with the visualization of processes within the digital factory to simplify and clarify processes at the workplace.

Overexpression of human epidermal growth factor receptor 2 (HER2) in breast and gastric cancers is an important target for monoclonal antibody (mAb) therapy. All therapeutic mAbs, including anti-HER2 mAbs, exhibit adverse effects probably due to the recognition of antigens expressed in normal cells. Therefore, tumor-selective or specific mAbs can be beneficial in reducing the adverse effects. In this study, we established a novel cancer-specific anti-HER2 antibody, named H₂Mab-250/H₂CasMab-2 (IgG₁, kappa). H₂Mab-250 reacted with HER2-positive breast cancer BT-474 and SK-BR-3 cells. Importantly, H₂Mab-250 did not react with non-transformed normal epithelial cells (HaCaT and MCF 10A) and immortalized normal epithelial cells in flow cytometry. In contrast, most anti-HER2 mAbs including H₂Mab-119 (IgG₁, kappa) reacted with both cancer and normal epithelial cells. Furthermore, a core-fucose deleted IgG_2a-type H₂Mab-250 (H₂Mab-250-mG_2a-f) could trigger the antibody-dependent cellular cytotoxicity activity to BT-474, but not to HaCaT cells. Furthermore, H₂Mab-250-mG_2a-f exhibited an in vivo antitumor effect against BT-474 xenograft. Immunohistochemical analysis demonstrated that H₂Mab-250 possesses much higher reactivity to the HER2-positive breast cancer tissues compared to H₂Mab-119, and did not react with normal tissues, including heart, breast, stomach, lung, colon, kidney, and esophagus. The epitope mapping demonstrated that the Trp614 of HER2 domain IV mainly contributes to the recognition by H₂Mab-250. H₂Mab-250 could contribute to the development of chimeric antigen receptor-T or antibody-drug conjugates without adverse effects for breast cancer therapy.

The heat generated during the startup process of dry gas seals, such as the friction heat of the asperities, viscous shear heat, and the expansion heat of the gas film, easily leads to seal failure and endangers the stable operation of turbomachinery. This study combines the statistically modified contact model and the average Reynolds equation by considering the adiabatic index and the microscale effects of dry gas seals to explore the heat generation characteristics of dry gas seals formed in series at multiple times. In particular, the change laws and influencing factors among the components, including the friction heat of asperities and the shear heat and expansion heat of the gas film and total heat, are investigated. A comparative analysis indicates that the slip flow effect increases the total heat during the startup process. The friction heat is much greater than expansion heat and shear heat. Despite constant acceleration, exponential acceleration, or Harrision acceleration, the heat changes are uneven during the startup process. In particular, the heat changes sharply in the early stage and gently in the later stage. The Harrision acceleration mode is the most conducive to sealing stability.

Introduction: The coronary flow reserve (CFR) is a sign of early-stage coronary artery disease (CAD). Plasma atherogenic index (PAI) is related to atherosclerosis and cardiovascular mortality. Therefore, our aim was to determine CFR and PAI in patients with primary hyperparathyroidism (PHPT) and investigate whether PAI can be used in the detection of early-stage CAD. Material and Methods: The sample was comprised of 44 patients with PTHT and 33 healthy volunteers. We defined CFR as the ratio of the hyperemic diastolic peak velocity to the baseline diastolic peak velocity. PAI values were calculated with the formula of log 10 triglyceride (TRG) / high-density lipoprotein (HDL). Result: The comparison of the groups for PAI and CFR demonstrated that PAI levels were significantly higher while CFR levels were significantly lower in the PTHT patients (p<0.01, p=0.01, respectively). The correlation analysis revealed that CFR was negatively correlated with PAI and TRG (PAI- p<0.0001 r=-0.537).The multivariate logistic regression analysis showed that only a high PAI level (OR: 151.6, 95% confidence interval (CI): 4.1-5480, p=0.006) was an independent predictor of reduction in CFR in PHPT patients. Conclusion: Overall, we found an independent correlation between PAI and CFR values. Hence, PAI may be useful in identifying PHPT patients facing a high risk of adverse cardiovascular events and may also allow early diagnosis of subclinical atherosclerosis.

Microstructured optical fibres (MOFs) are a new type of optical fibres that possess a wide range of optical properties and many advantages over common optical fibres. Those are provided by unique structures defined by a pattern of periodic or quasi-periodic arrangement of air holes that run through the fibre length. In recent years, MOFs have opened up new possibilities in the field of optics and photonics, enabling the development of advanced devices and novel optical systems for different applications. The key application areas of PCFs vary from telecommunications and high-power energy transmission to quantum optics and sensing. The stack-and-draw method is a standard manufacturing technique for MOFs, where a preform is first manually created and then drawn in a high-tech furnace into a fibre with the required final dimensions and position of the air holes. Since in the manufacturing process experimenters can control only a few parameters, mathematical models and numerical simulations of the drawing process are highly requested. They not only allow to deepen the understanding of physical phenomena occurring during the drawing process, but they also accurately predict the final cross-section shape and size of the fibre. In this manuscript, we assume thermal equilibrium between the furnace and the fibre and propose a functional form of the fibre temperature distribution. We utilise it with asymptotic mass, momentum, and evolution equations for free surfaces already available in the literature to describe the process of fibre drawing. By doing so, the complex heat exchange problem between the fibre and the furnace need not be solved. The numerical results of the whole asymptotic model overall agree well with experimental data available in the literature, both for the case of annular capillaries and for the case of holey fibres.

Recanalization poses challenge in coil embolization for cerebral aneurysms. Establishing predictive models for post-embolization recanalization is important for clinical decision-making. However, conventional statistical and machine learning (ML) models may overlook critical parameters during the initial selection process. In this study, we automated the identification of significant hemodynamic parameters using a PointNet-based deep neural network (DNN), leveraging their inherent 3D features. Further feature analysis was conducted utilizing saliency mapping, an explainable artificial intelligence (XAI) technique. The study encompassed the analysis of velocity, pressure, and wall shear stress (WSS) in both pre- and post-coiling models derived from computational fluid dynamic (CFD) simulations for 59 aneurysms. Velocity was identified as the most pivotal parameter, supported by the lowest P-value from statistical analysis and the highest area under the curves (AUROC)/precision-recall curves (AUPRC) values from DNN model. Moreover, visual XAI analysis revealed robust injection flow zones with notable impingement points in pre-coiling models, as well as pronounced interplay between flow dynamics and the coiling plane were important 3D features in identifying the recanalized aneurysms. The combination of DNN and XAI was found to be an accurate and explainable approach not only at predicting post-embolization recanalization but also at discovering unknown features in the future.